Diagnostic and therapeutic dilemmas in a patient with myocarditis, Brugada syndrome and arrhythmic syncope

We present a case of a previously healthy 23-year-old male who presented with chest pain, palpitations and spontaneous type 1 Brugada electrocardiographic (ECG) pattern. Positive family history for sudden cardiac death (SCD) was remarkable. Initially, clinical symptoms in combination with myocardial enzymes elevation, regional myocardial oedema with late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) and inflammatory lymphocytoid-cell infiltrates in the endomyocardial biopsy (EMB) suggested the diagnosis of a myocarditis-induced Brugada phenocopy (BrP). Under immunosuppressive therapy with methylprednisolone and azathioprine, a complete remission of both symptoms and biomarkers was accomplished. However, the Brugada pattern did not resolve. The eventually spontaneous Brugada pattern type 1 established the diagnosis of Brugada syndrome (BrS). Due to his previous history of syncope, the patient was offered an ICD that he declined. After his discharge he experienced a new episode of arrhythmic syncope. He was readmitted and received an ICD.

Assessment of machine learning algorithms in national data to classify the risk of self-harm among young adults in hospital: A retrospective study

BACKGROUND

Self-harm is one of the most common presentations at accident and emergency departments in the UK and is a strong predictor of suicide risk. The UK Government has prioritised identifying risk factors and developing preventative strategies for self-harm. Machine learning offers a potential method to identify complex patterns with predictive value for the risk of self-harm.

METHODS

National data in the UK Mental Health Services Data Set were isolated for patients aged 18-30 years who started a mental health hospital admission between Aug 1, 2020 and Aug 1, 2021, and had been discharged by Jan 1, 2022. Data were obtained on age group, gender, ethnicity, employment status, marital status, accommodation status and source of admission to hospital and used to construct seven machine learning models that were used individually and as an ensemble to predict hospital stays that would be associated with a risk of self-harm.

OUTCOMES

The training dataset included 23 808 items (including 1081 episodes of self-harm) and the testing dataset 5951 items (including 270 episodes of self-harm). The best performing algorithms were the random forest model (AUC-ROC 0.70, 95%CI:0.66-0.74) and the ensemble model (AUC-ROC 0.77 95%CI:0.75-0.79).

INTERPRETATION

Machine learning algorithms could predict hospital stays with a high risk of self-harm based on readily available data that are routinely collected by health providers and recorded in the Mental Health Services Data Set. The findings should be validated externally with other real-world, prospective data.

FUNDING

This study was supported by the Midlands and Lancashire Commissioning Support Unit.

Spatially-aware clustering improves AJCC-8 risk stratification performance in oropharyngeal carcinomas

OBJECTIVE

Evaluate the effectiveness of machine learning tools that incorporate spatial information such as disease location and lymph node metastatic patterns-of-spread, for prediction of survival and toxicity in HPV+ oropharyngeal cancer (OPC).

MATERIALS & METHODS

675 HPV+ OPC patients that were treated at MD Anderson Cancer Center between 2005 and 2013 with curative intent IMRT were retrospectively collected under IRB approval. Risk stratifications incorporating patient radiometric data and lymph node metastasis patterns via an anatomically-adjacent representation with hierarchical clustering were identified. These clusterings were combined into a 3-level patient stratification and included along with other known clinical features in a Cox model for predicting survival outcomes, and logistic regression for toxicity, using independent subsets for training and validation.

RESULTS

Four groups were identified and combined into a 3-level stratification. The inclusion of patient stratifications in predictive models for 5-yr Overall survival (OS), 5-year recurrence free survival, (RFS) and Radiation-associated dysphagia (RAD) consistently improved model performance measured using the area under the curve (AUC). Test set AUC improvements over models with clinical covariates, was 9 % for predicting OS, and 18 % for predicting RFS, and 7 % for predicting RAD. For models with both clinical and AJCC covariates, AUC improvement was 7 %, 9 %, and 2 % for OS, RFS, and RAD, respectively.

CONCLUSION

Including data-driven patient stratifications considerably improve prognosis for survival and toxicity outcomes over the performance achieved by clinical staging and clinical covariates alone. These stratifications generalize well to across cohorts, and sufficient information for reproducing these clusters is included.

A validation study of the high acuity readmission risk pediatric screen (HARRPS) tool©: Predicting readmission risk within the pediatric population

BACKGROUND

The initial research study of the High Acuity Readmission Risk Pediatric Screen (HARRPS) Tool © focused on using retrospective data to apply weighted values to the questions within the tool, identify overall risk score, and attribute risk categories (low, moderate, high risk) to the overall risk score. This study focused on validating the data from the initial study, as well as cross examining the need to include admission diagnosis within the tool.

METHOD

Study was a single-centered, retrospective chart review study using a different subset of patients from the initial study. Pediatric patients with thirty-day readmissions were compared to pediatric patients without a thirty-day readmission over a twelve-month period. Utilized same statistical software and methodology from initial study to identify if readmission risk probability could be replicated with a different population.

RESULTS

The initial study performed in 2018 demonstrated a c-statistic score/ area under the curve (AUC) of 0.68 [95% CI: 0.67, 0.69]. In addition, the initial study demonstrated as risk score increases, the probability of readmission gradually increased until a patient had a risk score of seven or greater, at which point readmission risk plateaued. This resulted in low, moderate, and high readmission risk categories. The current study performed using data from 2019 demonstrated an improved c-statistic score / AUC of 0.83 [95% CI: 0.80, 0.87] with admission diagnosis included, and a c-statistic score / AUC of 0.80 [95% CI: 0.76, 0.83] without the admission diagnosis included. The analysis of overall risk score demonstrated a substantial difference in how to interpret final readmission risk scores. Both the initial study and validation study were consistent in demonstrating a risk score of three or less was associated with low readmission risk. However, in the validation study, there was no substantial difference between moderate or high risk, leading to updating the tool from 3 risk categories into 2 risk categories of low risk and at risk of readmission.

CONCLUSION

Based on the finding from the validation study, the admission diagnosis was removed from the HARRPS Tool© as the difference in c-statistic score was nominal, and the risk categories were changed from three categories (low, moderate, high risk) to two categories of low risk (score 0-2) and at risk of readmission for a score of 3+. The ability of the HARRPS Tool© to predict readmission risk preforms best with a c-statistic = 0.80, outperforming the following tools: LACE (0.65), LACE -SDH (0.67), LACE + (0.61), Epic's readmission risk model (0.69), and SQLAPE ® (0.71) (Ryan, et al., 2021; Hwang, et al., 2021).

Construction and validation of a SEER-based prognostic nomogram for young and middle-aged males patients with hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common digestive tumor, and we aimed to develop and validate nomogram models, predicting the overall survival (OS) of young and middle-aged male patients with HCC.

METHODS

We extracted eligible data from relevant patients between 2000 and 2017 from the Surveillance, Epidemiology, and End Results (SEER) database. In addition, randomly divided all patients into two groups (training and validation = 7:3). The nomogram was established using effective risk factors based on univariate and multivariate analysis. The area under the time-dependent curve, calibration plots, and decision curve analysis (DCA) were used to evaluate the effective performance of the nomogram. The risk stratifications of the nomogram and the AJCC criteria-based tumor stage were compared.

RESULTS

11 variables were selected by univariate and multivariate analysis to establish the nomogram of HCC. The AUC values of 3, 4, and 5 years of the time-ROC curve are 0.858, 0.862 and 0.859 for the training cohort, and 0.858, 0.877 and 0.869 for the validation cohort, respectively, indicating that the nomogram has a good ability of discrimination. The calibration plots showed favorable consistency between the prediction of the nomogram and actual observations in both the training and validation cohorts. In addition, the decision curve DCA showed that the nomogram was clinically useful and had better discriminative ability to recognize patients at high risk than the AJCC criteria-based tumor stage.

CONCLUSION

Prognostic nomogram of young and middle-aged male patients with HCC was developed and validated to help clinicians evaluate the prognosis of patients.

Recommendations for risk stratification of periocular squamous cell carcinoma

Periocular squamous cell carcinoma is a common cutaneous malignancy with generally favorable outcomes; however, the periocular region is intrinsically a high-risk location, and there exist a subset of lesions with a propensity for poor outcomes. Orbital invasion, intracranial perineural spread, nodal and distant metastasis are feared complications. There are several staging systems for eyelid carcinoma and cutaneous squamous cell carcinoma, but the definition of high-risk lesions remains heterogeneous. It is unclear exactly which lesions can be safely deescalated, and which require nodal evaluation and adjuvant multimodal therapy. We seek to answer these questions by summarizing the literature on clinicopathologic variables, molecular markers, and gene profiling tests in periocular squamous cell carcinoma, with the extrapolation of data from the cutaneous squamous cell carcinoma literature. Standardized pathology reports with information on tumor dimensions, histological subtype and grade, perineural invasion, and lymphovascular invasion should become uniform. Integration with gene expression profiling assessments will individualize and improve the predictive accuracy of risk stratification tools to ultimately inform multidisciplinary decision-making.

Development of the national Dutch PEWS: the challenge against heterogeneity and implementation difficulties of PEWS in the Netherlands

BACKGROUND

For the early recognition of deteriorating patients several Pediatric Early Warning Score (PEWS) systems have been developed with the assumption that early detection can prevent further deterioration. Although PEWS are widely being used in hospitals in the Netherlands, there is no national consensus on which score to use and how to embed the score into a PEWS system. This resulted in a substantial heterogeneity of PEWS systems, of which many are unvalidated or self-designed. The primary objective of this study was to develop a pragmatic consensus-based PEWS system that can be utilized in all Dutch hospitals (University Medical Centers, teaching hospitals, and general hospitals).

METHODS

This study is an iterative mixed-methods study. The methods from the Core Outcome Measures in Effectiveness Trials (COMET) initiative were used and consisted of two Delphi rounds, two inventories set out to all Dutch hospitals and a focus group session with parents. The study was guided by five expert meetings with different stakeholders and a final consensus meeting that resulted in a core PEWS set.

RESULTS

The first Delphi round was completed by 292 healthcare professionals, consisting of pediatric nurses and physicians. In the second Delphi round 217 healthcare professionals participated. Eventually, the core PEWS set was been developed comprising of the parameters work of breathing, respiratory rate, oxygen therapy, heart rate and capillary refill time, and AVPU (Alert, Verbal, Pain, and Unresponsive). In addition, risk stratification was added to the core set with standardized risk factors consisting of [1] worried signs from healthcare professionals and parents and [2] high-risk treatment, with the option to add applicable local defined risk factors. Lastly, the three categories of risk stratification were defined (standard, medium, and high risk) in combination with standardized actions of the professionals for each category.

CONCLUSION

This study demonstrates a way to end a country's struggle with PEWS heterogeneity by co-designing a national Dutch PEWS system. Currently, the power of the system is being investigated in a large multi-center study in the Netherlands.

Risk Stratification in Pediatric Wolff-Parkinson-White: Practice Variation Among Pediatric Cardiologists and Electrophysiologists

BACKGROUND

Published guidelines provide recommendations for risk stratification in pediatric Wolff-Parkinson-White (WPW). There are no data on provider concordance with these guidelines. We hypothesized that significant practice variation exists between pediatric cardiologists (PC) and electrophysiologists (EP).

METHOD

The records of all patients, age 8 to 21 years, with a new ECG diagnosis of WPW between 1/1/2013 and 12/31/2018, from a single center, were retrospectively reviewed. Subjects were categorized on the basis of symptoms and resting ECG findings as one of the following: asymptomatic intermittent WPW, asymptomatic persistent WPW, or symptomatic WPW. The performance and results of diagnostic testing, including Holter monitor, event monitor, exercise stress test (EST), and electrophysiology study (EPS), were recorded. The primary outcome was concordance with published guidelines. A secondary outcome was documentation of a discussion of sudden cardiac death (SCD) risk.

RESULTS

615 patient encounters were analyzed in 231 patients with newly diagnosed WPW pattern on ECG (56% male; mean age at diagnosis 13.9 ± 2.5 years). EP were observed to have a significantly higher rate of guideline concordance than PC (95% vs. 71%, p < 0.001). There was significant practice variation between PC and EP in the documentation of a discussion of SCD risk: 96% in EP vs. 39% in PC (p < 0.001).

CONCLUSION

Significant practice variation exists in the non-invasive and invasive risk stratification of pediatric WPW, with lower concordance to published guidelines amongst PC, when compared to EP. This report highlights the need to promote awareness of current WPW guidelines in the pediatric cardiology community at large.

Performance of a multi-sensor implantable defibrillator algorithm for heart failure monitoring in the presence of atrial fibrillation

AIMS

The HeartLogic Index combines data from multiple implantable cardioverter defibrillators (ICDs) sensors and has been shown to accurately stratify patients at risk of heart failure (HF) events. We evaluated and compared the performance of this algorithm during sinus rhythm and during long-lasting atrial fibrillation (AF).

METHODS AND RESULTS

HeartLogic was activated in 568 ICD patients from 26 centres. We found periods of ≥30 consecutive days with an atrial high-rate episode (AHRE) burden <1 h/day and periods with an AHRE burden ≥20 h/day. We then identified patients who met both criteria during the follow-up (AHRE group, n = 53), to allow pairwise comparison of periods. For control purposes, we identified patients with an AHRE burden <1 h throughout their follow-up and implemented 2:1 propensity score matching vs. the AHRE group (matched non-AHRE group, n = 106). In the AHRE group, the rate of alerts was 1.2 [95% confidence interval (CI): 1.0-1.5]/patient-year during periods with an AHRE burden <1 h/day and 2.0 (95% CI: 1.5-2.6)/patient-year during periods with an AHRE-burden ≥20 h/day (P = 0.004). The rate of HF hospitalizations was 0.34 (95% CI: 0.15-0.69)/patient-year during IN-alert periods and 0.06 (95% CI: 0.02-0.14)/patient-year during OUT-of-alert periods (P < 0.001). The IN/OUT-of-alert state incidence rate ratio of HF hospitalizations was 8.59 (95% CI: 1.67-55.31) during periods with an AHRE burden <1 h/day and 2.70 (95% CI: 1.01-28.33) during periods with an AHRE burden ≥20 h/day. In the matched non-AHRE group, the rate of HF hospitalizations was 0.29 (95% CI: 0.12-0.60)/patient-year during IN-alert periods and 0.04 (95% CI: 0.02-0.08)/patient-year during OUT-of-alert periods (P < 0.001). The incidence rate ratio was 7.11 (95% CI: 2.19-22.44).

CONCLUSION

Patients received more alerts during periods of AF. The ability of the algorithm to identify increased risk of HF events was confirmed during AF, despite a lower IN/OUT-of-alert incidence rate ratio in comparison with non-AF periods and non-AF patients.

CLINICAL TRIAL REGISTRATION

http://clinicaltrials.gov/Identifier: NCT02275637.

Prognostic value of circulating Epstein-Barr virus DNA level post-induction chemotherapy for patients with nasopharyngeal carcinoma: A recursive partitioning risk stratification analysis

BACKGROUND

To evaluate the prognostic value of plasma Epstein-Barr virus (EBV) DNA level post-induction chemotherapy (IC) for patients with nasopharyngeal carcinoma (NPC).

METHODS

A total of 893 newly diagnosed NPC patients treated with IC were retrospectively reviewed. The recursive partitioning analysis (RPA) was performed to construct a risk stratification model. The receiver operating characteristic (ROC) analysis was applied to determine the optimal cut-off value of post-IC EBV DNA.

RESULTS

Post-IC EBV DNA levels and overall stage were independent predictors for distant metastasis-free survival (DMFS), overall survival (OS), and progression-free survival (PFS). The RPA model base on post-IC EBV DNA and overall stage categorized the patients into three distinct risk groups: RPA I (low-risk: stage II-III and post-IC EBV DNA < 200 copies/mL), RPA II (median-risk: stage II-III and post-IC EBV DNA ≥ 200 copies/mL, or stage IVA and post-IC EBV DNA < 200 copies/mL), and RPA III (high-risk: stage IVA and post-IC EBV DNA ≥ 200 copies/mL), with 3-year PFS of 91.1%, 82.6%, and 60.2%, respectively (p < 0.001). The DMFS and OS rates in different RPA groups were also distinct. The RPA model showed better risk discrimination than either the overall stage or post-RT EBV DNA alone.

CONCLUSIONS

Plasma EBV DNA level post-IC was a robust prognostic biomarker for NPC. We developed an RPA model that provides improved risk discrimination over the 8th edition of the TNM staging system by integrating the post-IC EBV DNA level and the overall stage.

AIMS65, Glasgow-Blatchford bleeding score and modified Glasgow-Blatchford bleeding score in predicting outcomes of upper gastrointestinal bleeding: An accuracy and calibration study

BACKGROUND

Albumin, international normalized ratio (INR), mental status, systolic blood pressure, age >65 years (AIMS65), Glasgow-Blatchford bleeding score (GBS) and modified GBS (mGBS) are three pre-endoscopy scoring systems used in the risk stratification of upper gastrointestinal bleeding (UGIB). The utility of such scoring systems in a population is estimated by their accuracy and calibration in the population. We aimed at validating and comparing the accuracy of the three scoring systems in predicting clinical outcomes including in-hospital mortality, need for blood transfusion, endoscopic treatment and rebleeding risk.

METHOD

We conducted a single-center, retrospective cohort study on patients with UGIB at a tertiary care center in India over 12 months. Clinical and laboratory data was collected from all patients admitted with UGIB. All patients were risk stratified using AIMS65, GBS and mGBS. The clinical outcome examined were: in-hospital mortality, requirement of blood transfusion, need for endoscopic treatment and rebleeding during hospital stay. The area under receiver-operating curve (AUROC) was calculated to assess the performance and calibration curves (Hosmer-Lemeshow goodness of fit curve) were plotted to examine how accurately the model describes the data of all three scoring systems.

RESULTS

Total 260 patients were included in the study, of which 236 (90.8%) were males. As many as 144 (55.4%) patients required blood transfusion and 64 (30.8%) required endoscopic treatment. While the incidence of rebleeding was 7.7%, in hospital mortality was 15.4%. Of 208 who underwent endoscopy, the most common causes identified were varices (49%) and gastritis (18.2%), followed by ulcer (11%), Mallory-Weiss tear (8.1%), portal hypertensive gastropathy (6.7%), malignancy (4.8%) and esophageal candidiasis (1.9%). The median AIMS65 score was 1, GBS 7 and mGBS 6. The area under curve (AUROC) for AIMS65, GBS and mGBS was (0.77, 0.73,0.70), (0.75, 0.82,0.83), (0.56, 0.58,0.83), (0.81, 0.94,0.53) for in-hospital mortality, blood transfusion requirement, endoscopic treatment and rebleeding prediction, respectively.

CONCLUSION

GBS and mGBS are superior to AIMS65 in predicting the requirement of blood transfusion and rebleeding risk, whereas in-hospital mortality was better predicted by AIMS 65. Both scores performed poorly in predicting the need of endoscopic treatment. An AIMS65 of 0,1 and a GBS of ≤ 1 are not associated with significant adverse events. A poor calibration of the scores in our population points to the lack of generalizability of these scoring systems.

Adverse birth outcomes among women with 'low-risk' pregnancies in India: findings from the Fifth National Family Health Survey, 2019-21

Background

Despite substantial progress in improving maternal and newborn health, India continues to experience high rates of newborn mortality and stillbirths. One reason may be that many births happen in health facilities that lack advanced services-such as Caesarean section, blood transfusion, or newborn intensive care. Stratification based on pregnancy risk factors is used to guide 'high-risk' women to advanced facilities. To assess the utility of risk stratification for guiding the choice of facility, we estimated the frequency of adverse newborn outcomes among women classified as 'low risk' in India.

Methods

We used the 2019-21 Fifth National Family Health Survey (NFHS-5)-India's Demographic and Health Survey-which includes modules administered to women aged 15-49 years. In addition to pregnancy history and outcomes, the survey collected a range of risk factors, including biomarkers. We used national obstetric risk guidelines to classify women as 'high risk' versus 'low risk' and assessed the frequency of stillbirths, newborn deaths, and unplanned Caesarean sections for the respondent's last pregnancy lasting 7 or more months in the past five years. We calculated the proportion of deliveries occurring at non-hospital facilities in all the Indian states.

Findings

Using data from nearly 176,699 recent pregnancies, we found that 46.6% of India's newborn deaths and 56.3% of stillbirths were among women who were 'low risk' according to national guidelines. Women classified as 'low risk' had a Caesarean section rate of 8.4% (95% CI 8.1-8.7%), marginally lower than the national average of 10.0% (95% CI 9.8-10.3%). In India as a whole, 32.0% (95% CI 31.5-32.5%) of deliveries occurred in facilities that were likely to lack advanced services. There was substantial variation across the country, with less than 5% non-hospital public facility deliveries in Punjab, Kerala, and Delhi compared to more than 40% in Odisha, Madhya Pradesh, and Rajasthan. Newborn mortality tended to be lower in states with highest hospital delivery rates.

Interpretation

Individual risk stratification based on factors identified in pregnancy fails to accurately predict which women will have delivery complications and experience stillbirth and newborn death in India. Thus a determination of 'low risk' should not be used to guide women to health facilities lacking key life saving services, including Caesarean section, blood transfusion, and advanced newborn resuscitation and care.

Funding

Bill and Melinda Gates Foundation and the World Bank. The findings, interpretations and conclusions expressed in the paper are entirely those of the authors, and do not represent the views of the Gates Foundation or of the World Bank, its Executive Directors, or the countries they represent.

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.