Recent advances in the management and implementation of care for familial hypercholesterolaemia

Familial hypercholesterolaemia (FH) is a common autosomal semi-dominant and highly penetrant disorder of the low-density lipoprotein (LDL) receptor pathway, characterised by lifelong elevated levels of low-density lipoprotein cholesterol (LDL-C) and increased risk of atherosclerotic cardiovascular disease (ASCVD). However, many patients with FH are not diagnosed and do not attain recommended LDL-C goals despite maximally tolerated doses of potent statin and ezetimibe. Over the past decade, several cholesterol-lowering therapies such as those targeting proprotein convertase subtilisin/kexin type 9 (PCSK9) or angiopoietin-like 3 (ANGPTL3) with monoclonal antibody or ribonucleic acid (RNA) approaches have been developed that promise to close the treatment gap. The availability of new therapies with complementary modes of action of lipid metabolism has enabled many patients with FH to attain guideline-recommended LDL-C goals. Emerging therapies for FH include liver-directed gene transfer of the LDLR, vaccines targeting key proteins involved in cholesterol metabolism, and CRISPR-based gene editing of PCSK9 and ANGPTL3, but further clinical trials are required. In this review, current and emerging treatment strategies for lowering LDL-C, and ASCVD risk-stratification, as well as implementation strategies for the care of patients with FH are reviewed.

Prediction of in-hospital deterioration in normotensive pulmonary embolism remains elusive: external validation of the calgary acute pulmonary embolism score

Acute pulmonary embolism (PE) is a frequently diagnosed condition. Prediction of in-hospital deterioration is challenging with current risk models. The Calgary Acute Pulmonary Embolism (CAPE) score was recently derived to predict in-hospital adverse PE outcomes but has not yet been externally validated. Retrospective cohort study of normotensive acute pulmonary embolism cases diagnosed in our emergency department between 2017 and 2019. An external validation of the CAPE score was performed in this population for prediction of in-hospital adverse outcomes and a secondary outcome of 30-day all-cause mortality. Performance of the simplified Pulmonary Embolism Severity Index (sPESI) and Bova score was also evaluated. 712 patients met inclusion and exclusion criteria, with 536 patients having a sPESI score of 1 or more. Among this population, the CAPE score had a weak discriminative power to predict in-hospital adverse outcomes, with a calculated c-statistic of 0.57. In this study population, an external validation study found weak discriminative power of the CAPE score to predict in-hospital adverse outcomes among normotensive PE patients. Further efforts are needed to define risk assessment models that can identify normotensive PE patients at risk for in hospital deterioration. Identification of such patients will better guide intensive care utilization and invasive procedural management of PE.

Biomarkers of Progression and Risk Stratification in Asymptomatic Waldenström Macroglobulinemia

Waldenström macroglobulinemia is an indolent IgM-secreting B-cell lymphoplasmacytic lymphoma that is preceded by an asymptomatic stage. Clinical and molecular features have been used in risk models to predict progression rates in different asymptomatic subgroups. Risk models used both disease-specific and nonspecific biomarkers for asymptomatic patients. Recently, models that incorporate continuous variables rather than distinct cutoffs have emerged to more accurately predict the risk of progression. Integrating genetic alterations to the clinical models is a promising approach that could improve risk stratification and management of asymptomatic patients.

Global trans-lesional computed tomography-derived fractional flow reserve gradient is associated with clinical outcomes in diabetic patients with non-obstructive coronary artery disease

BACKGROUND

Coronary computed tomography angiography (CCTA)-derived fractional flow reserve (CT-FFR) enables physiological assessment and risk stratification, which is of significance in diabetic patients with nonobstructive coronary artery disease (CAD). We aim to evaluate prognostic value of the global trans-lesional CT-FFR gradient (GΔCT-FFR), a novel metric, in patients with diabetes without flow-limiting stenosis.

METHODS

Patients with diabetes suspected of having CAD were prospectively enrolled. GΔCT-FFR was calculated as the sum of trans-lesional CT-FFR gradient in all epicardial vessels greater than 2 mm. Patients were stratified into low-gradient without flow-limiting group (CT-FFR > 0.75 and GΔCT-FFR < 0.20), high-gradient without flow-limiting group (CT-FFR > 0.75 and GΔCT-FFR ≥ 0.20), and flow-limiting group (CT-FFR ≤ 0.75). Discriminant ability for major adverse cardiovascular events (MACE) prediction was compared among 4 models [model 1: Framingham risk score; model 2: model 1 + Leiden score; model 3: model 2 + high-risk plaques (HRP); model 4: model 3 + GΔCT-FFR] to determine incremental prognostic value of GΔCT-FFR.

RESULTS

Of 1215 patients (60.1 ± 10.3 years, 53.7% male), 11.3% suffered from MACE after a median follow-up of 57.3 months. GΔCT-FFR (HR: 2.88, 95% CI 1.76-4.70, P < 0.001) remained independent risk factors of MACE in multivariable analysis. Compared with the low-gradient without flow-limiting group, the high-gradient without flow-limiting group (HR: 2.86, 95% CI 1.75-4.68, P < 0.001) was associated with higher risk of MACE. Among the 4 risk models, model 4, which included GΔCT-FFR, showed the highest C-statistics (C-statistics: 0.75, P = 0.002) as well as a significant net reclassification improvement (NRI) beyond model 3 (NRI: 0.605, P < 0.001).

CONCLUSIONS

In diabetic patients with non-obstructive CAD, GΔCT-FFR was associated with clinical outcomes at 5 year follow-up, which illuminates a novel and feasible approach to improved risk stratification for a global hemodynamic assessment of coronary artery in diabetic patients.

A novel nomogram and risk stratification system predicting the cancer-specific survival of patients with gastric neuroendocrine carcinoma: a study based on SEER database and external validation

BACKGROUND

Gastric neuroendocrine carcinoma (GNEC) is a rare histology of gastric cancer. The retrospective study was designed to construct and validate a nomogram for predicting the cancer-specific survival (CSS) of postoperative GNEC patients.

METHODS

Data for 28 patients from the Hangzhou TCM Hospital were identified as the external validation cohort. A total of 1493 patients were included in the SEER database and randomly assigned to the training group (1045 patients) and internal validation group (448 patients). The nomogram was constructed using the findings of univariate and multivariate Cox regression studies. The model was evaluated by consistency index (C-index), calibration plots, and clinical net benefit. Finally, the effect between the nomogram and AJCC staging system was compared by net reclassification index (NRI) and integrated discrimination improvement (IDI).

RESULTS

Age, gender, grade, T stage, N stage, metastasis, primary site, tumor size, RNE, and chemotherapy were incorporated in the nomogram. The C-indexes were 0.792 and 0.782 in the training and internal verification sets. The 1-, 3-, and 5-year CSS predicted by the nomogram and actual measurements had good agreement in calibration plots. The 1-, 3-, and 5-year NRI were 0.21, 0.29, and 0.37, respectively. The 1-, 3-, and 5-year IDI values were 0.10, 0.12, and 0.13 (P < 0.001), respectively. In 1-, 3-, and 5-year CSS prediction using DCA curves, the nomogram outperformed the AJCC staging system. The nomogram performed well in both the internal and external validation cohorts.

CONCLUSION

We developed and validated a nomogram to predict 1-, 3-, and 5-year CSS for GNEC patients after surgical resection. This well-performing model could help doctors enhance the treatment plan.

Development and validation of a clinic machine-learning nomogram for the prediction of risk stratifications of prostate cancer based on functional subsets of peripheral lymphocyte

BACKGROUND

Non-invasive risk stratification contributes to the precise treatment of prostate cancer (PCa). In previous studies, lymphocyte subsets were used to differentiate between low-/intermediate-risk and high-risk PCa, with limited clinical value and poor interpretability. Based on functional subsets of peripheral lymphocyte with the largest sample size to date, this study aims to construct an easy-to-use and robust nomogram to guide the tripartite risk stratifications for PCa.

METHODS

We retrospectively collected data from 2039 PCa and benign prostate disease (BPD) patients with 42 clinical characteristics on functional subsets of peripheral lymphocyte. After quality control and feature selection, clinical data with the optimal feature subset were utilized for the 10-fold cross-validation of five Machine Learning (ML) models for the task of predicting low-, intermediate- and high-risk stratification of PCa. Then, a novel clinic-ML nomogram was constructed using probabilistic predictions of the trained ML models via the combination of a multivariable Ordinal Logistic Regression analysis and the proposed feature mapping algorithm.

RESULTS

197 PCa patients, including 56 BPD, were enrolled in the study. An optimal subset with nine clinical features was selected. Compared with the best ML model and the clinic nomogram, the clinic-ML nomogram achieved the superior performance with a sensitivity of 0.713 (95% CI 0.573-0.853), specificity of 0.869 (95% CI 0.764-0.974), F1 of 0.699 (95% CI 0.557-0.841), and AUC of 0.864 (95% CI 0.794-0.935). The calibration curve and Decision Curve Analysis (DCA) indicated the predictive capacity and net benefits of the clinic-ML nomogram were improved.

CONCLUSION

Combining the interpretability and simplicity of a nomogram with the efficacy and robustness of ML models, the proposed clinic-ML nomogram can serve as an insight tool for preoperative assessment of PCa risk stratifications, and could provide essential information for the individual diagnosis and treatment in PCa patients.

A Novel Risk Calculator Incorporating Clinical Parameters, Multiparametric Magnetic Resonance Imaging, and Prostate-Specific Membrane Antigen Positron Emission Tomography for Prostate Cancer Risk Stratification Before Transperineal Prostate Biopsy

Background

Prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) can detect multiparametric magnetic resonance imaging (mpMRI)-invisible prostate tumours and improve the sensitivity of detection of prostate cancer (PCa) in comparison to mpMRI alone. Numerous risk calculators have been validated as tools for stratification of men at risk of being diagnosed with clinically significant (cs)PCa.

Objective

To develop a novel risk calculator using clinical parameters and imaging parameters from mpMRI and PSMA PET/CT in a cohort of patients undergoing mpMRI and PSMA PET/CT before biopsy.

Design setting and participants

A total of 291 men from the PRIMARY prospective trial underwent mpMRI and PSMA PET/CT before transperineal prostate biopsy with sampling of systematic and targeted cores.

Outcome measurements and statistical analysis

Novel risk calculators were developed using multivariable logistic regression analysis to predict detection of overall PCa (International Society of Urological Pathology grade group [GG] ≥1) and csPCa (GG ≥2). The risk calculators were then compared with the European Randomised Study of Screening for Prostate Cancer risk calculator incorporating mpMRI (ERSPC-MRI). Resampling methods were used to evaluate the discrimination and calibration of the risk calculators and to perform decision curve analysis.

Results and limitations

Age, prostate-specific antigen, prostate volume, and mpMRI Prostate Imaging-Reporting and Data System scores were included in the MRI risk calculator, resulting in area under the receiver operating characteristic curve (AUC) values of 0.791 for overall PCa (GG ≥1) and 0.812 for csPCa (GG ≥2). Addition of the maximum standardised uptake value (SUVmax) on PSMA PET/CT for the prostate lesion, and of SUVmax for the mpMRI lesions for the MRI-PSMA risk calculator resulted in AUCs of 0.831 for overall PCa and 0.876 for csPCa (≥ISUP2).The ERSPC-MRI risk calculator had AUCs of 0.758 (p = 0.02) for overall PCa and 0.805 (p = 0.001) for csPCa. Both the MRI and MRI-PSMA risk calculators were superior to the ERSPC-MRI for both overall PCa and csPCa.

Conclusions

These novel risk calculators incorporate clinical and radiological parameters for stratification of men at risk of csPCa. The risk calculator including PSMA PET/CT data is superior to a calculator incorporating mpMRI data alone.

Patient summary

We evaluated a new risk calculator that uses clinical information and results from two types of scan to predict the risk of clinically significant prostate cancer on prostate biopsy. This risk model can guide patients and clinicians in shared decision-making and may help in avoiding unnecessary prostate biopsies.

Artificial intelligence in coronary artery calcium measurement: Barriers and solutions for implementation into daily practice

Coronary artery calcification (CAC) measurement is a valuable predictor of cardiovascular risk. However, its measurement can be time-consuming and complex, thus driving the desire for artificial intelligence (AI)-based approaches. The aim of this review is to explore the current status of CAC volume measurement using AI-based systems for the automated prediction of cardiovascular events. We also make proposals for the implementation of these systems into clinical practice. Research to date on applying AI to CAC scoring has shown the potential for automation and risk stratification, and, overall, efficacy and a high level of agreement with categorisation by trained clinicians have been demonstrated. However, research in this field has not been uniform or directed. One contributing factor may be a lack of integration and communication between computer scientists and cardiologists. Clinicians, institutions, and organisations should work together towards applying this technology to improve processes, preserve healthcare resources, and improve patient outcomes.

A novel congenital diaphragmatic hernia prediction model for Chinese subjects: A multicenter cohort investigation

Purpose of the study

Brindle et al. (2014) and the Congenital Diaphragmatic Hernia Study Group constructed a simplified clinical prediction rule (Brindle score) to stratify infants with congenital diaphragmatic hernia based on disease severity. We aimed to develop a predictive model applicable to Chinese patients with congenital diaphragmatic hernia and externally validate whether the Brindle score is applicable to the Chinese population.

Patients and the methods

Multiple imputations supplemented the missing data. A least absolute shrinkage and selection operator regression was used to screen the factors influencing adverse outcomes. Internal validation was performed by bootstrap resampling. The C-index, area under the receiver operating characteristic curve, and the Hosmer-Lemeshow test evaluated the predictive power.

Results

A nomogram named "CCDH score" (Chinese Congenital Diaphragmatic Hernia score), including pulmonary hypertension, low 5-min Apgar score (<7), chromosomal anomaly, major cardiac anomalies (MCAs), observed-to-expected lung-to-head ratio, and the percentage of liver herniation, was constructed. The CCDH score revealed good calibration and discriminative abilities, with a C-index of 0.941. In the training and external validation cohorts, the area under the receiver operating characteristic curve of the Brindle score were 0.820 and 0.881, respectively. The Brindle score has fair predictive power in the Chinese population, but the newly established CCDH score seems more suitable for Chinese patients with congenital diaphragmatic hernia.

Conclusion

The CCDH score is the first predictive model constructed based on the characteristics of the Chinese population and can accurately predict the survival outcomes of patients with congenital diaphragmatic hernia.

History of peripheral artery disease and cardiovascular risk of real-world patients with acute coronary syndrome: Role of inflammation and comorbidities

BACKGROUND

Patients with acute coronary syndromes (ACS) remain at risk of cardiovascular disease (CVD) recurrences. Peripheral artery disease (PAD) may identify a very high risk (VHR) group who may derive greater benefit from intensified secondary prevention.

METHODS

Among ACS-patients enrolled in the prospective multi-center Special Program University Medicine (SPUM), we assessed the impact of PAD on major cardiovascular events (MACE: composite of myocardial infarction, stroke and all-cause death) and major bleeding. Multivariate analysis tested the relation of each significant variable with MACE, as well as biomarkers of inflammation and novel markers of atherogenesis.

RESULTS

Out of 4787 ACS patients, 6.0% (n = 285) had PAD. PAD-patients were older (p < 0.001), with established CVD and signs of increased persistent inflammation (hs-CRP; 23.6 ± 46.5 vs 10.4 ± 27.2 mg/l, p < 0.001 and sFlt-1; 1399.5 ± 1501.3 vs 1047.2 ± 1378.6 ng/l, p = 0.018). In-hospital-death (3.2% vs 1.4%, p = 0.022) and -MACE (5.6% vs 3.0%, p = 0.017) were higher in PAD-patients. MACE at 1 year (18.6% vs 7.9%,p < 0.001) remained increased even after adjustment for confounders (Adj. HR 1.53, 95% CI: 1.14-2.08, p = 0.005). Major bleeding did not differ between groups (Adj. HR 1.18; 95% CI 0.71-1.97, p = 0.512). Although PAD predicted MACE, PAD-patients were prescribed less frequently for secondary prevention at discharge.

CONCLUSIONS

In this real-world ACS patient cohort, concomitant PAD is a marker of VHR and is associated with increased and persistent inflammation, higher risk for MACE without an increased risk of major bleeding. Therefore, a history of PAD may be useful to identify those ACS patients at VHR who require more aggressive secondary prevention.

The value of serum HE4 and CA125 levels for monitoring the recurrence and risk stratification of endometrial endometrioid carcinoma

To evaluate the role of serum human epididymis secretory protein 4 (HE4) and carbohydrate antigen 125 (CA125) levels for predicting and monitoring the recurrence of endometrial endometrioid carcinoma (EEC) and assessing preoperative risk stratification in EEC patients. A total of 434 EEC patients were selected for this retrospective study between May 2011 and August 2018. Serum HE4 and CA125 levels were analyzed before the initial treatment, at the first postoperative follow-up, and at recurrence or the last follow-up. Patients were risk stratified according to the European Society for Medical Oncology (ESMO), European Society for Radiotherapy & Oncology (ESTRO) and European Society of Gynaecological Oncology (ESGO) guideline. We compared the ability of these biomarkers for prediction and monitoring by performing receiver operating characteristic curve analysis and identified optimal cut-off values by determining the Youden index. Kaplan-Meier analyses were also performed to determine prognostic value. Preoperative serum HE4 was identified as a significant predictor for the recurrence of EEC (p = 0.014). Preoperative serum HE4 and CA125 levels were related to depth of myometrial invasion, lymph node status and FIGO stage. Serum HE4 and CA125 levels were both statistically significant markers for monitoring the recurrence of EEC (P = 0.000 for each biomarker). When combined, the two markers showed higher levels of sensitivity and specificity. The two biomarkers were also significant biomarkers for evaluating the risk stratification of patients undergoing lymphadenectomy (P = 0.000 for each biomarker). For premenopausal stage I patients, preoperative serum HE4 and CA125 levels were significant predictors of the need for ovarian preservation (P = 0.000 and P = 0.002, respectively). For premenopausal patients with stage I intramucosal differentiation, preoperative serum levels of HE4 were significant predictors for fertility preservation (P = 0.024). Preoperative serum HE4 level can be used to predict the recurrence of EEC. Postoperative serum HE4 and CA125 levels can be used to monitor the recurrence of EEC and are more sensitive when combined. Preoperative serum levels of CA125 and HE4 levels are of significant value for risk stratification in EEC patients.

An adjusted Asia-Pacific colorectal screening score system to predict advanced colorectal neoplasia in asymptomatic Chinese patients

PURPOSE

The Asia-Pacific Colorectal Screening (APCS) score and its derivatives have been used to predict advanced colorectal neoplasia (ACN). However, it remains unknown whether they apply to the current Chinese population in general clinical practice. Therefore, we aimed to update the APCS score system by applying data from two independent asymptomatic populations to predict the risk of ACN in China.

METHODS

We developed an adjusted APCS (A-APCS) score by using the data of asymptomatic Chinese patients undergoing colonoscopies from January 2014 to December 2018. Furthermore, we validated this system in another cohort of 812 patients who underwent screening colonoscopy between January and December 2021. The discriminative calibration ability of the A-APCS and APCS scores was comparatively evaluated.

RESULTS

Univariate and multivariate logistic regression were applied to assess the risk factors for ACN, and an adjusted scoring system of 0 to 6.5 points was schemed according to the results. Utilizing the developed score, 20.2%, 41.2%, and 38.6% of patients in the validation cohort were classified as average, moderate, and high risk, respectively. The corresponding ACN incidence rates were 1.2%, 6.0%, and 11.1%, respectively. In addition, the A-APCS score (c-statistics: 0.68 for the derivation and 0.80 for the validation cohort) showed better discriminative power than using predictors of APCS alone.

CONCLUSIONS

The A-APCS score may be simple and useful in clinical applications for predicting ACN risk in China.

Prognostic value of pre-therapeutic nutritional risk factors in elderly patients with locally advanced esophageal squamous cell carcinoma receiving definitive chemoradiotherapy or radiotherapy

BACKGROUND

The nutritional status of cancer patients is a crucial factor in determining their prognosis. The objective of this study was to investigate and compare the prognostic value of pretreatment nutrition-related indicators in elderly esophageal squamous cell carcinoma (ESCC). Risk stratification was performed according to independent risk factors and a new nutritional prognostic index was constructed.

METHODS

We retrospectively reviewed 460 older locally advanced ESCC patients receiving definitive chemoradiotherapy (dCRT) or radiotherapy (dRT). This study included five pre- therapeutic nutrition-related indicators. The optimal cut-off values for these indices were calculated from the Receiver Operating Curve (ROC). Univariate and multivariate COX analyses were employed to determine the association between each indicator and clinical outcomes. The predictive ability of each independently nutrition-related prognostic indicator was assessed using the time-dependent ROC (time-ROC) and C-index.

RESULTS

Multivariate analyses indicated that the geriatric nutrition risk index (GNRI), body mass index (BMI), the controlling nutritional status (CONUT) score, and platelet-albumin ratio (PAR) could independently predict overall survival (OS) and progression-free survival (PFS) in elderly patients with ESCC (all p < 0.05), except for prognostic nutritional index (PNI). Based on four independently nutrition-related prognostic indicators, we developed pre-therapeutic nutritional prognostic score (PTNPS) and new nutritional prognostic index (NNPI). No-risk (PTNPS = 0-1 point), moderate-risk (PTNPS = 2 points), and high-risk (PTNPS = 3-4 points) groups had 5-year OS rates of 42.3%, 22.9%, and 8.8%, respectively (p < 0.001), and 5-year PFS rates of 44.4%, 26.5%, and 11.3%, respectively (p < 0.001). The Kaplan-Meier curves showed that the mortality of elderly ESCC patients in the high-risk group was higher than that in the low-risk group according to the NNPI. Analysis of time-AUC and C-index revealed that the NNPI (C-index: 0.663) had the greatest predictive power on the prognosis in older ESCC patients.

CONCLUSIONS

In elderly ESCC patients, the GNRI, BMI, CONUT score, and PAR can be used as objective assessment measures for the risk of nutrition-related death. Compared to the other four indexes, the NNPI has the greatest prognostic value for prognosis, and elderly patients with a higher nutritional risk have a poor prognosis, which is helpful in guiding early clinical nutrition intervention.

Prognostic models for upper urinary tract urothelial carcinoma patients after radical nephroureterectomy based on a novel systemic immune-inflammation score with machine learning

PURPOSE

This study aimed to evaluate the clinical significance of a novel systemic immune-inflammation score (SIIS) to predict oncological outcomes in upper urinary tract urothelial carcinoma(UTUC) after radical nephroureterectomy(RNU).

METHOD

The clinical data of 483 patients with nonmetastatic UTUC underwent surgery in our center were analyzed. Five inflammation-related biomarkers were screened in the Lasso-Cox model and then aggregated to generate the SIIS based on the regression coefficients. Overall survival (OS) was assessed using Kaplan-Meier analyses. The Cox proportional hazards regression and random survival forest model were adopted to build the prognostic model. Then we established an effective nomogram for UTUC after RNU based on SIIS. The discrimination and calibration of the nomogram were evaluated using the concordance index (C-index), area under the time-dependent receiver operating characteristic curve (time-dependent AUC), and calibration curves. Decision curve analysis (DCA) was used to assess the net benefits of the nomogram at different threshold probabilities.

RESULT

According to the median value SIIS computed by the lasso Cox model, the high-risk group had worse OS (p<0.0001) than low risk-group. Variables with a minimum depth greater than the depth threshold or negative variable importance were excluded, and the remaining six variables were included in the model. The area under the ROC curve (AUROC) of the Cox and random survival forest models were 0.801 and 0.872 for OS at five years, respectively. Multivariate Cox analysis showed that elevated SIIS was significantly associated with poorer OS (p<0.001). In terms of predicting overall survival, a nomogram that considered the SIIS and clinical prognostic factors performed better than the AJCC staging.

CONCLUSION

The pretreatment levels of SIIS were an independent predictor of prognosis in upper urinary tract urothelial carcinoma after RNU. Therefore, incorporating SIIS into currently available clinical parameters helps predict the long-term survival of UTUC.

Use, misuse, and pitfalls of the drug challenge test in the diagnosis of the Brugada syndrome

The diagnosis of Brugada syndrome (BrS) requires the presence of a coved (Type 1) ST segment elevation in the right precordial leads of the electrocardiogram (ECG). The dynamic nature of the ECG is well known, and in patients with suspected BrS but non-diagnostic ECG at baseline, a sodium channel blocker test (SCBT) is routinely used to unmask BrS. There is little doubt, however, that in asymptomatic patients, a drug-induced Brugada pattern is associated with a much better prognosis compared to a spontaneous Type 1 ECG. The SCBT is also increasingly used to delineate the arrhythmogenic substrate during ablation studies. In the absence of a "gold standard" for the diagnosis of BrS, sensitivity and specificity of the SCBT remain elusive. By studying patient groups with different underlying diseases, it has become clear that the specificity of the test may not be optimal. This review aims to discuss the pitfalls of the SCBT and provides some directions in whom and when to perform the test. It is concluded that because of the debated specificity and the overall very low risk for future events in asymptomatic individuals, patients should be properly selected and counseled before SCBT is performed and that SCBT should not be performed in asymptomatic patients with a Type 2 Brugada pattern and no family history of BrS or sudden death.

[Prediabetes as a therapeutic challenge in internal medicine]

The term prediabetes describes a fasting blood glucose level that is elevated but not yet in the diabetic range, a blood glucose level that is elevated after 120 min in a standard 75‑g oral glucose tolerance test, or both. The American Diabetes Association definition also includes glycated hemoglobin A (HbA1c). The incidence of prediabetes is rapidly increasing. Progression from normal glucose tolerance to diabetes is a continuous process. Insulin resistance and insulin secretory dysfunction, the simultaneous presence of which characterizes manifest diabetes, are already present in the prediabetic stage. Prediabetes is associated with an increased risk of diabetes; however, by no means all people with prediabetes go on to develop diabetes. Nevertheless, the identification of an increased risk of diabetes is still relevant insofar as it requires the adoption of diabetes prevention measures. Structured lifestyle intervention has been shown to be the most effective strategy for treating prediabetes. To increase its efficiency, it should, as far as possible, be made exclusively available to those people on whom it is most likely to confer a benefit. This would make it necessary to stratify people with prediabetes according to their risk profile. In a population of people at increased risk of diabetes (Tübingen Diabetes Family Study), a cluster analysis was performed, resulting in six clusters/subgroups. Within these, three high-risk subgroups were identified: Two of these risk groups show predominant insulin secretory dysfunction or predominant insulin resistance and high diabetes and cardiovascular risk. The third group shows a high risk of nephropathy and high mortality, but a comparatively lower diabetes risk. In general, prediabetes cannot yet be treated in a targeted pathophysiologically oriented manner. The new classification of prediabetes-based on pathophysiology-is now opening up new avenues for diabetes prevention. Current and future studies should confirm the assumption that the effectiveness of established, or not yet established, preventive measures depends on the respective subgroup.

Performance of a multisensor implantable defibrillator algorithm for heart failure monitoring related to co-morbidities

AIMS

The HeartLogic algorithm combines multiple implantable defibrillator (ICD) sensor data and has proved to be a sensitive and timely predictor of impending heart failure (HF) decompensation in cardiac resynchronization therapy (CRT-D) patients. We evaluated the performance of this algorithm in non-CRT ICD patients and in the presence of co-morbidities.

METHODS AND RESULTS

The HeartLogic feature was activated in 568 ICD patients (410 with CRT-D) from 26 centres. The median follow-up was 26 months [25th-75th percentile: 16-37]. During follow-up, 97 hospitalizations were reported (53 cardiovascular) and 55 patients died. We recorded 1200 HeartLogic alerts in 370 patients. Overall, the time IN the alert state was 13% of the total observation period. The rate of cardiovascular hospitalizations or death was 0.48/patient-year (95% CI: 0.37-0.60) with the HeartLogic IN the alert state and 0.04/patient-year (95% CI: 0.03-0.05) OUT of the alert state, with an incidence rate ratio of 13.35 (95% CI: 8.83-20.51, P < 0.001). Among patient characteristics, atrial fibrillation (AF) on implantation (HR: 1.62, 95% CI: 1.27-2.07, P < 0.001) and chronic kidney disease (CKD) (HR: 1.53, 95% CI: 1.21-1.93, P < 0.001) independently predicted alerts. HeartLogic alerts were not associated with CRT-D versus ICD implantation (HR: 1.03, 95% CI: 0.82-1.30, P = 0.775). Comparisons of the clinical event rates in the IN alert state with those in the OUT of alert state yielded incidence rate ratios ranging from 9.72 to 14.54 (all P < 0.001) in all groups of patients stratified by: CRT-D/ICD, AF/non-AF, and CKD/non-CKD. After multivariate correction, the occurrence of alerts was associated with cardiovascular hospitalization or death (HR: 1.92, 95% CI: 1.05-3.51, P = 0.036).

CONCLUSIONS

The burden of HeartLogic alerts was similar between CRT-D and ICD patients, while patients with AF and CKD seemed more exposed to alerts. Nonetheless, the ability of the HeartLogic algorithm to identify periods of significantly increased risk of clinical events was confirmed, regardless of the type of device and the presence of AF or CKD.

Low concordance between CTPA and echocardiography in identification of right ventricular strain in PERT patients with acute pulmonary embolism

PURPOSE

Right ventricular strain (RVS) is used to risk stratify patients with acute pulmonary embolism (PE) and influence treatment decisions. Guidelines suggest that either computed tomography pulmonary angiography (CTPA) or transthoracic echocardiography (TTE) can be used to assess RVS. We sought to determine how often CTPA and TTE yield discordant results and to assess the test characteristics of CTPA compared to TTE.

METHODS

We analyzed data from a single-center registry of PE cases severe enough to warrant activation of the hospital's Pulmonary Embolism Response Team (PERT). We defined RVS as a right ventricular to left ventricular ratio (RV/LV) ≥ 1 or radiologist's interpretation of RVS on CTPA or as the presence of either RV dilation, hypokinesis, or septal bowing on TTE.

RESULTS

We included 554 patients in our analysis, of whom 333 (60%) had concordant RVS findings on CTPA and TTE. Using TTE as the reference standard, CTPA had a sensitivity of 95% (95% CI 92-97%) and a specificity of 4% (95% CI 2-8%) for identifying RVS.

CONCLUSIONS

In a selected population of patients with acute PE for which PERT was activated, CTPA is highly sensitive but not specific for the detection of RVS when compared to TTE.

Combined effects of high sensitivity C-reactive protein and triglyceride-glucose index on risk of cardiovascular disease among middle-aged and older Chinese: Evidence from the China Health and Retirement Longitudinal Study

BACKGROUND AND AIMS

High sensitivity C-reactive protein (hsCRP) and triglyceride glucose (TyG) index were proved to be independent risk factors of cardiovascular disease (CVD). However, individual hsCRP or TyG index might not provide sufficient predictive value on CVD risk. The current study aimed to evaluate the cumulative effect of hsCRP and TyG index on CVD risk prospectively.

METHODS AND RESULTS

A total of 9626 participants were enrolled in the analysis. The TyG index was calculated as ln(triglyceride [mg/dL] × fasting glucose [mg/dL]/2). The primary outcome was new-onset CVD events (cardiac events or stroke), and the secondary outcomes were new-onset cardiac events and stroke, separately. Participants were divided into 4 groups through the median of hsCRP and TyG index. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using multivariable Cox proportion hazard models. From 2013 to 2018, 1730 participants experienced CVD (570 stroke and 1306 cardiac events). Linear associations were found between hsCRP, TyG index, hsCRP/TyG ratio and CVD (all p < 0.05). Compared to participants with low hsCRP/low TyG index, multivariable adjusted HRs (95% CIs) for those with high hsCRP/high TyG index were 1.17 (1.03-1.37) for CVD. No interaction of hsCRP and TyG index was found on CVD (p_-interaction ≥0.05). Furthermore, adding hsCRP and TyG index simultaneously to conventional risk model improved risk reclassification for CVD, stroke and cardiac events (all p < 0.05).

CONCLUSION

The present study suggested combination of hsCRP and TyG index might better improved the ability for risk stratification of CVD among middle-aged and older Chinese.

Middle eastern college of obstetricians and gynecologists (MCOG) practice guidelines: Role of prediction models in management of trial of labor after cesarean section. Practice guideline no. 05-O-22✰,✰✰,★,★★

Cesarean delivery rates have been steadily rising since the beginning of the 21st century. The growing incidence is even more prominent in developing countries owing to lack of evidence-based guidance and audit, and the expansion of private practice. The uprise in Cesarean delivery rate has been associated with considerable financial burden and has increased the risk otherwise uncommon serious complications such as placenta accreta disorders and uterine rupture. In addition to primary prevention of Cesarean delivery, trial of labor after cesarean section is one of the most successful strategies to reduce Cesarean deliveries and minimize risks associated with higher order Cesarean deliveries. This guideline appraises patient selection strategies and use of prediction model to promote counseling and enhance safety in women considering vaginal birth after Cesarean.

Risk and Management of Patients with Cancer and Heart Disease

Cancer and cardiovascular disease are two of the leading causes of global mortality and morbidity. Medical research has generated powerful lifesaving treatments for patients with cancer; however, such treatments may sometimes be at the expense of the patient's myocardium, leading to heart failure. Anti-cancer drugs, including anthracyclines, can result in deleterious cardiac effects, significantly impacting patients' functional capacity, mental well-being, and quality of life. Recognizing this, recent international guidelines and expert papers published recommendations on risk stratification and care delivery, including that of cardio-oncology services. This review will summarize key evidence with a focus on anthracycline therapy, providing clinical guidance for the non-oncology professional caring for a patient with cancer and heart failure.

Comparison of machine learning techniques in prediction of mortality following cardiac surgery: analysis of over 220 000 patients from a large national database

OBJECTIVES

To perform a systematic comparison of in-hospital mortality risk prediction post-cardiac surgery, between the predominant scoring system-European System for Cardiac Operative Risk Evaluation (EuroSCORE) II, logistic regression (LR) retrained on the same variables and alternative machine learning techniques (ML)-random forest (RF), neural networks (NN), XGBoost and weighted support vector machine.

METHODS

Retrospective analyses of prospectively routinely collected data on adult patients undergoing cardiac surgery in the UK from January 2012 to March 2019. Data were temporally split 70:30 into training and validation subsets. Mortality prediction models were created using the 18 variables of EuroSCORE II. Comparisons of discrimination, calibration and clinical utility were then conducted. Changes in model performance, variable-importance over time and hospital/operation-based model performance were also reviewed.

RESULTS

Of the 227 087 adults who underwent cardiac surgery during the study period, there were 6258 deaths (2.76%). In the testing cohort, there was an improvement in discrimination [XGBoost (95% confidence interval (CI) area under the receiver operator curve (AUC), 0.834-0.834, F1 score, 0.276-0.280) and RF (95% CI AUC, 0.833-0.834, F1, 0.277-0.281)] compared with EuroSCORE II (95% CI AUC, 0.817-0.818, F1, 0.243-0.245). There was no significant improvement in calibration with ML and retrained-LR compared to EuroSCORE II. However, EuroSCORE II overestimated risk across all deciles of risk and over time. The calibration drift was lowest in NN, XGBoost and RF compared with EuroSCORE II. Decision curve analysis showed XGBoost and RF to have greater net benefit than EuroSCORE II.

CONCLUSIONS

ML techniques showed some statistical improvements over retrained-LR and EuroSCORE II. The clinical impact of this improvement is modest at present. However the incorporation of additional risk factors in future studies may improve upon these findings and warrants further study.

Elderly patients over 80 years undergoing colorectal cancer resection: Development and validation of a predictive nomogram for survival

BACKGROUND

Surgery remains the primary treatment for localized colorectal cancer (CRC). Improving surgical decision-making for elderly CRC patients necessitates an accurate predictive tool.

AIM

To build a nomogram to predict the overall survival of elderly patients over 80 years undergoing CRC resection.

METHODS

Two hundred and ninety-five elderly CRC patients over 80 years undergoing surgery at Singapore General Hospital between 2018 and 2021 were identified from the American College of Surgeons – National Surgical Quality Improvement Program (ACS-NSQIP) database. Prognostic variables were selected using univariate Cox regression, and clinical feature selection was performed by the least absolute shrinkage and selection operator regression. A nomogram for 1- and 3-year overall survival was constructed based on 60% of the study cohort and tested on the remaining 40%. The performance of the nomogram was evaluated using the concordance index (C-index), area under the receiver operating characteristic curve (AUC), and calibration plots. Risk groups were stratified using the total risk points derived from the nomogram and the optimal cut-off point. Survival curves were compared between the high- and low-risk groups.

RESULTS

Eight predictors: Age, Charlson comorbidity index, body mass index, serum albumin level, distant metastasis, emergency surgery, postoperative pneumonia, and postoperative myocardial infarction, were included in the nomogram. The AUC values for the 1-year survival were 0.843 and 0.826 for the training and validation cohorts, respectively. The AUC values for the 3-year survival were 0.788 and 0.750 for the training and validation cohorts, respectively. C-index values of the training cohort (0.845) and validation cohort (0.793) suggested the excellent discriminative ability of the nomogram. Calibration curves demonstrated a good consistency between the predictions and actual observations of overall survival in both training and validation cohorts. A significant difference in overall survival was seen between elderly patients stratified into low- and high-risk groups (P < 0.001).

CONCLUSION

We constructed and validated a nomogram predicting 1- and 3-year survival probability in elderly patients over 80 years undergoing CRC resection, thereby facilitating holistic and informed decision-making among these patients.

Prognostic significance of L1CAM expression in addition to ProMisE in endometrial cancer

OBJECTIVE

To investigate the prognostic significance of L1 cell-adhesion molecule (L1CAM), β-catenin, and programmed death-ligand 1 (PD-L1) in endometrial cancer (EC) patients, with a focus on p53 wild-type subgroup, for additional risk stratification.

METHODS

This retrospective cohort study included EC patients classified according to Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE) who underwent primary surgical treatment at the single center between January 2014 and December 2018. Immunohistochemical staining was performed for four mismatch repair (MMR) proteins, p53, L1CAM, β-catenin, and PD-L1. DNA polymerase epsilon (POLE) mutation was detected by hot spot sequencing via droplet digital polymerase chain reaction. Survival outcome of each subgroup of L1CAM, β-catenin, and PD-L1 was measured according to their expression.

RESULTS

A total of 162 EC patients were included. Endometrioid histologic type and early-stage disease were 140 (86.4%) and 109 (67.3%), respectively. ProMisE classification assigned 48 (29.6%), 16 (9.9%), 72 (44.4%), and 26 (16.0%) patients to MMR-deficient, POLE-mutated, p53 wild-type, and p53 abnormal subgroups, respectively. L1CAM was identified as an independent poor prognostic factor for progression-free survival (PFS; adjusted hazard ratio [aHR], 3.207; 95% confidence interval (CI), 1.432-7.187; P = 0.005), whereas β-catenin and PD-L1 positivity were not associated with recurrence (P = 0.462 and P = 0.152, respectively). In p53 wild-type subgroup, L1CAM positivity was associated with worse PFS (aHR, 4.906; 95% CI, 1.685-14.287; P = 0.004).

CONCLUSION

L1CAM positivity was associated with poor prognosis in EC and further stratified the risk of recurrence in p53 wild-type subgroup, whereas β-catenin and PD-L1 were not informative for risk stratification.

[Development and validation of prognostic nomogram for malignant pleural mesothelioma]

Objective: To development the prognostic nomogram for malignant pleural mesothelioma (MPM). Methods: Two hundred and ten patients pathologically confirmed as MPM were enrolled in this retrospective study from 2007 to 2020 in the People's Hospital of Chuxiong Yi Autonomous Prefecture, the First and Third Affiliated Hospital of Kunming Medical University, and divided into training (n=112) and test (n=98) sets according to the admission time. The observation factors included demography, symptoms, history, clinical score and stage, blood cell and biochemistry, tumor markers, pathology and treatment. The Cox proportional risk model was used to analyze the prognostic factors of 112 patients in the training set. According to the results of multivariate Cox regression analysis, the prognostic prediction nomogram was established. C-Index and calibration curve were used to evaluate the model's discrimination and consistency in raining and test sets, respectively. Patients were stratified according to the median risk score of nomogram in the training set. Log rank test was performed to compare the survival differences between the high and low risk groups in the two sets. Results: The median overall survival (OS) of 210 MPM patients was 384 days (IQR=472 days), and the 6-month, 1-year, 2-year, and 3-year survival rates were 75.7%, 52.6%, 19.7%, and 13.0%, respectively. Cox multivariate regression analysis showed that residence (HR=2.127, 95% CI: 1.154-3.920), serum albumin (HR=1.583, 95% CI: 1.017-2.464), clinical stage (stage Ⅳ: HR=3.073, 95% CI: 1.366-6.910) and the chemotherapy (HR=0.476, 95% CI: 0.292-0.777) were independent prognostic factors for MPM patients. The C-index of the nomogram established based on the results of Cox multivariate regression analysis in the training and test sets were 0.662 and 0.613, respectively. Calibration curves for both the training and test sets showed moderate consistency between the predicted and actual survival probabilities of MPM patients at 6 months, 1 year, and 2 years. The low-risk group had better outcomes than the high-risk group in both training (P=0.001) and test (P=0.003) sets. Conclusion: The survival prediction nomogram established based on routine clinical indicators of MPM patients provides a reliable tool for prognostic prediction and risk stratification.

Biomarker-based risk model to predict persistent multiple organ dysfunctions after congenital heart surgery: a prospective observational cohort study

BACKGROUND

Multiple organ dysfunction syndrome (MODS) is an important cause of post-operative morbidity and mortality for children undergoing cardiac surgery requiring cardiopulmonary bypass (CPB). Dysregulated inflammation is widely regarded as a key contributor to bypass-related MODS pathobiology, with considerable overlap of pathways associated with septic shock. The pediatric sepsis biomarker risk model (PERSEVERE) is comprised of seven protein biomarkers of inflammation and reliably predicts baseline risk of mortality and organ dysfunction among critically ill children with septic shock. We aimed to determine if PERSEVERE biomarkers and clinical data could be combined to derive a new model to assess the risk of persistent CPB-related MODS in the early post-operative period.

METHODS

This study included 306 patients < 18 years old admitted to a pediatric cardiac ICU after surgery requiring cardiopulmonary bypass (CPB) for congenital heart disease. Persistent MODS, defined as dysfunction of two or more organ systems on postoperative day 5, was the primary outcome. PERSEVERE biomarkers were collected 4 and 12 h after CPB. Classification and regression tree methodology were used to derive a model to assess the risk of persistent MODS.

RESULTS

The optimal model containing interleukin-8 (IL-8), chemokine ligand 3 (CCL3), and age as predictor variables had an area under the receiver operating characteristic curve (AUROC) of 0.86 (0.81-0.91) for differentiating those with or without persistent MODS and a negative predictive value of 99% (95-100). Ten-fold cross-validation of the model yielded a corrected AUROC of 0.75 (0.68-0.84).

CONCLUSIONS

We present a novel risk prediction model to assess the risk for development of multiple organ dysfunction after pediatric cardiac surgery requiring CPB. Pending prospective validation, our model may facilitate identification of a high-risk cohort to direct interventions and studies aimed at improving outcomes via mitigation of post-operative organ dysfunction.

A spatial indicator of environmental and climatic vulnerability in Rome

BACKGROUND

Urban areas are disproportionately affected by multiple pressures from overbuilding, traffic, air pollution, and heat waves that often interact and are interconnected in producing health effects. A new synthetic tool to summarize environmental and climatic vulnerability has been introduced for the city of Rome, Italy, to provide the basis for environmental and health policies.

METHODS

From a literature overview and based on the availability of data, several macro-dimensions were identified on 1,461 grid cells with a width of 1 km² in Rome: land use, roads and traffic-related exposure, green space data, soil sealing, air pollution (PM_2.5, PM₁₀, NO₂, C₆H₆, SO₂), urban heat island intensity. The Geographically Weighted Principal Component Analysis (GWPCA) method was performed to produce a composite spatial indicator to describe and interpret each spatial feature by integrating all environmental dimensions. The method of natural breaks was used to define the risk classes. A bivariate map of environmental and social vulnerability was described.

RESULTS

The first three components explained most of the variation in the data structure with an average of 78.2% of the total percentage of variance (PTV) explained by the GWPCA, with air pollution and soil sealing contributing most in the first component; green space in the second component; road and traffic density and SO₂ in the third component. 56% of the population lives in areas with high or very high levels of environmental and climatic vulnerability, showing a periphery-centre trend, inverse to the deprivation index.

CONCLUSIONS

A new environmental and climatic vulnerability indicator for the city of Rome was able to identify the areas and population at risk in the city, and can be integrated with other vulnerability dimensions, such as social deprivation, providing the basis for risk stratification of the population and for the design of policies to address environmental, climatic and social injustice.

A novel prognostic nomogram for adult acute lymphoblastic leukemia: a comprehensive analysis of 321 patients

The cure rate of acute lymphoblastic leukemia (ALL) in adolescents and adults remains poor. This study aimed to establish a prognostic model for ≥14-year-old patients with ALL to guide treatment decisions. We retrospectively analyzed the data of 321 ALL patients between January 2017 and June 2020. Patients were randomly (2:1 ratio) divided into either the training or validation set. A nomogram was used to construct a prognostic model. Multivariate Cox analysis of the training set showed that age > 50 years, white blood cell count > 28.52×10⁹/L, and MLL rearrangement were independent risk factors for overall survival (OS), while platelet count >37×10⁹/L was an independent protective factor. The nomogram was established according to these independent prognostic factors in the training set, where patients were grouped into two categories: low-risk (≤13.15) and high-risk (>13.15). The survival analysis, for either total patients or sub-group patients, showed that both OS and progression-free survival (PFS) of low-risk patients was significantly better than that of high-risk patients. Moreover, treatment analysis showed that both OS and progression-free survival (PFS) of ALL with stem cell transplantation (SCT) were significantly better than that of ALL without SCT. Further stratified analysis showed that in low-risk patients, the OS and PFS of patients with SCT were significantly better than those of patients without SCT. In contrast, in high-risk patients, compared with non-SCT patients, receiving SCT can only significantly prolong the PFS, but it does not benefit the OS. We established a simple and effective prognostic model for ≥ 14-year-old patients with ALL that can provide accurate risk stratification and determine the clinical strategy.

A novel exosome-derived prognostic signature and risk stratification for breast cancer based on multi-omics and systematic biological heterogeneity

Tumor heterogeneity remains a major challenge for disease subtyping, risk stratification, and accurate clinical management. Exosome-based liquid biopsy can effectively overcome the limitations of tissue biopsy, achieving minimal invasion, multi-point dynamic monitoring, and good prognosis assessment, and has broad clinical prospects. However, there is still lacking comprehensive analysis of tumor-derived exosome (TDE)-based stratification of risk patients and prognostic assessment for breast cancer with systematic dissection of biological heterogeneity. In this study, the robust corroborative analysis for biomarker discovery (RCABD) strategy was used for the identification of exosome molecules, differential expression verification, risk prediction modeling, heterogenous dissection with multi-ome (6101 molecules), our ExoBCD database (306 molecules), and 53 independent studies (481 molecules). Our results showed that a 10-molecule exosome-derived signature (exoSIG) could successfully fulfill breast cancer risk stratification, making it a novel and accurate exosome prognostic indicator (Cox P = 9.9E-04, HR = 3.3, 95% CI 1.6-6.8). Interestingly, HLA-DQB2 and COL17A1, closely related to tumor metastasis, achieved high performance in prognosis prediction (86.35% contribution) and accuracy (Log-rank P = 0.028, AUC = 85.42%). With the combined information of patient age and tumor stage, they formed a bimolecular risk signature (Clinmin-exoSIG) and a convenient nomogram as operable tools for clinical applications. In conclusion, as an extension of ExoBCD, this study conducted systematic analyses to identify prognostic multi-molecular panel and risk signature, stratify patients and dissect biological heterogeneity based on breast cancer exosomes from a multi-omics perspective. Our results provide an important reference for in-depth exploration of the "biological heterogeneity - risk stratification - prognosis prediction".

Risk factors for avascular necrosis in patients with systemic lupus erythematosus: a multi-center cohort study of Chinese SLE Treatment and Research Group (CSTAR) Registry XXII

BACKGROUND

Avascular necrosis is a common organ damage in SLE patients, which can influence patients' life quality. Conflicting results exist in risk factors of AVN in SLE patients. The aim of this study was to illustrate risk factors predicting the occurrence of avascular necrosis (AVN), also known as osteonecrosis, in systemic lupus erythematosus (SLE) patients in Chinese SLE Treatment and Research Group (CSTAR), a multi-center cohort of Chinese SLE patients.

METHODS

SLE patients in CSTAR without existing AVN at registration were included. At least two follow-ups and an observation period of no less than 2 years for AVN event were required. Univariate and multivariate Cox regression analyses were used to evaluate risk factors for AVN in SLE patients. Coefficient B was transformed to risk score for the development of a risk stratification model.

RESULTS

One hundred six (2.59%) of 4091 SLE patients were diagnosed AVN during follow-ups of no less than 2 years. Multi-variate Cox regression analysis suggested that SLE onset age ≤ 30 (HR 1.616, p 0.023), arthritis (HR 1.642, p 0.018), existing organ damage (SDI ≥ 1) at registration (HR 2.610, p < 0.001), positive anti-RNP (HR 1.709, p 0.006), and high glucocorticoid maximum daily dose at registration (HR 1.747, p 0.02) were independent risk factors. A risk stratification system was developed according to the risk factors, and patients were divided into high risk (3-6) and low risk (0-2). The AUC of 0.692 indicated moderate discrimination. The calibration curve in internal validation was drawn.

CONCLUSION

Patients with SLE onset age ≤ 30, arthritis, existing organ damage (SDI ≥ 1) at registration, positive anti-RNP, and high glucocorticoid maximum daily dose at registration are at high risk for AVN and require attention.

Risk stratification based on acute-on-chronic liver failure in cirrhotic patients hospitalized for acute variceal bleeding

BACKGROUND AND AIMS

Acute variceal bleeding (AVB) is a life-threatening complication of cirrhosis. Acute-on-chronic liver failure (ACLF) is a syndrome characterized by acute decompensation of cirrhosis, multiple organ failures and high short-term mortality. This study aimed to evaluate the role of ACLF in the risk stratification of cirrhotic patients with AVB.

METHODS

Prospective data of 335 cirrhotic patients hospitalized for AVB were retrospectively extracted from Medical Information Mart for Intensive Care (MIMIC)-IV database. ACLF was defined by European Association for the Study of Liver-Chronic Liver Failure Consortium and diagnosed/graded with chronic liver failure-organ failure (CLIF-OF) score. Cox-proportional hazards regression analysis was performed to identify the risk factors for 6-week morality in AVB patients. Discrimination and calibration of prognostic scores were evaluated by plotting the receiver operating characteristics (ROC) curve and calibration curve, respectively. Overall performance was assessed by calculating the Brier score and R² value.

RESULTS

A total of 181 (54.0%) patients were diagnosed with ACLF (grade 1: 18.2%, grade 2: 33.7%, grade 3: 48.1%) at admission. The 6-week mortality in patients with ACLF was significantly higher than that in patients without ACLF (43.6% vs. 8.4%, P < 0.001) and increased in line with the severity of ACLF (22.5%, 34.2% and 63.8% for ACLF grade 1, 2 and 3, P < 0.001). In multivariate analysis, presence of ACLF remained as an independent risk factor for 6-week mortality after adjusting for confounding factors (HR = 2.12, P = 0.03). The discrimination, calibration and overall performance of CLIF-C ACLF and CLIF-C AD were superior to the traditional prognostic scores (CTP, MELD and MELD-Na) in the prediction of 6-week mortality of patients with and without ACLF, respectively.

CONCLUSION

The prognosis of cirrhotic patients with AVB is poor when accompanied by ACLF. ACLF at admission is an independent predictor for the 6-week mortality in cirrhotic patients with AVB. CLIF-C ACLF and CLIF-C AD are the best prognostic scores in AVB patients with and without ACLF, respectively, and can be used for the risk stratification of these two distinct entities.

The clinical importance of high-sensitivity cardiac troponin measurements for risk prediction in non-cardiac surgery

INTRODUCTION

The global healthcare burden associated with surgery is substantial, with many patients experiencing perioperative complications. Cardiac troponin I and T measured with high-sensitivity assays are cardiac specific biomarkers that associate closely with adverse outcomes in most patient populations. Perioperative physiological stress can induce troponin release from cardiomyocytes, a condition known as perioperative myocardial injury (PMI). PMI is associated with increased risk of poor short- and long-term outcomes, and current European guidelines recommend screening for PMI in at-risk individuals undergoing non-cardiac surgery.

AREAS COVERED

In this review we summarize current knowledge of the prognostic attributes of cardiac troponins, as well as the challenges associated with their application as biomarkers in the perioperative phase.

EXPERT OPINION

Measurement of circulating levels of cardiac troponins identify individuals at increased risk of poor postoperative outcomes. Systematic screening of at-risk individuals undergoing non-cardiac surgery will result in a large proportion of patients in need of further diagnostic workup to establish the exact nature of their PMI. The lack of concrete evidence of clinical benefit and the increased cost associated with such a strategy is concerning and underscore the need for further research.

Limited ability of the renal ablation-specific (MC)2 risk scoring system to predict major adverse events from percutaneous renal microwave ablation

PURPOSE

To access if the (MC)2 scoring system can identify patients at risk for major adverse events following percutaneous microwave ablation of renal tumors.

METHODS

Retrospective review of all adult patients who underwent percutaneous renal microwave ablation at two centers. Patient demographics, medical histories, laboratory work, technical details of the procedure, tumor characteristics, and clinical outcomes were collected. The (MC)2 score was calculated for each patient. Patients were assigned to low-risk (<5), moderate-risk (5-8) and high-risk (>8) groups. Adverse events were graded according to the criteria from the Society of Interventional Radiology guidelines.

RESULTS

A total of 116 patients (mean age = 67.8 [95%CI 65.5-69.9], 66 men) were included. 10 (8.6%) and 22 (19.0%) experienced major or minor adverse events, respectively. The mean (MC)2 score for patients with major adverse events (4.6 [95%CI 3.3-5.8]) was not higher than those with either minor adverse events (4.1 [95%CI 3.4-4.8], p = 0.49) or no adverse events (3.7 [95%CI 3.4-4.1], p = 0.25). However, mean tumor size was greater in those with major adverse events (3.1 cm [95%CI 2.0-4.1]) than minor adverse events (2.0 cm [95%CI 1.8-2.3], p = 0.01). Patients with central tumors were also more likely to experience major adverse events compared to those without central tumors (p = 0.02). The area under the receiver operator curve to predict major adverse events was 0.61 (p = 0.15), indicating a poor ability of the (MC)2 score to predict major adverse events.

CONCLUSION

The (MC)2 risk scoring system does not accurately identify patients at risk for major adverse events from percutaneous microwave ablation of renal tumors. The mean tumor size and central tumor location may serve as a better indicator for risk assessment of major adverse events.

Scoping review of the literature to ascertain how the STUMBL Score clinical prediction model is used to manage patients with blunt chest wall trauma in emergency care

INTRODUCTION

The STUMBL Score clinical prediction model was originally developed and externally validated to support clinical decision-making of patients with blunt chest wall trauma in the Emergency Department. The aim of this scoping review was to understand the extent and type of evidence in relation to the STUMBL Score clinical prediction model as a component of the management of patients with blunt chest wall trauma managed in the Emergency Care setting.

METHODS

A systematic search was conducted across databases, including Medline, Embase and the Cochrane Central Register of Controlled Trials from Jan 2014 to Feb 2023. In addition, a search of the grey literature was undertaken along with citation searching of relevant studies. Published and non-published sources of all research designs were included. Data extracted included specific details about the participants, concept, context, study methods and key findings relevant to the review question. Data extraction followed the JBI guidance and results presented in tabular format accompanied with a narrative summary.

RESULTS

A total of 44 sources originating from eight countries were identified, 28 were published and 16 grey literature. Sources were grouped into four separate categories: 1) external validation studies, 2) guidance documents, 3) practice reviews and educational resources 3) research studies and quality improvement projects, 4) grey literature unpublished resources. This body of evidence describes the clinical utility of the STUMBL Score and has identify how the score is being implemented and used differently in different settings including analgesic selection and participant eligibility for including in chest wall injury research studies.

DISCUSSION

This review demonstrates how the STUMBL Score has evolved from solely predicting risk of respiratory complications to a measure which supports clinical decision making for the use of complex analgesic modes and as a guide for eligibility in chest wall injury trauma research studies. Despite external validation of the STUMBL Score, there is a need for further calibration and evaluation, particularly relating to these repurposed functions of the score. Overall, the clinical benefit of the score remains clear and its wide usage demonstrates the impact it has on clinical care, patient experience and clinician decision making.

Prediction of the mitotic index and preoperative risk stratification of gastrointestinal stromal tumors with CT radiomic features

OBJECTIVE

The objective is to develop a mitotic prediction model and preoperative risk stratification nomogram for gastrointestinal stromal tumor (GIST) based on computed tomography (CT) radiomic features.

METHODS

A total of 267 GIST patients from 2009.07 to 2015.09 were retrospectively collected and randomly divided into (6:4) training cohort and validation cohort. The 2D-tumor region of interest was delineated from the portal-phase images on contrast-enhanced (CE)-CT, and radiomic features were extracted. Lasso regression method was used to select valuable features to establish a radiomic model for predicting mitotic index in GIST. Finally, the nomogram of preoperative risk stratification was constructed by combining the radiomic features and clinical risk factors.

RESULTS

Four radiomic features closely related to the level of mitosis were obtained, and a mitotic radiomic model was constructed. The area under the curve (AUC) of the radiomics signature model used to predict mitotic levels in training and validation cohorts (training cohort AUC = 0.752; 95% confidence interval [95%CI] 0.674-0.829; validation cohort AUC = 0.764; 95% CI 0.667-0.862). Finally, the preoperative risk stratification nomogram combining radiomic features was equivalent to the clinically recognized gold standard AUC (0.965 vs. 0.983) (p = 0.117). The Cox regression analysis found that the nomogram score was one of the independent risk factors for the long-term prognosis of the patients.

CONCLUSION

Preoperative CT radiomic features can effectively predict the level of mitosis in GIST, and combined with preoperative tumor size, accurate preoperative risk stratification can be performed to guide clinical decision-making and individualized treatment.

[Pulmonary embolism]

Pulmonary embolism is a frequent cardiovascular disease which in recent years has shown a reduction in the mortality but an increase in the incidence. Due to the optimization of clinical probability scores and the interpretation of the D‑dimer test, unnecessary examinations using computed tomography with respect to the exclusion of an acute pulmonary embolism can be avoided, also in pregnant women. The evaluation of the right ventricle contributes to a risk-adapted treatment. Treatment consists of anticoagulation, alone or in combination with reperfusion treatment, such as systemic thrombolysis and also catheter-assisted or surgical treatment. In addition to acute treatment of pulmonary embolisms, an adequate aftercare is important, particularly for the early detection of long-term sequelae. This review article summarizes the current recommendations of international guidelines for patients with pulmonary embolism, accompanied by clinical case examples and a critical discussion.

Risk stratification of HPV-positive results using extended genotyping and cytology: Data from the baseline phase of the Onclarity trial

BACKGROUND

Optimizing the balance between colposcopy referrals and the detection of high-grade cervical intraepithelial neoplasia (CIN) during cervical cancer screening requires robust triage strategies. We evaluated the performance of extended HPV genotyping (xGT), in combination with cytology triage, and compared it to previously published performance data for high-grade CIN detection by HPV16/18 primary screening in combination with p16/Ki-67 dual staining (DS).

METHODS AND MATERIALS

The baseline phase of the Onclarity trial enrolled 33,858 individuals, yielding 2978 HPV-positive participants. Risk values for ≥CIN3 were determined for Onclarity result groupings corresponding to HPV16, not HPV16 but HPV18 or 31, not HPV16/18/31 but HPV33/58 or 52, not HPV16/18/31/33/58/52 but HPV35/39/68 or 45 or 51 or 56/59/66 across all cytology categories. Published data from the IMPACT trial for HPV16/18 plus DS was utilized as a comparator during ROC analyses.

RESULTS

There were 163 ≥ CIN3 cases detected. The ≥CIN3 risk stratum hierarchy (% risk of ≥CIN3) that resulted from this analysis included: >LSIL (39.4%); HPV16, ≤LSIL (13.3%); HPV18/31, ≤LSIL (5.9%); HPV33/58/52/45, ASC-US/LSIL (2.4%); HPV33/58/52, NILM (2.1%); HPV35/39/68/51/56/59/66, ASC-US/LSIL (0.9%); and HPV45/35/39/68/51/56/59/66, NILM (0.6%). For ≥CIN3 ROC analysis, the optimal cutoff for sensitivity versus specificity was approximated between not HPV16 but HPV18 or 31, any cytology (≥CIN3 sensitivity = 85.9% and colposcopy-to- ≥ CIN3 = 7.4) and not HPV16/18/31 but HPV33/58/52, NILM (≥CIN3 sensitivity = 94.5% and colposcopy-to- ≥CIN3 = 10.8). HPV16/18 with DS triage showed a sensitivity of 94.3%, with a colposcopy-to- ≥ CIN3 ratio of 11.4.

CONCLUSIONS

xGT performed similarly compared to HPV primary screening plus DS for detection of high-grade CIN. xGT provides results that stratify risk in a flexible and reliable manner for colposcopy risk thresholds set by different guidelines or organizations.

The Brugada syndrome: risk stratification

Thirty years after its first description, the knowledge regarding Brugada syndrome has greatly increased. Spontaneous type 1 ECG pattern (BrECG) is a well-defined prognostic marker in asymptomatic patients and is associated with a double risk of arrhythmic events during follow-up as compared to drug-induced ECG pattern. Due to the extreme variability of the ECG pattern over time, the spontaneous type 1 BrECG must be carefully sought, not only through periodic ECGs but especially with repeated 12-lead 24-h Holter monitoring, with V1 and V2 electrodes placed also on the second and third intercostal space, in order to explore the right ventricular outflow tract. 12-lead 24-h Holter should also be performed in all the patients with a dubious BrECG pattern even before the drug challenge with sodium channel blockers, which carries a low but definite risk of complications. In addition to spontaneous type 1, other electrocardiographic markers of increased arrhythmic risk have been described, such as first-degree AV block, QRS fragmentation, S wave in lead I and II, and increased QRS duration. The electrophysiological study in asymptomatic patients with a spontaneous ECG Brugada pattern is still under jury and further studies need to clarify its precise role.

Development and validation of a survival prediction model and risk stratification for pancreatic neuroendocrine neoplasms

PURPOSE

We explored risk variables associated with cancer-specific survival (CSS) in patients with pancreatic neuroendocrine neoplasms (PNENs) and created a network dynamic nomogram model to predict patient survival time.

METHODS

A total of 7750 patients with PNENs were included in this analysis, including 134 with functional PNENs and 7616 with nonfunctional PNENs. Clinical feature and prognosis differences between functional and nonfunctional PNENs were compared. Independent prognostic factors affecting CSS were analyzed by univariate and multifactorial Cox regression. Nomogram and web-based prognosis prediction of PNENs were developed and validated by C indices, decision curve analysis, and calibration plots.

RESULTS

Patients with functional PNENs were younger at diagnosis than those with nonfunctional PNENs. Functional PNENs had better prognoses than nonfunctional PNENs (5-year survival rates: 78.55% and 71.10%, respectively). Univariate and multifactorial Cox regression analyses showed that tumor infiltration (T), nodal metastasis (N), metastasis (M), tumor site, differentiation grade, age, marital status, and surgical treatment were independent prognostic risk factors for CSS, which were included in the prognostic nomogram and web-based prognosis calculator. The calibration plots and decision curve analysis showed that the nomogram had excellent prediction and clinical practical ability. The C indices for CSS in the training and validation cohorts were 0.848 (95% CI 0.838-0.8578) and 0.823 (95% CI 0.807-0.839), respectively. We scored all patients according to the nomogram and divided patients into three different risk groups. The prognosis of the low-risk population was significantly better than those of the middle- and high-risk populations based on Kaplan-Meier survival curve.

CONCLUSION

We analyzed the clinical features of PNENs and developed a convenient and web dynamic nomogram to predict CSS.

Utility of serial conventional troponin testing for emergency department patients stratified by HEART score and symptom timing

BACKGROUND

The HEART score for risk stratifying chest pain patients in the emergency department (ED) has been widely adopted in clinical practice, but is often employed with nonconformant serial troponin measurements.

OBJECTIVE

The primary objective of this study was to examine the utility of obtaining a second conventional 3-h troponin I (TnI) level in ED patients presenting with potential acute coronary syndrome (ACS), stratified by HEART score and duration of symptoms.

METHODS

This was a retrospective cohort study of consecutive adult ED patients with a complete HEART score. We assessed the utility of repeat TnI measurement by examining the positivity rate of ΔTnI = [Second TnI] - [Initial TnI] stratified by HEART score and time elapsed since onset or resolution of symptoms. Major adverse cardiac events (MACE) within 6 weeks of index visit were assessed.

RESULTS

A total of 944 patients were included with 433 (45.9%) assigned a low risk HEART score 0-3. Of the 268 (61.9%) low risk HEART score patients receiving a second TnI, only 3 (1.1%, [0.2-3.2%]) resulted in a positive ΔTnI, one of which occurred in the setting of an elevated initial TnI. Overall, patients presenting within 3 h of symptoms were more likely to experience positive ΔTnI, index MACE and MACE at 6 weeks compared to patients presenting ≥3 h since symptoms onset/resolution and patients with unknown timing of symptoms (15.9% vs 11.0% vs 10.3%, p < 0.001; 10.0% vs 5.3% vs 4.6%, p = 0.021; 12.7% vs 6.6% vs 6.4%, p = 0.047).

CONCLUSION

Our data suggest serial measurement of conventional troponin provides limited added benefit in low risk HEART score patients, regardless of duration and timing of symptoms. Conversely, serial troponin measurement may confer utility in moderate/high risk HEART score patients, particularly those presenting within 3 h of symptoms.

Construction and validation of a novel prognostic signature for cutaneous melanoma based on ferroptosis-related genes

Ferroptosis, a recently uncovered iron-dependent, non-apoptotic cell death process, has been increasingly linked to cancer development. In this study, our objective was to develop a prognostic model centered on ferroptosis-related genes (FRGs) and assess its efficacy as an overall survival (OS) prediction biomarker. We conducted a systematic analysis of cutaneous melanoma (CM) and devised a novel ferroptosis-related prognostic signature (FRGSig) using the TCGA database. An independent dataset from GSE65904 was employed to corroborate the validity of the FRGSig. Both univariate and multivariate Cox proportional hazard regression analyses were utilized to construct a FRGSig composed of five FRGs. mRNA expression and immunohistochemistry (IHC) analysis demonstrated that the expression of FRGSig genes varied between tumor and normal tissues. According to Kaplan-Meier analysis, patients with elevated FRGsig scores faced a worse prognosis. The predictive accuracy of FRGSig was evaluated using the time-dependent receiver operating characteristic curve (ROC), with the area under the curve (AUC) values for 1, 3, and 5 OS at 0.682, 0.711, 0.735 in the TCGA cohort, and 0.662, 0.695, 0.712 in the validation dataset, respectively. Univariate and multivariate Cox regression analyses demonstrated that FRGSig served as an independent prognostic factor. Further analysis revealed a significant relationship between FRGSig and Tumor Mutational Burden (TMB) as well as immune infiltration levels. Gene set enrichment analysis (GSEA) disclosed functional disparities between high- and low-risk groups, suggesting that immune checkpoint-related pathways could be instrumental in the improved prognosis of the low-risk group. Taken together, the FRGSig has potential guidance for prognosis prediction and clinical treatment of CM.

Use of machine learning algorithms to predict life-threatening ventricular arrhythmia in sepsis

Aims

Life-threatening ventricular arrhythmias (LTVAs) are common manifestations of sepsis. The majority of sepsis patients with LTVA are unresponsive to initial standard treatment and thus have a poor prognosis. There are very limited studies focusing on the early identification of patients at high risk of LTVA in sepsis to perform optimal preventive treatment interventions. We aimed to develop a prediction model to predict LTVA in sepsis using machine learning (ML) approaches.

Methods and results

Six ML algorithms including CatBoost, LightGBM, and XGBoost were employed to perform the model fitting. The least absolute shrinkage and selection operator (LASSO) regression was used to identify key features. Methods of model evaluation involved in this study included area under the receiver operating characteristic curve (AUROC), for model discrimination, calibration curve, and Brier score, for model calibration. Finally, we validated the prediction model both internally and externally. A total of 27 139 patients with sepsis were identified in this study, 1136 (4.2%) suffered from LTVA during hospitalization. We screened out 10 key features from the initial 54 variables via LASSO regression to improve the practicability of the model. CatBoost showed the best prediction performance among the six ML algorithms, with excellent discrimination (AUROC = 0.874) and calibration (Brier score = 0.157). The remarkable performance of the model was presented in the external validation cohort (n = 9492), with an AUROC of 0.836, suggesting certain generalizability of the model. Finally, a nomogram with risk classification of LTVA was shown in this study.

Conclusion

We established and validated a machine leaning-based prediction model, which was conducive to early identification of high-risk LTVA patients in sepsis, thus appropriate methods could be conducted to improve outcomes.

Cardiovascular disease risk assessment using a deep-learning-based retinal biomarker: a comparison with existing risk scores

Aims

This study aims to evaluate the ability of a deep-learning-based cardiovascular disease (CVD) retinal biomarker, Reti-CVD, to identify individuals with intermediate- and high-risk for CVD.

Methods and results

We defined the intermediate- and high-risk groups according to Pooled Cohort Equation (PCE), QRISK3, and modified Framingham Risk Score (FRS). Reti-CVD's prediction was compared to the number of individuals identified as intermediate- and high-risk according to standard CVD risk assessment tools, and sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to assess the results. In the UK Biobank, among 48 260 participants, 20 643 (42.8%) and 7192 (14.9%) were classified into the intermediate- and high-risk groups according to PCE, and QRISK3, respectively. In the Singapore Epidemiology of Eye Diseases study, among 6810 participants, 3799 (55.8%) were classified as intermediate- and high-risk group according to modified FRS. Reti-CVD identified PCE-based intermediate- and high-risk groups with a sensitivity, specificity, PPV, and NPV of 82.7%, 87.6%, 86.5%, and 84.0%, respectively. Reti-CVD identified QRISK3-based intermediate- and high-risk groups with a sensitivity, specificity, PPV, and NPV of 82.6%, 85.5%, 49.9%, and 96.6%, respectively. Reti-CVD identified intermediate- and high-risk groups according to the modified FRS with a sensitivity, specificity, PPV, and NPV of 82.1%, 80.6%, 76.4%, and 85.5%, respectively.

Conclusion

The retinal photograph biomarker (Reti-CVD) was able to identify individuals with intermediate and high-risk for CVD, in accordance with existing risk assessment tools.

Development, validation, and evaluation of a risk assessment tool for personalized screening of gastric cancer in Chinese populations

BACKGROUND

Effective risk prediction models are lacking for personalized endoscopic screening of gastric cancer (GC). We aimed to develop, validate, and evaluate a questionnaire-based GC risk assessment tool for risk prediction and stratification in the Chinese population.

METHODS

In this three-stage multicenter study, we first selected eligible variables by Cox regression models and constructed a GC risk score (GCRS) based on regression coefficients in 416,343 subjects (aged 40-75 years) from the China Kadoorie Biobank (CKB, development cohort). In the same age range, we validated the GCRS effectiveness in 13,982 subjects from another independent Changzhou cohort (validation cohort) as well as in 5348 subjects from an endoscopy screening program in Yangzhou. Finally, we categorized participants into low (bottom 20%), intermediate (20-80%), and high risk (top 20%) groups by the GCRS distribution in the development cohort.

RESULTS

The GCRS using 11 questionnaire-based variables demonstrated a Harrell's C-index of 0.754 (95% CI, 0.745-0.762) and 0.736 (95% CI, 0.710-0.761) in the two cohorts, respectively. In the validation cohort, the 10-year risk was 0.34%, 1.05%, and 4.32% for individuals with a low (≤ 13.6), intermediate (13.7~30.6), and high (≥ 30.7) GCRS, respectively. In the endoscopic screening program, the detection rate of GC varied from 0.00% in low-GCRS individuals, 0.27% with intermediate GCRS, to 2.59% with high GCRS. A proportion of 81.6% of all GC cases was identified from the high-GCRS group, which represented 28.9% of all the screened participants.

CONCLUSIONS

The GCRS can be an effective risk assessment tool for tailored endoscopic screening of GC in China. Risk Evaluation for Stomach Cancer by Yourself (RESCUE), an online tool was developed to aid the use of GCRS.

The pre-thyroidectomy surgeon's checklist. Recommendations of the AFC>E (Association francophone de chirurgie endocrinienne), with the SFE (Société française d'endocrinologie) and the SFMN (Société française de médecine nucléaire)

During the patient interview, signs of compression or invasion are sought out: dyspnea, dysphagia, dysphonia. The circumstances of discovery of the thyroid pathology are indicated. The surgeon must be closely acquainted with the EU-TIRADS and Bethesda classifications so as to be able to evaluate and explain to the patient the risk of malignancy. He must also be able to interpret a cervical ultrasound in view of proposing a procedure adapted to the pathology. Cervicothoracic CT-scan (or MRI) must be prescribed in the event of suspected plunging nodule or clinical/echography signs: non-palpable lower pole of the thyroid behind the clavicle, dyspnea, dysphagia, collateral circulation. The surgeon goes on to investigate possible relationships with adjacent organs, to evaluate extension toward the aortic arch and the positions (anterior, posterior or mixed) of the goiter, the objective being to determine the most adapted approach: classical cervicotomy, manubriotomy or sternotomy. Even in the event of a tumoral pathology, PET-FDG is not one of the imagery exams carried out systematically. Only in case of TSH < 0.5μU/mL should thyroid scintigraphy be proposed. Prior to any thyroid surgery, serum TSH levels, calcitoninemia and calcemia must be measured.

Subjective and objective survival prediction in mechanically ventilated critically ill patients: a prospective cohort study

BACKGROUND

ICU risk assessment tools, routinely used for predicting population outcomes, are not recommended for evaluating individual risk. The state of health of single patients is mostly subjectively assessed to inform relatives and presumably to decide on treatment decisions. However, little is known how subjective and objective survival estimates compare.

METHODS

We performed a prospective cohort study in mechanically ventilated critically ill patients across five European centres, assessed 62 objective markers and asked the clinical staff to subjectively estimate the probability of surviving 28 days.

RESULTS

Within the 961 included patients, we identified 27 single objective predictors for 28-day survival (73.8%) and pooled them into predictive groups. While patient characteristics and treatment models performed poorly, the disease and biomarker models had a moderate discriminative performance for predicting 28-day survival, which improved for predicting 1-year survival. Subjective estimates of nurses (c-statistic [95% CI] 0.74 [0.70-0.78]), junior physicians (0.78 [0.74-0.81]) and attending physicians (0.75 [0.72-0.79]) discriminated survivors from non-survivors at least as good as the combination of all objective predictors (c-statistic: 0.67-0.72). Unexpectedly, subjective estimates were insufficiently calibrated, overestimating death in high-risk patients by about 20% in absolute terms. Combining subjective and objective measures refined discrimination and reduced the overestimation of death.

CONCLUSIONS

Subjective survival estimates are simple, cheap and similarly discriminative as objective models; however, they overestimate death risking that live-saving therapies are withheld. Therefore, subjective survival estimates of individual patients should be compared with objective tools and interpreted with caution if not agreeing. Trial registration ISRCTN ISRCTN59376582 , retrospectively registered October 31st 2013.

Feasibility of stone recurrence risk stratification using the recurrence of kidney stone (ROKS) nomogram

This study seeks to evaluate the recurrence of kidney stones (ROKS) nomogram for risk stratification of recurrence in a retrospective study. To do this, we analyzed the performance of the 2018 ROKS nomogram in a case-control study of 200 patients (100 with and 100 without subsequent recurrence). All patients underwent kidney stone surgery between 2013 and 2015 and had at least 5 years of follow-up. We evaluated ROKS performance for prediction of recurrence at 2- and 5-year via area under the receiver operating curve (ROC-AUC). Specifically, we assessed the nomogram's potential for stratifying patients based on low or high risk of recurrence at: a) an optimized cutoff threshold (i.e., optimized for both sensitivity and specificity), and b) a sensitive cutoff threshold (i.e., high sensitivity (0.80) and low specificity). We found fair performance of the nomogram for recurrence prediction at 2 and 5 years (ROC-AUC of 0.67 and 0.63, respectively). At the optimized cutoff threshold, recurrence rates for the low and high-risk groups were 20 and 45% at 2 years, and 50 and 70% at 5 years, respectively. At the sensitive cutoff threshold, the corresponding recurrence rates for the low and high-risk groups were of 16 and 38% at 2 years, and 42 and 66% at 5 years, respectively. Kaplan-Meier analysis revealed a recurrence-free advantage between the groups for both cutoff thresholds (p < 0.01, Fig. 2). Therefore, we believe that the ROKS nomogram could facilitate risk stratification for stone recurrence and adherence to risk-based surveillance protocols.

Avoiding Prostate Biopsies in Patients at Low Risk for Prostate Cancer: A Prospective Evaluation of a PSA-Density-Based Safety Net

INTRODUCTION AND OBJECTIVES

Decision-making to perform prostate biopsy should include individual risk assessment. Patients classified as low risk by the Rotterdam Prostate Cancer Risk Calculator are advised to forego biopsy (PBx). There is concern about missing clinically significant prostate cancer (csPCa). A clear pathway for follow-up is needed.

MATERIAL AND METHODS

Data for 111 consecutive patients were collected. Patients were encouraged to adhere to a PSA-density-based safety net after PBx was omitted. Cut off values indicating a re-evaluation were PSA density &gt;0.15 ng/mL/ccm in PBx-naïve patients and &gt;0.2 ng/mL/ccm in men with past-PBx. Primary endpoint was whether men had their PSA taken regularly. Secondary endpoint was whether a new multiparametric MRI was performed when PSA-density increased. Tertiary endpoint was whether biopsy was performed when risk stratification revealed an increased risk.

RESULTS

Median follow-up was 12 months (IQR 9-15 months). The primary endpoint was reached by 97.2% (n = 106). The secondary endpoint was reached by 30% (n = 3). The tertiary endpoint was reached by 50% (n = 2). Histopathologic analyses revealed csPCa in none of these cases. Risk stratification did not change (p = 0.187) with the majority of patients (89.2%, n = 99).

CONCLUSION

The concern of missing csPCa when omitting PBx in the risk-stratified pathway may be negated. Changes in risk stratification during follow-up should lead to subsequent PBx. We suggest implementing a safety net based on PSA density and digital rectal examination (DRE).

[Common errors, pitfalls, and management of complications of prostate biopsy : The most common diagnostic and procedural challenges of transrectal fusion prostate biopsy in the initial diagnosis of clinically significant prostate cancer]

BACKGROUND

Transrectal (TR) prostate biopsy is the gold standard in diagnosis of prostate cancer (PC). It requires a precise and safe technique for sample acquisition.

OBJECTIVE

Several approaches will be discussed to avoid overdiagnosis, false-negative results, and complications of the procedure.

MATERIALS AND METHODS

We analyzed national and European guidelines, systematic reviews, meta-analyses, as well as prospective and retrospective studies to describe current trends in indication and performance of biopsies.

RESULTS

Incorporation of risk calculators and magnetic resonance imaging (MRI) into daily routine reduces biopsy rates and results in a more precise diagnosis of clinically significant prostate cancer (csPC). Combination of random- and MRI-fusion guided biopsy-but also extending the radius of sampling by 10 mm beyond the MRI lesion and a transperineal (TP) sampling approach - lead to a higher tumor-detection rate. Bleeding is the most common complication after prostate biopsy and is usually self-limiting. Postbiopsy infection rates can be reduced through TP biopsy.

CONCLUSION

TR MRI-fusion guided biopsy is a widely acknowledged tool in primary diagnostics of csPC. Higher detection rates and safety can be achieved through a TP sampling approach.

Prediction of new onset postoperative atrial fibrillation using a simple Nomogram

BACKGROUND

New onset postoperative atrial fibrillation (POAF) is the most common complication of cardiac surgery, with an incidence ranging from 15 to 50%. This study aimed to develop a new nomogram to predict POAF using preoperative and intraoperative risk factors.

METHODS

We retrospectively analyzed the data of 2108 consecutive adult patients (> 18 years old) who underwent cardiac surgery at our medical institution. The types of surgery included isolated coronary artery bypass grafting, valve surgery, combined valve and coronary artery bypass grafting (CABG), or aortic surgery. Logistic regression or machine learning methods were applied to predict POAF incidence from a subset of 123 parameters. We also developed a simple nomogram based on the strength of the results and compared its predictive ability with that of the CHA2DS2-VASc and POAF scores currently used in clinical practice.

RESULTS

POAF was observed in 414 hospitalized patients. Logistic regression provided the highest area under the receiver operating characteristic curve (ROC) in the validation cohort. A simple bedside tool comprising three variables (age, left atrial diameter, and surgery type) was established, which had a discriminative ability with a ROC of 0.726 (95% CI 0.693-0.759) and 0.727 (95% CI 0.676-0.778) in derivation and validation subsets respectively. The calibration curve of the new model was relatively well-fit (p = 0.502).

CONCLUSIONS

Logistic regression performed better than machine learning in predicting POAF. We developed a nomogram that may assist clinicians in identifying individuals who are prone to POAF.