Features of cardiovascular magnetic resonance native T1 mapping in maintenance hemodialysis patients and their related factors

PURPOSE

Increased myocardial T1 values on cardiovascular MRI (CMRI) have been shown to be a surrogate marker for myocardial fibrosis. The use of CMRI in patients on hemodialysis (HD) remains limited. This research aimed to explore the characteristics of native T1 values in HD patients and identify factors related to T1 values.

METHODS

A total of thirty-two patients on HD and fourteen healthy controls were included in this study. All participants underwent CMRI. Using modified Look-Locker inversion recovery (MOLLI) sequence, native T1 mapping was achieved. Native CMRI T1 values were compared between the two groups. In order to analyze the relationship between T1 values and clinical parameters, correlation analysis was performed in patients on HD.

RESULTS

Patients on HD exhibited elevated global native T1 values compared to control subjects. In the HD group, the global native T1 value correlated positively with intact parathyroid hormone (iPTH) (r = 0.418, p = 0.017) and negatively with triglycerides (r= -0.366, p = 0.039). Moreover, the global native T1 value exhibited a positive correlation with the left ventricular end-diastolic volume indexed to body surface area (BSA; r = 0.528, p = 0.014), left ventricular end-systolic volume indexed to BSA (r = 0.506, p = 0.019), and left ventricular mass indexed to BSA (r = 0.600, p = 0.005). A negative correlation was observed between the global native T1 value and ejection fraction (r = 0.-0.551, p = 0.010).

CONCLUSION

The global native T1 value was prolonged in HD patients compared with controls. In the HD group, the global T1 value correlated strongly with iPTH, triglycerides, and cardiac structural and functional parameters.

Enhancing pre-transplant cardiac assessment: Validation and utility of the CAD-LT score with CCTA in liver transplant candidates

BACKGROUND

Coronary computed tomography angiography (CCTA) is increasingly being used in the preoperative workup for liver transplantation (LT). We sought to assess the utility of integrating CCTA with the novel CAD-LT (Coronary Artery Disease in Liver Transplantation) score and its impact on reducing the need for invasive coronary angiography prior to LT.

METHODS

We conducted a retrospective cohort study of consecutive patients (age ≥ 18 years) who underwent CCTA for LT workup between 2011 and 2018 at the Victorian Liver Transplant Unit, Melbourne, Australia. CAD-LT scores, a traditional risk factor-based criteria, were calculated, and patients stratified as low-, intermediate- or high-risk.

RESULTS

Overall, 229 patients underwent CCTA. The mean age was 66 ± 5 years (82% male) with a modest-to-high risk factor burden (diabetes, 53%; hypertension, 46%; current or former smoker, 62%). The mean CAD-LT score of our cohort was 12.4 ± 4.0. No patients were classified as low-risk, 49 patients (21.4%) were deemed intermediate-risk and 180 patients (78.6%) were deemed high-risk. A high CAD-LT score (≥ 9) showed high sensitivity (95.3% [95% CI 86-98%]) and modest specificity (27.8% [95% CI 21-35%]) for the detection of obstructive coronary artery disease on CCTA, with a negative predictive value of 94%. Following multidisciplinary discussions, only 41 patients (18%) of patients proceeded to ICA of which 27% received percutaneous coronary intervention.

CONCLUSIONS

The use of CCTA in patients deemed intermediate- to high-risk by the CAD-LT score has the potential to reduce the need for invasive coronary angiography in patients undergoing LT workup.

Tissue mapping by cardiac magnetic resonance imaging for the prognostication of cardiac amyloidosis: A systematic review and meta-analysis

BACKGROUND

Cardiac amyloidosis is increasingly recognized as a significant contributor to cardiovascular morbidity and mortality. With the emergence of novel therapies, there is a growing interest in prognostication of patients with cardiac amyloidosis using cardiac magnetic resonance imaging (CMR). In this systematic review and meta-analysis, we aimed to examine the prognostic significance of myocardial native T1 and T2, and extracellular volume (ECV).

METHODS

Observational cohort studies or single arms of clinical trials were eligible. MEDLINE, EMBASE and CENTRAL were systematically searched from their respective dates of inception to January 2023. No exclusions were made based on date of publication, study outcomes, or study language. The study populations composed of adult patients (≥18 years old) with amyloid cardiomyopathy. All studies included the use of CMR with and without intravenous gadolinium contrast administration to assess myocardial native T1 mapping, T2 mapping, and ECV in association with the pre-specified primary outcome of all-cause mortality. Data were extracted from eligible primary studies by two independent reviewers and pooled via the inverse variance method using random effects models for meta-analysis.

RESULTS

A total of 3852 citations were reviewed. A final nine studies including a total of 955 patients (mean age 65 ± 10 years old, 32% female, mean left ventricular ejection fraction (LVEF) 59 ± 12% and 24% had NYHA class III or IV symptoms) with cardiac amyloidosis [light chain amyloidosis (AL) 50%, transthyretin amyloidosis (ATTR) 49%, other 1%] were eligible for inclusion and suitable for data extraction. All included studies were single centered (seven with 1.5 T MRI scanners, two with 3.0 T MRI scanners) and non-randomized in design, with follow-up spanning from 8 to 64 months (median follow-up = 25 months); 320 patients died during follow-up, rendering a weighted mortality rate of 33% across studies. Compared with patients with AL amyloid, patients with ATTR amyloid had significantly higher mean left ventricular mass index (LVMi) (102 ± 34 g/m2 vs 127 ± 37 g/m2, p = 0.02). N-terminal pro-brain natriuretic peptide (NT-proBNP), troponin T levels, mean native T1 values, ECV and T2 values did not differ between patients with ATTR amyloid and AL amyloid (all p > 0.25). Overall, the hazard ratios for mortality were 1.33 (95% CI = [1.10, 1.60]; p = 0.003; I2 = 29%) for every 60 ms higher T1 time, 1.16 (95% CI = [1.09, 1.23], p < 0.0001; I2 = 76%) for every 3% higher ECV, and 5.23 (95% CI = [2.27, 12.02]; p < 0.0001; I2 = 0%) for myocardial-to-skeletal T2 ratio below the mean (vs above the mean).

CONCLUSION

Higher native T1 time and ECV, and lower myocardial to skeletal T2 ratio, on CMR are associated with worse mortality in patients with cardiac amyloidosis. Therefore, tissue mapping using CMR may offer a useful non-invasive technique to monitor disease progression and determine prognosis in patients with cardiac amyloidosis.

Predicting Hospital Survival in Patients Admitted to ICU with Pulmonary Embolism

OBJECTIVE

The Pulmonary Embolism Severity Index (PESI) and simplified PESI (sPESI) predict mortality for patients with PE. We compared PESI/sPESI to the Acute Physiology and Chronic Health Evaluation IV (APACHE-IV) in predicting mortality in patients with PE admitted to the intensive care unit (ICU). Additionally, we assessed the performance of a novel ICU-sPESI score created by adding three clinical variables associated with acuity of PE presentation (intubation, confusion [altered mental status], use of vasoactive infusions) to sPESI.

MATERIALS AND METHODS

Using the eICU Collaborative Research Database from 2014 to 2015, we conducted a large retrospective cohort study of adult patients admitted to the ICU with a primary diagnosis of PE. We calculated APACHE-IV, PESI, sPESI, and ICU-sPESI scores and compared their performance for predicting in-hospital mortality using area under the receiver operating characteristic (AUROC) curve. Score thresholds for >99% negative predictive values (NPV) were calculated for each score. Survival was estimated using the Kaplan-Meier method.

RESULTS

We included 1424 PE cases. In-hospital mortality was 6.3% [95% CI: 5.1%-7.6%]. AUROC for APACHE-IV, PESI, and sPESI were 0.870, 0.848, and 0.777, respectively. APACHE-IV and PESI outperformed sPESI (P < 0.01 for both comparisons), while APACHE-IV and PESI demonstrated similar performance (P = 0.322). The ICU-sPESI performance was similar to APACHE-IV and PESI (AUROC = 0.847; AUROC comparison: APACHE-IV vs ICU-sPESI: P = 0.396; PESI vs ICU-sPESI: P = 0.945). Hospital mortality for ICU-sPESI scores 0-2 was 1.1%, and for scores 3, 4, 5, 6, and ≥7 was 8.6%, 11.7%, 29.2%, 37.5%, and 76.9%, respectively. Score thresholds for >99% NPV were ≤48 for APACHE-IV, ≤115 for PESI, and 0 points for sPESI and ICU-sPESI.

CONCLUSIONS

By accounting for severity of PE presentation, our newly proposed ICU-sPESI score provided improved PE mortality prediction compared to the original sPESI score and offered excellent discrimination of mortality risk.

Evaluation of models of sequestration flow in coronary arteries-Physiology versus anatomy?

BACKGROUND

Myocardial ischaemia results from insufficient coronary blood flow. Computed virtual fractional flow reserve (vFFR) allows quantification of proportional flow loss without the need for invasive pressure-wire testing. In the current study, we describe a novel, conductivity model of side branch flow, referred to as 'leak'. This leak model is a function of taper and local pressure, the latter of which may change radically when focal disease is present. This builds upon previous techniques, which either ignore side branch flow, or rely purely on anatomical factors. This study aimed to describe a new, conductivity model of side branch flow and compare this with established anatomical models.

METHODS AND RESULTS

The novel technique was used to quantify vFFR, distal absolute flow (Qd) and microvascular resistance (CMVR) in 325 idealised 1D models of coronary arteries, modelled from invasive clinical data. Outputs were compared to an established anatomical model of flow. The conductivity model correlated and agreed with the reference model for vFFR (r = 0.895, p < 0.0001; ＋0.02, 95% CI 0.00 to ＋ 0.22), Qd (r = 0.959, p < 0.0001; -5.2 mL/min, 95% CI -52.2 to ＋13.0) and CMVR (r = 0.624, p < 0.0001; ＋50 Woods Units, 95% CI -325 to ＋2549).

CONCLUSION

Agreement between the two techniques was closest for vFFR, with greater proportional differences seen for Qd and CMVR. The conductivity function assumes vessel taper was optimised for the healthy state and that CMVR was not affected by local disease. The latter may be addressed with further refinement of the technique or inferred from complementary image data. The conductivity technique may represent a refinement of current techniques for modelling coronary side-branch flow. Further work is needed to validate the technique against invasive clinical data.

Prognostic impact of MRI-derived feature tracking myocardial strain in patients with non-ischaemic dilated cardiomyopathy: a systematic review and meta-analysis

AIM

To evaluate the clinical utility of feature tracking (FT)-derived myocardial strain in patients with non-ischaemic dilated cardiomyopathy (NIDCM).

MATERIALS AND METHODS

Electronic database searches of PubMed, Web of Science Core Collection, Cochrane advanced search, and EMBASE were performed. Studies on NIDCM were divided into categories according to left ventricular ejection fraction (LVEF; <30%, 30-40%, >40%), and correlations between strains and prevalence of late gadolinium enhancement (LGE) were evaluated by weighted correlation coefficients. Global longitudinal strain (GLS) hazard ratios were also integrated for prediction of future adverse events.

RESULTS

The present meta-analysis analysed data from 5,767 patients with NIDCM from 30 eligible studies. GLS and global circumferential strain significantly differed across the three LVEF categories (all p<0.05); however, global radial strain did not. Only GLS showed a strong correlation with the prevalence of LGE (Spearman's correlation coefficient = 0.61). The pooled HR of GLS for predicting adverse events was 1.15 (95% confidence interval [CI]: 1.07-1.23, p<0.001).

CONCLUSION

In this meta-analysis, FT-derived GLS was strongly correlated with myocardial fibrosis and was an important predictor of future adverse events. These results suggest that FT-derived GLS may be useful in the pathological evaluation and risk stratification of NIDCM.

Differentiating Macrovascular and Microvascular Ischemia Using Fractal Analysis of Dynamic Myocardial Perfusion Stress-CT

OBJECTIVES

Fractal analysis of dynamic myocardial stress computed tomography perfusion imaging (4D-CTP) has shown potential to noninvasively differentiate obstructive coronary artery disease (CAD) and coronary microvascular disease (CMD). This study validates fractal analysis of 4D-CTP in a multicenter setting and assesses its diagnostic accuracy in subgroups with ischemia and nonobstructed coronary arteries (INOCA) and with mild to moderate stenosis.

MATERIALS AND METHODS

From the AMPLIFiED multicenter trial, patients with suspected or known chronic myocardial ischemia and an indication for invasive coronary angiography were included. Patients underwent dual-source CT angiography, 4D-CTP, and CT delayed-enhancement imaging. Coronary artery disease, CMD, and normal perfusion were defined by a combined reference standard comprising invasive coronary angiography with fractional flow reserve, and absolute or relative CT-derived myocardial blood flow. Nonobstructed coronary arteries were defined as ≤25% stenosis and mild to moderate stenosis as 26%-80%.

RESULTS

In 127 patients (27% female), fractal analysis accurately differentiated CAD (n = 61, 23% female), CMD (n = 23, 30% female), and normal perfusion (n = 34, 35% female) with a multiclass area under the receiver operating characteristic curve (AUC) of 0.92 and high agreement (multiclass κ = 0.89). In patients with ischemia (n = 84), fractal analysis detected CAD (n = 61) over CMD (n = 23) with sensitivity of 95%, specificity of 74%, accuracy of 89%, and AUC of 0.83. In patients with nonobstructed coronary arteries (n = 33), INOCA (n = 15) was detected with sensitivity of 100%, specificity of 78%, accuracy of 88%, and AUC of 0.94. In patients with mild to moderate stenosis (n = 27), fractal analysis detected CAD (n = 19) over CMD with sensitivity of 84%, specificity of 100%, accuracy of 89%, and AUC of 0.95.

CONCLUSIONS

In this multicenter study, fractal analysis of 4D-CTP accurately differentiated CAD and CMD including subgroups with INOCA and with mild to moderate stenosis.

Stress and Rest Pulmonary Transit Times Assessed by Cardiovascular Magnetic Resonance

Acquiring pulmonary circulation parameters as a potential marker of cardiopulmonary function is not new. Methods to obtain these parameters have been developed over time, with the latest being first-pass perfusion sequences in cardiovascular magnetic resonance (CMR). Even though more data on these parameters has been recently published, different nomenclature and acquisition methods are used across studies; some works even reported conflicting data. The most commonly used circulation parameters obtained using CMR include pulmonary transit time (PTT) and pulmonary transit beats (PTB). PTT is the time needed for a contrast agent (typically gadolinium-based) to circulate from the right ventricle (RV) to the left ventricle (LV). PTB is the number of cardiac cycles the process takes. Some authors also include corrected heart rate (HR) versions along with standard PTT. Besides other methods, CMR offers an option to assess stress circulation parameters, but data are minimal. This review aims to summarize the up-to-date findings and provide an overview of the latest progress on this promising, dynamically evolving topic.

Personalized Pressure Conditions and Calibration for a Predictive Computational Model of Coronary and Myocardial Blood Flow

Predictive modeling of hyperemic coronary and myocardial blood flow (MBF) greatly supports diagnosis and prognostic stratification of patients suffering from coronary artery disease (CAD). In this work, we propose a novel strategy, using only readily available clinical data, to build personalized inlet conditions for coronary and MBF models and to achieve an effective calibration for their predictive application to real clinical cases. Experimental data are used to build personalized pressure waveforms at the aortic root, representative of the hyperemic state and adapted to surrogate the systolic contraction, to be used in computational fluid-dynamics analyses. Model calibration to simulate hyperemic flow is performed in a "blinded" way, not requiring any additional exam. Coronary and myocardial flow simulations are performed in eight patients with different clinical conditions to predict FFR and MBF. Realistic pressure waveforms are recovered for all the patients. Consistent pressure distribution, blood velocities in the large arteries, and distribution of MBF in the healthy myocardium are obtained. FFR results show great accuracy with a per-vessel sensitivity and specificity of 100% according to clinical threshold values. Mean MBF shows good agreement with values from stress-CTP, with lower values in patients with diagnosed perfusion defects. The proposed methodology allows us to quantitatively predict FFR and MBF, by the exclusive use of standard measures easily obtainable in a clinical context. This represents a fundamental step to avoid catheter-based exams and stress tests in CAD diagnosis.

Enhanced identification of women at risk for preterm birth via quantitative ultrasound: a prospective cohort study

BACKGROUND

Historically, clinicians have relied on medical risk factors and clinical symptoms for preterm birth risk assessment. In nulliparous women, clinicians may rely solely on reported symptoms to assess for the risk of preterm birth. The routine use of ultrasound during pregnancy offers the opportunity to incorporate quantitative ultrasound scanning of the cervix to potentially improve assessment of preterm birth risk.

OBJECTIVE

This study aimed to investigate the efficiency of quantitative ultrasound measurements at relatively early stages of pregnancy to enhance identification of women who might be at risk for spontaneous preterm birth.

STUDY DESIGN

A prospective cohort study of pregnant women was conducted with volunteer participants receiving care from the University of Illinois Hospital in Chicago, Illinois. Participants received a standard clinical screening followed by 2 research screenings conducted at 20±2 and 24±2 weeks. Quantitative ultrasound scans were performed during research screenings by registered diagnostic medical sonographers using a standard cervical length approach. Quantitative ultrasound features were computed from calibrated raw radiofrequency backscattered signals. Full-term birth outcomes and spontaneous preterm birth outcomes were included in the analysis. Medically indicated preterm births were excluded from the analysis. Using data from each visit, logistic regression with Akaike information criterion feature selection was conducted to derive predictive models for each time frame based on historical clinical and quantitative ultrasound features. Model evaluations included a likelihood ratio test of quantitative ultrasound features, cross-validated receiver operating characteristic curve analysis, sensitivity, and specificity.

RESULTS

On the basis of historical clinical features alone, the best predictive model had an estimated receiver operating characteristic area under the curve of 0.56±0.03. By the time frame of Visit 1, a predictive model using both historical clinical and quantitative ultrasound features provided a modest improvement in the area under the curve (0.63±0.03) relative to that of the predictive model using only historical clinical features. By the time frame of Visit 2, the predictive model using historical clinical and quantitative ultrasound features provided significant improvement (likelihood ratio test, P<.01), with an area under the curve of 0.69±0.03.

CONCLUSION

Accurate identification of women at risk for spontaneous preterm birth solely through historical clinical features has been proven to be difficult. In this study, a history of preterm birth was the most significant historical clinical predictor of preterm birth risk, but the historical clinical predictive model performance was not statistically significantly better than the no-skill level. According to our study results, including quantitative ultrasound yields a statistically significant improvement in risk prediction as the pregnancy progresses.

Use of artificial intelligence and I-Score for prediction of recurrence before catheter ablation of atrial fibrillation

BACKGROUND

Based solely on pre-ablation characteristics, previous risk scores have demonstrated variable predictive performance. This study aimed to predict the recurrence of AF after catheter ablation by using artificial intelligence (AI)-enabled pre-ablation computed tomography (PVCT) images and pre-ablation clinical data.

METHODS

A total of 638 drug-refractory paroxysmal atrial fibrillation (AF) patients undergone ablation were recruited. For model training, we used left atria (LA) acquired from pre-ablation PVCT slices (126,288 images). A total of 29 clinical variables were collected before ablation, including baseline characteristics, medical histories, laboratory results, transthoracic echocardiographic parameters, and 3D reconstructed LA volumes. The I-Score was applied to select variables for model training. For the prediction of one-year AF recurrence, PVCT deep-learning and clinical variable machine-learning models were developed. We then applied machine learning to ensemble the PVCT and clinical variable models.

RESULTS

The PVCT model achieved an AUC of 0.63 in the test set. Various combinations of clinical variables selected by I-Score can yield an AUC of 0.72, which is significantly better than all variables or features selected by nonparametric statistics (AUCs of 0.66 to 0.69). The ensemble model (PVCT images and clinical variables) significantly improved predictive performance up to an AUC of 0.76 (sensitivity of 86.7% and specificity of 51.0%).

CONCLUSIONS

Before ablation, AI-enabled PVCT combined with I-Score features was applicable in predicting recurrence in paroxysmal AF patients. Based on all possible predictors, the I-Score is capable of identifying the most influential combination.

Coronary Artery Disease: Role of Computed Tomography and Recent Advances

In this review, the authors summarize the role of coronary computed tomography angiography and coronary artery calcium scoring in different clinical presentations of chest pain and preventative care and discuss future directions and new technologies such as pericoronary fat inflammation and the growing footprint of artificial intelligence in cardiovascular medicine.

Diagnostic value of cardiothoracic ratio in patients with non-ischaemic cardiomyopathy: comparison to cardiovascular magnetic resonance imaging

PURPOSE

To determine the reliability of the cardiothoracic ratio (CTR) as a simple method to assess the cardiac size and function in patients with non-ischemic cardiomyopathy (NICM).

METHODS

In a sample of 91 patients (66 patients with diagnosed non-ischemic cardiomyopathy and 25 controls) we calculated the CTR on a posteroanterior chest radiograph and ventricular and atrial size based on accepted cardiovascular magnetic resonance (CMR) imaging values. Left and right ventricular ejection fraction was also calculated. The CTR and cardiac chamber size were compared between patients with NICM and healthy individuals. The distinction between normal and increased cardiac chamber size was made using published normal CMR reference values stratified by age and gender.

RESULTS

CTR values were higher in the NICM group (50.7±5.5 % Vs. 45.3±4.7 %, p<0.001). Likewise, LVEDVi, LV indexed mass, LA indexed volume, LA indexed area, and RA indexed area were higher, and LVEF and RVEF were lower in patients with non-ischemic cardiomyopathy (p < 0.05). In patients with non-ischemic cardiomyopathy, the greatest correlation between CTR and CMR values was with LVEDVi (ρ=0.4, p < 0.001), LA indexed volume (ρ=0.5, p < 0.001), LA indexed area (ρ=0.5, p < 0.001) and RA indexed area (ρ=0.4, p < 0.001). However, the correlation strength was only moderate.

CONCLUSION

Despite patients with NICM had higher CTR values than the control group, a substantial proportion of these patients showed normal CTRs (<50 %). This fact limits the usefulness of CTR to reliably predict NICM. Correlation between CTR and heart chamber dilation on CMR was only weak to moderate.

Predictive value of C-reactive protein for postoperative liver-specific surgical site infections

BACKGROUND

C-reactive protein is a useful biological tool to predict infectious complications, but its predictive value in detecting organ-specific surgical site infection after liver resection has never been studied. We aimed to evaluate the predictive value of c-reactive protein and determine the cut-off values to detect postoperative liver resection-surgical site infection.

METHODS

A multicentric analysis of consecutive patients with liver resection between 2018 and 2021 was performed. The predictive value of postoperative day 1, postoperative day 3, and postoperative day 5 C-reactive protein levels was evaluated using the area under the receiver operating characteristic curve. Cut-off values were determined using the Youden index in a 500-fold bootstrap resampling of 500 patients treated at 3 centers, who comprised the development cohort and were tested in an external independent validation cohort of 166 patients at a fourth center.

RESULTS

Among the 500 patients who underwent liver resection of the development cohort, liver resection-surgical site infection occurred in 66 patients (13.2%), and the median time to diagnosis was 6.0 days (interquartile range, 4.0-9.0) days. Median C-reactive protein levels were significantly higher on postoperative day 1, postoperative day 3, and postoperative day 5 in the liver resection-surgical site infection group compared with the non-surgical site infection group (50.5 vs 34.5 ng/mL, 148.0 vs 72.5 ng/mL, and 128.4 vs 35.2 ng/mL, respectively; P < .001). Postoperative day 3 and postoperative day 5 C-reactive protein-level area under the curve values were 0.76 (95% confidence interval, 0.64-0.88, P < .001) and 0.82 (95% confidence interval, 0.72-0.92, P < .001), respectively. Postoperative day 3 and postoperative day 5 optimal cut-off values of 100 mg/L and 87.0 mg/L could be used to rule out liver resection-surgical site infection, with a negative predictive value of 87.0% (interquartile range, 70.2-93.8) and 76.0% (interquartile range, 65.0-88.0), respectively, in the validation cohort.

CONCLUSION

Postoperative day 3 and postoperative day 5 C-reactive protein levels may be valuable predictive tools for liver resection-surgical site infection and aid in hospital discharge decision-making in the absence of other liver-related complications.

Quantitative computed tomography angiography evaluation of the coronary fractional flow reserve in patients with left anterior descending artery myocardial bridging

PURPOSE

To quantitatively investigate the effect of myocardial bridge (MB) in the left anterior descending artery (LAD) on the fractional flow reserve (FFR).

MATERIALS AND METHODS

Three-hundred patients with LAD MB who had undergone coronary artery CT angiography (CCTA) were retrospectively enroled, and 104 normal patients were enroled as the control. The CCTA-derived fractional flow reserve (FFRCT) was measured at the LAD 10 mm proximal (FFR1) and 20-40 mm distal (FFR3) to the MB and at the MB location (FFR2).

RESULTS

FFR2 and FFR3 of the MB (with BM only) and MBLA (with both MB and atherosclerosis) groups were significantly (p < 0.01) lower than those of the control. The FFR3 distal to the MB was significantly lower (p < 0.01) than that of the control. The FFRCT of the whole LAD in the MBLA group was significantly (p < 0.05) lower than that of the MB and control group (p < 0.05). MB length (OR 1.061) and MB muscle index (odds ratio or OR 1.007) were two risk factors for abnormal FFRCT, and MB length was a significant independent risk factor for abnormal FFRCT (OR = 1.077). LAD stenosis degree was a risk factor for abnormal FFRCT values (OR 3.301, 95% confidence interval [CI] 1.441-7.562, p = 0.005) and was also a significant independent risk factor (OR = 3.369, 95% CI: 1.392-8.152; p = 0.007) for abnormal FFRCT.

CONCLUSION

MB significantly affects the FFRCT of distal coronary artery. For patients with MB without atherosclerosis, the MB length is a risk factor significantly affecting FFRCT, and for patients with MB accompanied by atherosclerosis, LAD stenotic severity is an independent risk factor for FFRCT.

Positive predictive value of myositis antibody line blot testing in patients with suspected idiopathic inflammatory myopathy

INTRODUCTION/AIMS

Line blot (LB) is in widespread use for myositis antibody detection. Yet, studies of its positive predictive value (PPV) in patients with suspected idiopathic inflammatory myopathy (IIM), which would be of particular relevance to neuromuscular clinicians, are lacking. We aimed to determine the PPV of myositis antibody LB testing in patients with suspected IIM, and examine whether PPV was significantly impacted by intensity of antibody positivity.

METHODS

This was a retrospective study of patients who underwent myositis antibody LB testing for suspected IIM between March 2019 and August 2022.

RESULTS

Of 70 patients who underwent testing for suspected IIM and had positive myositis antibody LB results, 43 (61%) were female and the median age was 61 years (range: 10-83 years). Forty-four were classified as true-positives, yielding a PPV of 63%. The PPV of patients with weak-positive myositis antibody results (14/30, 47%) was significantly lower than the PPV of patients with moderate-positive or strong-positive myositis antibody results (30/40, 75%) (p = .02).

DISCUSSION

Our study found that myositis antibody LB testing in patients with suspected IIM had a modest PPV, underscoring the need for antibody interpretation in the context of all available clinical and ancillary test data to avoid misdiagnosis. The significantly lower PPV in patients with weak-positive results emphasizes the particular importance of clinical correlation in such patients. Further study into the diagnostic performance of various LBs for myositis antibody detection is needed to inform their interpretation in clinical practice.

The role of cardiac magnetic resonance in sports cardiology: results from a large cohort of athletes

BACKGROUND

Cardiac magnetic resonance (CMR) provides information on morpho-functional abnormalities and myocardial tissue characterisation. Appropriate indications for CMR in athletes are uncertain.

OBJECTIVE

To analyse the CMR performed at our Institute to evaluate variables associated with pathologic findings in a large cohort of athletes presenting with different clinical conditions.

METHODS

All the CMR performed at our Institute in athletes aged > 14 years were recruited. CMR indications were investigated. CMR was categorised as "positive" or "negative" based on the presence of morphological and/or functional abnormalities and/or the presence of late gadolinium enhancement (excluding the right ventricular insertion point), fat infiltration, or oedema. Variables associated with "positive" CMR were explored.

RESULTS

A total of 503 CMR were included in the analysis. "Negative" and "positive" CMR were 61% and 39%, respectively. Uncommon ventricular arrhythmias (VAs) were the most frequent indications for CMR, but the proportion of positive results was low (37%), and only polymorphic ventricular patterns were associated with positive CMR (p = 0.006). T-wave inversion at 12-lead ECG, particularly on lateral and inferolateral leads, was associated with positive CMR in 34% of athletes (p = 0.05). Echocardiography abnormalities resulted in a large proportion (58%) of positive CMR, mostly cardiomyopathies.

CONCLUSION

CMR is more efficient in identifying a pathologic cardiac substrate in athletes in case of VAs (i.e., polymorphic beats), abnormal ECG repolarisation (negative T-waves in inferolateral leads), and borderline echocardiographic findings (LV hypertrophy, mildly depressed LV function). On the other hand, CMR is associated with a large proportion of negative results. Therefore, a careful clinical selection is needed to indicate CMR in athletes appropriately.

Comparison of the predictive validity of the Braden and Waterlow scales in intensive care unit patients: A multicentre study

BACKGROUND

The first step in preventing pressure injuries (PIs), which represent a significant burden on intensive care unit (ICU) patients and the health care system, is to assess the risk for developing PIs. A valid risk assessment scale is essential to evaluate the risk and avoid PIs.

OBJECTIVES

To compare the predictive validity of the Braden scale and Waterlow scale in ICUs.

DESIGN

A multicentre, prospective and cross-sectional study.

METHODS

We conducted this study among 6416 patients admitted to ICUs in Gansu province of China from April 2021 to October 2022. The incidence and characteristics of PIs were collected. The risk assessment of PIs was determined using the Braden and Waterlow scale. The sensitivity, specificity, positive and negative predictive values, and the area under the receiver operating characteristic curve of the two scales were compared.

RESULTS

Out of 5903 patients, 72 (1.2%) developed PIs. The sensitivity, specificity, positive and negative predictive, and the area under the curve of the Braden scale were 77.8%, 50.9%, 0.014 and 0.996, and 0.689, respectively. These values for the Waterlow scale were 54.2%, 71.1%, 0.017, 0.994 and 0.651.

CONCLUSIONS

Both scales could be used for risk assessment of PIs in ICU patients. However, the accuracy of visual inspection for assessment of skin colour, nursing preventive measures for patients and scales inter-rater inconsistency may limited the predictive validity statistics.

RELEVANCE TO CLINICAL PRACTICE

Both scales could be used for PIs risk assessment. The low specificity of the Braden scale and low sensitivity of the Waterlow scale remind medical staff to use them in combination with clinical judgement and other objective indicators.

PATIENT OR PUBLIC CONTRIBUTION

This study was designed to enhance the management of PIs. Patients and the general public were not involved in the study design, analysis, and interpretation of the data or manuscript preparation.

Implementation of remote monitoring strategies to improve chronic heart failure management

PURPOSE OF REVIEW

The goal of this review is to describe the current evidence available for remote monitoring devices available for patients with chronic heart failure, and also detail practical clinical recommendations for implementing these tools in daily clinical practice.

RECENT FINDINGS

Several devices ranging from sophisticated multiparametric algorithms in defibrillators, implantable pulmonary artery pressure sensors, and wearable devices to measure thoracic impedance can be utilized as important adjunctive tools to reduce the risk of heart failure hospitalization in patients with chronic heart failure. Pulmonary artery pressure sensors provide the most granular data regarding hemodynamic status, while alerts from wearable devices for thoracic impedance and defibrillator-based algorithms increase the likelihood of worsening clinical status while also having high negative predictive value when values are within normal range.

SUMMARY

Multiple device-based monitoring strategies are available to reduce longitudinal risk in patients with chronic heart failure. Further studies are needed to best understand a practical pathway to integrate multiple signals of data for early clinical decompensation risk predictionVideo abstract: http://links.lww.com/HCO/A95.

Quantitative Analysis of Radiation Therapy-Induced Cardiac and Aortic Sequelae in Patients With Lung Cancer via Magnetic Resonance Imaging: A Pilot Study

PURPOSE

The objective of this study was to quantify early radiation therapy (RT)-induced cardiac and aortic changes in patients with lung cancer using cardiac magnetic resonance imaging (MRI).

METHODS AND MATERIALS

Nine patients with lung cancer treated with RT completed MR scans at baseline (before RT) and at 3 and 6 months after RT completion. Cine, T1/T2, late gadolinium enhancement (LGE), and 4-dimensional flow MRIs were acquired to assess biological and mechanical cardiovascular changes globally (ie, over the entire left ventricle (LV) or aorta) and regionally (according to an American Heart Association model).

RESULTS

Regional metrics demonstrated multiple significant changes and dose-dependent responses. Notably, LGE showed changes at 3 and 6 months over septal and high-dose regions (P < .0458). Longitudinal strain changes were notable at septal and high-dose regions at 3 months and at septal regions at 6 months (P < .0469). Elevated T1/T2 signals (P < .0391) and changes in radial/circumferential strain at the septum (P < .0391) were observed at 3 months. Both T1/T2 signal and LGE were correlated with dose at 6 months (T1 signal also at 3 months), with significantly greater changes in regions receiving >50 Gy (P < .0331). LV dose was not correlated with LV strain changes (P > .1), but ascending aortic dose was correlated with strain changes at segments 1 and 2 of the LV (P < .0362). Global metrics identified only 2 significant responses: increase in LGE volume at 6 months and a reduction in ascending aortic circumferential strain at 3 months (P < .0356).

CONCLUSIONS

Early MR-based changes after RT occurred primarily in high-dose regions and the LV septal wall. Although several early signals resolved by 6 months, LGE and longitudinal strain changes persisted for at least 6 months. Dose-dependent responses/correlations were observed for T1/T2/LGE changes at 6 months, with the greatest effect in regions exposed to >50 Gy. Further investigations with larger cohorts and longer follow-up are warranted to confirm regional dose dependence and the association between aortic dose and LV strain observed in this pilot study.

Cardiac MRI feature-tracking-derived torsion mechanics in systolic and diastolic dysfunction in systemic light-chain cardiac amyloidosis

AIM

To describe the myocardial torsion mechanics in cardiac amyloidosis (CA), and evaluate the correlations between left ventricle (LV) torsion mechanics and conventional parameters using cardiac magnetic resonance imaging feature tracking (CMR-FT).

MATERIALS AND METHODS

One hundred and thirty-nine patients with light-chain CA (AL-CA) were divided into three groups: group 1 with preserved systolic function (LV ejection fraction [LVEF] ≥50%, n=55), group 2 with mildly reduced systolic function (40% ≤ LVEF <50%, n=51), and group 3 with reduced systolic function (LVEF <40%, n=33), and compared with age- and gender-matched healthy controls (n=26). All patients underwent cine imaging and late gadolinium-enhancement (LGE). Cine images were analysed offline using CMR-FT to estimate torsion parameters.

RESULTS

Global torsion, base-mid torsion, and peak diastolic torsion rate (diasTR) were significantly impaired in patients with preserved systolic function (p<0.05 for all), whereas mid-apex torsion and peak systolic torsion rate (sysTR) were preserved (p>0.05 for both) compared with healthy controls. In patients with mildly reduced systolic function, global torsion and base-mid torsion were lower compared to those with preserved systolic function (p<0.05 for both), while mid-apex torsion, sysTR, and diasTR were preserved (p>0.05 for all). In patients with reduced systolic function, only sysTR was significantly worse compared with mildly reduced systolic function (p<0.05). At multivariable analysis, right ventricle (RV) end-systolic volume RVESV index and NYHA class were independently related to global torsion, whereas LVEF was independently related to sysTR. RV ejection fraction (RVEF) was independently related to diasTR. LV global torsion performed well (AUC 0.71; 95% confidence interval [CI]: 0.61, 0.77) in discriminating transmural from non-transmural LGE in AL-CA patients.

CONCLUSION

LV torsion mechanics derived by CMR-FT could help to monitor LV systolic and diastolic function in AL-CA patients and function as a new imaging marker for LV dysfunction and LGE transmurality.

A supervised machine learning model for identifying predictive factors for recommending head and neck cancer surgery

BACKGROUND

New patient referrals are often processed by practice coordinators with little-to-no medical background. Treatment delays due to incorrect referral processing, however, have detrimental consequences. Identifying variables that are associated with a higher likelihood of surgical oncological resection may improve patient referral processing and expedite the time to treatment. The study objective is to develop a supervised machine learning (ML) platform that identifies relevant variables associated with head and neck surgical resection.

METHODS

A retrospective cohort study was conducted on 64 222 patient datapoints from the SEER database.

RESULTS

The random forest ML model correctly classified patients who were offered head and neck surgery with an 81% accuracy rate. The sensitivity and specificity rates were 86% and 71%. The positive and negative predictive values were 85% and 73%.

CONCLUSIONS

ML modeling accurately predicts head and neck cancer surgery recommendations based on patient and cancer information from a large population-based dataset. ML adjuncts for referral processing may decrease the time to treatment for patients with cancer.

Comparison of the Predictive Validity of Norton and Braden Scales in Determining the Risk of Pressure Injury in Elderly Patients

AIM

To compare the reliability and predictive validity of Norton and Braden scales in determining the risk of pressure injury in elderly patients.

DESIGN

This research used a comparative design. One hundred thirty elderly patients participated in the study.

METHODS

The daily pressure injury risk of participants was evaluated by a researcher using both the Norton and Braden scales in a consecutive manner.

RESULTS

The mean age of patients was 75.1 ± 8.5 years, and that for those without and with pressure injury development was 75.0 ± 8.3 years and 76.1 ± 9.7 years (P < .001), respectively. The reliability coefficients of the Norton and Braden scales were .82 and .89, respectively. The sensitivity, specificity, and positive and negative predictive values of the Norton Scale were 100%, 40.7%, 20.2%, and 100%, and those of the Braden Scale were 100%, 32.7%, 18.3%, and 100%, respectively.

CONCLUSIONS

The reliability of both scales for elderly patients was found to be high, and their ability to differentiate patients at risk was comparable. However, both scales had low specificity. Further research is needed to develop scales that have higher predictive validity for the elderly population, taking into account other risk factors that influence total scale scores.

S100B vs. "GFAP and UCH-L1" assays in the management of mTBI patients

OBJECTIVES

To compare for the first time the performance of "GFAP and UCH-L1" vs. S100B in a cohort of patients managed for mild traumatic brain injury (mTBI) according to actualized French guidelines.

METHODS

A prospective study was recently carried at the Emergency Department of Clermont-Ferrand University Hospital in France. Patients with mTBI presenting a medium risk of complications were enrolled. Blood S100B and "GFAP and UCHL-1" were sampled and measured according to French guidelines. S100B was measured in patients with samples within 3 h of trauma (Cobas®, Roche Diagnostics), while GFAP and UCHL-1 were measured in all patients (samples <3 h and 3-12 h) using another automated assay (i-STAT® Alinity, Abbott).

RESULTS

For sampling <3 h, serum S100B correctly identifies intracranial lesions with a specificity of 25.7 % (95 % CI; 19.5-32.6 %), a sensitivity of 100 % (95 % CI; 66.4-100 %), and a negative predictive value of 100 % (95 % CI; 92.5-100 %). For sampling <12 h, plasma "GFAP and UCH-L1" levels correctly identify intracranial lesions with a specificity of 31.7 % (95 % CI; 25.7-38.2 %), a sensitivity of 100 % (95 % CI; 73.5-100 %), and a negative predictive value of 100 % (95 % CI; 95-100 %). Comparison of specificities (25.7 vs. 31.7 %) did not reveal a statistically significant difference (p=0.16).

CONCLUSIONS

We highlight the usefulness of measuring plasma "GFAP and UCH-L1" levels to target mTBI patients (sampling within 12 h post-injury) and optimize the reduction of CT scans.

Baseline TREM-1 Whole Blood Gene Expression Does Not Predict Response to Adalimumab Treatment in Patients with Ulcerative Colitis or Crohn's Disease in the SERENE Studies

BACKGROUND AND AIMS

This study assessed whether baseline triggering receptor expressed on myeloid cells [TREM-1] whole blood gene expression predicts response to anti-tumour necrosis factor [anti-TNF] therapy in patients with ulcerative colitis [UC] or Crohn's disease [CD].

METHODS

TREM-1 whole blood gene expression was analysed by RNA sequencing in patients with moderately to severely active UC or CD treated with adalimumab in the Phase 3 SERENE-UC and SERENE-CD clinical trials. The predictive value of baseline TREM-1 expression was evaluated and compared according to endoscopic and clinical response vs non-response, and remission vs non-remission, at Weeks 8 and 52 [SERENE-UC], and Weeks 12 and 56 [SERENE-CD].

RESULTS

TREM-1 expression was analysed in 95 and 106 patients with UC and CD, respectively, receiving standard-dose adalimumab induction treatment. In SERENE-UC, baseline TREM-1 expression was not predictive of endoscopic response [p = 0.48], endoscopic remission [p = 0.53], clinical response [p = 0.58], or clinical remission [p = 0.79] at Week 8, or clinical response [p = 0.60] at Week 52. However, an association was observed with endoscopic response [p = 0.01], endoscopic remission [p = 0.048], and clinical remission [p = 0.04997] at Week 52. For SERENE-CD, baseline TREM-1 expression was not predictive of endoscopic response [p = 0.56], endoscopic remission [p = 0.33], clinical response [p = 0.07], or clinical remission [p = 0.65] at Week 12, or endoscopic response [p = 0.61], endoscopic remission [p = 0.51], clinical response [p = 0.62], or clinical remission [p = 0.97] at Week 56.

CONCLUSIONS

Baseline TREM-1 gene expression did not uniformly predict adalimumab response in SERENE clinical trials. Further research is needed to identify potential blood-based biomarkers predictive of response to anti-TNF therapy in patients with inflammatory bowel disease.

CLINICALTRIALS.GOV IDENTIFIERS

NCT02065622; NCT02065570.

Predictive improvement of adding coronary calcium score and a genetic risk score to a traditional risk model for cardiovascular event prediction

AIMS

Coronary artery calcium score (CACS) and polygenic risk score have been used as novel markers to predict cardiovascular (CV) events of asymptomatic individuals compared with traditional scores. No previous studies have directly compared the additive capacity of these two markers relative to conventional scores. The aim of the study was to evaluate the change in CV risk prediction ability when CACS, genetic risk score (GRS), or both are added to Systematic Coronary Risk Evaluation 2 (SCORE2).

METHODS AND RESULTS

In a prospective, observational population-based study, 1002 asymptomatic subjects (mean age 53.1 ± 6.8 years, 73.8% male), free of clinical coronary disease and diabetes, were selected from GENEMACOR-study controls. SCORE2, CACS, and GRS were estimated to evaluate CV events' predictive and discriminative ability through Harrell's C-statistics. Net reclassification improvement (NRI) and integrated discrimination index were used to reclassify the population. Multivariable Cox proportional hazard ratio (HR) analysis assessed the variables independently associated with CV events. C-statistic demonstrated that the discriminative value for CV event occurrence was 0.608 for SCORE2, increasing to 0.749 (P = 0.001) when CACS was added, and improved to 0.802 (P = 0.0008) with GRS, showing a better discriminative capacity for CV events. Continuous NRI reclassified >70% of the population. Cox proportional analysis showed that the highest categories of SCORE2, CACS, and GRS remained in the equation with an HR of 2.9 (P = 0.003), 5.0 (P < 0.0001), and 3.2 (P = 0.003), respectively, when compared with the lowest categories.

CONCLUSION

In our population, CACS added to SCORE2 had better ability than GRS in CV event risk prediction, discrimination, and reclassification. However, adding the three scores can become clinically relevant, especially in intermediate-risk persons.

Comprehensive characterization of cardiac contraction for improved post-infarction risk assessment

This study aims at identifying risk-related patterns of left ventricular contraction dynamics via novel volume transient characterization. A multicenter cohort of AMI survivors (n = 1021) who underwent Cardiac Magnetic Resonance (CMR) after infarction was considered for the study. The clinical endpoint was the 12-month rate of major adverse cardiac events (MACE, n = 73), consisting of all-cause death, reinfarction, and new congestive heart failure. Cardiac function was characterized from CMR in 3 potential directions: by (1) volume temporal transients (i.e. contraction dynamics); (2) feature tracking strain analysis (i.e. bulk tissue peak contraction); and (3) 3D shape analysis (i.e. 3D contraction morphology). A fully automated pipeline was developed to extract conventional and novel artificial-intelligence-derived metrics of cardiac contraction, and their relationship with MACE was investigated. Any of the 3 proposed directions demonstrated its additional prognostic value on top of established CMR indexes, myocardial injury markers, basic characteristics, and cardiovascular risk factors (P < 0.001). The combination of these 3 directions of enhancement towards a final CMR risk model improved MACE prediction by 13% compared to clinical baseline (0.774 (0.771-0.777) vs. 0.683 (0.681-0.685) cross-validated AUC, P < 0.001). The study evidences the contribution of the novel contraction characterization, enabled by a fully automated pipeline, to post-infarction assessment.

Comprehensive Angiography-Derived Functional Assessment of Epicardial and Microvascular Coronary Disease. Correlation With Non-invasive Myocardial Stress Imaging

Coronary angiography (CA) is poorly correlated with non-invasive myocardial stress imaging (NSI) and myocardial ischemia is often observed in patients with unobstructed coronary arteries. Moreover, the diagnostic performance of combined epicardial and microcirculatory angiography-derived physiological assessment and its correlation with NSI remains unknown. A total of 917 coronary vessels in 319 patients who underwent both CA and NSI were included in this multicenter observational retrospective analysis. Quantitative flow ratio (QFR) and angiography-derived index of microcirculatory resistance (IMRangio) analyses were performed to estimate coronary epicardial and microcirculatory function respectively. NSI demonstrated evidence of myocardial ischemia in 76% of the cases. IMRangio (36 [22 to 50] vs 29 [21 to 41], p <0.001) was significantly higher and QFR (0.92 [0.78 to 0.99] vs 0.97 [0.91 to 0.99], p <0.001) was significantly lower in vessels subtending ischemic territories. Overall, the diagnostic accuracy of QFR was moderate (area under the curve of receiver operating characteristic [AUCROC] 0.632 [95% confidence interval [CI] 0.589 to 0.674], p <0.0001) but it was higher in patients with normal microcirculatory function (AUCROC = 0.726 [95% CI 0.669 to 0.784], p <0.0001, p Value for AUCROC comparison = 0.009). Combined QFR/IMRangio assessment provided incremental diagnostic performance compared with the evaluation of epicardial or microcirculatory districts in isolation (p Value for AUC comparison <0.0001) and it was able to identify the predominant mechanism of myocardial ischemia in 77% of the patients with positive NSI. Our study suggests the value of a combined angiography-derived assessment of epicardial and microvascular function for the definition of the predominant mechanism of myocardial ischemia in patients with suspected coronary artery disease.

Evaluating Linkage Quality of Population-Based Administrative Data for Health Service Research

BACKGROUND

To overcome the limitations of relying on data from a single institution, many researchers have studied data linkage methodologies. Data linkage includes errors owing to legal issues surrounding personal information and technical issues related to data processing. Linkage errors affect selection bias, and external and internal validity. Therefore, quality verification for each connection method with adherence to personal information protection is an important issue. This study evaluated the linkage quality of linked data and analyzed the potential bias resulting from linkage errors.

METHODS

This study analyzed claims data submitted to the Health Insurance Review and Assessment Service (HIRA DATA). The linkage errors of the two deterministic linkage methods were evaluated based on the use of the match key. The first deterministic linkage uses a unique identification number, and the second deterministic linkage uses the name, gender, and date of birth as a set of partial identifiers. The linkage error included in this deterministic linkage method was compared with the absolute standardized difference (ASD) of Cohen's according to the baseline characteristics, and the linkage quality was evaluated through the following indicators: linked rate, false match rate, missed match rate, positive predictive value, sensitivity, specificity, and F1-score.

RESULTS

For the deterministic linkage method that used the name, gender, and date of birth as a set of partial identifiers, the true match rate was 83.5 and the missed match rate was 16.5. Although there was bias in some characteristics of the data, most of the ASD values were less than 0.1, with no case greater than 0.5. Therefore, it is difficult to determine whether linked data constructed with deterministic linkages have substantial differences.

CONCLUSION

This study confirms the possibility of building health and medical data at the national level as the first data linkage quality verification study using big data from the HIRA. Analyzing the quality of linkages is crucial for comprehending linkage errors and generating reliable analytical outcomes. Linkers should increase the reliability of linked data by providing linkage error-related information to researchers. The results of this study will serve as reference data to increase the reliability of multicenter data linkage studies.

Radiomics-based discrimination of coronary chronic total occlusion and subtotal occlusion on coronary computed tomography angiography

OBJECTIVES

Differentiating chronic total occlusion (CTO) from subtotal occlusion (SO) is often difficult to make from coronary computed tomography angiography (CCTA). We developed a CCTA-based radiomics model to differentiate CTO and SO.

METHODS

A total of 66 patients with SO underwent CCTA before invasive angiography and were matched to 66 patients with CTO. Comprehensive imaging analysis was conducted for all lesioned vessels, involving the automatic identification of the lumen within the occluded segment and extraction of 1,904 radiomics features. Radiomics models were then constructed to assess the discriminative value of these features in distinguishing CTO from SO. External validation of the model was performed using data from another medical center.

RESULTS

Compared to SO patients, CTO patients had more blunt stumps (internal: 53/66 (80.3%) vs. 39/66 (59.1%); external: 36/50 (72.0%) vs. 20/50 (40.0%), both p < 0.01), longer lesion length (internal: median length 15.4 mm[IQR: 10.4-22.3 mm] vs. 8.7 mm[IQR: 4.9-12.6 mm]; external:11.8 mm[IQR: 6.1-23.4 mm] vs. 6.2 mm[IQR: 3.5-9.1 mm]; both p < 0.001). Sixteen unique radiomics features were identified after the least absolute shrinkage and selection operator regression. When added to the combined model including imaging features, radiomics features provided increased value for distinguishing CTO from SO (AUC, internal: 0.772 vs. 0.846; p = 0.023; external: 0.718 vs. 0.781, p = 0.146).

CONCLUSIONS

The occluded segment vessels of CTO and SO have different radiomics signatures. The combined application of radiomics features and imaging features based on CCTA extraction can enhance diagnostic confidence.

Dynamic radiomics based on contrast-enhanced MRI for predicting microvascular invasion in hepatocellular carcinoma

OBJECTIVE

To exploit the improved prediction performance based on dynamic contrast-enhanced (DCE) MRI by using dynamic radiomics for microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

METHODS

We retrospectively included 175 and 75 HCC patients who underwent preoperative DCE-MRI from September 2019 to August 2022 in institution 1 (development cohort) and institution 2 (validation cohort), respectively. Static radiomics features were extracted from the mask, arterial, portal venous, and equilibrium phase images and used to construct dynamic features. The static, dynamic, and dynamic-static radiomics (SR, DR, and DSR) signatures were separately constructed based on the feature selection method of LASSO and classification algorithm of logistic regression. The receiver operating characteristic (ROC) curves and the area under the curve (AUC) were plotted to evaluate and compare the predictive performance of each signature.

RESULTS

In the three radiomics signatures, the DSR signature performed the best. The AUCs of the SR, DR, and DSR signatures in the training set were 0.750, 0.751 and 0.805, respectively, while in the external validation set, the corresponding AUCs were 0.706, 0756 and 0.777. The DSR signature showed significant improvement over the SR signature in predicting MVI status (training cohort: P = 0.019; validation cohort: P = 0.044). After external validation, the AUC value of the SR signature decreased from 0.750 to 0.706, while the AUC value of the DR signature did not show a decline (AUCs: 0.756 vs. 0.751).

CONCLUSIONS

The dynamic radiomics had an improved effect on the MVI prediction in HCC, compared with the static DCE MRI-based radiomics models.

A Clinical and Imaging Fused Deep Learning Model Matches Expert Clinician Prediction of 90-Day Stroke Outcomes

BACKGROUND AND PURPOSE

Predicting long-term clinical outcome in acute ischemic stroke is beneficial for prognosis, clinical trial design, resource management, and patient expectations. This study used a deep learning-based predictive model (DLPD) to predict 90-day mRS outcomes and compared its predictions with those made by physicians.

MATERIALS AND METHODS

A previously developed DLPD that incorporated DWI and clinical data from the acute period was used to predict 90-day mRS outcomes in 80 consecutive patients with acute ischemic stroke from a single-center registry. We assessed the predictions of the model alongside those of 5 physicians (2 stroke neurologists and 3 neuroradiologists provided with the same imaging and clinical information). The primary analysis was the agreement between the ordinal mRS predictions of the model or physician and the ground truth using the Gwet Agreement Coefficient. We also evaluated the ability to identify unfavorable outcomes (mRS >2) using the area under the curve, sensitivity, and specificity. Noninferiority analyses were undertaken using limits of 0.1 for the Gwet Agreement Coefficient and 0.05 for the area under the curve analysis. The accuracy of prediction was also assessed using the mean absolute error for prediction, percentage of predictions ±1 categories away from the ground truth (±1 accuracy [ACC]), and percentage of exact predictions (ACC).

RESULTS

To predict the specific mRS score, the DLPD yielded a Gwet Agreement Coefficient score of 0.79 (95% CI, 0.71-0.86), surpassing the physicians' score of 0.76 (95% CI, 0.67-0.84), and was noninferior to the readers (P < .001). For identifying unfavorable outcome, the model achieved an area under the curve of 0.81 (95% CI, 0.72-0.89), again noninferior to the readers' area under the curve of 0.79 (95% CI, 0.69-0.87) (P < .005). The mean absolute error, ±1ACC, and ACC were 0.89, 81%, and 36% for the DLPD.

CONCLUSIONS

A deep learning method using acute clinical and imaging data for long-term functional outcome prediction in patients with acute ischemic stroke, the DLPD, was noninferior to that of clinical readers.

Critical Assessment of the Management of Unstable Angina in a Specialized Cardiology Emergency Room

BACKGROUND

The management of unstable angina (UA) presents a challenge due to its subjective diagnosis and limited representation in randomized clinical trials that inform current practices.

OBJECTIVES

This study aims to identify key factors associated with the indication for invasive versus non-invasive stratification in this population and to evaluate factors associated with stratification test results.

METHODS

This retrospective cohort study included patients hospitalized with UA over a consecutive 20-month period. To assess factors associated with stratification strategies, patients were divided into invasive stratification (coronary angiography) and non-invasive stratification (other methods) groups. For the analysis of factors related to changes in stratification tests, patients were categorized into groups with or without obstructive coronary artery disease (CAD) or ischemia, as per the results of the requested tests. Comparisons between groups and multiple logistic regression analyses were performed, with statistical significance set at a 5% level.

RESULTS

A total of 729 patients were included, with a median age of 63 years and a predominance of males (64.6%). Factors associated with invasive stratification included smoking (p = 0.001); type of chest pain (p < 0.001); "crescendo" pain (p = 0.006); TIMI score (p = 0.006); HEART score (p = 0.011). In multivariate analysis, current smokers (OR 2.23, 95% CI 1.13-4.8), former smokers (OR 2.19, 95% CI 1.39-3.53), and type A chest pain (OR 3.39, 95% CI 1.93-6.66) were independently associated. Factors associated with obstructive CAD or ischemia included length of hospital stay (p < 0.001); male gender (p = 0.032); effort-induced pain (p = 0.037); Diamond-Forrester score (p = 0.026); TIMI score (p = 0.001). In multivariate analysis, only chest pain (type B chest pain: OR 0.6, 95% CI 0.38-0.93, p = 0.026) and previous CAD (OR 1.42, 95% CI 1.01-2.0, p = 0.048) were independently associated.

CONCLUSION

The type of chest pain plays a crucial role not only in the diagnosis of UA but also in determining the appropriate treatment. Our results highlight the importance of incorporating pain characteristics into prognostic scores endorsed by guidelines to optimize UA management.

Native T1-mapping as a predictor of progressive renal function decline in chronic kidney disease patients

BACKGROUND

To investigate the potential of Native T1-mapping in predicting the prognosis of patients with chronic kidney disease (CKD).

METHODS

We enrolled 119 CKD patients as the study subjects and included 20 healthy volunteers as the control group, with follow-up extending until October 2022. Out of these patients, 63 underwent kidney biopsy measurements, and these patients were categorized into high (25-50%), low (< 25%), and no renal interstitial fibrosis (IF) (0%) groups. The study's endpoint event was the initiation of renal replacement therapy, kidney transplantation, or an increase of over 30% in serum creatinine levels. Cox regression analysis determined factors influencing unfavorable kidney outcomes. We employed Kaplan-Meier analysis to contrast kidney survival rates between the high and low T1 groups. Additionally, receiver-operating characteristic (ROC) curve analysis assessed the predictive accuracy of Native T1-mapping for kidney endpoint events.

RESULTS

T1 values across varying fibrosis degree groups showed statistical significance (F = 4.772, P < 0.05). Multivariate Cox regression pinpointed 24-h urine protein, cystatin C(CysC), hemoglobin(Hb), and T1 as factors tied to the emergence of kidney endpoint events. Kaplan-Meier survival analysis revealed a markedly higher likelihood of kidney endpoint events in the high T1 group compared to the low T1 value group (P < 0.001). The ROC curves for variables (CysC, T1, Hb) tied to kidney endpoint events demonstrated area under the curves(AUCs) of 0.83 (95%CI: 0.75-0.91) for CysC, 0.77 (95%CI: 0.68-0.86) for T1, and 0.73 (95%CI: 0.63-0.83) for Hb. Combining these variables elevated the AUC to 0.88 (95%CI: 0.81-0.94).

CONCLUSION

Native T1-mapping holds promise in facilitating more precise and earlier detection of CKD patients most at risk for end-stage renal disease.

The diagnostic yield of inferior petrosal sinus sampling in Cushing syndrome in the era of ovine CRH shortage

PURPOSE

The ovine corticotropin-releasing hormone (oCRH) stimulation test has been routinely used in the diagnostic work-up of ACTH-dependent Cushing syndrome (CS). With oCRH currently being out-of-stock in Europe, we aimed at evaluating the diagnostic performance of inferior petrosal sinus sampling (IPSS) without oCRH stimulation.

METHODS

We compared the values of 40 patients with ACTH-dependent CS and negative MRI findings in whom ACTH was measured before and after oCRH stimulation.

RESULTS

The ratio of central-to-peripheral ACTH measurement (IPS:P) before the combined 3, 5, and 10 min of oCRH stimulation yielded diminished sensitivity (85% vs. 97%), alongside markedly decreased specificity (57% vs. 71%), as well as reduced positive and negative predictive values (90% vs. 94% and 44% vs. 83%), respectively.

CONCLUSIONS

With the current drug shortages in Europe, ACTH measurements without oCRH stimulation in IPSS cannot be recommended. Thus, we call for desmopressin or the commercially available human CRH as a potential alternative in the confirmation of ACTH excess by IPSS in equivocal MRI findings.

Next-generation microbiological testing in intraabdominal infections with PCR technology

PURPOSE

Intraabdominal infections (IAI) are increasing worldwide and are a major contributor to morbidity and mortality. Among IAI, the number of multi-drug resistant organisms (MDRO) is increasing globally. We tested the Unyvero A50® for intraabdominal infections, compared the detected microorganisms and antibiotic resistance, and compared the results with those of routine microbiology.

METHODS

We prospectively compared samples obtained from surgical patients using PCR-based Unyvero IAI cartridges against routine microbiology for the detection of microorganisms. Additionally, we identified clinical parameters that correlated with the microbiological findings. Data were analyzed using the t-test and Mann-Whitney U test.

RESULTS

Sixty-two samples were analyzed. The PCR system identified more microorganisms, mostly Bacteroides species, Escherichia coli, and Enterococcus spp. For bacterial resistance, the PCR system results were fully concordant with those of routine microbiology, resulting in a sensitivity, specificity, and positive and negative predictive value (PPV, NPV) of 100%. The sensitivity, specificity, PPV, and NPV for the detection of microorganisms were 74%, 58%, 60%, and 72%, respectively. CRP levels were significantly higher in patients with detectable microorganisms. We identified more microorganisms and bacterial resistance in hospital-acquired intra-abdominal infections by using the PCR system.

DISCUSSION

IAI warrants early identification of the microorganisms involved and their resistance to allow for adequate antibiotic therapy. PCR systems enable physicians to rapidly adjust their antibiotic treatment. Conventional microbiological culture and testing remain essential for determining the minimal growth inhibition concentrations for antibiotic therapy.

Evaluation of the Diagnostic Performance of American College of Rheumatology, EULAR, and National Institute for Health and Clinical Excellence Criteria Against Clinically Relevant Knee Osteoarthritis: Data From the CHECK Cohort

OBJECTIVE

Our objective was to evaluate the diagnostic performance of the EULAR, American College of Rheumatology (ACR), and National Institute for Health and Care Excellence (NICE) criteria by using clinical experts' diagnosis of clinically relevant knee osteoarthritis (OA) as the outcome of interest.

METHODS

In a previous study, we recruited clinical experts to evaluate longitudinal (5-, 8-, and 10-year follow-up) clinical and radiographic data of symptomatic knees from the Cohort Hip and Cohort Knee (CHECK) study for the presence or absence of clinically relevant OA. In the current study, ACR, EULAR, and NICE criteria were applied to the same 5-, 8-, and 10-year follow-up data; then a knee was diagnosed with OA if fulfilling the criteria at one of the three time points (F1), two of the time points (F2), or at all three time points (F3). Using clinically relevant OA as the reference standard, the sensitivity, specificity, and positive and negative predictive values for the three criteria were assessed.

RESULTS

A total of 539 participants for a total of 833 examined knees were included. Thirty-six percent of knees were diagnosed with clinically relevant OA by experts. Sixty-seven percent to 74% of the knees received the same diagnosis (OA or non-OA) by the three criteria sets for the different definitions (F1 to F3). EULAR consistently (F1 through F3) had the highest specificity, and NICE consistently had the highest sensitivity.

CONCLUSION

The diagnoses only moderately overlapped among the three criteria sets. The EULAR criteria seemed to be more suitable for study enrollment (when aimed at recruiting clinically relevant OA knees), given the highest specificities. The NICE criteria, given the highest sensitivities, could be more useful for an initial diagnosis in clinical practice.

Echocardiography-Based Deep Learning Model to Differentiate Constrictive Pericarditis and Restrictive Cardiomyopathy

BACKGROUND

Constrictive pericarditis (CP) is an uncommon but reversible cause of diastolic heart failure if appropriately identified and treated. However, its diagnosis remains a challenge for clinicians. Artificial intelligence may enhance the identification of CP.

OBJECTIVES

The authors proposed a deep learning approach based on transthoracic echocardiography to differentiate CP from restrictive cardiomyopathy.

METHODS

Patients with a confirmed diagnosis of CP and cardiac amyloidosis (CA) (as the representative disease of restrictive cardiomyopathy) at Mayo Clinic Rochester from January 2003 to December 2021 were identified to extract baseline demographics. The apical 4-chamber view from transthoracic echocardiography studies was used as input data. The patients were split into a 60:20:20 ratio for training, validation, and held-out test sets of the ResNet50 deep learning model. The model performance (differentiating CP and CA) was evaluated in the test set with the area under the curve. GradCAM was used for model interpretation.

RESULTS

A total of 381 patients were identified, including 184 (48.3%) CP, and 197 (51.7%) CA cases. The mean age was 68.7 ± 11.4 years, and 72.8% were male. ResNet50 had a performance with an area under the curve of 0.97 to differentiate the 2-class classification task (CP vs CA). The GradCAM heatmap showed activation around the ventricular septal area.

CONCLUSIONS

With a standard apical 4-chamber view, our artificial intelligence model provides a platform to facilitate the detection of CP, allowing for improved workflow efficiency and prompt referral for more advanced evaluation and intervention of CP.

Myocardial Strain Measurements Derived From MR Feature-Tracking: Influence of Sex, Age, Field Strength, and Vendor

BACKGROUND

Cardiac magnetic resonance feature tracking (CMR-FT) is a novel technique for assessing myocardial deformation and dysfunction. However, a comprehensive assessment of normal values of strain parameters in all 4 cardiac chambers using different vendors is lacking.

OBJECTIVES

This study aimed to characterize the normal values for myocardial strain in all 4 cardiac chambers and identify factors that contribute to variations in FT strain through a systematic review and meta-analysis of the CMR-FT published reports.

METHODS

The investigators searched PubMed, Embase, and Scopus for myocardial strains of all 4 chambers measured by CMR-FT in healthy adults. The pooled means of all strain parameters were generated using a random-effects model. Subgroup analyses and meta-regressions were performed to identify the sources of variations.

RESULTS

This meta-analysis included 44 studies with a total of 3,359 healthy subjects. The pooled means of left ventricular global longitudinal strain (LV-GLS), LV global radial strain, and LV global circumferential strain (GCS) were -18.4% (95% CI: -19.2% to -17.6%), 43.7% (95% CI: 40.0%-47.4%), and -21.4% (95% CI: -22.3% to -20.6%), respectively. The pooled means of left atrial (LA)-GLS (corresponding to total strain, passive strain, and active strain) were 34.9% (95% CI: 29.6%-40.2%), 21.3% (95% CI: 16.6%-26.1%) and 14.3% (95% CI: 11.8%-16.8%), respectively. The pooled means of right ventricular (RV)-GLS and right atrial global longitudinal total strain were -24.0% (95% CI: -25.8% to -22.1%) and 36.3% (95% CI: 15.5%-57.0%), respectively. Meta-regression identified field strength (P < 0.001; I2 = 98.6%) and FT vendor (P < 0.001; I2 = 98.5%) as significant confounders contributing to heterogeneity of LV-GLS. The variations of LA-GLSactive were associated with regional distribution (P < 0.001; I2 = 97.3%) and FT vendor (P < 0.001; I2 = 97.4%). Differences in FT vendor were attributed to variations of LV-GCS and RV-GLS (P = 0.02; I2 = 98.8% and P = 0.01; I2 = 93.8%).

CONCLUSIONS

This study demonstrated the normal values of CMR-FT strain parameters in all 4 cardiac chambers in healthy subjects. Differences in FT vendor contributed to the heterogeneity of LV-GLS, LV-GCS, LA-GLSactive, and RV-GLS, whereas sex, age, and MR vendor had no effect on the normal values of CMR-FT strain measurements.

The effect of the combination of prostate-specific antigen derivatives with multiparametric prostate magnetic resonance imaging scores on the negative predictive value of it in grey zone patients

OBJECTIVE

To calculate the negative predictive value (NPV) of negative multiparametric prostate magnetic resonance imaging (mpMRI), accepted as no lesions on images, when combined with prostate-specific antigen density (PSAD) and free/total prostate-specific antigen ratio (f/t PSA) in grey zone patients.

METHODS

191 patients with PSA levels between 4-10 mg/mL and negative mpMRI were analyzed. The NPV of negative mpMRI was calculated according to a PSAD level of <0.15 ng/mL/mL, f/t PSA ratio of >0.15, and a combination of both. Patients were divided into three risk groups according to these two parameters, which were PSAD 0.01-0.07 ng/mL/mL and f/t PSA ratio ≥25 in a low-risk group, PSAD 0.08-0.15 ng/mL/mL, and f/t PSA ratio 0.15-0.24 in an intermediate-risk group and high-risk group, in which PSAD > 0.15 ng/mL/mL and f/t PSA ratio <15.

RESULTS

NPV of negative mpMRI was 92.6% for clinically significant prostate carcinoma (CSPCa). It increased to 97.5% in a low-risk group and decreased to 33.3% for CSPCa in a high-risk group. NPV of negative mpMRI results were so close when combined with PSAD < 0.15 ng/mL/mL and f/t PSA > 15.

CONCLUSION

f/t PSA ratio might also be used to increase the NPV of mpMRI, like PSAD. We advise not to avoid prostate biopsy when PSAD is >0.15 ng/mL/mL and the f/t PSA ratio is <0.15. However, we need randomized controlled studies with more patients to confirm our study.

Positive Predictive Values of Abnormality Scores From a Commercial Artificial Intelligence-Based Computer-Aided Diagnosis for Mammography

OBJECTIVE

Artificial intelligence-based computer-aided diagnosis (AI-CAD) is increasingly used in mammography. While the continuous scores of AI-CAD have been related to malignancy risk, the understanding of how to interpret and apply these scores remains limited. We investigated the positive predictive values (PPVs) of the abnormality scores generated by a deep learning-based commercial AI-CAD system and analyzed them in relation to clinical and radiological findings.

MATERIALS AND METHODS

From March 2020 to May 2022, 656 breasts from 599 women (mean age 52.6 ± 11.5 years, including 0.6% [4/599] high-risk women) who underwent mammography and received positive AI-CAD results (Lunit Insight MMG, abnormality score ≥ 10) were retrospectively included in this study. Univariable and multivariable analyses were performed to evaluate the associations between the AI-CAD abnormality scores and clinical and radiological factors. The breasts were subdivided according to the abnormality scores into groups 1 (10-49), 2 (50-69), 3 (70-89), and 4 (90-100) using the optimal binning method. The PPVs were calculated for all breasts and subgroups.

RESULTS

Diagnostic indications and positive imaging findings by radiologists were associated with higher abnormality scores in the multivariable regression analysis. The overall PPV of AI-CAD was 32.5% (213/656) for all breasts, including 213 breast cancers, 129 breasts with benign biopsy results, and 314 breasts with benign outcomes in the follow-up or diagnostic studies. In the screening mammography subgroup, the PPVs were 18.6% (58/312) overall and 5.1% (12/235), 29.0% (9/31), 57.9% (11/19), and 96.3% (26/27) for score groups 1, 2, 3, and 4, respectively. The PPVs were significantly higher in women with diagnostic indications (45.1% [155/344]), palpability (51.9% [149/287]), fatty breasts (61.2% [60/98]), and certain imaging findings (masses with or without calcifications and distortion).

CONCLUSION

PPV increased with increasing AI-CAD abnormality scores. The PPVs of AI-CAD satisfied the acceptable PPV range according to Breast Imaging-Reporting and Data System for screening mammography and were higher for diagnostic mammography.

Consistency between the National Patient Register and the Swedish Cancer Register

PURPOSE

The Swedish National Patient Register (NPR) is widely used as a data source in epidemiological studies, but the consistency of all cancer diagnoses compared to the Swedish Cancer Register (SCR) remains unclear. Using NPR supplementary for detecting safety signals is beneficial due to shorter data extraction delays compared to using SCR alone. This study aims to evaluate the consistency of NPR for cancer diagnoses compared to SCR and its potential use in pharmacoepidemiology.

METHODS

Patients with a cancer diagnosis recorded in SCR during 2018-2020 were included. To measure the consistency of NPR diagnoses with SCR as the gold standard, positive predictive value (PPV), and sensitivity were calculated. As an empirical example showing differences in identification of cancer diagnoses in NPR and SCR, two nested case-control studies for the association between antidiabetic medications and pancreatic cancer were repeated using the two registers. Conditional logistic regression was performed and the 95% confidence intervals (CIs) for the odds ratios (ORs) were checked for overlaps.

RESULTS

For breast, male genital organs, and oral cancers consistency was high (PPV: 87.5%-97.4%, sensitivity: 82.2%-91.0%), while for female genital organs, thyroid, and ill-defined, secondary, and unspecified sites cancers it was low (PPV: 8.8%-90.0%, sensitivity: 19.9%-32.3%). All the CIs for the ORs from the nested case-control studies overlapped when pancreatic cancer was identified in NPR or SCR.

CONCLUSION

Consistency of cancer diagnoses in NPR when compared to SCR depends on cancer type with higher consistency for some cancers and lower for others. Differences in diagnostic processes for different cancer types and coding of cancer in the two registers may explain part of the inconsistent results.

Validation of alopecia coding in US claims data among women of childbearing age

BACKGROUND

Accurately identifying alopecia in claims data is important to study this rare medication side effect.

OBJECTIVES

To develop and validate a claims-based algorithm to identify alopecia in women of childbearing age.

METHODS

We linked electronic health records from a large healthcare system in Massachusetts (Mass General Brigham) with Medicaid claims data from 2016 through 2018 to identify all women aged 18 to 50 years with an ICD-10 code for alopecia, including alopecia areata, androgenic alopecia, non-scarring alopecia, or cicatricial alopecia, from a visit to the MGB system. Using eight predefined algorithms to identify alopecia in Medicaid claims data, we randomly selected 300 women for whom we reviewed their charts to validate the alopecia diagnosis. Positive predictive values (PPVs) were computed for the primary algorithm and seven algorithm variations, stratified by race.

RESULTS

Out of 300 patients with at least 1 ICD-10 code for alopecia in the Medicaid claims, 286 had chart-confirmed alopecia (PPV = 95.3%). The algorithm requiring two diagnosis codes plus one prescription claim for alopecia treatment identified 55 patients (PPV = 100%). The algorithm requiring 1 diagnosis code for alopecia plus 1 procedure claim for intralesional triamcinolone injection identified 35 patients (PPV = 100%). Across all 8 algorithms tested, the PPV varied between 95.3% and 100%. The PPV for alopecia ranged from 94% to 100% in White and 96%-100% in 48 non-White women. The exact date of alopecia onset was difficult to determine in charts.

CONCLUSION

At least one recorded ICD-10 code for alopecia in claims data identified alopecia in women of childbearing age with high accuracy.

Right Ventricular Function on Cardiovascular Magnetic Resonance Imaging and Long-Term Outcomes in Stable Heart Transplant Recipients

BACKGROUND

In heart transplant recipients, right ventricular (RV) dysfunction may occur for a variety of reasons. Whether RV dysfunction in the stable phase after heart transplantation is associated with long-term adverse outcomes is unknown. We aimed to determine the long-term prognostic significance of RV dysfunction identified on cardiovascular magnetic resonance imaging (CMR) at least 1 year after heart transplantation.

METHODS

In consecutive heart transplant recipients who underwent CMR for surveillance, we assessed 2 CMR measures of RV function: RV ejection fraction and RV global longitudinal strain (RVGLS). We investigated associations between RV dysfunction and a composite end point of death or major adverse cardiac events, including retransplantation, nonfatal myocardial infarction, coronary revascularization, and heart failure hospitalization.

RESULTS

A total of 257 heart transplant recipients (median age, 59 years; 75% men) who had CMR at a median of 4.3 years after heart transplantation were included. Over a median follow-up of 4.4 years after the CMR, 108 recipients experienced death or major adverse cardiac events. In a multivariable Cox regression analysis adjusted for age, time since transplantation, indication for transplantation, cardiac allograft vasculopathy, history of rejection, and CMR covariates, RV ejection fraction was not associated with the composite end point, but RVGLS was independently associated with the composite end point with a hazard ratio of 1.08 per 1% worsening in RVGLS ([95% CI, 1.00-1.17]; P=0.046). RVGLS provided incremental prognostic value over other variables in multivariable analyses. The association was replicated in subgroups of recipients with normal RV ejection fraction and recipients with late gadolinium enhancement imaging. A similar association was seen with a composite end point of cardiovascular death or major adverse cardiac events.

CONCLUSIONS

CMR feature tracking-derived RVGLS assessed at least 1 year after heart transplantation was independently associated with the long-term risk of death or major adverse cardiac events. Future studies should investigate its role in guiding clinical decision-making in heart transplant recipients.

Diagnosis and subtyping of idiopathic inflammatory myopathies: caution required in the use of myositis autoantibodies

Detection of myositis autoantibodies (MAs) has utility in both the diagnosis and subtyping of idiopathic inflammatory myopathies (IIMs). Multiplex assays such as the Euroimmun line immunoassay (LIA) have significant limitations in rare diseases like IIM. A retrospective cohort study was performed on positive MA detected on LIA in 171 patients using the manufacturer's recommended cut-off. Only 16.7% were deemed true positive after clinical correlation. Autoantibody-specific cut-offs were created and applied to the original cohort, along with generically applied higher cut-offs. Positive predictive value (PPV) improved, but there was variable increase in false negatives. False positive MA results are common using LIA, but locally derived cut-offs can improve performance. Clinicians must be aware of the limitations of LIA, which is the commonest method for MA detection in Australasia.