Diagnostic value of Kaiser score combined with breast vascular assessment from breast MRI for the characterization of breast lesions

Objectives

The Kaiser scoring system for breast magnetic resonance imaging is a clinical decision-making tool for diagnosing breast lesions. However, the Kaiser score (KS) did not include the evaluation of breast vascularity. Therefore, this study aimed to use KS combined with breast vascular assessment, defined as KS^*, and investigate the effectiveness of KS^* in differentiating benign from malignant breast lesions.

Methods

This retrospective study included 223 patients with suspicious breast lesions and pathologically verified results. The histopathological diagnostic criteria were according to the fifth edition of the WHO classification of breast tumors. The KS^* was obtained after a joint evaluation combining the original KS and breast vasculature assessment. The receiver operating characteristic (ROC) curve was used for comparing differences in the diagnostic performance between KS^* and KS, and the area under the receiver operating characteristic (AUC) was compared.

Results

There were 119 (53.4%) benign and 104 (46.6%) malignant lesions in total. The overall sensitivity, specificity, and accuracy of increased ipsilateral breast vascularity were 69.2%, 76.5%, and 73.1%, respectively. The overall sensitivity, specificity, and accuracy of AVS were 82.7%, 76.5%, and 79.4%, respectively. For all lesions included the AUC of KS^* was greater than that of KS (0.877 vs. 0.858, P = 0.016). The largest difference in AUC was observed in the non-mass subgroup (0.793 vs. 0.725, P = 0.029).

Conclusion

Ipsilaterally increased breast vascularity and a positive AVS sign were significantly associated with malignancy. KS combined with breast vascular assessment can effectively improve the diagnostic ability of KS for breast lesions, especially for non-mass lesions.

Eliciting Low-Risk Thyroid Cancer Treatment Preferences Using Clinical Vignettes: A Pilot Study

OBJECTIVE

While surgical resection has been the traditional standard treatment for small (≤1 cm), differentiated thyroid cancers, active surveillance (AS) and radiofrequency ablation (RFA) are increasingly considered. The aim of this study was to explore patient preferences in thyroid cancer treatment using a series of clinical vignettes.

METHODS

Thyroid cancer survivors and general population volunteers were recruited to rank experience-driven clinical vignettes in order of preference. Rankings were compared using Wilcoxon signed rank. Formative qualitative methods were used to develop and refine clinical vignettes that captured 4 treatments-thyroid lobectomy (TL), total thyroidectomy (TT), AS, and RFA-along with 6 treatment complications. Content was validated via interviews with 5 academic subspecialists.

RESULTS

Nineteen volunteers participated (10 survivors, 9 general population). Treatment complications were ranked lower than uncomplicated counterparts in 99.0% of cases, indicating excellent comprehension. Counter to our hypothesis, among uncomplicated vignettes, median rankings were 1 for AS, 2 for RFA, 3.5 for TL, and 5 for TT. Trends were consistent between thyroid cancer survivors and the general population. AS was significantly preferred over RFA (P = .02) and TT (P < .01). Among surgical options, TL was significantly preferred over TT (P < .01).

CONCLUSION

When treatments for low-risk thyroid cancer are described clearly and accurately through clinical vignettes, patients may be more likely to choose less invasive treatment options over traditional surgical resection.

Simultaneous Quantitative SARS-CoV-2 Antigen and Host Antibody Detection and Pre-Screening Strategy at the Point of Care

As COVID-19 pandemic public health measures are easing globally, the emergence of new SARS-CoV-2 strains continue to present high risk for vulnerable populations. The antibody-mediated protection acquired from vaccination and/or infection is seen to wane over time and the immunocompromised populations can no longer expect benefit from monoclonal antibody prophylaxis. Hence, there is a need to monitor new variants and its effect on vaccine performance. In this context, surveillance of new SARS-CoV-2 infections and serology testing are gaining consensus for use as screening methods, especially for at-risk groups. Here, we described an improved COVID-19 screening strategy, comprising predictive algorithms and concurrent, rapid, accurate, and quantitative SARS-CoV-2 antigen and host antibody testing strategy, at point of care (POC). We conducted a retrospective analysis of 2553 pre- and asymptomatic patients who were tested for SARS-CoV-2 by RT-PCR. The pre-screening model had an AUC (CI) of 0.76 (0.73-0.78). Despite being the default method for screening, body temperature had lower AUC (0.52 [0.49-0.55]) compared to case incidence rate (0.65 [0.62-0.68]). POC assays for SARS-CoV-2 nucleocapsid protein (NP) and spike (S) receptor binding domain (RBD) IgG antibody showed promising preliminary results, demonstrating a convenient, rapid (<20 min), quantitative, and sensitive (ng/mL) antigen/antibody assay. This integrated pre-screening model and simultaneous antigen/antibody approach may significantly improve accuracy of COVID-19 infection and host immunity screening, helping address unmet needs for monitoring vaccine effectiveness and severe disease surveillance.

Predicting Colorectal Surgery Readmission Risk: a Surgery-Specific Predictive Model

Most current predictive models for risk of readmission were primarily designed from non-surgical patients and often utilize administrative data alone. Models built upon comprehensive data sources specific to colorectal surgery may be key to implementing interventions aimed at reducing readmissions. This study aimed to develop a predictive model for risk of 30-day readmission specific to colorectal surgery patients including administrative, clinical, laboratory, and socioeconomic status (SES) data. Patients admitted to the colorectal surgery service who underwent surgery and were discharged from an academic tertiary hospital between 2017 and 2019 were included. A total of 1549 patients met eligibility criteria for this retrospective split-sample cohort study. The 30-day readmission rate of the cohort was 19.62%. A multivariable logistic regression was developed (C=0.70, 95% CI 0.61-0.73), which outperformed two internationally used readmission risk prediction indices (C=0.58, 95% CI 0.52-0.65) and (C=0.60, 95% CI 0.53-0.66). Tailored surgery-specific readmission models with comprehensive data sources outperform the most used readmission indices in predicting 30-day readmission in colorectal surgery patients. Model performance is improved by using more comprehensive datasets that include administrative and socioeconomic details about a patient, as well as clinical information used for decision-making around the time of discharge.

Limited Clinical Impact of Ultralow-Dose Computed Tomography in Suspected Community-Acquired Pneumonia

Patients clinically suspected of community-acquired pneumonia (CAP) were randomized between ultralow-dose chest computed tomography ([ULDCT] 261 patients) and chest radiograph ([CXR] 231 patients). We did not find evidence that performing ULDCT instead of CXR affects antibiotic treatment policy or patient outcomes. However, in a subgroup of afebrile patients, there were more patients diagnosed with CAP in the ULDCT group (ULDCT, 106 of 608 patients; CXR, 71 of 654 patients; P = .001).

Planning management for complex colorectal polyps: a qualitative assessment of factors influencing decision-making among colonoscopists

OBJECTIVE

Endoscopic therapy is the recommended primary treatment for most complex colorectal polyps, but high colonic resection rates are reported. The aim of this qualitative study was to understand and compare between specialities, the clinical and non-clinical factors influencing decision making when planning management.

DESIGN

Semi-structured interviews were performed among colonoscopists across the UK. Interviews were conducted virtually and transcribed verbatim. Complex polyps were defined as lesions requiring further management planning rather than those treatable at the time of endoscopy. A thematic analysis was performed. Findings were coded to identify themes and reported narratively.

RESULTS

Twenty colonoscopists were interviewed. Four major themes were identified including gathering information regarding the patient and their polyp, aids to decision making, barriers in achieving optimal management and improving services. Participants advocated endoscopic management where possible. Factors such as younger age, suspicion of malignancy, right colon or difficult polyp location lead towards surgical intervention and were similar between surgical and medical specialties. Availability of expertise, timely endoscopy and challenges in referral pathways were reported barriers to optimal management. Experiences of team decision-making strategies were positive and advocated in improving complex polyp management. Recommendations based on these findings to improve complex polyp management are provided.

CONCLUSION

The increasing recognition of complex colorectal polyps requires consistency in decision making and access to a full range of treatment options. Colonoscopists advocated the availability of clinical expertise, timely treatment and education in avoiding surgical intervention and providing good patient outcomes. Team decision-making strategies for complex polyps may provide an opportunity to coordinate and improve these issues.

Joint Asian Pacific Association of Gastroenterology (APAGE)-Asian Pacific Society of Digestive Endoscopy (APSDE) clinical practice guidelines on the use of non-invasive biomarkers for diagnosis of colorectal neoplasia

Screening for colorectal cancer (CRC) is effective in reducing CRC related mortality. Current screening methods include endoscopy based and biomarker based approaches. This guideline is a joint official statement of the Asian Pacific Association of Gastroenterology (APAGE) and the Asian Pacific Society of Digestive Endoscopy (APSDE), developed in response to the increasing use of, and accumulating supportive evidence for the role of, non-invasive biomarkers for the diagnosis of CRC and its precursor lesions. A systematic review of 678 publications and a two stage Delphi consensus process involving 16 clinicians in various disciplines was undertaken to develop 32 evidence based and expert opinion based recommendations for the use of faecal immunochemical tests, faecal based tumour biomarkers or microbial biomarkers, and blood based tumour biomarkers for the detection of CRC and adenoma. Comprehensive up-to-date guidance is provided on indications, patient selection and strengths and limitations of each screening tool. Future research to inform clinical applications are discussed alongside objective measurement of research priorities. This joint APAGE-APSDE practice guideline is intended to provide an up-to-date guide to assist clinicians worldwide in utilising non-invasive biomarkers for CRC screening; it has particular salience for clinicians in the Asia-Pacific region.

Clinical decision making of implant guidance methods guided by new classification of surgical area mouth ope-ning

When selecting implant guidance methods or judging whether the patient can be implanted, many doctors ignore or only use visual inspection to estimate a patient's mouth opening. This phenomenon often leads to failure to complete the implantation due to insufficient mouth opening or the deflection of the implant due to limited angle, resulting in the high incidence of corresponding complications. The main reason is that doctors lack accurate analysis and control of the overall geometric conditions of the intraoral surgical area, and three-dimensional position blocking of surgical instruments occurs during the operation. In the past, mouth opening was defined as the distance between the incisor edges of the upper and lower central incisors when the patient opens his mouth widely, and the implant area could be in any missing tooth position. When it is in the posterior tooth area, the specific measurement scheme of the mouth opening could not be simply equivalent to the previous measurement method in the anterior tooth area. However, how to measure quickly and conveniently the mouth opening of any surgical area to determine whether it could be implanted and meet the needs of the selected guidance method remains unclear. This paper introduces new concepts, establishes new classification and corresponding accurate measurement scheme of implant area, and establishes a decision tree of implant methods guided by the actually measured value. Results provide a quantitative basis for rational formulation and implementation of implant treatment.

Feasibility of an online consensus approach for the diagnosis of cognitive impairment and dementia in rural South Africa

INTRODUCTION

We describe the development and feasibility of using an online consensus approach for diagnosing cognitive impairment and dementia in rural South Africa.

METHODS

Cognitive assessments, clinical evaluations, and informant interviews from Cognition and Dementia in the Health and Aging in Africa Longitudinal Study (HAALSI Dementia) were reviewed by an expert panel using a web-based platform to assign a diagnosis of cognitively normal, mild cognitive impairment (MCI), or dementia.

RESULTS

Six hundred thirty-five participants were assigned a final diagnostic category, with 298 requiring adjudication conference calls. Overall agreement between each rater's independent diagnosis and final diagnosis (via the portal or consensus conference) was 78.3%. A moderate level of agreement between raters' individual ratings and the final diagnostic outcomes was observed (average κ coefficient = 0.50).

DISCUSSION

Findings show initial feasibility in using an online consensus approach for the diagnosis of cognitive impairment and dementia in remote, rural, and low-resource settings.

Decomposing clinical practice guidelines panels' deliberation into decision theoretical constructs

RATIONALE, AIMS AND OBJECTIVES: The development of clinical practice guidelines (CPG) suffers from the lack of an explicit and transparent framework for synthesising the key elements necessary to formulate practice recommendations. We matched deliberations of the American Society of Haematology (ASH) CPG panel for the management of pulmonary embolism (PE) with the corresponding decision-theoretical constructs to assess agreement of the panel recommendations with explicit decision modelling.

METHODS

Five constructs were identified of which three were used to reformulate the panel's recommendations: (1) standard, expected utility threshold (EUT) decision model; (2) acceptable regret threshold model (ARg) to determine the frequency of tolerable false negative (FN) or false positive (FP) recommendations, and (3) fast-and-frugal tree (FFT) decision trees to formulate the entire strategy for management of PE. We compared four management strategies: withhold testing versus d-dimer → computerized pulmonary angiography (CTPA) ('ASH-Low') versus CTPA→ d-dimer ('ASH-High') versus treat without testing.

RESULTS

Different models generated different recommendations. For example, according to EUT, testing should be withheld for prior probability PE < 0.13%, a clinically untenable threshold which is up to 15 times (2/0.13) below the ASH guidelines threshold of ruling out PE (at post probability of PE ≤ 2%). Three models only agreed that the 'ASH low' strategy should be used for the range of pretest probabilities of PE between 0.13% and 13.27% and that the 'ASH high' management should be employed in a narrow range of the prior PE probabilities between 90.85% and 93.07%. For all other prior probabilities of PE, choosing one model did not ensure coherence with other models.

CONCLUSIONS

CPG panels rely on various decision-theoretical strategies to develop its recommendations. Decomposing CPG panels' deliberation can provide insights if the panels' deliberation retains a necessary coherence in developing guidelines. CPG recommendations often do not agree with the EUT decision analysis, widely used in medical decision-making modelling.

Distinct blood protein profiles associated with the risk of short-term and mid/long-term clinical relapse in patients with Crohn's disease stopping infliximab: when the remission state hides different types of residual disease activity

OBJECTIVE

Despite being in sustained and stable remission, patients with Crohn's disease (CD) stopping anti-tumour necrosis factor α (TNFα) show a high rate of relapse (~50% within 2 years). Characterising non-invasively the biological profiles of those patients is needed to better guide the decision of anti-TNFα withdrawal.

DESIGN

Ninety-two immune-related proteins were measured by proximity extension assay in serum of patients with CD (n=102) in sustained steroid-free remission and stopping anti-TNFα (infliximab). As previously shown, a stratification based on time to clinical relapse was used to characterise the distinct biological profiles of relapsers (short-term relapsers: <6 months vs mid/long-term relapsers: >6 months). Associations between protein levels and time to clinical relapse were determined by univariable Cox model.

RESULTS

The risk (HR) of mid/long-term clinical relapse was specifically associated with a high serum level of proteins mainly expressed in lymphocytes (LAG3, SH2B3, SIT1; HR: 2.2-4.5; p<0.05), a low serum level of anti-inflammatory effectors (IL-10, HSD11B1; HR: 0.2-0.3; p<0.05) and cellular junction proteins (CDSN, CNTNAP2, CXADR, ITGA11; HR: 0.4; p<0.05). The risk of short-term clinical relapse was specifically associated with a high serum level of pro-inflammatory effectors (IL-6, IL12RB1; HR: 3.5-3.6; p<0.05) and a low or high serum level of proteins mainly expressed in antigen presenting cells (CLEC4A, CLEC4C, CLEC7A, LAMP3; HR: 0.4-4.1; p<0.05).

CONCLUSION

We identified distinct blood protein profiles associated with the risk of short-term and mid/long-term clinical relapse in patients with CD stopping infliximab. These findings constitute an advance for the development of non-invasive biomarkers guiding the decision of anti-TNFα withdrawal.

Early management of acute severe UC in the biologics era: development and international validation of a prognostic clinical index to predict steroid response

OBJECTIVES

We aimed to determine whether changes in acute severe colitis (ASC) management have translated to improved outcomes and to develop a simple model predicting steroid non-response on admission.

DESIGN

Outcomes of 131 adult ASC admissions (117 patients) in Oxford, UK between 2015 and 2019 were compared with data from 1992 to 1993. All patients received standard treatment with intravenous corticosteroids and endoscopic disease activity scoring (Ulcerative Colitis Endoscopic Index of Severity (UCEIS)). Steroid non-response was defined as receiving medical rescue therapy or surgery. A predictive model developed in the Oxford cohort was validated in Australia and India (Gold Coast University Hospital 2015-2020, n=110; All India Institute of Medical Sciences, New Delhi 2018-2020, n=62).

RESULTS

In the 2015-2019 Oxford cohort, 15% required colectomy during admission vs 29% in 1992-1993 (p=0.033), while 71 (54%) patients received medical rescue therapy (27% ciclosporin, 27% anti-tumour necrosis factor, compared with 27% ciclosporin in 1992-1993 (p=0.0015). Admission C reactive protein (CRP) (false discovery rate, p=0.00066), albumin (0.0066) and UCEIS scores (0.015) predicted steroid non-response. A four-point model was developed involving CRP of ≥100 mg/L (one point), albumin of ≤25 g/L (one point), and UCEIS score of ≥4 (1 point) or ≥7 (2 points). Patients scoring 0, 1, 2, 3 and 4 in the validation cohorts had steroid response rates of 100, 75.0%, 54.9%, 18.2% and 0%, respectively. Scoring of ≥3 was 84% (95% CI 0.70 to 0.98) predictive of steroid failure (OR 11.9, 95% CI 10.8 to 13.0). Colectomy rates in the validation cohorts were were 8%-11%.

CONCLUSIONS

Emergency colectomy rates for ASC have halved in 25 years to 8%-15% worldwide. Patients who will not respond to corticosteroids are readily identified on admission and may be prioritised for early intensification of therapy.

Assessing the Accuracy and Reliability of AI-Generated Medical Responses: An Evaluation of the Chat-GPT Model

Background

Natural language processing models such as ChatGPT can generate text-based content and are poised to become a major information source in medicine and beyond. The accuracy and completeness of ChatGPT for medical queries is not known.

Methods

Thirty-three physicians across 17 specialties generated 284 medical questions that they subjectively classified as easy, medium, or hard with either binary (yes/no) or descriptive answers. The physicians then graded ChatGPT-generated answers to these questions for accuracy (6-point Likert scale; range 1 - completely incorrect to 6 - completely correct) and completeness (3-point Likert scale; range 1 - incomplete to 3 - complete plus additional context). Scores were summarized with descriptive statistics and compared using Mann-Whitney U or Kruskal-Wallis testing.

Results

Across all questions (n=284), median accuracy score was 5.5 (between almost completely and completely correct) with mean score of 4.8 (between mostly and almost completely correct). Median completeness score was 3 (complete and comprehensive) with mean score of 2.5. For questions rated easy, medium, and hard, median accuracy scores were 6, 5.5, and 5 (mean 5.0, 4.7, and 4.6; p=0.05). Accuracy scores for binary and descriptive questions were similar (median 6 vs. 5; mean 4.9 vs. 4.7; p=0.07). Of 36 questions with scores of 1-2, 34 were re-queried/re-graded 8-17 days later with substantial improvement (median 2 vs. 4; p<0.01).

Conclusions

ChatGPT generated largely accurate information to diverse medical queries as judged by academic physician specialists although with important limitations. Further research and model development are needed to correct inaccuracies and for validation.

Piloting a Nurse-Led Critical Care Outreach Service to Pre-Empt Medical Emergency Team Calls and Facilitate Staff Learning

A nurse-led critical care outreach service (NLCCOS) can support staff education and decision making in the wards, managing at-risk patients with ward nurses to avoid further deterioration. We aimed to investigate the characteristics of patients identified as at-risk, the types of treatments they required to prevent deterioration, the education initiated by the NLCCOS, and the perceived experiences of ward nurses. This prospective observational pilot study using mixed methods took place in one medical and one surgical ward at a university hospital in Denmark. Participants were patients nominated as at-risk by head nurses in each ward, the ward nurses, and nurses from the NLCCOS. In total, 100 patients were reviewed, 51 medical and 49 surgical patients, over a six-month period. Most patients (70%) visited by the NLCCOS had a compromised respiratory status, and ward nurses received teaching and advice regarding interventions. Sixty-one surveys were collected from ward nurses on their learning experience. Over 90% (n = 55) of nurses believed they had learned from, and were more confident with, managing patients following the experience. The main educational areas were respiratory therapy, invasive procedures, medications, and benefits of mobilization. Further research needs to measure the impact of the intervention on patient outcomes and MET call frequency over time in larger samples.

Prognostic role of microsatellites in melanoma and implications in the American Joint Committee on Cancer classification system: A cohort study

BACKGROUND

There is limited information on microsatellite survival outcomes in patients with melanoma.

OBJECTIVE

To evaluate survival outcomes in patients with microsatellites, assess their role within stage III stratification of the American Joint Committee on Cancer classification, and assess the results of sentinel lymph node biopsies in patients with microsatellites.

METHODS

A retrospective bicenter cohort study from 1998 to 2019 included patients with a diagnosis of invasive cutaneous melanoma.

RESULTS

Of a total of 5216 patients, 108 (2.1%) had microsatellites at initial staging. Survival analysis showed that microsatellites were an independent risk factor with decreased overall survival (OS), melanoma-specific survival (MSS), and disease-free survival, with hazard ratios of 1.57, 1.76, and 1.76, respectively. Stratified analysis in patients with stage III melanoma showed a 5-year OS of 35% (95% CI, 17.3%-73.4%) and a MSS of 45% (95% CI, 23.1-87.5) for patients with stage IIIB melanoma with microsatellites.

LIMITATIONS

Retrospective design of the study.

CONCLUSION

Microsatellites were associated with other adverse melanoma prognostic factors. A multivariate Cox regression analysis showed that they are an independent risk factor for worse OS, MSS, and disease-free survival. Patients with stage IIIB melanoma with microsatellites had worse OS and MSS, whereas patients with stage IIIC melanoma had worse OS but not MSS.

Prognostic accuracy and impact of cerebral collateral status on clinical and safety outcomes in acute ischemic stroke patients receiving reperfusion therapy: a systematic meta-analysis

BACKGROUND

Cerebral collateral status has a potential role in mediating postreperfusion clinical and safety outcomes in acute ischemic stroke (AIS).

PURPOSE

To investigate the prognostic accuracy and impact of collateral status on clinical and safety outcomes in patients with AIS receiving reperfusion therapy.

MATERIAL AND METHODS

Studies with AIS patients treated with reperfusion therapy, collateral status assessed using Tan, ASITN/SIR, or similar collateral grading methods and data stratified according to collateral status were included. Relevant data on clinical outcomes, such as functional outcome at 90 days, mortality at 90 days, angiographic reperfusion, symptomatic intracerebral hemorrhage (sICH) and hemorrhagic transformation (HT), were collated and analyzed.

RESULTS

A meta-analysis of 18 studies involving 4132 patients with AIS was conducted. Good collateral status was significantly associated with angiographic reperfusion (odds ratio [OR]=1.97, 95% confidence interval [CI]=1.38-2.80; P < 0.0001), sICH (OR=0.67, 95% CI=0.46-0.99; P = 0.042), and 90-day functional outcome (OR=3.05, 95% CI=1.78-5.24; P < 0.0001). However, its association with HT (OR=0.76, 95% CI=0.38-1.51; P = 0.425) and three-month mortality (OR=0.53, 95% CI=0.17-1.69; P = 0.280) did not reach statistical significance. The prognostic accuracy of collaterals for predicting angiographic reperfusion, HT, functional outcome (at 90 days), and mortality (at 90 days) were 63%, 49%, 66%, and 48%, respectively.

CONCLUSION

Cerebral collaterals are significantly associated with clinical and safety outcomes, albeit with a prognostic accuracy range of 48%-66%; thus, evaluation of their patency is a useful prognostic tool in patients with AIS receiving reperfusion therapy.

Evaluation of a fast-and-frugal clinical decision algorithm ('pathways') on clinical outcomes in hospitalised patients with COVID-19 treated with anticoagulants

RATIONALE, AIMS AND OBJECTIVES

Critics have charged that evidence-based medicine (EBM) overemphasises algorithmic rules over unstructured clinical experience and intuition, but the role of structured decision support systems in improving health outcomes remains uncertain. We aim to assess if delivery of anticoagulant prophylaxis in hospitalised patients with COVID-19 according to an algorithm based on evidence-based clinical practice guideline (CPG) improved clinical outcomes compared with administration of anticoagulant treatment given at individual practitioners' discretion.

METHODS

An observational design consisting of the analysis of all acutely ill, consecutive patients (n = 1783) with confirmed COVID-19 diagnosis admitted between 10 March 2020 to 11 January 2022 to an US academic center. American Society of Haematology CPG for anticoagulant prophylaxis in hospitalised patients with COVID-19 was converted into a clinical pathway and translated into fast-and-frugal decision (FFT) tree ('algorithm'). We compared delivery of anticoagulant prophylaxis in hospitalised patients with COVID-19 according to the FFT algorithm with administration of anticoagulant treatment given at individual practitioners' discretion.

RESULTS

In an adjusted analysis, using combination of Lasso (least absolute shrinkage and selection operator) and propensity score based weighting [augmented inverse-probability weighting] statistical techniques controlling for cluster data, the algorithm did not reduce death, venous thromboembolism, or major bleeding, but helped avoid longer hospital stay [number of patients needed to be treated (NNT) = 40 (95% CI: 23-143), indicating that for every 40 patients (23-143) managed on FFT algorithm, one avoided staying in hospital longer than 10 days] and averted admission to intensive-care unit (ICU) [NNT = 19 (95% CI: 13-40)]. All model's selected covariates were well balanced. The results remained robust to sensitivity analyses used to test the stability of the findings.

CONCLUSIONS

When delivered using a structured FFT algorithm, CPG shortened the hospital stay and help avoided admission to ICU, but it did not affect other relevant outcomes.

Interstitial Ectopic Pregnancy-Case Reports and Medical Management

The term intramural (interstitial) ectopic pregnancy refers to a pregnancy developing outside the uterine cavity, with a gestational sac implanted into the interstitial part of the Fallopian tube, surrounded by a layer of the myometrium. The prevalence rate of interstitial pregnancy (IP) is 2-4% of all ectopic pregnancies. Surgery is the primary treatment for interstitial ectopic pregnancy; the pharmacological management of ectopic pregnancy, including IP, in asymptomatic patients includes systemic administration of methotrexate. In this report, we present two cases of this rare pregnancy type, reviewing our management technique and treatment ways presented in the literature. In our patients, the management was initially conservative and included methotrexate, administered as intravenous bolus injection, regular beta-human chorionic gonadotropins (β-HCG) level measurements in peripheral blood, and monitoring of the patient's general condition. Due to signs of intra-abdominal bleeding in patient A and inadequate β-HCG level reduction in patient B, both patients eventually underwent laparoscopic cornual resection. Pregnancy, implanted into the interstitial part of the Fallopian tube and surrounded by myometrial tissue with myometrial invasion of the trophoblast, poses a serious diagnostic challenge to modern gynecology due to particularly low sensitivity and specificity of symptoms, and may require both pharmacological and surgical treatment.

Miscalibration of lung allocation models leads to inaccurate waitlist mortality predictions

The importance of waitlist (WL) mortality risk estimates will increase with the adoption of the US Composite Allocation Score (CAS) system. Calibration is rarely assessed in clinical prediction models, yet it is a key factor in determining access to lung transplant. We assessed the calibration of the WL-lung allocation score (LAS)/CAS models and developed alternative models to minimize miscalibration. Scientific Registry of Transplant Recipients data from 2015 to 2020 were used to assess the calibration of the WL model and for subgroups (age, sex, diagnosis, and race/ethnicity). Three recalibrated models were developed and compared: (1) simple recalibration model (SRM), (2) weighted recalibration model 1 (WRM1), and (3) weighted recalibration model 2 (WRM2). The current WL-LAS/CAS model underestimated risk for 78% of individuals (predicted mortality risk, <42%) and overpredicted risk for 22% of individuals (predicted mortality risk, ≥42%), with divergent results among subgroups. Error measures improved in SRM, WRM1, and WRM2. SRM generally preserved candidate rankings, whereas WRM1 and WRM2 led to changes in ranking by age and diagnosis. Differential miscalibration occurred in the WL-LAS/CAS model, which improved with recalibration measures. Further inquiry is needed to develop mortality models in which risk predictions approximate observed data to ensure accurate ranking and timely access to transplant. IMPACT: With changes to the lung transplant allocation system planned in 2023, evaluation of the accuracy and precision of survival models used to rank candidates for lung transplant is important. The waitlist model underpredicts risk for 78% of US transplant candidates with an unequal distribution of miscalibration across subgroups leading to inaccurate ranking of transplant candidates. This work will serve to inform future efforts to improve modeling efforts in the US lung transplant allocation system.

Prediction of Mortality and Major Adverse Kidney Events in Critically Ill Patients With Acute Kidney Injury

RATIONALE & OBJECTIVE

Risk prediction tools for assisting acute kidney injury (AKI) management have focused on AKI onset but have infrequently addressed kidney recovery. We developed clinical models for risk stratification of mortality and major adverse kidney events (MAKE) in critically ill patients with incident AKI.

STUDY DESIGN

Multicenter cohort study.

SETTING & PARTICIPANTS

9,587 adult patients admitted to heterogeneous intensive care units (ICUs; March 2009 to February 2017) who experienced AKI within the first 3 days of their ICU stays.

PREDICTORS

Multimodal clinical data consisting of 71 features collected in the first 3 days of ICU stay.

OUTCOMES

(1) Hospital mortality and (2) MAKE, defined as the composite of death during hospitalization or within 120 days of discharge, receipt of kidney replacement therapy in the last 48 hours of hospital stay, initiation of maintenance kidney replacement therapy within 120 days, or a ≥50% decrease in estimated glomerular filtration rate from baseline to 120 days from hospital discharge.

ANALYTICAL APPROACH

Four machine-learning algorithms (logistic regression, random forest, support vector machine, and extreme gradient boosting) and the SHAP (Shapley Additive Explanations) framework were used for feature selection and interpretation. Model performance was evaluated by 10-fold cross-validation and external validation.

RESULTS

One developed model including 15 features outperformed the SOFA (Sequential Organ Failure Assessment) score for the prediction of hospital mortality, with areas under the curve of 0.79 (95% CI, 0.79-0.80) and 0.71 (95% CI, 0.71-0.71) in the development cohort and 0.74 (95% CI, 0.73-0.74) and 0.71 (95% CI, 0.71-0.71) in the validation cohort (P < 0.001 for both). A second developed model including 14 features outperformed KDIGO (Kidney Disease: Improving Global Outcomes) AKI severity staging for the prediction of MAKE: 0.78 (95% CI, 0.78-0.78) versus 0.66 (95% CI, 0.66-0.66) in the development cohort and 0.73 (95% CI, 0.72-0.74) versus 0.67 (95% CI, 0.67-0.67) in the validation cohort (P < 0.001 for both).

LIMITATIONS

The models are applicable only to critically ill adult patients with incident AKI within the first 3 days of an ICU stay.

CONCLUSIONS

The reported clinical models exhibited better performance for mortality and kidney recovery prediction than standard scoring tools commonly used in critically ill patients with AKI in the ICU. Additional validation is needed to support the utility and implementation of these models.

PLAIN-LANGUAGE SUMMARY

Acute kidney injury (AKI) occurs commonly in critically ill patients admitted to the intensive care unit (ICU) and is associated with high morbidity and mortality rates. Prediction of mortality and recovery after an episode of AKI may assist bedside decision making. In this report, we describe the development and validation of a clinical model using data from the first 3 days of an ICU stay to predict hospital mortality and major adverse kidney events occurring as long as 120 days after hospital discharge among critically ill adult patients who experienced AKI within the first 3 days of an ICU stay. The proposed clinical models exhibited good performance for outcome prediction and, if further validated, could enable risk stratification for timely interventions that promote kidney recovery.

The Role of Cell-Free DNA in Cancer Treatment Decision Making

The aim of this review is to evaluate the present status of the use of cell-free DNA and its fraction of circulating tumor DNA (ctDNA) because this year July 2022, an ESMO guideline was published regarding the application of ctDNA in patient care. This review is for clinical oncologists to explain the concept, the terms used, the pros and cons of ctDNA; thus, the technical aspects of the different platforms are not reviewed in detail, but we try to help in navigating the current knowledge in liquid biopsy. Since the validated and adequately sensitive ctDNA assays have utility in identifying actionable mutations to direct targeted therapy, ctDNA may be used for this soon in routine clinical practice and in other different areas as well. The cfDNA fragments can be obtained by liquid biopsy and can be used for diagnosis, prognosis, and selecting among treatment options in cancer patients. A great proportion of cfDNA comes from normal cells of the body or from food uptake. Only a small part (<1%) of it is related to tumors, originating from primary tumors, metastatic sites, or circulating tumor cells (CTCs). Soon the data obtained from ctDNA may routinely be used for finding minimal residual disease, detecting relapse, and determining the sites of metastases. It might also be used for deciding appropriate therapy, and/or emerging resistance to the therapy and the data analysis of ctDNA may be combined with imaging or other markers. However, to achieve this goal, further clinical validations are inevitable. As a result, clinicians should be aware of the limitations of the assays. Of course, several open questions are still under research and because of it cfDNA and ctDNA testing are not part of routine care yet.

Bayesian Decision Analysis: An Underutilized Tool in Veterinary Medicine

Bayesian inference and decision analysis can be used to identify the most probable differential diagnosis and use those probabilities to identify the best choice of diagnostic or treatment among several alternatives. In this retrospective case analysis, we surveyed three experts on the prior probability of several differential diagnoses, given the signalment and history of a ferret presenting for lethargy and anorexia, and the conditional probability of different clinical findings (physical, bloodwork, imaging, etc.), given a diagnosis. Using these data and utility estimates provided by other clinicians, we constructed a decision tree to retrospectively identify the optimal treatment choice between exploratory laparotomy and medical management. We identified medical management as the optimal choice, in contrast to the original clinical team which performed an exploratory laparotomy. We discuss the potential cognitive biases of the original clinical team. We also discuss the strengths, e.g., shared decision making, and limitations of a Bayesian decision analysis in the veterinary clinic. Bayesian decision analysis can be a useful tool for retrospective case analysis and prospective decision making, especially for deciding on invasive interventions or end-of-life care. The dissimilarity of expert-derived probability estimates makes Bayesian decision analysis somewhat challenging to apply, particularly in wide-ranging specialties like zoological medicine.

NHS knowledge and library services in England in the digital age

National Health Service (NHS) knowledge and library services in England are integrating digital advances into their systems and services. Health Education England (HEE) leads on the development of NHS library services. A key workstream focuses on (1) improving the infrastructure to enable discovery and management of digital knowledge resources; (2) collaborating with local teams to establish regional library management systems that are integrated with the new national discovery service for healthcare staff and learners. This article explores initiatives on resource discovery as well as the need for system-wide partnership working to ensure that biomedical knowledge in computable form is findable, accessible, interoperable and reusable. Low levels of health and digital literacy pose a significant barrier to using health information and accessing health services. A range of interventions are aimed at enhancing citizens' digital and health literacy skills. The education and life-long learning needs of the knowledge and library services workforce are considered. Working with CILIP and higher education institutions, HEE delivers a range of educational offers through its Learning Academy. As Artificial Intelligence and automation are implemented in health systems, knowledge and library staff form a crucial bridge between technology and those who use it.

Evaluating user-personas as supplementary tools in AAC intervention and clinician decision making

Models used for the design and service delivery of Augmentative and Alternative Communication (AAC) systems are limited. There are no standardized protocols for gathering user requirements beyond clinical/diagnostic information relating to AAC access needs (i.e., physical and cognitive capabilities). Nonetheless, information on the social, cultural, and psychological aspects of technology orientation and use are important to understanding how an AAC system will complement the user's lifestyle, personal goals, values, and activities. Persona development is a user-centered design method that creates descriptive user models of different segments of a user population. Personas describe users' personal characteristics, and the ways in which they think, behave, and engage in activities (with or without technology). The objective of this study is to investigate the utility of user personas as a supplementary tool to aid SLPs in AAC assessment and service delivery.Three personas of individuals with Amyotrophic Lateral Sclerosis (ALS) were developed and validated in our prior research. Twelve SLPs engaged in mock AAC assessments of the three ALS case studies under two conditions: with or without the use of personas as a supplemental informational tool. By and large, there were no statistically significant differences between groups across objective measures; however, interview sessions with the SLP participants revealed benefits to using personas during clinical decision-making, particularly for training novice SLPs. Discussion also focuses on ways in which user personas can be adapted and improved to mitigate some of the challenges and risks identified.