STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration

The Prognostic Value of Transcutaneous Oxygen Pressure (TcPO2) in Diabetic Foot Ulcer Healing: A Protocol for a Systematic Review

Background/Objectives: Due to poor perfusion, diabetic foot ulcers (DFUs) create hypoxic environments, and their chronicity represents a negative factor in wound healing. Transcutaneous oxygen pressure (TcPO2) is a non-invasive method that provides information on oxygen supply to microvascular circulation, useful for determining the severity and progression of peripheral arterial disease (PAD) as well as potentially predicting DFU healing. However, the current literature does not provide strong support for the use of TcPO2 as an independent predictive tool. Methods: This protocol aims to systematically review the available evidence according to PRISMA (2020) guidelines, registered with the International Prospective Register of Systematic Reviews (registration number: CRD42024505907). The following databases will be used: Cochrane Library, EMBASE, Ovid Medline, PubMed, and Web of Science. Additionally, a manual search will be conducted through the references of the included articles. Results: The systematic review will summarize the current evidence on the prognostic value of TcPO2 in DFU healing, identifying gaps in knowledge and potential areas for future research. Conclusions: The findings of this study may clarify the prognostic value of TcPO2 in DFU healing, which could ultimately facilitate clinical management, decision-making, patient care, and potentially reduce treatment costs.

Comparison of Diffusion-Weighted MRI Using Single-Shot Echo-Planar Imaging and Split Acquisition of Fast Spin-Echo Signal Imaging, a Non-EPI Technique, in Tumors of the Head and Neck

BACKGROUND AND PURPOSE

DWI using single-shot echo-planar imaging (DWI-EPI) is susceptible to distortions around air-filled cavities and dental fillings, typical for the head and neck area. Non-EPI, split acquisition of fast spin-echo signals for diffusion imaging (DW-SPLICE) could reduce these distortions and enhance image quality, thereby potentially improving recurrence assessment in squamous cell carcinoma (SCC) of the head and neck region. This study evaluated whether DW-SPLICE is a viable alternative to DWI-EPI through quantitative and qualitative analyses.

MATERIALS AND METHODS

The DW-SPLICE sequence was incorporated into the standard 3T head and neck MRI protocol with DWI-EPI. Retrospective analysis was conducted on 2 subgroups: first benign or malignant lesions, and second, posttreatment SCC recurrence. In both subgroups, image quality and distortion were scored by 2 independent radiologists, blinded to the DWI technique and evaluated using mixed-effect linear models. Lesion ADC values were assessed with interclass correlation and Bland-Altman analyses. The delineation geometric similarity of DWI to T1-weighted postcontrast MRI was evaluated using the DSC before and after registration. Recurrence in posttreatment SCC scans was evaluated by the same 2 radiologists blinded to the DWI technique. Recurrence detection rates were then compared between DW-SPLICE and DWI-EPI using mixed logistic regression at 6 months and 1 year postscan follow-up data.

RESULTS

From August 2020 to January 2022, fifty-five benign or malignant lesion scans (55 patients) and 74 posttreatment SCC scans (66 patients) were analyzed. DW-SPLICE scored better on image quality and showed less overall distortion than DWI-EPI (0.04

CONCLUSIONS

DW-SPLICE surpasses DWI-EPI on image distortion and quality and improves diagnostic reliability for detecting recurrent or residual SCC on 3T MRI of the head and neck. Consistent use of 1 method for follow-up is advised, because ADC values are not completely interchangeable. Integrating DW-SPLICE can significantly improve tumor assessments in clinical practice.

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MESH Headings

• Humans
• Echo-Planar Imaging/methods
• Diffusion Magnetic Resonance Imaging/methods
• Head and Neck Neoplasms/pathology
• Head and Neck Neoplasms/diagnostic imaging
• Male
• Female
• Middle Aged
• Aged
• Adult
• Reproducibility of Results
• Retrospective Studies
• Carcinoma, Squamous Cell/pathology
• Carcinoma, Squamous Cell/diagnostic imaging
• Aged, 80 and over
• Neoplasm Recurrence, Local/diagnostic imaging
• Sensitivity and Specificity
• Squamous Cell Carcinoma of Head and Neck/diagnostic imaging
• Image Interpretation, Computer-Assisted/methods

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Affiliation(s)

Hedda J van der Hulst From the Department of Radiology (H.J.v.d.H., L.B., B.W., G.A., M.A., R.G.H.B.-T., J.A.C.), Netherlands Cancer Institute, Amsterdam, the Netherlands GROW School for Oncology and Developmental Biology (H.J.v.d.H., R.G.H.B.-T.), University of Maastricht, Maastricht, the Netherlands Department of Head and Neck Oncology and Surgery (H.J.v.d.H., M.A., M.W.M.v.d.B.), the Netherlands Cancer Institute, Amsterdam, the Netherlands
Loes Braun From the Department of Radiology (H.J.v.d.H., L.B., B.W., G.A., M.A., R.G.H.B.-T., J.A.C.), Netherlands Cancer Institute, Amsterdam, the Netherlands
Bram Westerink From the Department of Radiology (H.J.v.d.H., L.B., B.W., G.A., M.A., R.G.H.B.-T., J.A.C.), Netherlands Cancer Institute, Amsterdam, the Netherlands
Georgios Agrotis From the Department of Radiology (H.J.v.d.H., L.B., B.W., G.A., M.A., R.G.H.B.-T., J.A.C.), Netherlands Cancer Institute, Amsterdam, the Netherlands Department of Radiology (G.A.), University Hospital of Larissa, Thessaly, Greece
Leon C Ter Beek Department of Clinical Physics (L.C.t.B.), Netherlands Cancer Institute, Amsterdam, the Netherlands
Renaud Tissier Biostatistics Unit (R.T.), Netherlands Cancer Institute, Amsterdam, the Netherlands
Milad Ahmadian From the Department of Radiology (H.J.v.d.H., L.B., B.W., G.A., M.A., R.G.H.B.-T., J.A.C.), Netherlands Cancer Institute, Amsterdam, the Netherlands Department of Head and Neck Oncology and Surgery (H.J.v.d.H., M.A., M.W.M.v.d.B.), the Netherlands Cancer Institute, Amsterdam, the Netherlands Amsterdam Center for Language and Communication (M.A.), University of Amsterdam, Amsterdam, the Netherlands
Roland M Martens Department of Radiology and Nuclear Medicine (R.M.M.), Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
Jan W Casselman Department of Radiology (J.W.C.), Dalhousie University, Halifax, Nova Scotia, Canada Department of Radiology (J.W.C.), Arizona St Lucas Gent, Ghent, Belgium
Regina G H Beets-Tan From the Department of Radiology (H.J.v.d.H., L.B., B.W., G.A., M.A., R.G.H.B.-T., J.A.C.), Netherlands Cancer Institute, Amsterdam, the Netherlands GROW School for Oncology and Developmental Biology (H.J.v.d.H., R.G.H.B.-T.), University of Maastricht, Maastricht, the Netherlands Department of Regional Health Research (R.G.H.B.-T.), University of Southern Denmark, Odense, Denmark
Michiel W M van den Brekel Department of Head and Neck Oncology and Surgery (H.J.v.d.H., M.A., M.W.M.v.d.B.), the Netherlands Cancer Institute, Amsterdam, the Netherlands Department of Oral and Maxillofacial Surgery (M.W.M.v.d.B.), Amsterdam University Medical Center, Amsterdam, the Netherlands
Jonas A Castelijns From the Department of Radiology (H.J.v.d.H., L.B., B.W., G.A., M.A., R.G.H.B.-T., J.A.C.), Netherlands Cancer Institute, Amsterdam, the Netherlands

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Cochlear Implantation in Vestibular Schwannoma Surgery: Diagnostic Accuracy Analysis of Intraoperative Monitoring with Intracochlear Electrode

OBJECTIVE

To investigate the role of intraoperative cochlear nerve (CN) electric monitoring with MED-EL intracochlear test electrode (ITE) in assessing the CN functional integrity.

SETTING

Tertiary referral center.

PATIENTS

Patients with intrameatal or 2 to 13 mm in the cerebello-pontine angle vestibular schwannoma (VS), not suitable for hearing preservation surgery but eligible for tumor resection via translabyrinthine approach and simultaneous cochlear implant (CI) rehabilitation.

INTERVENTION

ITE was used to register electrically evoked auditory brainstem response (eABR) before and after VS resection. All patients with anatomical preservation of CN underwent CI, regardless of eABR results, which served as the index test and was compared with postoperative sound perception by CI stimuli (gold standard test).

RESULTS

Twelve of seventeen cases allowed anatomical preservation of CN and were considered for the study. Seven of twelve cases demonstrated sound detection with CI, and six of twelve showed some degree of speech discrimination. eABR test with ITE achieved an accuracy of 66.7%, a sensitivity of 42.9%, and a specificity of 100%. Positive and negative predictive values were 100% and 55.6%, respectively.

CONCLUSION

When eABR can be evoked with ITE, the attempt of CI was likely to be successful, whereas in cases of eABR absence, other factors should be considered to reduce unsuccessful CI and not preclude rehabilitation in patients who would benefit from CI. Further studies and longer follow-up are needed to analyze the role of ITE in VS surgery with CI.

Digital hand-held arthrometry is a reliable and accurate adjunct for diagnosing acute anterior cruciate ligament tears

Purpose

To evaluate the intrarater reliability and predictive validity of Lachmeter® measurements for diagnosing acute anterior cruciate ligament (ACL) tears, and to propose diagnostic thresholds.

Methods

Lachmeter® measurements were recorded during the stabilised Lachman test for consecutive participants presenting to an acute knee injury clinic within 21-days of injury. Intrarater reliability for individual limb and side-to-side (STS) difference (injured limb minus uninjured limb) measurements was investigated using a cross-sectional, repeated-measures design and the intraclass correlation coefficient (ICC). The predictive validity of STS difference and injured limb measurements was investigated using a prospective cohort design; sensitivity, specificity, negative (LR-) and positive likelihood ratios (LR+) were calculated using magnetic resonance imaging as the reference standard.

Results

Intrarater reliability was excellent for individual limb and STS difference measurements in 102 participants. Of the 63 participants included in the validity analysis, 31 had a normal ACL and 32 had an ACL tear. LR- point estimates for STS differences <1.4 mm (0.07 [95% confidence interval [CI]: 0.02-0.29]) or injured limb measurements <7.5 mm (0.09 [95% CI: 0.02-0.34] produced 'large' shifts in the probability of ruling out an ACL tear. LR+ point estimates for STS differences ≥3.8 mm (10.67 [95% CI: 2.68-42.51]) or injured limb measurements ≥11.8 mm (10.67 [95% CI: 1.42-80.26]) produced 'large' shifts in the probability of ruling in a full-thickness ACL tear.

Conclusion

In participants presenting within 21-days of knee injury, intrarater reliability was excellent for Lachmeter® measurements recorded during the stabilised Lachman test. Based on predictive validity estimates, Lachmeter® measurements can be used to differentiate normal from torn ACLs in acute presentations, but not partial from full-thickness ACL tears. Diagnostic thresholds are proposed based on STS difference and injured limb measurements, and with consideration of the Lachman end point. Level of Evidence: Level I.

Optimization of a milk pregnancy-associated glycoprotein enzyme-linked immunosorbent assay test for pregnancy in Holstein cows using time-dependent cut-points between 23 and 90 days after insemination

Our hypothesis was that the accuracy of a commercial milk pregnancy-associated glycoprotein (PAG) ELISA test using the same thresholds at all stages of gestation would be improved by adjusting the cut-points according to the number of days since last breeding (DSLB) between 23 and 90 d after insemination in Holstein dairy cows. Our objectives were to develop a DSLB-specific set of thresholds that would provide better test performance under field conditions and provide more information for the inconclusive test results, by dichotomizing these into "probably open" and "probably pregnant" categories. Milk samples (n = 182,738) submitted to the Lactanet (Canadian Dairy Herd Improvement) laboratory from 2013 to 2021 for pregnancy testing using a commercial PAG ELISA test were compared with records on insemination outcomes. The data were separated randomly into a training dataset used to develop the DSLB-specific interpretation grid and a validation dataset to quantify its test characteristics and compare the performance of the DSLB-specific and fixed thresholds. Our aim was to achieve negative predictive value >0.99 at all stages of test use and positive predictive value (PPV) ≥0.95 at ≤59 d and ≥0.99 between 60 and 90 d after insemination. Neither approach met these targets between 23 and 25 DSLB. The DSLB-specific interpretation grid had greater PPV than the fixed threshold between 26 and 49 DSLB and met the targets. Both approaches were very near the targets of performance between 50 and 90 DSLB. The DSLB-specific interpretation grid has a similar prevalence of inconclusive test results compared with the fixed threshold but provided additional information on the likelihood of the cow being pregnant or open. Classification of milk PAG results using DSLB-specific cut-points improved the predictive value of pregnancy diagnosis between 23 and 49 d after insemination.

Comparative analysis of deep learning architectures for thyroid eye disease detection using facial photographs

PURPOSE

To compare two artificial intelligence (AI) models, residual neural networks ResNet-50 and ResNet-101, for screening thyroid eye disease (TED) using frontal face photographs, and to test these models under clinical conditions.

METHODS

A total of 1601 face photographs were obtained. These photographs were preprocessed by cropping to a region centered around the eyes. For the deep learning process, photographs from 643 TED patients and 643 healthy individuals were used for training the ResNet models. Additionally, 81 photographs of TED patients and 74 of normal subjects were used as the validation dataset. Finally, 80 TED cases and 80 healthy subjects comprised the test dataset. For application tests under clinical conditions, data from 25 TED patients and 25 healthy individuals were utilized to evaluate the non-inferiority of the AI models, with general ophthalmologists and fellowships as the control group.

RESULTS

In the test set verification of the ResNet-50 AI model, the area under the receiver operating characteristic (ROC) curve (AUC), accuracy, sensitivity, and specificity were 0.94, 0.88, 0.64, and 0.92, respectively. For the ResNet-101 AI model, these metrics were 0.93, 0.84, 0.76, and 0.92, respectively. In the application tests under clinical conditions, to evaluate the non-inferiority of the ResNet-50 AI model, the AUC, accuracy, sensitivity, and specificity were 0.82, 0.82, 0.88, and 0.76, respectively. For the ResNet-101 AI model, these metrics were 0.91, 0.84, 0.92, and 0.76, respectively, with no statistically significant differences between the two models for any of the metrics (all p-values > 0.05).

CONCLUSIONS

Face image-based TED screening using ResNet-50 and ResNet-101 AI models shows acceptable accuracy, sensitivity, and specificity for distinguishing TED from healthy subjects.

Diagnostic accuracy of hip joint ultrasound for detection of calcium pyrophosphate deposition

OBJECTIVE

CPPD disease is a chronic and disabling arthropathy. US has been shown to be a tool with high sensitivity and specificity for the diagnosis of CPPD disease, but its value at the hip joint has not yet been determined. Therefore, our objective was to evaluate the diagnostic accuracy of US for the identification of CPP crystals in the hip joint as compared with histopathology.

METHODS

Diagnostic test study involving patients over 50 years of age with osteoarthritis, scheduled for hip replacement surgery. US was performed on the affected hip. Acetabular fibrocartilage (FC) and hyaline cartilage (HC) of the femoral head were assessed, and a dichotomous score was used for the presence/absence of CPP crystals. SF was obtained from the affected hip and examined using polarized light microscopy. Histopathological examination was performed by an experienced pathologist in search of CPP crystals in FC and HC samples.

RESULTS

One hundred patients were enrolled, of whom 62% were found to have hyperechoic areas suggestive of CPP deposition on US examination. Pathological evaluation revealed a prevalence of 61% of CPP crystals. The sensitivity, specificity and the positive predictive and the negative predictive values were 90%, 82%, 89%, and 84%, respectively. The area under the curve for US compared with histopathology for the diagnosis of hip CPPD was 0.86 (95% CI: 0.78-0.94).

CONCLUSION

US is a valid imaging modality with good diagnostic accuracy for the detection of hip CPPD.

The Value of Second-look Ultrasound and Mammography for Assessment and Biopsy of MRI-detected Breast Lesions

RATIONALE AND OBJECTIVES

Suspicious lesions detected in multiparametric breast MRI can be further analyzed with second-look ultrasound (SLUS) and/or mammography. This study aims to assess the value of second-look imaging in selecting the appropriate biopsy method for different lesion characteristics.

MATERIALS AND METHODS

Between January 2021 and December 2023, 212 women underwent contrast-enhanced multiparametric breast MRI at 3 Tesla. A total of 241 suspicious lesions (108 malignancies, 44.8%) were further assessed with SLUS and second-look mammography. Subsequent image-guided biopsy of each lesion was performed using the most suitable modality. Size-dependent lesion detection rates in SLUS and mammography were compared by means of the McNemar test.

RESULTS

Lesions referred to MRI-guided biopsy were predominantly ≤ 10 mm in size (52.8%). SLUS allowed for higher detection rates than mammography in mass lesions (55.6% [95% confidence interval 46.4-64.4%] versus 16.7% [10.6-24.3%]; p < 0.001) with a particularly high sensitivity for malignant mass lesions > 10 mm (88.5% [69.9-97.6%]). In contrast, the detection rate for malignant non-mass lesions was lower in SLUS than in second-look mammography (22.0% [11.5-36.0%] versus 38.0% [24.7-52.8%]; p < 0.001). The malignancy rates in ultrasound-, mammography-, and MRI-guided biopsies were 53.7%, 55.2%, and 35.0%, respectively.

CONCLUSION

SLUS is an excellent tool for further assessment and biopsy of suspicious mass lesions > 10 mm without associated calcifications. In contrast, supplemental ultrasound is of limited value in the evaluation and biopsy guidance of suspicious non-mass lesions compared to second-look mammography.

A comparison of the accuracy and feasibility of a low-cost mobile application versus higher-cost handheld 3D scanner for digital ear prosthetics

BACKGROUND

Facial prosthetics are an important means to rehabilitate patients with congenital or acquired facial defects. However, with a time-consuming manual workflow and workforce shortage, access to facial prosthetics is limited in Australia and worldwide, especially for rural and remote patients. Optical 3D scanning has been increasingly integrated in digitizing data. With the development of TrueDepth® camera technology on smartphones, there is increasing availability of mobile applications which can generate 3D images to improve accessibility and reduce cost. This study compares the accuracy of mobile phone applications to high resolution 3D scanners for auricular data acquisition.

METHODS

We conducted a case-control study comparing the EM3D smartphone application (EM3D) with the EinScan Pro 2× Plus Shining 3D handheld scanner (EinScan) in 22 healthy participants equating to 44 ears, using CloudCompare software analysis.

RESULTS

On average, EM3D acquired images 2.5 minutes quicker than the EinScan. The mean absolute directional distance difference was 1.10 mm, within the accepted deviation range of 2 mm. Out of the 44 ears, only 1 ear (2.27%) did not meet the accepted value of accuracy within 2 mm. The average completeness was 85% and the overall quality of images obtained from EinScanand EM3D were 53.5% and 57.7%, respectively, through observational analysis.

CONCLUSION

Mobile iPhone applications such as EM3D are a viable alternative to 3D handheld scanners such as EinScan. This study demonstrates reliable results in accuracy, and improved results in time, cost and operational feasibility.

Artificial intelligence in bronchoscopy: a systematic review

BACKGROUND

Artificial intelligence (AI) systems have been implemented to improve the diagnostic yield and operators' skills within endoscopy. Similar AI systems are now emerging in bronchoscopy. Our objective was to identify and describe AI systems in bronchoscopy.

METHODS

A systematic review was performed using MEDLINE, Embase and Scopus databases, focusing on two terms: bronchoscopy and AI. All studies had to evaluate their AI against human ratings. The methodological quality of each study was assessed using the Medical Education Research Study Quality Instrument (MERSQI).

RESULTS

1196 studies were identified, with 20 passing the eligibility criteria. The studies could be divided into three categories: nine studies in airway anatomy and navigation, seven studies in computer-aided detection and classification of nodules in endobronchial ultrasound, and four studies in rapid on-site evaluation. 16 were assessment studies, with 12 showing equal performance and four showing superior performance of AI compared with human ratings. Four studies within airway anatomy implemented their AI, all favouring AI guidance to no AI guidance. The methodological quality of the studies was moderate (mean MERSQI 12.9 points, out of a maximum 18 points).

INTERPRETATION

20 studies developed AI systems, with only four examining the implementation of their AI. The four studies were all within airway navigation and favoured AI to no AI in a simulated setting. Future implementation studies are warranted to test for the clinical effect of AI systems within bronchoscopy.

Ultrasound-Guided Versus Freehand Fine Needle Aspiration: A Comparative Study in Diagnosing Non-Salivary, Non-Thyroidal Head, and Neck Masses

Background Fine needle aspiration cytology (FNAC) is widely used to evaluate head and neck masses, with both ultrasound (US)-guided and freehand techniques being employed. While US-guided FNAC is thought to enhance accuracy, freehand FNAC remains commonly used due to its practicality and speed. This study compares the diagnostic performance of US-guided and freehand FNAC, evaluating their sensitivity, specificity, accuracy, inconclusive rates, and time to histological confirmation. Aim of the study The aim of this study is to compare the inconclusive rates and time to histological confirmation of US-guided versus freehand FNAC in assessing non-salivary, non-thyroidal head, and neck masses. Methods A retrospective analysis of 439 FNAC reports (2012-2016) was conducted. Diagnostic metrics, including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, inconclusive rates, and median time to histological confirmation, were analyzed. Results Among 439 FNAC procedures, 294 were US-guided and 145 were freehand. US-guided FNAC had a lower inconclusive rate (11.6% vs. 17.9%; p = 0.068) and higher specificity (61% vs. 38%), while sensitivity was comparable (91% vs. 95%). Accuracy was 81.6% for US-guided FNAC and 86.3% for freehand FNAC. Freehand FNAC had a shorter median reporting time (29 vs. 42 days). Conclusions Both techniques demonstrated similar diagnostic accuracy. While US-guided FNAC reduced inconclusive rates and improved specificity, freehand FNAC provided faster results, aiding quicker clinical decision-making. These findings suggest that both techniques have distinct benefits, and their use should be tailored to individual patient needs and clinical settings.

Diagnostic performance of a novel point-of-care test for the diagnosis of visceral leishmaniasis in Sudan: A Comparative Accuracy Study

METHODS

This study enrolled 107 VL suspects who attended a health centre in Gedaref between October 2022 and June 2023. Diagnostic accuracy was assessed by comparing the performance of the new index test (INgezimLeishma-CROM) with the comparator test (IT-LEISH) and parasitological examination as reference standard.

RESULTS

Of 107 VL suspects screened by parasitological examination, 77 VL patients were smear positive and 30 were smear negative. Independent serological testing of these patients using INgezim Leishma-CROM showed a sensitivity of 98.7% [95% CI 92.23-99.97] and specificity of 92.5% [95% CI 75.71-99.09]. For IT-LEISH, both sensitivity [95% CI 84.39-97.20] and specificity [95% CI 75.71-99.09] were 92.5%. INgezim Leishma-CROM demonstrated increased diagnostic accuracy (97.2%) compared to IT-LEISH RDT (92.5%). Both RDTs gave positive results in 2 cases from the smear negative group that were previously treated for VL. All other non-VL cases (malaria, typhoid, brucellosis) were negative in both RDTs, showing 100% specificity, while VL patients co-infected with malaria were positive in both tests. Within the smear-negative group, 3 VL symptomatic cases that had been previously treated but still show clinical signs were all positive with INgezim Leishma-CROM but only 2 cases were positive with IT-LEISH.

Novel pain assessment tool specific for pulp symptoms to aid diagnosis

AIM

Although many pain assessment tools exist, none are specific to the relatively unique presentation of pulpal pain. The aim of this study was to develop and validate a novel pain assessment tool based on pulp symptoms.

METHODOLOGY

A preliminary list of items best-describing pulpitis was developed based on deductive and inductive approaches and the preliminary tool was piloted (n = 80). A final 11-item pain assessment tool was developed comprising 5 closed-ended items evaluating pain intensity to diverse stimuli (thermal and sweet) and 6 closed-ended items assessing various aspects of pulp pain (such as spontaneity, duration, referral, postural pain, pain upon biting and requirement for analgesics). The tool was tested on 300 adult patients (age range = 18-54 years) who presented with symptoms indicating some form of pulpitis. The 11 items were each scored from 1 to 4, yielding a total score between 11 and 44. These scores were subsequently compared to a set of diagnoses made utilizing established clinical reference standards, these include patient history, clinical examination, periapical radiographs, and pulp testing.

RESULTS

All items in the tool reached an excellent content validity index score (≥0.83) for relevance. Following the pilot, six items were rephrased and five were removed. After final testing the constructed tool had a reliability coefficient of .8641, indicating a high level of internal consistency. Factor analysis extracted two factors that accounted for 59.61% of variance. The sensitivity and specificity was 95.36% and 86.58%, respectively. Likelihood ratio was 7.104 (LR+) and 0.05 (LR-) at cut-off point. The area under the ROC curve was 0.9714 with a SE of 0.0076. The cut off score by Youden index was 25 between reversible and irreversible pulpitis.

CONCLUSIONS

The developed tool proved to be both valid and reliable. It is the first comprehensive multidimensional tool designed to standardize the pulp pain assessment protocol, covering various attributes of pulp pain and effectively distinguishing between reversible and irreversible pulpitis with a defined cut-off score. Furthermore, its use is anticipated to provide support in diagnosing ambiguous cases of inflamed pulp, which is especially helpful for less experienced dentists.

Subjective and objectives measures of frailty among adults with advanced chronic kidney disease: a cross-sectional analysis of clinician misclassification

BACKGROUND

Frailty is a recognisable clinical measure of impaired physiological reserve and vulnerability to adverse outcomes that is validated among patients with kidney disease. Practice patterns reveal inconsistent use of objective frailty measures by nephrologists, with clinicians prioritising subjective clinical impressions, possibly risking misclassification and discrimination.

AIMS

The aim of this study was to examine correlations between subjective and objective measures of frailty in a cohort of patients attending routine nephrologist review.

METHODS

Eighty-nine participants attending scheduled review with their primary treating nephrologist (n = 6) were included in cross-sectional analysis. Measured frailty based on Fried phenotype and subjective clinician impression were assessed for congruence using Pearson's correlation analysis and ĸ statistic. Ordinal logistic regression examined patient demographics associated with perceived frailty. Misclassification was explored using descriptive statistics and contingency table analysis.

RESULTS

Frailty and prefrailty were prevalent by both objective and subjective means of assessment with minimal correlation between clinician impression and measured Fried phenotype (r = 0.50, P = 0.00, ĸ = 0.25, P =& 0.00). Subjective clinician impression misclassified half of participants, influenced by surrogate frailty measures including female sex, comorbidity and reliance on a walking aid. Clinicians were equally likely to over-classify prefrailty as to under-recognise established frailty, with no evidence of systemic misclassification bias. Subjective clinican impression of frailty had a positive predictive value of 19.1% and a negative predictive value of 56.2%.

CONCLUSIONS

Nephrologists' reliance on subjective clinical impressions that overlook or misclassify prefrailty offers incomplete prognostic assessment and potentially misses opportunities for early intervention.

Is the YES/NO classification accurate in screening scapular dyskinesis in asymptomatic individuals? - A novel validation study utilizing surface electromyography as a surrogate measure in identifying movement asymmetries

BACKGROUND

Scapular dyskinesis is a known risk factor for shoulder pain, making it important to screen for prevention. Physical therapists screen scapular dyskinesis by visually comparing asymmetries in scapular movement during overhead reach using the Scapular Dyskinesis Test Yes/No classification (Y/N). Although scapular kinematics has been used to quantify scapular dyskinesis, current measurement techniques are inaccurate. Optimal scapular muscle activity is crucial for normal shoulder function and is measured using surface electromyography (sEMG). Research suggests that impaired scapular muscles can lead to scapular dyskinesis. Despite kinematics being a poor reference standard, there is currently no validated method to identify movement asymmetries using muscle activity as an alternative. We utilized sEMG to establish Y/N's validity. We hypothesized that Y/N is a valid tool using sEMG as a viable surrogate measure for identifying scapular dyskinesis.

METHODS

We employed a known-groups (symmetrical vs. asymmetrical shoulders) validity design following the Standards for Reporting Diagnostic Accuracy Studies. Seventy-two asymptomatic subjects were evaluated using Y/N as the index test and sEMG as the reference standard. We created a criterion to assign the sEMG as the reference standard to establish the known groups. We calculated the sensitivity (Sn), specificity (Sp), positive and negative predictive values (PPV, NPV), likelihood ratios (LR+, LR-), and diagnostic odds ratio (DOR) using a 2 × 2 table analysis.

RESULTS

The diagnostic accuracy values were Sn = 0.56 (0.37-0.74), Sp = 0.36 (0.08-0.65), PPV = 0.68 (0.49-0.88), NPV = 0.25 (0.04-0.46), LR+ = 0.87 (0.50-1.53), and LR- = 1.22 (0.50-2.97).

CONCLUSION

The Y/N's diagnostic accuracy was poor against the sEMG, suggesting clinicians should rely less on Y/N to screen scapular dyskinesis in the asymptomatic population. Our study demonstrated that sEMG might be a suitable alternative as a reference standard in validating methods designed to screen movement asymmetries.

Diagnostic validity of drinking behaviour for identifying alcohol use disorder: Findings from a representative sample of community adults and an inpatient clinical sample

BACKGROUND AND AIMS

Alcohol consumption is an inherent feature of alcohol use disorder (AUD), and drinking patterns may be diagnostically informative. This study had three aims: (1) to examine the classification accuracy of several individually analysed drinking behavior measures in a large sample of US community adults; (2) to extend the findings to an adult clinical sample; and (3) to examine potential sex differences.

DESIGN

In cross-sectional epidemiological and clinical datasets, receiver operating characteristic (ROC) curves were used to evaluate diagnostic classification using area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV).

SETTING AND PARTICIPANTS

Two samples were examined: a large random sample of US community adults who reported past-year drinking (n = 25 773, AUD = 20%) and a clinical sample from a Canadian inpatient addiction treatment centre (n = 1341, AUD = 82%).

MEASUREMENTS

Classifiers included measures of quantity/frequency (e.g. drinks/drinking day, largest drinks/drinking day, number of drinking days and heavy drinking frequency). The clinical criterion (reference standard) was AUD diagnostic status per structured clinical interview (community sample) or a symptom checklist (clinical sample).

FINDINGS

All drinking indicators were statistically significant classifiers of AUD (AUCs = 0.60-0.92, Ps<0.0001). Heavy drinking frequency indicators performed optimally in both the community (AUCs = 0.78-0.87; accuracy = 0.72-0.80) and clinical (AUCs = 0.85-0.92; accuracy = 0.77-0.89) samples. Collectively, the most discriminating drinking behaviours were number of heavy drinking episodes and frequency of exceeding drinking low-risk guidelines. No substantive sex differences were observed across drinking metrics.

CONCLUSIONS

Quantitative drinking indices appear to perform well at classifying alcohol use disorder (AUD) in both a large community adult and inpatient sample, robustly identifying AUD at rates much better than chance and above accepted clinical classification benchmarks, with limited differences by sex. These findings broadly support the potential clinical utility of quantitative drinking indicators in routine patient assessment.

Real-Time Snoring Detection Using Deep Learning: A Home-Based Smartphone Approach for Sleep Monitoring

Background

Despite the prevalence of sleep-related disorders, few studies have developed deep learning models to predict snoring using home-recorded smartphone audio. This study proposes a real-time snoring detection method utilizing a Vision Transformer-based deep learning model and smartphone recordings.

Methods

Participants' sleep-breathing sounds were recorded using smartphones, with concurrent Level I or II polysomnography (PSG) conducted in home or hospital settings. A total of 200 minutes of smartphone audio per participant, corresponding to 400 30-second sleep stage epochs on PSG, were sampled. Each epoch was annotated independently by two trained labelers, with snoring labeled only when both agreed. Model performance was evaluated by epoch-by-epoch prediction accuracy and correlation between observed and predicted snoring ratios.

Results

The study included 214 participants (85,600 epochs). Hospital audio data from 105 participants (42,000 epochs) were used for training, while home audio data from 109 participants were split into 54 participants (21,600 epochs) for training and 55 participants (22,000 epochs) for testing. On the test dataset, the model demonstrated a sensitivity of 89.8% and a specificity of 91.3%. Correlation analysis showed strong agreement between observed and predicted snoring ratios (r = 0.97, 95% CI: 0.95-0.99).

Conclusion

This study demonstrates the feasibility of using deep learning for real-time snoring detection from home-recorded smartphone audio. With high accuracy and scalability, the approach offers a practical and accessible tool for monitoring sleep-related disorders, paving the way for home-based sleep health management solutions.

International external validation of the SORG machine learning algorithm for predicting sustained postoperative opioid prescription after anterior cervical discectomy and fusion using a Taiwanese cohort of 1,037 patients

BACKGROUND CONTEXT

Anterior cervical discectomy and fusion (ACDF) is widely performed for cervical spine disorders, with opioids commonly prescribed postoperatively for pain management. However, prolonged opioid use carries significant risks such as dependency and adverse health effects. Predictive models like the SORG machine learning algorithm (SORG-MLA) have been developed to forecast prolonged opioid use post-ACDF. External validation is essential to ensure their effectiveness across different healthcare settings and populations.

PURPOSE

The study aimed to assess the generalizability of the SORG-MLA to a Taiwanese patient cohort for predicting prolonged opioid use after ACDF.

STUDY DESIGN

Retrospective cohort study utilizing data from a tertiary care center in Taiwan.

PATIENT SAMPLE

1,037 patients who underwent ACDF between 2010 and 2018 were included.

OUTCOME MEASURES

The primary outcome was sustained postoperative opioid prescription defined as continuous opioid use for at least 90 days following ACDF.

METHODS

The performance of the SORG-MLA in the validation cohort was assessed using discrimination measures (area under the receiver operating characteristic curve [AUROC] and the area under the precision-recall curve [AUPRC]), calibration, overall performance (Brier Score), and decision curve analysis. Comparing the validation cohort to the developmental revealed significant differences in demographic profiles, medicolegal frameworks, ethnic cultural contexts and key predictors of postoperative opioid use identified by the SORG-MLA. The Taiwanese cohort was characterized by an older age demographic, a lower proportion of female participants, higher smoking prevalence, higher incidence of preoperative myelopathy and radiculopathy, and more frequent use of antidepressants prior to surgery. Conversely, these patients were less likely to have extended preoperative opioid prescriptions beyond 180 days, undergo multilevel ACDF procedures, or be treated with concurrent medications such as Beta-2 agonists, Gabapentin, and ACE inhibitors. This study had no funding source or conflict of interests.

RESULTS

The model demonstrated good discriminative ability, with an AUROC of 0.78 and an AUPRC of 0.35. Calibration curves indicated that the model overestimated the risk of prolonged opioid use. This discrepancy may be attributed to the significantly higher incidence of sustained opioid consumption in the American development cohort, spanning from 2000 to 2018, which was threefold higher than that in the Taiwanese validation cohort between 2010 and 2018 (9.9% [270/2737] vs. 3.3% [34/1037]; p < .01). The Brier score was 0.033, which improved upon the null model's score of 0.040, indicating robust overall performance. Decision curve analysis confirmed the model's clinical utility, demonstrating net benefits across various decision thresholds.

CONCLUSIONS

The SORG-MLA has demonstrated robust discriminative abilities and overall performance when applied to a unique Taiwanese cohort. However, the model exhibited an overestimation of the risk of prolonged opioid use, suggesting the need for recalibration with more contemporary data to reflect current opioid prescription practices, ethnic and cultural differences, and opioid regulations. Following recalibration, integration and prospective validation within the electronic healthcare system should be pursued. This will enable clinicians to proactively identify patients at heightened risk of prolonged opioid use following ACDF.

Cytochemical analysis of cerebrospinal fluid in tuberculous meningitis versus other etiologies

BACKGROUND

Meningeal tuberculosis (TBM) is the most severe form of extrapulmonary tuberculosis due to its high mortality and long-term sequelae in survivors.

METHODS

A cross-sectional study of diagnostic tests was carried out in a private clinical laboratory in Lima, Peru. All cerebrospinal fluid (CSF) samples from patients with suspected meningitis were analyzed with cytochemical and biochemical studies, as well as smear microscopy, India ink, the FilmArray Meningitis/Encephalitis panel, Xpert® MTB/RIF or Xpert MTB/RIF Ultra, and culture for common bacterias, fungi or mycobacterial.

RESULTS

450 CSF samples were included. The main microorganisms detected were Mycobacterium tuberculosis (8.9%), Cryptococcus neoformans (6.0%), and Streptococcus pneumoniae (2.4%). 97.5% of patients with TBM presented positive Xpert MTB/RIF or Ultra. The median number of red blood cells, leukocytes, and percentage of mononuclear cells, glucose, and proteins in the CSF was 57.5 cells/μl, 91.5 cells/μl, 70%, 22.5 mg/dL and 218.3 mg/dL, respectively. Likewise, patients with TMB had the lowest glucose levels (median: 22.5, IQR: 11 - 35) compared to other etiologies of meningitis. While bacterial meningitis had the highest leukocyte (median: 173 μl; IQR: 17 - 520) and protein levels (median: 289.7; IQR: 92 - 556).

CONCLUSION

The characteristics of the cytochemical study of CSF can guide the differential diagnosis by identifying general trends of tuberculous meningitis and other meningitis etiologies. However, it remains necessary to establish methods with greater precision to properly define the etiological agent causing meningitis.

The NERVE-ML (neural engineering reproducibility and validity essentials for machine learning) checklist: ensuring machine learning advances neural engineering. J Neural Eng 2025;22:021002. [PMID: 40073450 PMCID: PMC11948487 DOI: 10.1088/1741-2552/adbfbd] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Objective.Machine learning's (MLs) ability to capture intricate patterns makes it vital in neural engineering research. With its increasing use, ensuring the validity and reproducibility of ML methods is critical. Unfortunately, this has not always been the case in practice, as there have been recent retractions across various scientific fields due to the misuse of ML methods and validation procedures. To address these concerns, we propose the first version of the neural engineering reproducibility and validity essentials for ML (NERVE-ML) checklist, a framework designed to promote the transparent, reproducible, and valid application of ML in neural engineering.Approach.We highlight some of the unique challenges of model validation in neural engineering, including the difficulties from limited subject numbers, repeated or non-independent samples, and high subject heterogeneity. Through detailed case studies, we demonstrate how different validation approaches can lead to divergent scientific conclusions, highlighting the importance of selecting appropriate procedures guided by the NERVE-ML checklist. Effectively addressing these challenges and properly scoping scientific conclusions will ensure that ML contributes to, rather than hinders, progress in neural engineering.Main results.Our case studies demonstrate that improper validation approaches can result in flawed studies or overclaimed scientific conclusions, complicating the scientific discourse. The NERVE-ML checklist effectively addresses these concerns by providing guidelines to ensure that ML approaches in neural engineering are reproducible and lead to valid scientific conclusions.Significance.By effectively addressing these challenges and properly scoping scientific conclusions guided by the NERVE-ML checklist, we aim to help pave the way for a future where ML reliably enhances the quality and impact of neural engineering research.

Relationship Between Infrared Thermography and Functional Parameters in the Lower Limbs of Hemiplegic Patients

INTRODUCTION

Reliable objective and non-invasive assessments of myotendinous alterations in patients with muscle tone disorders secondary to brain damage represent an important challenge in health science. The aim of this study was to observe the relationship between the skin temperature and the functional response in the triceps suralis of hemiplegic patients in relation to the healthy control group.

METHODS

A descriptive observational study was conducted based on the STARD recommendations. A total of 26 volunteers, 13 participants with unilateral motor impairment and 13 healthy patients, participated and completed the study. Intragroup and intergroup clinical thermography tests were performed, and the results were compared in relation to the timed up and go test, pain threshold to pressure, and modified Ashworth scale.

RESULTS

Statistically relevant differences (p < 0.01) could be observed between the two groups in each test performed. Thermographic analysis revealed a difference in temperature between the healthy and affected sides in the inter- and intra-group comparisons. It was possible to observe statistically significant differences (p < 0.01) between limbs in the brain damage group (the side affected was at a lower temperature), while no such differences were observed between limbs in the healthy control group (p > 0.05).

CONCLUSIONS

Our results confirmed that clinical thermography could be a potentially useful tool in the assessment of both structural and functional alterations of the musculoskeletal system in patients with chronic brain damage.

Generalized Anxiety Disorder 7-item (GAD-7) and 2-item (GAD-2) scales for detecting anxiety disorders in adults

BACKGROUND

Anxiety disorders often remain undetected and can cause substantial burden. Amongst the many anxiety screening tools, the 7-item Generalized Anxiety Disorder (GAD-7) scale and its short version, the 2-item Generalized Anxiety Disorder (GAD-2) scale, are the most frequently used instruments.

OBJECTIVES

Primary: to determine the diagnostic accuracy of GAD-7 and GAD-2 to detect generalised anxiety disorder (GAD) and any anxiety disorder (AAD) in adults. Secondary: to investigate whether their diagnostic accuracy varies by setting, anxiety disorder prevalence, reference standard, and risk of bias; to compare the diagnostic accuracy of GAD-7 and GAD-2; to investigate how diagnostic performance changes with the test threshold.

SEARCH METHODS

We searched MEDLINE, Embase, PubMed-not-MEDLINE subset, and PsycINFO from 1990 to 18 January 2024. We checked reference lists of included studies and review articles.

SELECTION CRITERIA

We included cross-sectional studies conducted in adults, containing diagnostic accuracy information on GAD-7 and/or GAD-2 questionnaires for the target conditions generalised anxiety disorder and/or any anxiety disorder, and allowing the generation of 2x2 tables. The target conditions must have been diagnosed using a structured or semi-structured clinical interview. We excluded case-control studies and studies in which the time elapsed between the index tests and reference standards exceeded four weeks. We excluded studies involving people (1) seeking help in mental health settings or (2) recruited specifically due to mental health symptoms in other settings.

DATA COLLECTION AND ANALYSIS

At least two review authors independently decided on study eligibility, extracted data, and assessed the risk of bias and applicability of included studies. For each questionnaire and each target condition, we present sensitivity and specificity with 95% confidence intervals (95% CI) in forest plots. We used the bivariate model to obtain summary estimates based on cut-offs closest to the recommended values (i.e. within a core range). In secondary analyses, we used the bivariate model and the multiple thresholds model to obtain summary estimates for all available cut-off points. Using the multiple thresholds model, we also calculated the area under the receiver operating characteristic curve to obtain a general indicator of the diagnostic accuracy of GAD-7 and GAD-2.

MAIN RESULTS

We included 48 studies with 19,228 participants from 27 different countries, evaluating the GAD-7 and the GAD-2 in 24 different languages. Seven studies were performed in non-clinical settings, nine in clinical settings recruiting participants across conditions, and 32 in clinical settings with participants having specific conditions. Even after categorisation into three settings, the study populations were substantially different. The most frequently studied populations were people: with epilepsy (nine studies); with cancer (five studies); with cardiovascular disease (five studies); and in primary care regardless of their condition (five studies). We considered the risk of bias low in eight studies, and we had low concerns about the applicability of findings in three studies. Thirty-five studies contributed to the primary analyses of GAD-7 for detecting generalised anxiety disorder (median prevalence 12%); 22 studies to analyses of GAD-7 for any anxiety disorder (median prevalence 19%); 24 studies to analyses of GAD-2 for generalised anxiety disorder (median prevalence 9%); and 19 studies to analyses of GAD-2 for any anxiety disorder (median prevalence 19%). At the recommended cut-off of 10 or higher (or the closest available cut-off), the GAD-7 questionnaire yielded a summary sensitivity of 0.64 (95% CI 0.56 to 0.72) and a summary specificity of 0.91 (95% CI 0.87 to 0.93) in detecting generalised anxiety disorder. For detecting any anxiety disorder, summary sensitivity was 0.48 (95% CI 0.40 to 0.57) and summary specificity 0.91 (95% CI 0.89 to 0.93). At the recommended cut-off of 3 or higher (or the closest available cut-off), the GAD-2 yielded a summary sensitivity of 0.68 (95% CI 0.59 to 0.75) and a summary specificity of 0.86 (95% CI 0.82 to 0.89) for detecting generalised anxiety disorder. For detecting any anxiety disorder, the summary sensitivity was 0.53 (95% CI 0.44 to 0.62) and the summary specificity was 0.89 (95% CI 0.86 to 0.91). The 95% prediction region of GAD-7 for detecting generalised anxiety disorder was larger (indicating pronounced statistical heterogeneity) than for the three other analyses. Specificity varied by setting in the analysis of GAD-7 and GAD-2 for detecting any anxiety disorder, and by reference standard in the analysis of GAD-2 for detecting generalised anxiety disorder. Sensitivity varied with prevalence in the analysis of GAD-7 for generalised anxiety disorder. Other investigations of potential sources of heterogeneity did not show statistically significant associations with test accuracy. In all analyses, sensitivity tended to be higher and specificity lower in participants with specific conditions compared to the other two settings. Overall, the heterogeneity in the subgroup analyses remained high. The area under the receiver operating characteristic curve in the multiple thresholds model was 0.86 (95% CI 0.84 to 0.88) for the GAD-7 scale in detecting generalised anxiety disorder, and 0.80 (95% CI 0.78 to 0.82) in detecting any anxiety disorders. For the GAD-2 scale, the value was 0.82 (95% CI 0.81 to 0.86) for detecting generalised anxiety disorder, and 0.77 (95% CI 0.76 to 0.82) for detecting any anxiety disorders. Comparative bivariate analyses revealed no statistically significant differences between the diagnostic test accuracy of GAD-7 and GAD-2.

AUTHORS' CONCLUSIONS

The GAD-7 and the GAD-2 scales have been tested in numerous languages and different populations. Overall, the GAD-7 and the GAD-2 seem to have acceptable or good diagnostic accuracy for both generalised anxiety disorder and any anxiety disorder. The GAD-2 scale seems to have similar diagnostic accuracy as the GAD-7 scale. However, due to the diversity of the included studies and the heterogeneity of our findings, our summary estimates of sensitivity and specificity should be interpreted as rough averages. The performance of GAD-7 and GAD-2 may deviate substantially from these values in specific situations.

Oral washes and tongue swabs for Xpert MTB/RIF Ultra-based tuberculosis diagnosis in people with and without the ability to make sputum

Background

Oral samples show promise for tuberculosis (TB) diagnosis. Data from different samples and people with sputum scarce TB are limited.

Methods

We assessed Xpert MTB/RIF Ultra (Ultra) in symptomatic people at clinics (Cohort A, n=891) or at antiretroviral therapy (ART)-initiation without syndromic preselection (Cohort B, n=258). In Cohort A, we collected oral washes (OWs) and, separately, tongue swabs (flocked, foam with heat). In Cohort B, we collected OWs, three flocked tongue swabs (comparing one with heat to two pooled swabs) and, separately, buccal swabs, periodontal brushes. We offered sputum induction and did different culture methods on a subset of Cohort B tongue swabs.

Results

In Cohort A, Ultra on OWs, flocked tongue and foam swabs had sensitivities of 80% (95% confidence interval 56, 94), 59% (53, 65) and 65% (58, 72) and high specificities. In Cohort B, OWs and single heated swabs had 71% (42, 92) and 64% (35, 87) sensitivity, respectively. Pooled tongue swabs, buccal swabs and periodontal brushes had low sensitivities. MGIT960 had the highest sensitivity [64% (35, 87)] of culture methods. Oral sampling detected TB in sputum-scarce people [Cohort A: 25% (7/28) flocked and foam swab-positive; Cohort B: 18% (10/56) OW-, 23% (13/56) single flocked swab-positive]. In Cohort B, this would at least double the people with a positive Ultra result (sputum or oral) if induction were unavailable.

Conclusion

Ultra on OWs or foam tongue swabs has higher sensitivity than other oral-based approaches and detects sputum-scarce TB, resulted in more people diagnosed compared to Ultra on expectorated sputum.

Volume-based complete automation for ultrasound fetal biometry: A pilot approach to assess feasibility, reliability, and perspectives

BACKGROUND

Detection algorithms targeting anatomic landmarks in three-dimensional (3D) ultrasound (US) volume (three-dimensional US) appear to be a relevant and easy-to-implement option to address junior and occasional operators' difficulties in probe positioning for two-dimensional (2D) fetal biometry.

OBJECTIVES

This study assesses the feasibility of complete automation for fetal biometry and the resulting agreement with standard 2D (US) measurements. The secondary objectives were to assess the impact of software-driven measurement on image quality scoring, reproducibility, and agreement with human-driven measurements issued from the same volumes.

METHODS

Datasets were collected from a consecutive sample of women attending standard US follow-up (singleton, 16-30 weeks of gestation). Each dataset contained 2D measurements for reference (head and abdomen circumference and femoral length) and 3D US volume acquisitions of the fetal head, abdomen, and thigh. Both algorithm-based and operator-based detection of the targeted plans and calipers positioning were applied to the 3D volumes to produce software-driven and human-driven measurements. The resulting 3D measurements were assessed for completion rates, image quality, and reproducibility.

RESULTS

On 175 datasets collected, completion rates in achieving software-driven 3D measurements ranged between 94% (abdomen) and 100% (head). A modest weakening in quality (of uncertain clinical significance) was notable for the head and abdomen measurements. Compared to the 2D measurements, the software-driven tended to slightly overestimate the estimated fetal weight (EFW; e.g., 95% confidence interval ranging from 445 to 635 g for a 525 g-sized fetus at 22 weeks of gestation). The random error tended to be inflated for fetuses >700 g. Intra- and inter-operator reproducibility were appropriate (intraclass correlation coefficient intervals ranged from 0.8 to 0.99).

CONCLUSION

Complete automation of US biometry appears feasible and presents appropriate reproducibility and image quality scoring, but third-trimester biometry needs improvement. Before clinical implementation, it is time to assess the impact of point-of-care use on large populations.

Endoscopic Prediction of Achalasia: Putting the CART Before the CARS

BACKGROUND AND AIMS

Endoscopy can detect features indicative of esophageal dysmotility, but standardized approaches for diagnosing achalasia based on these findings remain limited. Recently, the CARS score was developed to address this gap. This study aimed to evaluate the diagnostic utility of endoscopy in identifying achalasia, using the STARD framework and current reference standards.

METHODS

Adult patients with esophageal symptoms were prospectively enrolled from 2018 to 2023 and evaluated using endoscopy, esophageal manometry, FLIP panometry, and barium esophagram. The CARS score was assigned to endoscopic videos by two raters blinded to other clinical details. The diagnostic accuracy of the CARS score for predicting achalasia, based on Chicago Classification v4.0, was assessed through two interpretation methods: binary cutoffs for the total score and a classification tree model.

RESULTS

316 patients were included: 115 patients with achalasia (36%), 113 with normal motility (36%), and 88 with other manometric findings (28%). A CARS score ≥ 4 demonstrated 72% sensitivity and 99% specificity for achalasia, while a score ≥ 3 had 83% sensitivity and 96% specificity. The optimal classification tree had three levels (resistance score at the top, followed by anatomy and content scores, with hernia presence at the bottom) and had a sensitivity of 90% and a specificity 92% for achalasia.

CONCLUSION

Endoscopy can accurately identify achalasia with high specificity using the CARS score. While motility testing to confirm an achalasia diagnosis remains essential prior to therapy, a high CARS score may help in the early identification of achalasia, especially in settings where motility testing is not readily available.

Validation of the Phoenix Criteria for Sepsis and Septic Shock in a Pediatric Intensive Care Unit

The applicability of the Phoenix criteria and Phoenix Sepsis Score in higher-resource pediatric intensive care units (PICUs) outside the United States requires further validation. A retrospective cohort study analyzed electronic health records of 1,304 PICU admissions under 18 years old with suspected infection between February 2017 and December 2023. The score was calculated using two methods: 24-hour assessment, based on worst sub-scores within 24 hours of admission, and prompt assessment, using values closest to admission within 6 hours before or after. Based on the 24-hour assessment, in-hospital mortality was 8.3% for sepsis and 10.3% for septic shock. The score demonstrated an area under the precision-recall curve of 0.42 (95% confidence interval, 0.31-0.55) for in-hospital mortality. Results were consistent across both assessment methods. The Phoenix criteria and the Phoenix Sepsis Score are reliable predictors of mortality outcomes. Further investigation in diverse clinical settings is warranted.

Evaluation of Imaging Research Adherence to the STARD 2015 Reporting Guideline: Update 9 Years After Implementation and Baseline Assessment

Background: Adherence of diagnostic accuracy imaging research to the STARD 2015 reporting guideline was assessed at baseline in 2016; on average, only 55% of 30 items were reported. Several knowledge translation strategies have since been implemented by the STARD group. Purpose: The purpose of this study was to evaluate the adherence of diagnostic accuracy studies recently published in imaging journals to STARD 2015, to assess for changes in the level of adherence relative to the baseline study. Methods: We performed an electronic search on MEDLINE for diagnostic accuracy studies, published between May and June of 2024, from a select group of imaging journals. The timespan was modulated to achieve a sample size of 100 to 150 included studies. Overall and item-specific adherence to STARD 2015 was evaluated, in addition to associations with journal of publication, imaging modality, study design, country of corresponding author, imaging subspecialty area, journal impact factor, and journal STARD adoption. Statistical comparison to the baseline study from 2016 was also performed. Poisson Regression and two-tailed student's tests were used to compare STARD adherence relative to variables included in subgroup analysis. Results: In the 126 included studies, average adherence to STARD 2015 was 61% (18.3/30 items; SD = 3.1), improved compared to the baseline study (55%; 16.6/30 items; SD = 2.2; P < .0001). Studies published in higher impact factor journals reported more items than those in lower impact factor journals (20.6 vs 18.4 items, P-value <.0001). There was no significant association between reporting completeness and journal of publication (P = .7), imaging modality (P = .21), country of corresponding author (P = .46), imaging subspecialty (P = .31), and journal STARD adoption status (P = .55). Conclusion: Recently published diagnostic accuracy studies reported more STARD 2015 items than studies published in 2016, but completeness of reporting is still not optimal.

Metabolomic Profiles of Oral Rinse Samples to Distinguish Severe Periodontitis Patients From Non-Periodontitis Controls

AIMS

To explore the potential of metabolomic profiles of oral rinse samples to distinguish between patients with severe periodontitis (stage III/IV) and non-periodontitis controls. This is coupled to an analysis of differences in metabolomic profiles between individuals without periodontitis, patients with localized periodontitis, and patients with generalized periodontitis.

METHODS

Periodontitis patients and controls were recruited, all aged ≥ 40 years. Study participants were asked to rinse vigorously for 30 s with 10 mL phosphate buffered saline. Metabolites were identified using a semi-targeted liquid chromatography tandem mass spectrometry (LC-MS/MS) platform.

RESULTS

In total, 38 periodontitis patients (18 localized, 20 generalized stage III/IV periodontitis patients) and 16 controls were included. Metabolomic profiles of oral rinse samples were able to distinguish patients with severe periodontitis (stage III/IV) from non-periodontitis controls. Among various variables for the severity of periodontitis, we found that the number of sites with deep pockets (PPD) ≥ 6 mm explained best the differences in metabolomic profiles between controls and patients with severe periodontitis. Subjects with a high number of sites with PPD ≥ 6 mm were characterized by a higher level of phosphorylated nucleotides, amino acids, peptides, and dicarboxylic acids. Metabolomic profiles were also significantly different between controls vs. generalized periodontitis and between localized periodontitis vs. generalized periodontitis (p < 0.05).

CONCLUSION

Our study demonstrates that simply collected oral rinse samples are suitable for LC-MS/MS based metabolomic analysis. We show that a metabolomic profile with a substantial number of metabolites can distinguish severe periodontitis patients from non-periodontitis controls. These observations can be a basis for further studies into screening to identify subjects with the risk of having severe periodontitis.

miRNAs-Set of Plasmatic Extracellular Vesicles as Novel Biomarkers for Hepatocellular Carcinoma Diagnosis Across Tumor Stage and Etiologies

Hepatocellular carcinoma (HCC) is the most common primary liver cancer, often diagnosed at advanced stages due to insufficient early screening and monitoring. MicroRNAs (miRNAs) are key regulators of gene expression and potential biomarkers for cancer diagnosis. This study investigated the diagnostic potential of miRNAs in Extracellular Vesicles (EVs) from HCC. miRNA expression in EVs was analyzed using HCC cell lines, circulating EVs from a Diethylnitrosamine (DEN)-induced liver tumor rat model, and plasma samples from HCC patients. Receiver Operating Characteristics (ROCs) were applied to evaluate the diagnostic accuracy of circulating EV miRNAs in patients. Five miRNAs (miR-183-5p, miR-19a-3p, miR-148b-3p, miR-34a-5p, and miR-215-5p) were consistently up-regulated in EVs across in vitro and in vivo HCC models. These miRNAs showed statistically significant differences in HCC patients stratified by TNM staging and Edmondson-Steiner grading compared to healthy controls. They also differentiated HCC patients with various etiologies from the control group and distinguished HCC patients, with or without liver cirrhosis, from cirrhotic and healthy individuals. Individually and as a panel, they demonstrated high sensitivity, specificity, and accuracy in identifying HCC patients. Their consistent upregulation across models and clinical samples highlights their robustness as biomarkers for HCC diagnosis, offering the potential for early disease management and prognosis.

Validation of the capnodynamic method to calculate mixed venous oxygen saturation in postoperative cardiac patients

BACKGROUND

Cardiac output and mixed venous oxygen saturation are key variables in monitoring adequate oxygen delivery and have typically been measured using pulmonary artery catheterisation. The capnodynamic method measures effective pulmonary blood flow utilising carbon dioxide kinetics in ventilated patients. Combined with breath-by-breath measurements of carbon dioxide elimination, a non-invasive approximation of mixed venous oxygen saturation can be calculated.

METHODS

This study primarily investigated the agreement between mixed venous oxygen saturation calculated using the capnodynamic method and blood gas analysis of mixed venous blood sampled via a pulmonary artery catheter in 47 haemodynamically stable postoperative cardiac patients. Both measurements were synchronised and performed during alveolar recruitment by stepwise changes to the level of positive end-expiratory pressure. Simultaneously, we studied the agreement between effective pulmonary blood flow and thermodilution cardiac output. The Bland-Altman method for repeated measurements and calculation of percentage error were used to examine agreement. Measurements before and after alveolar recruitment were analysed by a paired t test. The study hypothesis for agreement was a limit of difference of ten percentage points between mixed venous oxygen saturation using the capnodynamic algorithm vs. catheter blood gas analysis.

RESULTS

Capnodynamic calculation of mixed venous saturation compared to blood gas analysis showed a bias of -0.02 [95% CI - 0.96-0.91] % and limits of agreement at 8.8 [95% CI 7.7-10] % and - 8.9 [95% CI -10-- 7.8] %. The percentage error was < 20%. The effective pulmonary blood flow compared to thermodilution showed a bias of - 0.41 [95% CI - 0.55-- 0.28] l.min-1 and limits of agreement at 0.56 [95% CI 0.41-0.75] l.min-1 and - 1.38 [95% CI - 1.57--1.24] l.min-1. The percentage error was < 30%. Only effective pulmonary blood flow increased by 0.38 [95% CI 0.20-0.56] l.min-1 (p < 0.01) after alveolar recruitment.

CONCLUSIONS

In this study, minimal bias and limits of agreement < 10% between mixed venous oxygen saturation calculated by the capnodynamic method and pulmonary arterial blood gas analysis confirmed the agreement hypothesis in stable postoperative patients. The effective pulmonary blood flow agreed with thermodilution cardiac output, while influenced by pulmonary shunt flow.

Evaluation of an Innovative Rapid Diagnostic Test for Human Strongyloidiasis to Detect Specific IgG Antibody in Whole-Blood Samples

Human strongyloidiasis is an important intestinal parasitic disease that affects public health globally and is transmitted through contact with infective larvae on contaminated soil. Immunocompromised hosts can experience hyperinfection, which can lead to fatal systemic strongyloidiasis. Here, an innovative point-of-care (POC) test kit, the strongyloidiasis immunochromatographic blood test (the NIE-SsIR whole-blood ICT) kit is described. The kit was used to detect anti-Strongyloides IgG antibody in whole-blood samples (WBSs) instead of serum to diagnose strongyloidiasis. The kit is based on a mixture of two recombinant Strongyloides stercoralis protein antigens (NIE and SsIR) and colloidal-gold-labeled conjugates of anti-human IgG antibody to evaluate diagnostic values with simulated and fresh anticoagulated WBSs. The NIE-SsIR whole-blood ICT kit showed potentially high diagnostic values with simulated WBSs, obtained by spiking patients' sera with red blood cells. The sensitivity, specificity, and positive and negative predictive values were 93.0%, 93.7%, 88.6%, and 96.2%, respectively, at the prevalence of disease simulated under the laboratory conditions of 34.5%. In addition, 18 of 20 fresh anticoagulated WBSs from strongyloidiasis cases were positive, and all 15 WBSs from healthy volunteers were negative. The NIE-SsIR whole-blood ICT kit is a simple and convenient POC testing tool and can possibly be used with fingerstick blood samples, thereby not requiring the drawing of venous blood and separation of the serum. The NIE-SsIR whole-blood ICT kit can assist clinical diagnosis in remote areas and field settings without sophisticated equipment.

Can we trust published evidence on point-of-care tests for cholesterol? A rapid review

OBJECTIVES

There is a need to better inform clinicians and decision-makers in primary or community care settings on selecting the appropriate point-of-care tests (POCTs) for screening purposes (as a part of the NHS Health Check Programme). Here we provide an overview of the published analytic validity and diagnostic accuracy studies on POCTs for measuring blood lipids that are available on the UK market to determine whether they meet the accuracy specifications based on the 1995 US National Cholesterol Education Program (NCEP) recommendations.

DESIGN

Rapid review of analytical validity and diagnostic accuracy studies.

DATA SOURCES

On 12 May 2023, Medline and Embase were searched. Google Scholar was manually scrutinised to identify additional studies. Key article reference lists were also hand-searched.

ELIGIBILITY CRITERIA

We included analytical validity and diagnostic accuracy studies that compared POCT to laboratory testing (or another POCT) performance for measuring at least total cholesterol (TC) and high-density lipoprotein cholesterol (HDL-C).

DATA EXTRACTION AND SYNTHESIS

Identified studies were independently reviewed by two researchers using standardised methods of screening. Where necessary, conflicts were resolved by a third reviewer. Title and abstract as well as full texts were screened using prespecified inclusion and exclusion criteria. The quality of identified studies was assessed using QUADAS-2 for diagnostic accuracy studies and a modified quality appraisal tool for studies of diagnostic reliability (QAREL) for analytical validity studies. We assessed the quality of analytical and diagnostic accuracy studies and compared the accuracy of the POCTs for TC, triglyceride (TG), HDL-C and low-density lipoprotein cholesterol (LDL-C) against NCEP standards for mean per cent bias, coefficient of variation or total error. We narratively synthesised analytical and clinical validity evidence from retrieved studies.

RESULTS

This study examined analytical and diagnostic accuracy evidence for the selected POCTs. Through the review of 22 studies, 6 POCTs were identified. All retrieved studies were analytical validity assessments, while five of them also reported diagnostic accuracy information. The majority of evidence focused on Cholestech LDX, CardioChek PA and Accutrend Plus. Evidence of between and within-study heterogeneity was found. Precision measures often showed systematic differences between the POCT and reference standards. Most devices, except for Elemark, met at least one NCEP standard for either TC, TG, HDL-C, or LDL-C.

CONCLUSIONS

We found that evidence for two of the devices mostly met the requirements of the NCEP standard of evidence for bias and precision and could be recommended to general practitioners to use in the NHS Health Check programme. These were the Cholestech LDX and the Cobas b101 system.

RESPIRATORY VARIATION OF VELOCITY TIME INTEGRAL AND PEAK VELOCITY OF LEFT VENTRICULAR OUTFLOW TRACT FOR PREDICTING HYPOTENSION AFTER INDUCTION OF GENERAL ANESTHESIA IN ELDERLY PATIENTS

ABSTRACT

Background : Hypotension after induction of general anesthesia may lead to severe complications in elderly patients. This study investigated whether the respiratory variation of velocity time integral (ΔVTI) and peak velocity (ΔVpeak) of left ventricular outflow tract (LVOT) could predict hypotension after induction of general anesthesia in elderly patients. Methods : 120 elderly patients undergoing selective operation under general anesthesia were enrolled in this study. ΔVTI and ΔVpeak of LVOT were measured by transthoracic echocardiography before induction of general anesthesia. After induction, mean arterial pressure (MAP) was recorded every 1 min for 15 min. Hypotension was defined as a decrease of more than 30% in MAP at baseline or MAP below 65 mmHg from the start of induction. Receiver operating characteristic curves with gray zone and multivariate logistic regression analysis were used to assess the ability of ΔVTI and ΔVpeak of LVOT to predict hypotension after induction of general anesthesia. Results : Hypotension occurred in 64 (53.3%) patients after induction of general anesthesia. The area under receiver operating characteristic curves (AUC) for δVpeak of LVOT to predict hypotension after induction of general anesthesia was 0.811, and the optimal cutoff value was 13.1% with a gray zone of 9.9% to 13.8%, including 45.0% of patients. The AUC for ΔVTI of LVOT was 0.890, and the optimal cutoff value was 13.8% with a gray zone of 11.1% to 13.9%, including 25.8% of patients. After adjusting for confounders, ΔVTI (Odds ratio = 2.24) and ΔVpeak (Odds ratio = 2.09) of LVOT were two significant independent predictors of hypotension after induction of general anesthesia. Conclusions : ΔVTI of LVOT was a reliable predictor of hypotension after the induction of general anesthesia in elderly patients. ΔVpeak of LVOT should be used cautiously to predict hypotension after induction of general anesthesia due to nearly half of elderly patients in the gray zone. Trial registration : This study was registered in the Chinese Clinical Trial Registry (registration number: ChiCTR2300077117).

Analysis of ILD-RADS reproducibility and validity: Can different degrees of experience affect the interpretation?

PURPOSE

To evaluate the reliability, validity and applicability of ILD-RADS among readers with different levels of experience.

METHODS

This prospective tri-center study included 159 patients with clinically diagnosed ILD who underwent high-resolution CT (HRCT). Two experienced thoracic radiologists, two general radiologists, and one pulmonologist independently evaluated the HRCT images blinded to the patient's clinical data and assigned ILD-RADS category for each patient. The Fleiss kappa test was employed to estimate the inter-reader agreement among all readers. Cohen's kappa test was applied to measure the pairwise inter-reader agreement. The multi-disciplinary team discussion (MDD) was used as a reference test to estimate the validity of ILD-RADS for diagnosing idiopathic pulmonary fibrosis (IPF). A 5-point Likert short survey was accomplished by the pulmonologists about the applicability of ILD-RADS in clinical practice.

RESULTS

The current study included 124 non-IPF and 35 IPF cases. Based on the radiologists, the ILD-RADS showed moderate inter-reader agreement (K = 0.515, P < 0.001) while being fair after the inclusion of the pulmonologist's input (K = 0.333, P < 0.001). The agreement was substantial among thoracic radiologists (K = 0.716, p < 0.001) and moderate among general radiologists (K = 0.461, p < 0.001). ILD-RADS ≤ 2 was the optimal cut-off for predicting IPF, with an accuracy ranging from 62.84 % to 80.54 %. Seventy-five percent of pulmonologists rated ILD-RADS as highly applicable in practice.

CONCLUSIONS

ILD-RADS is reliable and valid among radiologists but requires further refinement to enhance consistency and applicability in diverse clinical settings. Moreover, pulmonologists support its use in clinical practice.

Weekly Biological Variation of Urine Protein Creatinine Ratio and Urine Specific Gravity in Healthy Dogs

BACKGROUND

Urine protein-creatinine ratio (UPC) and urine specific gravity (USG) are important measurements in the determination of renal proteinuria and chronic kidney disease. Biological and analytical variation estimates of these analytes to calculate the index of individuality (IoI) and a reference change value (RCV) are important to determine whether a population-based reference interval can be used to detect clinically meaningful changes and facilitate the interpretation of serial measurements.

OBJECTIVE

Determine the biological variation of UPC and USG using calculations of RCV and IoI in healthy dogs.

ANIMALS

Eleven healthy client-owned young adult dogs.

METHODS

Prospective observational study. First-morning urine samples were collected by voiding once weekly for 6 consecutive weeks for batch analysis. Twenty random samples were run in duplicate. Urine protein concentration, urine creatinine concentration, and USG were measured using a colorimetric pyrogallol red molybdate complex, enzymatic Jaffe method, and manual refractometer, respectively. Restricted maximum likelihood estimations were used to determine within-individual, between-individual, and analytical coefficients of variation and calculation of RCV and IoI.

RESULTS

All dogs were non-proteinuric at enrollment (UPC < 0.2) and remained non-proteinuric on subsequent measurements. Urine protein concentration, urine creatinine concentration, UPC, and USG had intermediate individuality. The RCV was 73% for urine protein concentration, 68% for urine creatinine concentration, 31% for UPC, and 3% for USG.

CONCLUSION

Population-based reference intervals for UPC and USG should be interpreted cautiously for single measurements and calculated RCVs should be applied to serial measurements to identify clinically meaningful changes.

A direct comparison in diagnostic performance of CDUS, FDG-PET/CT and MRI in patients suspected of giant cell arteritis

OBJECTIVES

This study directly compares the diagnostic performance of colour duplex ultrasound (CDUS), fluor-18-deoxyglucose positron emission tomography computed tomography (FDG-PET/CT) and magnetic resonance imaging (MRI) in patients suspected of giant cell arteritis (GCA).

METHODS

Patients with suspected GCA were included in a nested-case control pilot study. CDUS, whole body FDG-PET/CT and cranial MRI were performed within 5 working days after initial clinical evaluation. Clinical diagnosis after six months follow-up by experienced rheumatologists in the field of GCA, blinded for imaging, was used as reference standard. Diagnostic performance of the imaging modalities was determined. Stratification for GCA subtype was performed and imaging results were evaluated in different risk stratification groups.

RESULTS

In total, 23 patients with GCA and 19 patients suspected of but not diagnosed with GCA were included. Sensitivity was 69.6% (95%CI 50.4%-88.8%) for CDUS, 52.2% (95%CI 31.4%-73.0%) for FDG-PET/CT and 56.5% (95%CI 35.8%-77.2%) for MRI. Specificity was 100% for CDUS, FDG-PET/CT and MRI. FDG-PET/CT was negative for GCA in all isolated cranial GCA patients (n = 8), while MRI was negative in all isolated extracranial GCA patients (n = 4). In four GCA patients with false-negative (n = 2; intermediate and high risk) or inconclusive (n = 2; low and intermediate risk) CDUS results, further imaging confirmed diagnosis.

CONCLUSIONS

Sensitivity of CDUS was highest, while specificity was excellent in all imaging modalities. Nevertheless, confidence intervals of all imaging modalities were overlapping. Following EULAR recommendations, CDUS can be used as a first test to diagnose GCA. With insufficient evidence for GCA, further testing considering GCA subtype is warranted.

Evaluation of GPT-4 concordance with north American spine society guidelines for lumbar fusion surgery

Background

Concordance with evidence-based medicine (EBM) guidelines is associated with improved clinical outcomes in spine surgery. The North American Spine Society (NASS) has published coverage guidelines on indications for lumbar fusion surgery, with a recent survey demonstrating a 60% concordance rate across its members. GPT-4 is a popular deep learning model that receives knowledge training across public databases including those containing EBM guidelines. There is prior research exploring the potential utility of artificial intelligence (AI) software in adherence with spine surgery practices and guidelines, inviting opportunity to further investigate application in the setting of lumbar fusion surgery with current AI models.

Methods

Seventeen well-validated clinical vignettes with specific indications for or against lumbar fusion based on NASS criteria were obtained from a prior published research study. Each case was transcribed into a standardized prompt and entered into GPT-4 to obtain a decision whether fusion is indicated. Interquery reliability was assessed with serial identical queries utilizing the Fleiss' Kappa statistic. Majority response among serial queries was considered as the final GPT-4 decision. Queries were all entered in separate strings. The investigator entering the prompts was blinded to the NASS-concordant decisions for the cases prior to complete data collection. Decisions by GPT-4 and NASS guidelines were compared with Chi-square analysis.

Results

GPT-4 responses for 15/17 (88.2%) of the clinical vignettes were in concordance with NASS EBM lumbar fusion guidelines. There was a significant association in clinical decision-making when determining indication for spine fusion surgery between GPT-4 and NASS guidelines (χ² = 9.75; p<.01). There was substantial agreement among the sets of responses generated by GPT-4 for each clinical case (K = 0.71; p<.001).

Conclusions

There is significant concordance between GPT-4 responses and NASS EBM indications for lumbar fusion surgery. AI and deep learning models may prove to be an effective adjunct tool for clinical decision-making within modern spine surgery practices.

Developing predictive nomogram models using quantitative electroencephalography for brain function in type a aortic dissection: a prospective observational study

BACKGROUND

Type A aortic dissection (TAAD) remains a significant challenge in cardiac surgery, presenting high risks of adverse outcomes such as permanent neurological dysfunction and mortality despite advances in medical technology and surgical techniques. This study investigates the use of quantitative electroencephalography (QEEG) to monitor and predict neurological outcomes during the perioperative period in TAAD patients.

METHODS

This prospective observational study was conducted at the hospital, involving patients undergoing TAAD surgery from February 2022 to January 2023. QEEG parameters, including the dynamic amplitude-integrated electroencephalography (aEEG) grade, which assesses changes in brain function over time, alongside aEEG and relative band power (RBP), were monitored and analyzed to assess brain function preoperatively, intraoperatively, and within 2 hours postoperatively. A predictive nomogram model was developed using these QEEG metrics along with other clinical variables to forecast neurological outcomes.

RESULTS

In this study, we analyzed the factors contributing to adverse outcomes (AO) and transient neurological dysfunction (TND) following TAAD surgery. For AO, multivariable analysis identified pre-mental status (odds ratio [OR] = 4.652, 95% confidence interval [CI] = 2.316-10.074, P < 0.001), cardiopulmonary bypass time (OR = 1.014, 95% CI = 1.006-1.023, P = 0.001), and dynamic aEEG grade (OR = 9.926, 95% CI = 4.493-25.268, P < 0.001) as independent risk factors. The AO model showed high discriminative ability with an area under the curve of 0.888 (95% CI = 0.818-0.960) and good calibration (Brier score = 0.0728). For TND, significant preoperative differences included dynamic aEEG grade ( P < 0.001) and Log(Post-RBP Alpha%) (6.00 vs. 4.00, P < 0.001). Multivariable analysis identified cardiopulmonary bypass time (OR = 1.014, 95% CI = 1.006-1.023, P = 0.001), Post-RBP Alpha% (OR = 0.263, 95% CI = 0.121-0.532, P < 0.001), and dynamic aEEG grade (OR = 12.444, 95% CI = 5.337-30.814, P < 0.001) as independent risk factors. The TND model had an area under the curve of 0.893 (95% CI = 0.844-0.941) and good calibration (Brier score = 0.125). These findings highlight the role of QEEG in predicting postoperative neurological dysfunction in TAAD patients.

CONCLUSION

Through perioperative QEEG monitoring of TAAD patients, combined with clinical indicators such as cardiopulmonary bypass time and preoperative mental status, we developed clinical predictive models for AO and TND after surgery. These models allow for early detection of postoperative brain function impairment, as assessed by QEEG parameters monitored intraoperatively and during the first 2 hours after surgery, a period chosen based on clinical definitions of delayed awakening and supported by the findings of this study. This study provides evidence supporting postoperative brain function monitoring in TAAD patients, with potential clinical implications for improved outcomes.

Comparing mini bronchoalveolar lavage and endotracheal aspirate in diagnosing bacterial pneumonia in the intensive care unit

Objectives

Pneumonia is a major cause of morbidity and mortality among patients in the intensive care unit (ICU). Timely and accurate diagnosis is crucial for effective treatment, but lower respiratory tract sampling techniques vary in sensitivity and specificity. This study aims to compare the diagnostic accuracy of endotracheal aspirate (ETA) with mini bronchoalveolar lavage (mBAL) in detecting bacterial pneumonia in intubated patients, assessing sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ETA against mBAL, the gold standard.

Methods

A cross-sectional comparative study was conducted at the ICU of Sindh Institute of Urology and Transplantation (SIUT), Karachi, Pakistan, over 7 months. Adult patients on mechanical ventilation with suspected or confirmed pneumonia were included. Both mBAL and ETA samples were collected under strict aseptic conditions.

Results

Out of 120 patients, 112 paired samples were analyzed. ETA exhibited a sensitivity of 81.1%, specificity of 92.1%, PPV of 95.2%, and NPV of 71.4%, with an overall accuracy of 84.8%. The most commonly isolated pathogens were Acinetobacter and Klebsiella. No serious adverse events occurred.

Conclusion

ETA is a cost-effective and reliable alternative to mBAL for diagnosing bacterial pneumonia in intubated ICU patients, but clinicians should carefully interpret negative results.

Assessment of Standards for Reporting of Diagnostic Accuracy (STARD) 2015 guideline adherence in medical imaging diagnostic accuracy studies published in 2023

BACKGROUND

The Standards for Reporting of Diagnostic Accuracy (STARD) 2015 guideline facilitates evaluation of key aspects of diagnostic test accuracy (DTA) studies and their findings, including the risk of bias and applicability of findings.

OBJECTIVE

To evaluate the completeness of reporting in medical imaging DTA research in a sample of studies published in 2023.

METHODS

A systematic search of Medline, Embase, and the Cochrane Library was performed to identify medical imaging DTA studies published between January and June 2023 that assessed one or more index imaging tests compared to a reference standard and reported test performance using relevant outcome measures. Completeness of reporting amongst the included studies was assessed using the 30-item STARD-2015 guideline. Multiple linear regression was subsequently performed to identify study characteristics associated with more complete reporting.

RESULTS

A total of 116 studies were included in our analysis with a median journal impact factor of 2.7 (range 0.9-19.7). The mean number of items reported was 17.5/30 (58%, SD 2.2). Items that were infrequently reported (reported in less than 33% of included studies) included items 9 ('whether participants formed a consecutive, random or convenience series'), 13.2 ('whether clinical information and index test results were available to the assessors of the reference standard'), 15 ('how indeterminate index test or reference standard results were handled'), 16 ('how missing data on the index test and reference standard were handled'), 22.1 ('time interval between the index test and the reference standard'), 22.2 ('clinical interventions between the index test and the reference standard') and 29 ('where the full study protocol can be accessed'). Adherence was significantly higher in journals with a higher than median journal impact factor (18.1/30 vs 16.8/30 items reported; P < .001).

CONCLUSION

The completeness of reporting in medical imaging DTA research is moderate and remains relatively static in absolute terms compared to a previous evaluation of studies published in 2016 performed by Hong and colleagues, acknowledging differences in sample study characteristics limit direct comparison. Potential strategies to support more complete reporting in medical imaging DTA research include mandating adherence to the STARD guideline in journal instructions to authors, requiring completed STARD checklists to be submitted alongside all DTA study manuscripts, and integrating quality of reporting assessment as a routine component of the peer review process.

Diagnostics Accuracy of Magnetic Resonance Imaging in Detection of Atherosclerotic Plaque Characteristics in Carotid Arteries Compared to Histology: A Systematic Review

Carotid plaque composition represents one of the main risk factors of future ischemic stroke. MRI provides excellent soft tissue contrast that can distinguish plaque characteristics. Our objective was to analyze the diagnostic accuracy of MRI imaging in the detection of carotid plaque characteristics compared to histology in patients with symptomatic and asymptomatic carotid atherosclerosis through a systematic review. After prospective registration in PROSPERO (ID CRD42022329690), Medline Ovid, Embase.com, Cochrane Library, and Web of Science Core were searched without any search limitation up to May 27, 2022 to identify eligible articles. Of the 8168 studies, 53 (37 × 1.5 T MRI, 17 × 3 T MRI) evaluated MRI accuracy in the detection of 13 specific carotid plaque characteristics in 169 comparisons. MRI demonstrated high diagnostic accuracy for detection of calcification (3 T MRI: mean sensitivity 92%/mean specificity 90%; 1.5 T MRI: mean sensitivity 81%/mean specificity 91%), fibrous cap (1.5 T: 89%/87%), unstable plaque (1.5 T: 89%/87%), intraplaque hemorrhage (1.5 T: 86%/88%), and lipid-rich necrotic core (1.5 T: 89%/79%). MRI also proved to have a high level of tissue discrimination for the carotid plaque characteristics investigated, allowing potentially for a better risk assessment and follow-up of patients who may benefit from more aggressive treatments. These results emphasize the role of MRI as the first-line imaging modality for comprehensive assessment of carotid plaque morphology, particularly for unstable plaque. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Ultrasound-guided Transcutaneous Phrenic Nerve Stimulation in Critically Ill Patients: A New Method to Evaluate Diaphragmatic Function

BACKGROUND

Diaphragm dysfunction is common in intensive care unit and associated with weaning failure and mortality. The diagnosis gold standard is the transdiaphragmatic or tracheal pressure induced by magnetic phrenic nerve stimulation. However, the equipment is not commonly available and requires specific technical skills. This study aimed to evaluate ultrasound-guided transcutaneous phrenic nerve stimulation for daily bedside assessment of diaphragm function by targeted electrical phrenic nerve stimulation.

METHODS

This randomized crossover study compared a new method of ultrasound-guided transcutaneous electrical phrenic nerve stimulation (SONOTEPS) using a peripheral nerve stimulator, with magnetic phrenic nerve stimulation. Intensive care unit adult patients under mechanical ventilation with a Richmond Agitation-Sedation Scale score of -4 or -5 were included. Each patient received the two methods of stimulation, in a randomized order. The primary outcome was the tracheal pressure induced by stimulation.

RESULTS

This study analyzed 232 measures of tracheal pressure from 116 patients, of whom 77 presented diaphragm dysfunction (tracheal pressure less than 11 cm H 2 O) and 50 presented severe diaphragm dysfunction (tracheal pressure less than 8 cm H 2 O). The Passing-Bablok regression showed no significant differences (intercept A of -0.03 [95% CI, -0.83 to 0.52] and slope B of 0.98 [95% CI, 0.90 to 1.05]) between the SONOTEPS method and magnetic stimulation, which were positively correlated ( R ² = 0.639). The mean bias was -1.08 (95% CI, 5.02 to -7.18) cm H 2 O. The receiver operating curves showed an excellent performance for the diagnosis of diaphragm dysfunction and severe diaphragm dysfunction with areas under the curve of 0.90 (95% CI, 0.83 to 0.97) and 0.88 (95% CI, 0.82 to 0.95), respectively. This performance was not significantly affected by the body mass index or the presence of a neck catheter.

CONCLUSIONS

The SONOTEPS method is a simple and accurate tool for bedside assessment of diaphragm function with ultrasound-guided transcutaneous phrenic nerve stimulation in sedated patients with no or minimal spontaneous respiratory activity.

Accuracy of Liferiver HarmoniaHPV and VenusHPV Assays on Urine and Vaginal Self-Samples

In this report, the clinical performance of Liferiver HarmoniaHPV and Liferiver VenusHPV was evaluated under the VALHUDES framework. Five hundred and twenty-three women collected first-void urine (FVU) with Colli-Pee and vaginal samples with Evalyn Brush or Qvintip. Cervical samples were taken with the Cervex Brush by a clinician. Both vaginal and cervical samples were resuspended in 20 mL ThinPrep. Triplet samples from 499 women were tested with HarmoniaHPV and VenusHPV tests. The clinical accuracy of HarmoniaHPV did not differ in FVU and vaginal self-samples versus cervical samples. The relative sensitivity for CIN2+ on FVU and vaginal samples was 0.95 [95% CI 0.89-1.02] and 0.95 [95% CI 0.88-1.02], respectively. Relative specificity for < CIN2 was 0.95 [0.86-1.04] on FVU and 0.93 [0.86-1.01] on vaginal samples. VenusHPV demonstrated lower sensitivity on both self-sample types, whereas the specificity was similar to cervical samples. Post-hoc adjustment of the VenusHPV Ct-values improved sensitivity (ratio FVU/cervical = 0.94 [95% CI 0.88-1.00]; ratio vaginal/cervical = 0.96 [95% CI 0.92-1.01]) without compromising specificity (ratio FVU/cervical = 1.00 [0.92-1.09]; ratio vaginal/cervical = 0.95 [95% CI 0.88-1.02]) on both self-samples. In conclusion, HarmoniaHPV and VenusHPV tests demonstrated similar clinical accuracy on FVU and vaginal self- versus cervical samples, although VenusHPV test required cut-off optimization.

Circulating miR-126-3p is a mechanistic biomarker for knee osteoarthritis

Osteoarthritis is a major contributor to pain and disability worldwide, yet there are currently no validated soluble biomarkers or disease-modifying treatments. Given that microRNAs are promising mechanistic biomarkers that can be therapeutically targeted, in this study, we aimed to identify and prioritize reproducible circulating microRNAs associated with radiographic knee osteoarthritis. Across four independent cohorts, we find circulating miR-126-3p is elevated in knee osteoarthritis versus controls. Across six primary human knee osteoarthritis tissues, miR-126-3p is highest in subchondral bone, fat pad and synovium, and lowest in cartilage. Following both intravenous and intra-articular miR-126-3p mimic treatment in a surgical mouse model of knee osteoarthritis, we show reduced disease severity in males. In human knee osteoarthritis biospecimens, miR-126-3p mimic treatment reduces genes and markers associated with angiogenesis, as well as genes linked to osteogenesis, adipogenesis, and synovitis-processes secondary to angiogenesis. Our findings indicate that miR-126-3p is elevated in knee osteoarthritis and mitigates disease severity, supporting its potential as a biomarker and therapeutic target.

Development of a diagnostic checklist to identify functional cognitive disorder versus other neurocognitive disorders

Background

Functional cognitive disorder (FCD) poses a diagnostic challenge due to its resemblance to other neurocognitive disorders and limited biomarker accuracy. We aimed to develop a new diagnostic checklist to identify FCD versus other neurocognitive disorders.

Methods

The clinical checklist was developed through mixed methods: (1) a literature review, (2) a three-round Delphi study with 45 clinicians from 12 countries and (3) a pilot discriminative accuracy study in consecutive patients attending seven memory services across the UK. Items gathering consensus were incorporated into a pilot checklist. Item redundancy was evaluated with phi coefficients. A briefer checklist was produced by removing items with >10% missing data. Internal validity was tested using Cronbach's alpha. Optimal cut-off scores were determined using receiver operating characteristic curve analysis.

Results

A full 11-item checklist and a 7-item briefer checklist were produced. Overall, 239 patients (143 FCD, 96 non-FCD diagnoses) were included. The checklist scores were significantly different across subgroups (FCD and other neurocognitive disorders) (F(2, 236)=313.3, p<0.001). The area under the curve was excellent for both the full checklist (0.97, 95% CI 0.95 to 0.99) and its brief version (0.96, 95% CI 0.93 to 0.98). Optimal cut-off scores corresponded to a specificity of 97% and positive predictive value of 91% for identifying FCD. Both versions showed good internal validity (>0.80).

Conclusions

This pilot study shows that a brief clinical checklist may serve as a quick complementary tool to differentiate patients with neurodegeneration from those with FCD. Prospective blind large-scale validation in diverse populations is warranted.Cite Now.

Diagnostic Accuracy of Timed Barium Esophagram for Achalasia

BACKGROUND & AIMS

Timed barium esophagram (TBE) is commonly used to evaluate esophageal motor disorders, though its accuracy is limited. The lack of standardized criteria for TBE interpretation, coupled with reliance on single measurements and outdated reference standards, limits its effectiveness. This study aimed to reexamine the accuracy of TBE interpretation using the Standards for Reporting of Diagnostic Accuracy Studies (STARD) approach and updated reference standards.

METHODS

Adult patients with esophageal dysphagia were prospectively enrolled from 2019 to 2022 and underwent motility testing with esophageal manometry, functional lumen imaging probe (FLIP) panometry, and TBE. TBE accuracy for predicting achalasia/FLIP+ esophagogastric junction (EGJ) outflow obstruction, as defined by Chicago Classification 4.0 and FLIP, was assessed using 2 approaches: barium column height >2 cm at 5 minutes/impacted tablet and a classification tree model.

RESULTS

The study included 290 participants: 121 (42%) with EGJ outflow disorders, 151 (52%) without, and 18 (6%) with inconclusive results. The optimal classification tree had 3 levels: maximum esophageal body width at the top, maximum EGJ diameter and barium height at the second level, and tablet passage at the bottom. The TBE column height and tablet approach had a sensitivity of 77.8%, specificity 86.0%, and accuracy 82.2%, whereas the classification tree model achieved a sensitivity of 84.2%, specificity 92.1%, and accuracy of 88.3%.

CONCLUSIONS

TBE can accurately identify achalasia/FLIP+ EGJ outflow obstruction when using multiple metrics in a classification tree model. This provides a simple, standardized approach to TBE interpretation that is superior to traditional single-metric methods.

Tryptophan metabolites profile predict remission with dietary therapy in pediatric Crohn's disease

Background

Crohn's disease (CD) exclusion diet combined with partial enteral nutrition (CDED + PEN) or exclusive enteral nutrition (EEN) is effective in inducing remission in mild-to-moderate pediatric CD. Although CDED + PEN is better tolerated and has higher compliance compared to EEN, a subset of patients does not achieve remission. Diet-induced remission is shown to be positively associated with specific changes in tryptophan-metabolites.

Objectives

To investigate whether the abundance of baseline fecal tryptophan-metabolites predicts dietary therapy outcomes in pediatric CD.

Design

Diagnostic accuracy study and secondary analysis of previously conducted Randomized Controlled Trial (RCT).

Methods

Twenty-six patients from previously performed RCT of mild-to-moderate pediatric CD were included. The patients were classified as having clinical remission (R) (n = 19 in total; CDED + PEN = 10 and to EEN = 9) or No-Remission (NR) (n = 7 in total; CDED + PEN = 3 and EEN = 4) following 6 weeks of therapy, based on the Pediatric Crohn's Disease Activity Index score (⩽10 = remission). We performed a targeted quantitative analysis of 21 tryptophan-metabolites in baseline (t = 0) fecal samples from both groups, utilizing liquid chromatography coupled with quadrupole mass spectrometry. Receiver operator characteristic curve (ROC) and random forest analysis (RFA) were used to assess the predictive power of fecal tryptophan-metabolites for dietary outcomes at baseline. Ratios of tryptophan-metabolites were compared to investigate different downstream tryptophan pathways.

Results

Baseline fecal kynurenine level was significantly higher in NR compared to R for CDED + PEN (p = 0.02) and EEN (p = 0.04). ROC analysis highlighted the robust predictive power of kynurenine for CDED + PEN (area under the curve (AUC = 0.97)) and EEN (AUC = 0.88)-induced remission. RFA corroborated these observations. The ratio serotonin/kynurenine was the strongest predictor of CDED + PEN-induced remission (AUC = 1). The ratio 5-hydroxytryptophan/kynurenine (AUC = 0.88) predicted EEN-induced remission. By combining data from CDED + PEN and EEN, kynurenine (AUC = 0.91) and ratios of quinolinic acid/kynurenine (AUC = 0.93) and kynurenine/indole-3-acetic acid (AUC = 0.88) demonstrated strong predictive performance for dietary therapy-induced remission.

Conclusion

Baseline tryptophan metabolites have the potential to serve as a biomarker for dietary remission in pediatric CD. Some tryptophan metabolite ratios showed the most promising predictive capabilities. If confirmed in validation studies, baseline fecal tryptophan markers may be able to provide much-needed guidance to personalize dietary intervention within the management of pediatric CD.

Trial registration

NCT01728870.

Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review

BACKGROUND

This scoping review systematically maps externally validated machine learning (ML)-based models in cancer patient care, quantifying their performance, and clinical utility, and examining relationships between models, cancer types, and clinical decisions. By synthesizing evidence, this study identifies, strengths, limitations, and areas requiring further research.

METHODS

The review followed the Joanna Briggs Institute's methodology, Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines, and the Population, Concept, and Context mnemonic. Searches were conducted across Embase, IEEE Xplore, PubMed, Scopus, and Web of Science (January 2014-September 2022), targeting English-language quantitative studies in Q1 journals (SciMago Journal and Country Ranking > 1) that used ML to evaluate clinical outcomes for human cancer patients with commonly available data. Eligible models required external validation, clinical utility assessment, and performance metric reporting. Studies involving genetics, synthetic patients, plants, or animals were excluded. Results were presented in tabular, graphical, and descriptive form.

RESULTS

From 4023 deduplicated abstracts and 636 full-text reviews, 56 studies (2018-2022) met the inclusion criteria, covering diverse cancer types and applications. Convolutional neural networks were most prevalent, demonstrating high performance, followed by gradient- and decision tree-based algorithms. Other algorithms, though underrepresented, showed promise. Lung and digestive system cancers were most frequently studied, focusing on diagnosis and outcome predictions. Most studies were retrospective and multi-institutional, primarily using image-based data, followed by text-based and hybrid approaches. Clinical utility assessments involved 499 clinicians and 12 tools, indicating improved clinician performance with AI assistance and superior performance to standard clinical systems.

DISCUSSION

Interest in ML-based clinical decision-making has grown in recent years alongside increased multi-institutional collaboration. However, small sample sizes likely impacted data quality and generalizability. Persistent challenges include limited international validation across ethnicities, inconsistent data sharing, disparities in validation metrics, and insufficient calibration reporting, hindering model comparison reliability.

CONCLUSION

Successful integration of ML in oncology decision-making requires standardized data and methodologies, larger sample sizes, greater transparency, and robust validation and clinical utility assessments.

OTHER

Financed by FCT-Fundação para a Ciência e a Tecnologia (Portugal, project LA/P/0063/2020, grant 2021.09040.BD) as part of CSS's Ph.D. This work was not registered.

Deep learning-based classification of diffusion-weighted imaging-fluid-attenuated inversion recovery mismatch

The presence of a diffusion-weighted imaging (DWI)-fluid-attenuated inversion recovery (FLAIR) mismatch holds potential value in identifying candidates for recanalization treatment. However, the visual assessment of DWI-FLAIR mismatch is subject to limitations due to variability among raters, which affects accuracy and consistency. To overcome these challenges, we aimed to develop and validate a deep learning-based classifier to categorize the mismatch. We screened consecutive acute ischemic stroke patients who underwent DWI and FLAIR imaging from a four stroke centers. Two centers were used for model development and internal testing (derivation cohort), while two independent centers served as external validation cohorts. We developed Convolutional Neural Network-based classifiers for two binary classifications: DWI-FLAIR match versus non-match (Label Set I) and match versus mismatch (Label Set II). A total of 2369 patients from the derivation set and 679 patients from two external validation sets (350 and 329 patients) were included in the analysis. For Label Set I, the internal test set AUC was 0.862 (95% CI 0.841-0.884, with external validation AUCs of 0.829 (0.785-0.873) and 0.835 (0.790-0.879). Label Set II showed higher performance with internal test AUC of 0.934 (0.911-0.957) and external validation AUCs of 0.883 (0.829-0.938) and 0.913 (0.876-0.951). A deep learning-based classifier for the DWI-FLAIR mismatch can be used to diminish subjectivity and support targeted decision-making in the treatment of acute stroke patients.