Use of Sequential Hot-Deck Imputation for Missing Health Care Systems Data for Population Health Research

Electronic medical record (EMR) data present many opportunities for population health research. The use of EMR data for population risk models can be impeded by the high proportion of missingness in key patient variables. Common approaches like complete case analysis and multiple imputation may not be appropriate for some population health initiatives that require a single, complete analytic data set. In this study, we demonstrate a sequential hot-deck imputation (HDI) procedure to address missingness in a set of cardiometabolic measures in an EMR data set. We assessed the performance of sequential HDI within the individual variables and a commonly used composite risk score. A data set of cardiometabolic measures based on EMR data from 2 large urban hospitals was used to create a benchmark data set with simulated missingness. Sequential HDI was applied, and the resulting data were used to calculate atherosclerotic cardiovascular disease risk scores. The performance of the imputation approach was assessed using a set of metrics to evaluate the distribution and validity of the imputed data. Of the 567,841 patients, 65% had at least 1 missing cardiometabolic measure. Sequential HDI resulted in the distribution of variables and risk scores that reflected those in the simulated data while retaining correlation. When stratified by age and sex, risk scores were plausible and captured patterns expected in the general population. The use of sequential HDI was shown to be a suitable approach to multivariate missingness in EMR data. Sequential HDI could benefit population health research by providing a straightforward, computationally nonintensive approach to missing EMR data that results in a single analytic data set.

The Utility of Risk Scores in Postcardiotomy Extracorporeal Membrane Oxygenation

BACKGROUND

The use of a venoarterial extracorporeal membrane oxygenation (ECMO) in the postcardiotomy shock setting (PC-ECMO) can be life-saving. Risk stratification for patients under PC-ECMO is currently challenging. The aim of this study was to assess the discriminatory ability of the different available risk scores for mortality in PC-ECMO patients.

METHODS

Patients aged >18 years undergoing coronary artery bypass, valve surgery, or a combination of these procedures and implanted an ECMO for postcardiotomy shock between January 2017 and June 2022 in a single ELSO registered center were retrospectively included. The STS, Euroscore II, SAVE, modified SAVE, APACHE II, and VIS scores were compared for their discriminatory ability concerning weaning and 30-day survival.

RESULTS

During the study period, 7342 patients underwent coronary bypass or valve surgery, of whom 109 patients with PC-ECMO were included in the analysis. The Euroscore II and STS scores were not associated significantly with 30-day mortality, whereas the SAVE, the modified SAVE, APACHE II, and VIS scores significantly predicted 30-day mortality. The SAVE and the modified SAVE scores showed moderate discrimination ability with AUCs of 0.672 and 0.695, while the APACHE and VIS scores had a satisfactory discriminatory ability with AUCs of 0.727 and 0.844, respectively.

CONCLUSION

Currently used risk scores for PC-ECMO patients do not provide satisfactory predictions for weaning and survival. VIS at the 24th hour can be a valuable parameter for risk analysis and prospective studies can investigate novel PC-ECMO risk scoring systems.

Is the Mayo Adhesive Probability Score Predictive in Patients Undergoing Percutaneous Nephrolithotomy?

Introduction: Mayo Adhesive Probability (MAP) score was developed as a means to predict the presence of adherent perinephric fat. Our aim was to determine the predictive value of the MAP score on surgical outcomes in patients undergoing standard adult percutaneous nephrolithotomy (PCNL). Materials and Methods: We retrospectively analyzed the data from 130 renal units that underwent PCNL between January 2022 and 2023. MAP scores 0-2 were classified as low, whereas MAP scores 3-5 were classified as high. The impact of the MAP score on perioperative and postoperative outcomes was studied. All statistical analyses were performed using SPSS 24.0 for Windows. Results: The median age of the patients at the time of surgery was 48 (21) years, with a female-to-male ratio of 1:1.82. The median MAP score was 2 (2), with 43.8% of patients falling into the high MAP score group. Advanced age, hypertension history, low estimated glomerular filtration rate (eGFR) levels, and low renal parenchymal thickness were significantly higher in the high MAP score group (P = .010, P = .004, P = .001, and P = .005, respectively). Female patients had a significantly higher MAP score of 0 (P = .021). Operation time, postoperative hematocrit decrease, blood transfusion rate, postoperative fever rate, hospitalization, and stone-free rates were comparable between the low and high MAP score groups (P = .535, P = .209, P = .313, P = .289, P = .281, and P = .264, respectively). Gender and eGFR levels were shown to be significant predictors of a MAP ≥3 (P = .004 and P = .003, respectively). Conclusion: The present study showed that the MAP score groups had similar perioperative and postoperative results. Low eGFR levels and the male gender were associated with MAP score ≥3. To determine the predictive MAP score value for PCNL outcomes, more prospective studies are needed.

Risk Factors and Innovations in Risk Assessment for Melanoma, Basal Cell Carcinoma, and Squamous Cell Carcinoma

Skin cancer is the most frequently diagnosed cancer globally and is preventable. Various risk factors contribute to different types of skin cancer, including melanoma, basal cell carcinoma, and squamous cell carcinoma. These risk factors encompass both extrinsic, such as UV exposure and behavioral components, and intrinsic factors, especially involving genetic predisposition. However, the specific risk factors vary among the skin cancer types, highlighting the importance of precise knowledge to facilitate appropriate early diagnosis and treatment for at-risk individuals. Better understanding of the individual risk factors has led to the development of risk scores, allowing the identification of individuals at particularly high risk. These advances contribute to improved prevention strategies, emphasizing the commitment to mitigating the impact of skin cancer.

Performance of Different Risk Scores for the Detection of Atrial Fibrillation Among Patients With Cryptogenic Stroke

BACKGROUND

Atrial fibrillation (AF) is a frequent underlying cause of cryptogenic stroke (CS) and its detection can be increased using implantable cardiac monitoring (ICM). We sought to evaluate different risk scores and assess their diagnostic ability in identifying patients with CS with underlying AF on ICM.

METHODS

Patients with CS, being admitted to a single tertiary stroke center between 2017 and 2022 and receiving ICM, were prospectively evaluated. The CHA2DS2-VASc, HAVOC, Brown ESUS-AF, and C2HEST scores were calculated at baseline. The primary outcome of interest was the detection of AF, which was defined as at least 1 AF episode on ICM lasting for 2 consecutive minutes or more. The diagnostic accuracy measures and the net reclassification improvement were calculated for the 4 risk scores. Stroke recurrence was evaluated as a secondary outcome.

RESULTS

A total of 250 patients with CS were included, and AF was detected by ICM in 20.4% (n=51) during a median monitoring period of 16 months. Patients with CS with AF detection were older compared with the rest (P=0.045). The median HAVOC, Brown ESUS-AF, and C2HEST scores were higher among the patients with AF compared with the patients without AF (all P<0.05), while the median CHA2DS2-VASc score was similar between the 2 groups. The corresponding C statistics for CHA2DS2-VASc, HAVOC, Brown ESUS-AF, and C2HEST for AF prediction were 0.576 (95% CI, 0.482-0.670), 0.612 (95% CI, 0.523-0.700), 0.666 (95% CI, 0.587-0.746), and 0.770 (95% CI, 0.699-0.839). The C2HEST score presented the highest diagnostic performance based on C statistics (P<0.05 after correction for multiple comparisons) and provided significant improvement in net reclassification for AF detection (>70%) compared with the other risk scores. Finally, stroke recurrence was documented in 5.6% of the study population, with no difference regarding the 4 risk scores between patients with and without recurrent stroke.

CONCLUSIONS

The C2HEST score was superior to the CHA2DS2-VASc, HAVOC, and Brown ESUS-AF scores for discriminating patients with CS with underlying AF using ICM.

Applicability of the Zwolle score for selection of very high-risk ST-elevation myocardial infarction patients treated with primary angioplasty

The Zwolle risk score was designed to stratify in-hospital mortality risk of ST-elevation myocardial infarction (STEMI) patients treated with primary percutaneous coronary intervention (pPCI) and for decision-making in the unit where patients are admitted. We assessed the accuracy of Zwolle risk score for in-hospital mortality estimation compared with the GRACE score in all patients (n = 4446) admitted for STEMI in 3 university hospitals. Only one fourth of the patients were classified as high-risk by the Zwolle risk score vs 60% by the GRACE score. In-hospital mortality was 10.6%. A statistically significant increase in in-hospital mortality, adjusted by age, gender, and revascularization, was observed with both scores. The assessment of the optimal cut-off points verified the accuracy of Zwolle score ≥4 as optimal threshold for high-risk categorization. In contrast, GRACE score ≥140 had very low specificity as well as percentage of patients correctly classified; GRACE score ≥175 was fairly better. The reclassification index of the Zwolle score after applying the GRACE score was 35.5%. Selection of high-risk STEMI patients treated with pPCI based on the Zwolle risk score has higher specificity than the GRACE score and might be useful in clinical practice.

Corrigendum: Assessment of risk scores to predict mortality of COVID-19 patients admitted to the intensive care unit

[This corrects the article DOI: 10.3389/fmed.2023.1130218.].

Cuproptosis-Related lncRNAs Modulate the Prognosis of MIBC by Regulating the Expression Pattern of Immunosuppressive Molecules Within the Tumor Microenvironment

Background

Cuproptosis-related gene and long non-coding RNA (lncRNA) modulation of cancer regulation is well-established. This investigation aimed to elucidate the prognostic implications of cuproptosis-associated lncRNAs in muscle-invasive bladder cancer (MIBC).

Methods

Employing the Cancer Genome Atlas (TCGA) and IMvigor210 cohorts, bioinformatics and statistical analyses probed the prognostic relevance of cuproptosis-related lncRNAs.

Results

Co-expression analysis revealed tight associations between lncRNA expression and cuproptosis-linked genes, with 13 cuproptosis-related lncRNAs found to correlate with MIBC prognosis. Lasso regression identified a six-lncRNA prognostic signature, enabling patient stratification into high- and low-risk categories. Tissue validation substantiated differential expression of FAM13A-AS1, GHRLOS, LINC00456, OPA1-AS1, RAP2C-AS1, and UBE2Q1-AS1 between MIBC tumor and normal tissues. Comparative analyses of tumor microenvironments and immune profiles between risk groups disclosed elevated immunosuppressive molecule expression, including programmed cell death-1 (PD-L1) and T-cell immunoglobulin-3 (TIM-3), in high-risk individuals.

Conclusion

These findings suggest that cuproptosis-related lncRNAs may modulate the expression of immunosuppressive molecules, thereby influencing MIBC tumorigenesis and progression. Further exploration is warranted to unveil novel therapeutic targets for MIBC based on the expression patterns of cuproptosis-related lncRNAs and their impact on immune responses in the tumor microenvironment.

Correlations between Resting Electrocardiogram Findings and Disease Profiles: Insights from the Qatar Biobank Cohort

BACKGROUND

Resting electrocardiogram (ECG) is a valuable non-invasive diagnostic tool used in clinical medicine to assess the electrical activity of the heart while the patient is resting. Abnormalities in ECG may be associated with clinical biomarkers and can predict early stages of diseases. In this study, we evaluated the association between ECG traits, clinical biomarkers, and diseases and developed risk scores to predict the risk of developing coronary artery disease (CAD) in the Qatar Biobank.

METHODS

This study used 12-lead ECG data from 13,827 participants. The ECG traits used for association analysis were RR, PR, QRS, QTc, PW, and JT. Association analysis using regression models was conducted between ECG variables and serum electrolytes, sugars, lipids, blood pressure (BP), blood and inflammatory biomarkers, and diseases (e.g., type 2 diabetes, CAD, and stroke). ECG-based and clinical risk scores were developed, and their performance was assessed to predict CAD. Classical regression and machine-learning models were used for risk score development.

RESULTS

Significant associations were observed with ECG traits. RR showed the largest number of associations: e.g., positive associations with bicarbonate, chloride, HDL-C, and monocytes, and negative associations with glucose, insulin, neutrophil, calcium, and risk of T2D. QRS was positively associated with phosphorus, bicarbonate, and risk of CAD. Elevated QTc was observed in CAD patients, whereas decreased QTc was correlated with decreased levels of calcium and potassium. Risk scores developed using regression models were outperformed by machine-learning models. The area under the receiver operating curve reached 0.84 using a machine-learning model that contains ECG traits, sugars, lipids, serum electrolytes, and cardiovascular disease risk factors. The odds ratio for the top decile of CAD risk score compared to the remaining deciles was 13.99.

CONCLUSIONS

ECG abnormalities were associated with serum electrolytes, sugars, lipids, and blood and inflammatory biomarkers. These abnormalities were also observed in T2D and CAD patients. Risk scores showed great predictive performance in predicting CAD.

Development and validation of a clinical prediction model for 90-day venous thromboembolism risk following total hip and total knee arthroplasty: a multinational study

BACKGROUND

The risk of venous thromboembolism (VTE) following total hip arthroplasty (THA) and total knee arthroplasty (TKA) is 1.0% to 1.5%, despite uniform thromboprophylaxis.

OBJECTIVES

To develop and validate a prediction model for 90-day VTE risk.

METHODS

A multinational cohort study was performed. For model development, records were used from the Oxford Royal College of General Practitioners Research and Surveillance Centre linked to Hospital Episode Statistics and Office of National Statistics UK routine data. For external validation, data were used from the Danish Hip and Knee Arthroplasty Registry, the National Patient Registry, and the National Prescription Registry. Binary multivariable logistic regression techniques were used for development.

RESULTS

In the UK data set, 64 032 THA/TKA procedures were performed and 1.4% developed VTE. The prediction model consisted of age, body mass index, sex, cystitis within 1 year before surgery, history of phlebitis, history of VTE, presence of varicose veins, presence of asthma, history of transient ischemic attack, history of myocardial infarction, presence of hypertension and THA or TKA. The area under the curve of the model was 0.65 (95% CI, 0.63-0.67). Furthermore, 36 169 procedures were performed in the Danish cohort, of whom 1.0% developed VTE. Here, the area under the curve was 0.64 (95% CI, 0.61-0.67). The calibration slope was 0.92 in the validation study and 1.00 in the development study.

CONCLUSION

This clinical prediction model for 90-day VTE risk following THA and TKA performed well in both development and validation data. This model can be used to estimate an individual's risk for VTE following THA/TKA.

Risk factors for venous ulceration in patients with varicose veins of lower extremities

The aim of this case-control study was to explore the potential risk factors for venous ulceration in patients with varicose veins of lower extremities and to establish a simplified diagnostic score model. Seventy subjects with varicose veins of lower extremities and venous ulceration were compared with 1164 controls with varicose veins of lower extremities and no history of venous ulceration. Stepwise multivariate logistic regression analysis was used to identify the risk factors for venous ulceration. The steps in developing the diagnostic score model were based on the Framingham Heart study. The area under the receiver operating characteristic curve (AUC) was calculated to assess the diagnostic ability of the diagnostic score model. Multivariate analysis showed that men, overweight, obesity, longer duration varicose veins, deep venous valve insufficiency, low lymphocyte counts, and high fibrinogen content were independently associated with an increased risk of venous ulceration. The AUC for the diagnostic score model was 0.75, which indicated good discriminatory ability. Special attention should be paid to the high-risk group of patients with lower extremity varicose veins. The diagnostic score model might be a useful screening tool for clinicians, policy makers, and patients.

Differences between SCORE, Framingham Risk Score, and Estimated Pulse Wave Velocity-Based Vascular Age Calculation Methods Based on Data from the Three Generations Health Program in Hungary

Early vascular ageing contributes to cardiovascular (CV) morbidity and mortality. There are different possibilities to calculate vascular age including methods based on CV risk scores, but different methods might identify different subjects with early vascular ageing. We aimed to compare SCORE and Framingham Risk Score (FRS)-based vascular age calculation methods on subjects that were involved in a national screening program in Hungary. We also aimed to compare the distribution of subjects identified with early vascular ageing based on estimated pulse wave velocity (ePWV). The Three Generations for Health program focuses on the development of primary health care in Hungary. One of the key elements of the program is the identification of risk factors of CV diseases. Vascular ages based on the SCORE and FRS were calculated based on previous publications and were compared with chronological age and with each other in the total population and in patients with hypertension or diabetes. ePWV was calculated based on a method published previously. Supernormal, normal, and early vascular ageing were defined as <10%, 10-90%, and >90% ePWV values for the participants. In total, 99,231 subjects were involved in the study, and among them, 49,191 patients had hypertension (HT) and 15,921 patients had diabetes (DM). The chronological age of the total population was 54.0 (48.0-60.0) years, while the SCORE and FRS vascular ages were 59.0 (51.0-66.0) and 64.0 (51-80) years, respectively. In the HT patients, the chronological, SCORE, and FRS vascular ages were 57.0 (51.0-62.0), 63.0 (56.0-68.0), and 79.0 (64.0-80.0) years, respectively. In the DM patients, the chronological, SCORE, and FRS vascular ages were 58.0 (52.0-62.0), 63.0 (56.0-68.0), and 80.0 (76.0-80.0) years, respectively. Based on ePWV, the FRS identified patients with an elevated vascular age with high sensitivity (97.3%), while in the case of the SCORE, the sensitivity was much lower (13.3%). In conclusion, different vascular age calculation methods can provide different vascular age results in a population-based cohort. The importance of this finding for the implementation in CV preventive strategies requires further studies.

New Score for Predicting Results after Catheter Ablation for Atrial Fibrillation: VAT-DHF

INTRODUCTION

Catheter ablation (CA) for atrial fibrillation (AF) has been proven to have the highest efficacy in maintaining sinus rhythm. Several studies have proposed different scores for predicting post-procedural success, but most have not been validated in prospective cohorts. Further research is required to determine the optimal formulae.

PURPOSE

This study aimed to identify independent predictors of AF recurrence after CA and develop a composite score.

METHODS

Consecutive patients with persistent and paroxysmal AF who underwent CA were retrospectively analyzed. The independent predictors of recurrence were used to create a new predictive score.

RESULTS

The cohort included 263 patients with a follow-up of 37.6 ± 23.4 months. Persistent AF, f-waves < 0.1 mV, indexed left atrium volume, the presence of type 2 diabetes, and smaller height were independent predictors of recurrence and were used to create a new scoring model, VAT-DHF (V = Volume, AT = AF Type, D = Diabetes, H = Height, F = f waves). The ROC curve for this new score showed an AUC of 0.869, p < 0.0001, 95% CI [0.802-0.936], while those for APPLE and CHA2DS2-VASc showed an AUC of 0.765, 95% CI [0.637-0.893] and an AUC of 0.655, 95% CI [0.580-0.730], respectively. Patients who had a VAT-DHF score between 0 and 3.25, 3.25 and 6, and ≥6, had success rates of 95.7%, 76.3%, and 25% (p < 0.0001), respectively.

CONCLUSIONS

The novel VAT-DHF score is easy to calculate and may be a useful clinical tool for identifying patients with a low, intermediate, or high risk of AF recurrence after CA.

Machine Learning for Predicting Postoperative Atrial Fibrillation After Cardiac Surgery: A Scoping Review of Current Literature

Postoperative atrial fibrillation (POAF) occurs in up to 20% to 55% of patients who underwent cardiac surgery. Machine learning (ML) has been increasingly employed in monitoring, screening, and identifying different cardiovascular clinical conditions. It was proposed that ML may be a useful tool for predicting POAF after cardiac surgery. An electronic database search was conducted on Medline, EMBASE, Cochrane, Google Scholar, and ClinicalTrials.gov to identify primary studies that investigated the role of ML in predicting POAF after cardiac surgery. A total of 5,955 citations were subjected to title and abstract screening, and ultimately 5 studies were included. The reported incidence of POAF ranged from 21.5% to 37.1%. The studied ML models included: deep learning, decision trees, logistic regression, support vector machines, gradient boosting decision tree, gradient-boosted machine, K-nearest neighbors, neural network, and random forest models. The sensitivity of the reported ML models ranged from 0.22 to 0.91, the specificity from 0.64 to 0.84, and the area under the receiver operating characteristic curve from 0.67 to 0.94. Age, gender, left atrial diameter, glomerular filtration rate, and duration of mechanical ventilation were significant clinical risk factors for POAF. Limited evidence suggest that machine learning models may play a role in predicting atrial fibrillation after cardiac surgery because of their ability to detect different patterns of correlations and the incorporation of several demographic and clinical variables. However, the heterogeneity of the included studies and the lack of external validation are the most important limitations against the routine incorporation of these models in routine practice. Artificial intelligence, cardiac surgery, decision tree, deep learning, gradient-boosted machine, gradient boosting decision tree, k-nearest neighbors, logistic regression, machine learning, neural network, postoperative atrial fibrillation, postoperative complications, random forest, risk scores, scoping review, support vector machine.

Predictors of All-Cause Mortality After Successful Transcatheter Aortic Valve Implantation in Patients With Atrial Fibrillation

Prevalent and incident atrial fibrillation are common in patients who undergo transcatheter aortic valve implantation and are associated with impaired postprocedural outcomes, including mortality. We determined predictors of long-term mortality in patients with atrial fibrillation after successful transcatheter aortic valve implantation. The EdoxabaN Versus standard of care and theIr effectS on clinical outcomes in pAtients havinG undergonE Transcatheter Aortic Valve Implantation-Atrial Fibrillation (ENVISAGE-TAVI AF) trial (NCT02943785) was a multicenter, prospective, randomized controlled trial in patients with prevalent or incident atrial fibrillation after successful transcatheter aortic valve implantation who received edoxaban or vitamin K antagonists. A Cox proportional hazard model was performed to identify predictors of all-cause mortality using a stepwise approach for multiple regression analysis. In addition, we assessed the performance of different risk scores and prediction models using ENVISAGE-TAVI AF data. Of 1,426 patients in ENVISAGE-TAVI AF, 178 (12.5%) died during the follow-up period (median 548 days). Our stepwise approach identified greater risk of mortality with older age, impaired renal function, nonparoxysmal atrial fibrillation, excessive alcohol use, New York Heart Association heart failure class III/IV, peripheral artery disease, and history of major bleeding or predisposition to bleeding. The present model (concordance statistic [c-statistic] 0.67) was a better discriminator than were other frequently used risk scores, such as the Society of Thoracic Surgeons score (c-statistic 0.56); Congestive heart failure, Hypertension, Age ≥75, Diabetes, Stroke, Vascular disease, Age 65 to 74 years, and Sex category (CHA2DS2-VASc) score (c-statistic 0.54); or Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized ratio, Elderly, and Drugs/alcohol concomitantly (HAS-BLED) score (c-statistic 0.58). In ENVISAGE-TAVI AF, several modifiable and nonmodifiable clinical characteristics were significantly associated with greater long-term all-cause mortality. Improved risk stratification to estimate the probability of mortality after successful transcatheter aortic valve implantation in patients with atrial fibrillation may improve long-term patient prognosis.

Prediction of adult asthma risk in early childhood using novel adult asthma predictive risk scores

BACKGROUND

Numerous risk scores have been developed to predict childhood asthma. However, they may not predict asthma beyond childhood. We aim to create childhood risk scores that predict development and persistence of asthma up to young adult life.

METHODS

The Isle of Wight Birth Cohort (n = 1456) was prospectively assessed up to 26 years of age. Asthma predictive scores were developed based on factors during the first 4 years, using logistic regression and tested for sensitivity, specificity and area under the curve (AUC) for prediction of asthma at (i) 18 and (ii) 26 years, and persistent asthma (PA) (iii) at 10 and 18 years, and (iv) at 10, 18 and 26 years. Models were internally and externally validated.

RESULTS

Four models were generated for prediction of each asthma outcome. ASthma PredIctive Risk scorE (ASPIRE)-1: a 2-factor model (recurrent wheeze [RW] and positive skin prick test [+SPT] at 4 years) for asthma at 18 years (sensitivity: 0.49, specificity: 0.80, AUC: 0.65). ASPIRE-2: a 3-factor model (RW, +SPT and maternal rhinitis) for asthma at 26 years (sensitivity: 0.60, specificity: 0.79, AUC: 0.73). ASPIRE-3: a 3-factor model (RW, +SPT and eczema at 4 years) for PA-18 (sensitivity: 0.63, specificity: 0.87, AUC: 0.77). ASPIRE-4: a 3-factor model (RW, +SPT at 4 years and recurrent chest infection at 2 years) for PA-26 (sensitivity: 0.68, specificity: 0.87, AUC: 0.80). ASPIRE-1 and ASPIRE-3 scores were replicated externally. Further assessments indicated that ASPIRE-1 can be used in place of ASPIRE-2-4 with same predictive accuracy.

CONCLUSION

ASPIRE predicts persistent asthma up to young adult life.

MIRACLE2 Score Compared With Downtime and Current Selection Criterion for Invasive Cardiovascular Therapies After OHCA

BACKGROUND

The MIRACLE2 score is the only risk score that does not incorporate and can be used for selection of therapies after out-of-hospital cardiac arrest (OHCA).

OBJECTIVES

This study sought to compare the discrimination performance of the MIRACLE2 score, downtime, and current randomized controlled trial (RCT) recruitment criteria in predicting poor neurologic outcome after out-of-hospital cardiac arrest (OHCA).

METHODS

We used the EUCAR (European Cardiac Arrest Registry), a retrospective cohort from 6 centers (May 2012-September 2022). The primary outcome was poor neurologic outcome on hospital discharge (cerebral performance category 3-5).

RESULTS

A total of 1,259 patients (total downtime = 25 minutes; IQR: 15-36 minutes) were included in the study. Poor outcome occurred in 41.8% with downtime <30 minutes and in 79.3% for those with downtime >30 minutes. In a multivariable logistic regression analysis, MIRACLE2 had a stronger association with outcome (OR: 2.23; 95% CI: 1.98-2.51; P < 0.0001) than zero flow (OR: 1.07; 95% CI: 1.01-1.13; P = 0.013), low flow (OR: 1.04; 95% CI: 0.99-1.09; P = 0.054), and total downtime (OR: 0.99; 95% CI: 0.95-1.03; P = 0.52). MIRACLE2 had substantially superior discrimination for the primary endpoint (AUC: 0.877; 95% CI: 0.854-0.897) than zero flow (AUC: 0.610; 95% CI: 0.577-0.642), low flow (AUC: 0.725; 95% CI: 0.695-0.754), and total downtime (AUC: 0.732; 95% CI: 0.701-0.760). For those modeled for exclusion from study recruitment, the positive predictive value of MIRACLE2 ≥5 for poor outcome was significantly higher (0.92) than the CULPRIT-SHOCK (Culprit lesion only PCI Versus Multivessel PCI in Cardiogenic Shock) (0.80), EUROSHOCK (Testing the value of Novel Strategy and Its Cost Efficacy In Order to Improve the Poor Outcomes in Cardiogenic Shock) (0.74) and ECLS-SHOCK (Extra-corporeal life support in Cardiogenic shock) criteria (0.81) (P < 0.001).

CONCLUSIONS

The MIRACLE2 score has superior prediction of outcome after OHCA than downtime and higher discrimination of poor outcome than the current RCT recruitment criteria. The potential for the MIRACLE2 score to improve the selection of OHCA patients should be evaluated formally in future RCTs.

Gender Differences and Amputation Risk in Peripheral Artery Disease-A Single-Center Experience

Background and Objectives: Peripheral artery disease (PAD) affects both genders, but the knowledge of clinical and therapeutic aspects particular to each gender has a prognostic value, modulating the risk of amputation and helping to reduce the risk of death or the occurrence of an acute vascular event secondary to optimal management. Materials and Methods: We conducted a retrospective, descriptive study that included 652 patients with PAD who were evaluated at "St. Spiridon" Hospital's Cardiology Department and divided into two groups according to gender: women (100 cases) and men (552 cases). We evaluated demographics, anthropometric data, as well as clinical and paraclinical parameters in the two groups. Results: Men had a lower mean age (p < 0.001), higher mean BMI (p = 0.049) and were more frequent smokers. (p = 0.008). Hypercholesterolemia (p = 0.026), obesity (p = 0.009), concomitant cerebrovascular (p = 0.005) and chronic kidney disease (p = 0.046) were more common in women, while coronary artery disease (p = 0.033) was more common in men. The number of angiographic stenotic lesions (p = 0.037) is a statistically significant parameter in our study, with both genders predominantly associated with stenotic lesions. In addition, directly proportional relationships were found between smoking, uric acid, inflammatory markers, and the number of stenotic lesions and thromboses or the ankle-brachial index (ABI). In the subgroup of men, the number of stenotic and thrombosed lesions positively correlated with the ABI value (p < 0.001). The presence of more than three cardiovascular risk factors (p = 0.001) and serum triglyceride levels (p = 0.019) significantly correlated with the number of angiographically detected lesions. We applied several risk scores (PREVENT III, Finnvasc Score, or GermanVasc risk score) in our study group for prognostic purposes, without showing statistically significant differences between genders. Men, rest pain, gangrene, smoking status, the presence of more than three cardiovascular risk factors, or a serum HDL-cholesterol level below 40 mg/dL (p < 0.001 for all parameters) are independent predictors associated with amputation in our study group. Conclusions: In our study, we demonstrated that several clinical-paraclinical particularities guide the diagnosis, providing the clinician with prognostic and therapeutic tools to choose the optimal management with maximum benefits.

Comparison of different risk scores for Parkinson disease in a population-based 10-year study

BACKGROUND AND PURPOSE

Different algorithms aiming to identify individuals at risk of Parkinson disease (PD) have been proposed. Comparative studies of these scores and their recent updates in the general elder population are needed.

METHODS

We have previously applied the "basic" PREDICT-PD algorithm, designed for remote screening, and the original and updated Movement Disorder Society (MDS) criteria for prodromal PD to the longitudinal population-based Bruneck study cohort. We have now additionally employed the "enhanced" PREDICT-PD algorithm (which includes motor assessment, olfaction, probable rapid eye movement sleep behaviour disorder status, pesticide exposure, and diabetes as additional factors). Risk scores were calculated based on comprehensive baseline assessments (2005) in 574 subjects aged 55-94 years (290 females), and cases of incident PD were identified at 5-year (n = 11) and 10-year follow-up (n = 9). We analysed the association of the different log-transformed risk scores with incident PD at follow-up (calculated per 1-SD unit change).

RESULTS

The enhanced PREDICT-PD algorithm was associated with incident PD over 10-years of follow-up, yielding higher odds for incident PD (odds ratio [OR] = 4.61, 95% confidence interval [CI] = 2.68-7.93, p < 0.001) compared with the basic PREDICT-PD score (OR = 2.38, 95% CI = 1.49-3.79, p < 0.001). The updated MDS prodromal criteria yielded a numerically higher OR of 7.13 (95% CI = 3.49-14.54, p < 0.001) in comparison with the original criteria as well as the enhanced PREDICT-PD algorithm, with overlapping 95% CIs.

CONCLUSIONS

The enhanced PREDICT-PD algorithm was significantly associated with incident PD. The consistent performance of both the enhanced PREDICT-PD algorithm and the updated MDS prodromal criteria compared to their original versions supports their use in PD risk screening.

A Developmental Surveillance Score for Quantitative Monitoring of Early Childhood Milestone Attainment: Algorithm Development and Validation

BACKGROUND

Developmental surveillance, conducted routinely worldwide, is fundamental for timely identification of children at risk of developmental delays. It is typically executed by assessing age-appropriate milestone attainment and applying clinical judgment during health supervision visits. Unlike developmental screening and evaluation tools, surveillance typically lacks standardized quantitative measures, and consequently, its interpretation is often qualitative and subjective.

OBJECTIVE

Herein, we suggested a novel method for aggregating developmental surveillance assessments into a single score that coherently depicts and monitors child development. We described the procedure for calculating the score and demonstrated its ability to effectively capture known population-level associations. Additionally, we showed that the score can be used to describe longitudinal patterns of development that may facilitate tracking and classifying developmental trajectories of children.

METHODS

We described the Developmental Surveillance Score (DSS), a simple-to-use tool that quantifies the age-dependent severity level of a failure at attaining developmental milestones based on the recently introduced Israeli developmental surveillance program. We evaluated the DSS using a nationwide cohort of >1 million Israeli children from birth to 36 months of age, assessed between July 1, 2014, and September 1, 2021. We measured the score's ability to capture known associations between developmental delays and characteristics of the mother and child. Additionally, we computed series of the DSS in consecutive visits to describe a child's longitudinal development and applied cluster analysis to identify distinct patterns of these developmental trajectories.

RESULTS

The analyzed cohort included 1,130,005 children. The evaluation of the DSS on subpopulations of the cohort, stratified by known risk factors of developmental delays, revealed expected relations between developmental delay and characteristics of the child and mother, including demographics and obstetrics-related variables. On average, the score was worse for preterm children compared to full-term children and for male children compared to female children, and it was correspondingly worse for lower levels of maternal education. The trajectories of scores in 6 consecutive visits were available for 294,000 children. The clustering of these trajectories revealed 3 main types of developmental patterns that are consistent with clinical experience: children who successfully attain milestones, children who initially tend to fail but improve over time, and children whose failures tend to increase over time.

CONCLUSIONS

The suggested score is straightforward to compute in its basic form and can be easily implemented as a web-based tool in its more elaborate form. It highlights known and novel relations between developmental delay and characteristics of the mother and child, demonstrating its potential usefulness for surveillance and research. Additionally, it can monitor the developmental trajectory of a child and characterize it. Future work is needed to calibrate the score vis-a-vis other screening tools, validate it worldwide, and integrate it into the clinical workflow of developmental surveillance.

The prediction of Alzheimer's disease through multi-trait genetic modeling

To better capture the polygenic architecture of Alzheimer's disease (AD), we developed a joint genetic score, MetaGRS. We incorporated genetic variants for AD and 24 other traits from two independent cohorts, NACC (n = 3,174, training set) and UPitt (n = 2,053, validation set). One standard deviation increase in the MetaGRS is associated with about 57% increase in the AD risk [hazard ratio (HR) = 1.577, p = 7.17 E-56], showing little difference from the HR for AD GRS alone (HR = 1.579, p = 1.20E-56), suggesting similar utility of both models. We also conducted APOE-stratified analyses to assess the role of the e4 allele on risk prediction. Similar to that of the combined model, our stratified results did not show a considerable improvement of the MetaGRS. Our study showed that the prediction power of the MetaGRS significantly outperformed that of the reference model without any genetic information, but was effectively equivalent to the prediction power of the AD GRS.

Surgical Mortality Risk Scores in Transcatheter Aortic Valve Implantation: Is Their Early Predictive Value Still Strong?

BACKGROUND

Surgical mortality risk scores, even if not properly designed and rarely tested in the transcatheter aortic valve implantation (TAVI) setting, still guide the heart team in managing significant aortic stenosis.

METHODS

After splitting 1763 consecutive patients retrospectively based on their mortality risk thresholds, the composite endpoint early safety (ES) was adjudicated according to Valve Academic Research Consortium (VARC)-2 and -3 consensus documents.

RESULTS

ES incidence was higher if VARC-2 rather than VARC-3 defined. Despite only patients showing VARC-2 ES had significantly lower absolute values of all three main risk scores, these last still failed to foresee both VARC-2 and -3 ES in intermediate-risk patients. The receiver operating characteristic analysis also showed a significant correlation, but with poor diagnostic accuracy, among the three scores and only VARC-2 ES; moreover, the absence of VARC-2 ES and low-osmolar contrast media administration were identified as independent predictors of 1-year mortality and absence of VARC-3 ES, respectively. Finally, even a single complication included in the ES definition could significantly affect 1-year mortality.

CONCLUSION

Currently, the most used mortality risk scores do not have adequate diagnostic accuracy in predicting ES after TAVI. The absence of VARC-2, instead of VARC-3, ES is an independent predictor of 1-year mortality.

A Review of Risk Scores within Upper Gastrointestinal Bleeding

Upper gastrointestinal bleeding is a common medical emergency. Thorough initial assessment and appropriate resuscitation are essential to stabilise the patient. Risk scores provide an important tool to discriminate between lower- and higher-risk patients. Very low-risk patients can be safely discharged for out-patient management, while higher-risk patients can receive appropriate in-patient care. The Glasgow Blatchford Score, with a score of 0-1, performs best in the identification of very low-risk patients who will not require hospital based intervention or die, and is recommended by most guidelines to facilitate safe out-patient management. The performance of risk scores in the identification of specific adverse events to define high-risk patients is less accurate, with no individual score performing consistently well. Ongoing developments in the use of machine learning models and artificial intelligence in predicting poor outcomes in UGIB appear promising and will likely form the basis of dynamic risk assessment in the future.

TRI-SCORE: a single-Centre validation study

BACKGROUND AND AIMS

The TRI-SCORE is a recently published risk score for predicting in-hospital mortality in patients undergoing isolated tricuspid valve surgery (ITVS). The aim of this study is to externally validate the ability of the TRI-SCORE in predicting in-hospital and long-term mortality following ITVS.

METHODS

A retrospective review of our institutional database was carried out to identify all patients undergoing isolated tricuspid valve repair or replacement from March 1997 to March 2021. The TRI-SCORE was calculated for all patients. Discrimination of the TRI-SCORE was assessed using receiver operating characteristic curves. Accuracy of the models was tested calculating the Brier score. Finally, a COX regression was employed to evaluate the relationship between the TRI-SCORE value and long-term mortality.

RESULTS

A total of 176 patients were identified and the median TRI-SCORE was 3 (1-5). The cut-off value identified for increased risk of isolated ITVS was 5. Regarding in-hospital outcomes, the TRI-SCORE showed high discrimination (area under the curve 0.82), and high accuracy (Brier score 0.054). This score showed also very good performance in predicting long-term mortality (at 10 years HR: 1.47, 95% CI [1.31-1.66], p < 0.001), with high discrimination (area under the curve >0.80 at 1-5 and 10 years) and high accuracy values (Brier score 0.179).

CONCLUSIONS

This external validation confirm the good performance of the TRI-SCORE in predicting in-hospital mortality. Moreover, the score showed also very good performance in predicting the long-term mortality.

Effect of Canagliflozin on Heart Failure Hospitalization in Diabetes According to Baseline Heart Failure Risk

BACKGROUND

In the CANVAS (Canagliflozin Cardiovascular Assessment Study) program, canagliflozin reduced the risk of heart failure (HF) hospitalization among individuals with type 2 diabetes mellitus (T2DM).

OBJECTIVES

The purpose of this study was to evaluate heterogeneity in absolute and relative treatment effects of canagliflozin on HF hospitalization according to baseline HF risk as assessed by diabetes-specific HF risk scores (WATCH-DM [Weight (body mass index), Age, hyperTension, Creatinine, HDL-C, Diabetes control (fasting plasma glucose) and QRS Duration, MI and CABG] and TRS-HF_DM [TIMI Risk Score for HF in Diabetes]).

METHODS

Participants in the CANVAS trial were categorized into low, medium, and high risk for HF using the WATCH-DM score (for participants without prevalent HF) and the TRS-HF_DM score (for all participants). The outcome of interest was time to first HF hospitalization. The treatment effect of canagliflozin vs placebo for HF hospitalization was compared across risk strata.

RESULTS

Among 10,137 participants with available HF data, 1,446 (14.3%) had HF at baseline. Among participants without baseline HF, WATCH-DM risk category did not modify the treatment effect of canagliflozin (vs placebo) on HF hospitalization (P interaction = 0.56). However, the absolute and relative risk reduction with canagliflozin was numerically greater in the high-risk group (cumulative incidence, canagliflozin vs placebo: 8.1% vs 12.7%; HR: 0.62 [95% CI: 0.37-0.93]; P = 0.03; number needed to treat: 22) than in the low- and intermediate-risk groups. When overall study participants were categorized according to the TRS-HF_DM score, a statistically significant difference in the treatment effect of canagliflozin across risk strata was observed (P interaction = 0.04). Canagliflozin significantly reduced the risk of HF hospitalization by 39% in the high-risk group (HR: 0.61 [95% CI: 0.48-0.78]; P < 0.001; number needed to treat: 20) but not in the intermediate- or low-risk groups.

CONCLUSIONS

Among participants with T2DM, the WATCH-DM and TRS-HF_DM can reliably identify those at high risk for HF hospitalization and most likely to benefit from canagliflozin.

A polygenic risk score to help discriminate primary adrenal insufficiency of different etiologies

BACKGROUND

Autoimmune Addison's disease (AAD) is the most common cause of primary adrenal insufficiency (PAI). Despite its exceptionally high heritability, tools to estimate disease susceptibility in individual patients are lacking. We hypothesized that a polygenic risk score (PRS) for AAD could help investigate PAI pathogenesis in pediatric patients.

METHODS

We here constructed and evaluated a PRS for AAD in 1223 seropositive cases and 4097 controls. To test its clinical utility, we reevaluated 18 pediatric patients, whose whole genome we also sequenced. We next explored the individual PRS in more than 120 seronegative patients with idiopathic PAI.

RESULTS

The genetic susceptibility to AAD-quantified using PRS-was on average 1.5 standard deviations (SD) higher in patients compared with healthy controls (p < 2e-16), and 1.2 SD higher in the young patients compared with the old (p = 3e-4). Using the novel PRS, we searched for pediatric patients with strikingly low AAD susceptibility and identified cases of monogenic PAI, previously misdiagnosed as AAD. By stratifying seronegative adult patients by autoimmune comorbidities and disease duration we could delineate subgroups of PRS suggesting various disease etiologies.

CONCLUSIONS

The PRS performed well for case-control differentiation and susceptibility estimation in individual patients. Remarkably, a PRS for AAD holds promise as a means to detect disease etiologies other than autoimmunity. This article is protected by copyright. All rights reserved.

Validation of the prognostic scoring system for inhospital mortality prediction in cardiogenic shock patients requiring venoarterial extracorporeal membrane oxygenation

BACKGROUND

A few prognostic scoring systems have been developed for predicting mortality in patients with cardiogenic shock requiring veno-arterial extracorporeal membrane oxygenation (VA-ECMO), albeit with variations in performance. This study aimed to assess and compare various mortality prediction models in a cohort of patients receiving VA-ECMO following cardiogenic shock or arrest.

METHODS

We retrospectively analyzed 77 patients with cardiogenic shock who were placed on VA-ECMO support between March 2014 and August 2021. The APACHE II, SAPS II, SAVE, Modified SAVE, ENCOURAGE, and ECMO-ACCEPTS scores were calculated for each patient to predict the in-hospital mortality.

RESULTS

Fifty-six (72.7%) patients died. All prediction model scores, except the ECMO-ACCEPTS, differed significantly between non-survivors and survivors as follows: ENCOURAGE, 23 versus 16 (p < 0.001); SAVE, -6 versus -3 (p = 0.008); Modified SAVE, -5 versus 0 (p = 0.005); APACHE II, 32 versus 22 (p = 0.009); and SAPS II, 67 versus 49 (p = 0.002). The ENCOURAGE score demonstrated the best discriminatory ability with an area under the receiver-operating characteristic curve of 0.81 (95% confidence interval: 0.7-0.81). All prognostic scoring systems possessed limited calibration ability. However, the SAPS II, SAVE, and ENCOURAGE scores had lower Akaike and Bayesian information criteria values, which were consistent with the results of the Hosmer-Lemeshow C statistic test, indicating better performance than the other scores.

CONCLUSIONS

The ENCOURAGE score can help predict in-hospital mortality in all subsets of VA-ECMO patients, even though it was originally designed to predict intensive care unit mortality in the post-acute myocardial infarction setting.

Prevalence of Traditional Risk Factors in First-Degree Relatives of Patients With Established Cardiovascular Disease

INTRODUCTION

World Health Organization (WHO)/International Society of Hypertension (ISH) risk prediction charts are useful for predicting 10-year combined myocardial infarction and stroke risk (fatal and non-fatal). Hence the current study was conducted to assess the 10-year risk of cardiovascular disease among adults in Ahmedabad, India.

AIMS

The primary aim of the study was to assess the cardiovascular risk among first-degree relatives of patients attending the outpatient clinic. Also, to create awareness regarding assessment of cardiovascular risk among the studied group.

METHODS AND MATERIALS

A cross-sectional study was carried out among 372 first-degree relatives of patients at an out-patient cardiology clinic present in Vadaj, Ahmedabad. The WHO/ISH risk prediction chart for South-East Asia Region D (SEAR D) was used for calculating the 10-year cardiovascular risk.

RESULTS

A maximum (80.10%) of the study participants were in the low-risk (<10%) category followed by 8.33% for moderate-risk (10-20%), 7.25% for moderately high-risk (20-30%), 2.42% for high-risk (30-40%) and 1.88% for very high-risk (>40%).

CONCLUSION

WHO/ISH risk prediction charts provide a quick and effective way to assess and categorize the population in a low-resource setting which in turn helps in delivering focused intervention to the high-risk groups.

Assessment of risk scores to predict mortality of COVID-19 patients admitted to the intensive care unit

Objectives

To assess the ABC2-SPH score in predicting COVID-19 in-hospital mortality, during intensive care unit (ICU) admission, and to compare its performance with other scores (SOFA, SAPS-3, NEWS2, 4C Mortality Score, SOARS, CURB-65, modified CHA2DS2-VASc, and a novel severity score).

Materials and methods

Consecutive patients (≥ 18 years) with laboratory-confirmed COVID-19 admitted to ICUs of 25 hospitals, located in 17 Brazilian cities, from October 2020 to March 2022, were included. Overall performance of the scores was evaluated using the Brier score. ABC2-SPH was used as the reference score, and comparisons between ABC2-SPH and the other scores were performed by using the Bonferroni method of correction. The primary outcome was in-hospital mortality.

Results

ABC2-SPH had an area under the curve of 0.716 (95% CI 0.693-0.738), significantly higher than CURB-65, SOFA, NEWS2, SOARS, and modified CHA2DS2-VASc scores. There was no statistically significant difference between ABC2-SPH and SAPS-3, 4C Mortality Score, and the novel severity score.

Conclusion

ABC2-SPH was superior to other risk scores, but it still did not demonstrate an excellent predictive ability for mortality in critically ill COVID-19 patients. Our results indicate the need to develop a new score, for this subset of patients.

Adaptation of adult right ventricular scoring systems to pediatric patients undergoing continuous LVAD implantation: Feasible or not?

PURPOSE

The aim of this study is to investigate the efficacy of adaptation of right ventricular (RV) risk scores used in adult patients to pediatric age group undergoing LVAD implantation.

METHODS

Twenty-two pediatric patients who underwent LVAD implantation were retrospectively reviewed from January 2014 to September 2018. Preoperative patient characteristics, hemodynamic parameters, and echocardiographic data were collected. Adult RV risk scores were calculated for all patients. Effects of all the parameters on RV function were also investigated. Study endpoints were RVF and in-hospital mortality.

RESULTS

Eleven (50%) of 22 patients were male. The mean age of the patients was 13.4 ± 3.8 years. The mean body surface area of the patients was 1.4 ± 0.4 m². In five patients BiVAD implantation was performed. Of these five BiVAD patients two underwent successful heart transplant; two weaned from temporary RVAD and last patient died due to multi-organ failure. Four patients showed signs of early RVF; one patient was transplanted successfully while on medical support. Three patients developing RVF did not respond medical therapy necessitating ECMO and died in the early postoperative period. All risk scores and potential predictive factors were evaluated individually and in combination of several parameters. No significant predictor for RVF in pediatric patients that underwent LVAD implantation was found (p > 0.05).

CONCLUSION

Neither an adult risk score nor a predictive factor was successful in predicting RVF, alone or in combination due to limited number of patients and events. Large further investigations are needed to identify the predictors or scoring system in pediatric population.

Early Recognition and Risk Stratification in Cardiogenic Shock: Well Begun Is Half Done

Cardiogenic shock is a complex syndrome manifesting with distinct phenotypes depending on the severity of the primary cardiac insult and the underlying status. As long as therapeutic interventions fail to divert its unopposed rapid evolution, poor outcomes will continue challenging health care systems. Thus, early recognition in the emergency setting is a priority, in order to avoid delays in appropriate management and to ensure immediate initial stabilization. Since advanced therapeutic strategies and specialized shock centers may provide beneficial support, it seems that directing patients towards the recently described shock network may improve survival rates. A multidisciplinary approach strategy commands the interconnections between the strategic role of the ED in affiliation with cardiac shock centers. This review outlines critical features of early recognition and initial therapeutic management, as well as the utility of diagnostic tools and risk stratification models regarding the facilitation of patient trajectories through the shock network. Further, it proposes the implementation of precise criteria for shock team activation and the establishment of definite exclusion criteria for streaming the right patient to the right place at the right time.

Patient-rated satisfaction and improvement following hip and knee replacements: Development of prediction models

RATIONALE

Effective preoperative assessments of determinants of health status and function may improve postoperative outcomes.

AIMS AND OBJECTIVES

We developed risk scores of preoperative patient factors and patient-reported outcome measures (PROMs) as predictors of patient-rated satisfaction and improvement following hip and knee replacements.

PATIENTS AND METHODS

Prospectively collected National Health Service and independent sector patient data (n = 30,457), including patients' self-reported demographics, comorbidities, PROMs (Oxford Hip/Knee score (OHS/OKS) and European Quality of Life (EQ5D index and health-scale), were analysed. Outcomes were defined as patient-reported satisfaction and improvement following surgery at 7-month follow-up. Univariable and multivariable-adjusted logistic regressions were undertaken to build prediction models; model discrimination was evaluated with the concordance index (c-index) and nomograms were developed to allow the estimation of probabilities.

RESULTS

Of the 14,651 subjects with responses for satisfaction following hip replacements 564 (3.8%) reported dissatisfaction, and 1433 (9.2%) of the 15,560 following knee replacement reported dissatisfaction. A total of 14,662 had responses for perceived improvement following hip replacement (lack of improvement in 391; 2.7%) and 15,588 following knee replacement (lack of improvements in 1092; 7.0%). Patients reporting poor outcomes had worse preoperative PROMs. Several factors, including age, gender, patient comorbidities and EQ5D, were included in the final prediction models: C-indices of these models were 0.613 and 0.618 for dissatisfaction and lack of improvement, respectively, for hip replacement and 0.614 and 0.598, respectively, for knee replacement.

CONCLUSIONS

Using easily accessible preoperative patient factors, including PROMs, we developed models which may help predict dissatisfaction and lack of improvement following hip and knee replacements and facilitate risk stratification and decision-making processes.

AKI3-Risk Predictors and Scores in Radical Nephrectomy with High Thrombectomy under Extracorporeal Circulation for Renal Cell Carcinoma with Supradiaphragmatic Inferior Vena Cava/Right Atrial Thrombus: A Single-Centre Retrospective Study

Background and Objectives: The recommended therapeutic management in renal cell carcinoma (RCC) with supradiaphragmatic inferior vena cava/right atrial thrombus (IVC/RA) is surgery. Extracorporeal circulation is required. Acute kidney injury (AKI), a frequent complication after nephrectomy and cardiac surgery is associated with long-term kidney disease. This study aims to identify the risk factors involved in the occurrence of the severe postoperative AKI (AKI3) and to analyse various preoperative validated risk scores from cardiac and noncardiac surgery in predicting this endpoint. Materials and Methods: The medical data of all patients with RCC with supradiaphragmatic IVC/RA thrombus who underwent radical nephrectomy with high thrombectomy, using extracorporeal circulation, between 2004-2018 in the Prof. C. C. Iliescu Emergency Institute for Cardiovascular Diseases, Bucharest, were retrospectively analysed. The patients who died intraoperatively were excluded from the study. The predefined study endpoint was the postoperative AKI3. Preoperative, intraoperative and postoperative data were collected according to the stratification of study population in two subgroups: AKI3-present and AKI3- absent patients. EuroSCORE, EuroSCORE II, Logistic EuroSCORE, NSQIP any-complications and NSQIP serious-complications were analysed. Results: We reviewed 30 patients who underwent this complex surgery between 2004-2018 in our institute. Two patients died intraoperatively. Nine patients (32.14%) presented postoperative AKI3. Age (OR 1.151, CI 95%: 1.009-1.312), preoperative creatinine clearance (OR 1.066, CI 95%: 1.010-1.123) and intraoperative arterial hypotension (OR 13.125, CI 95%: 1.924-89.515) were risk factors for AKI3 (univariable analysis). Intraoperative arterial hypotension emerged as the only independent risk factor in multivariable analysis (OR 11.66, CI 95%: 1.400-97.190). Logistic EuroSCORE (ROC analysis: AUC = 0.813, p = 0.008, CI 95%: 0.633-0.993) best predicted the endpoint. Conclusions: An integrated team effort is essential to avoid intraoperative arterial hypotension, the only independent risk factor of AKI3 in this highly complex surgery. Some risk scores can predict this complication. Further studies are needed.

Risk scores in cardiac resynchronization therapy-A review of the literature

Cardiac resynchronization therapy (CRT) for selected heart failure (HF) patients improves symptoms and reduces morbidity and mortality; however, the prognosis of HF is still poor. There is an emerging need for tools that might help in optimal patient selection and provide prognostic information for patients and their families. Several risk scores have been created in recent years; although, no literature review is available that would list the possible scores for the clinicians. We identified forty-eight risk scores in CRT and provided the calculation methods and formulas in a ready-to-use format. The reviewed score systems can predict the prognosis of CRT patients; some of them have even provided an online calculation tool. Significant heterogeneity is present between the various risk scores in terms of the variables incorporated and some variables are not yet used in daily clinical practice. The lack of cross-validation of the risk scores limits their routine use and objective selection. As the number of prognostic markers of CRT is overwhelming, further studies might be required to analyze and cross-validate the data.

Prehospital Respiratory Early Warning Score for airway management in-ambulance: A score comparison

BACKGROUND

Prehospital Respiratory Early Warning Scores to estimate the requirement for advanced respiratory support is needed. To develop a prehospital Respiratory Early Warning Score to estimate the requirement for advanced respiratory support.

METHODS

Multicentre, prospective, emergency medical services (EMS)-delivered, longitudinal cohort derivationvalidation study carried out in 59 ambulances and five hospitals across five Spanish provinces. Adults with acute diseases evaluated, supported and discharged to the Emergency Department with high priority were eligible. The primary outcome was the need for invasive or non-invasive respiratory support (NIRS or IRS) in the prehospital scope at the first contact with the patient. The measures included the following: epidemiological endpoints, prehospital vital signs (respiratory rate, pulse oximetry saturation, fraction of inspired oxygen, systolic and diastolic mean blood pressure, heart rate, tympanic temperature and consciousness level by the GCS).

RESULTS

Between 26 Oct 2018 and 26 Oct 2021, we enrolled 5793 cases. For NIRS prediction, the final model of the logistic regression included respiratory rate and pulse oximetry saturation/fraction of inspired oxygen ratio. For the IRS case, the motor response from the Glasgow Coma Scale was also included. The REWS showed an AUC of 0.938 (95% CI: 0.918-0.958), a calibration-in-large of 0.026 and a higher net benefit as compared with the other scores.

CONCLUSIONS

Our results showed that REWS is a remarkably aid for the decision-making process in the management of advanced respiratory support in prehospital care. Including this score in the prehospital scenario could improve patients' care and optimise the resources' management.

Contemporary risk models for infective endocarditis surgery: a narrative review

Infective endocarditis is a complex heterogeneous condition involving the infection of the endocardium and heart valves, leading to severe complications, including death. Surgery is often indicated in patients with infective endocarditis but is associated with elevated risk compared with other forms of cardiac surgery. Risk models play an important role in many cardiac surgeries as they can help inform clinicians and patients regarding procedural risk, decision-making to proceed or not, and influence perioperative management; however, they remain under-utilized in the infective endocarditis settings. Another crucial role of such risk models is to assess predicted versus found mortality, thereby allowing an assessment of institutional performance in infective endocarditis surgery. Traditionally, general cardiac surgery risk models such as European System for Cardiac Operative Risk Evaluation (EuroSCORE), EuroSCORE II, and Society of Thoracic Surgeon's score have been applied to endocarditis surgery. However, there has been the development of many endocarditis surgery-specific scores over the last decade. This review aims to discuss clinical characteristics and applications of all contemporary risk scores in the setting of surgical treatment of infective endocarditis.

Risk scores for predicting incident heart failure admission in patients with chronic coronary syndromes: Validation in a prospective, monocentric, long-term, cohort study

BACKGROUND

Heart failure (HF) admission in chronic coronary syndrome (CCS) patients has a prognostic impact. Stratification schemes have been described for predicting this endpoint, but none of them has been externally validated.

OBJECTIVES

Our aim was to develop point scores for predicting incident HF admission with data from previous studies, to perform an external validation in an independent prospective cohort and to compare their discriminative ability for this event.

METHODS

Independent predictive variables of HF admission in CCS patients without baseline HF were selected from four previous prospective studies (CARE, PEACE, CORONOR and CLARIFY), generating scores based on the relative magnitude of the coefficients of Cox of each variable. Finally, the scores were validated and compared in a monocentric prospective cohort.

RESULTS

The validation cohort included 1212 patients followed for up to 17 years, with 171 patients suffering at least one HF admission in the follow-up. Discriminative ability for predicting HF admission was statistically significant for all, and paired comparisons among them were all nonsignificant except for CORONOR score was superior to CLARIFY score (C-statistic 0.73, 95%CI 0.69-0.76 vs. 0.69, 95% CI 0.65-0.73; p = 0.03).

CONCLUSION

All tested scores showed significant discriminative ability for predicting incident HF admission in this independent validation study. Their discriminative ability was similar, with significant differences only between the two scores with higher and lower performance.

Predictive Score for Carbapenem-Resistant Gram-Negative Bacilli Sepsis: Single-Center Prospective Cohort Study

A clinical-epidemiological score to predict CR-GNB sepsis to guide empirical antimicrobial therapy (EAT), using local data, persists as an unmet need. On the basis of a case-case-control design in a prospective cohort study, the predictive factors for CR-GNB sepsis were previously determined as prior infection, use of mechanical ventilation and carbapenem, and length of hospital stay. In this study, each factor was scored according to the logistic regression coefficients, and the ROC curve analysis determined its accuracy in predicting CR-GNB sepsis in the entire cohort. Among the total of 629 admissions followed by 7797 patient-days, 329 single or recurrent episodes of SIRS/sepsis were enrolled, from August 2015 to March 2017. At least one species of CR-GNB was identified as the etiology in 108 (33%) episodes, and 221 were classified as the control group. The cutoff point of ≥3 (maximum of 4) had the best sensitivity/specificity, while ≤1 showed excellent sensitivity to exclude CR-GNB sepsis. The area under the curve was 0.80 (95% CI: 0.76-0.85) and the number needed to treat was 2.0. The score may improve CR-GNB coverage and spare polymyxins with 22% (95% CI: 17-28%) adequacy rate change. The score has a good ability to predict CR-GNB sepsis and to guide EAT in the future.

Circulating Biomarkers for Laboratory Diagnostics of Atherosclerosis-Literature Review

Atherosclerosis is still considered a disease burden with long-term damaging processes towards the cardiovascular system. Evaluation of atherosclerotic stages requires the use of independent markers such as those already considered traditional, that remain the main therapeutic target for patients with atherosclerosis, together with emerging biomarkers. The challenge is finding models of predictive markers that are particularly tailored to detect and evaluate the evolution of incipient vascular lesions. Important advances have been made in this field, resulting in a more comprehensible and stronger linkage between the lipidic profile and the continuous inflammatory process. In this paper, we analysed the most recent data from the literature studying the molecular mechanisms of biomarkers and their involvement in the cascade of events that occur in the pathophysiology of atherosclerosis.

Identification of risk factors for upper gastrointestinal bleeding in intensive care unit patients (GIBICU study)

BACKGROUND AND GOALS

Risk stratification for the need for therapeutic endoscopy and prediction of mortality in patients with upper gastrointestinal bleeding (UGIB) can be assessed by several scores. However, current scores are not validated for variceal bleeding and Intensive Care Unit (ICU) patients. The aim of this study was to evaluate potential parameters for the prediction of UGIB and patient outcomes.

PATIENTS AND STUDY METHODS

In this monocenter retrospective observational study, data from all esophagogastroduodenoscopies (EGD) between November 2014 and February 2020 with suspected hemorrhage in our ICU were evaluated.

RESULTS

Out of 345 included EGD, 42.3% of UGIB was diagnosed. 51.9% needed endoscopic intervention. Overall, 52.3% of included patients with UGIB died. Logistic regression showed that preceding variceal or non-variceal UGIB (p < .001), serum lactate (p = .001), heart rate (HR) (p = .005), and blood transfusions (p = .001) were significant predictors of UGIB. Previous UGIB (p < .001), male sex (p = .015), known varices (p < .001), serum albumin (p = .19) and use of catecholamines (p = .040) were significant predictors for the need of endoscopic intervention. Higher mortality was significantly associated with the usage of steroids (p < .001), malignant preconditions (p = .021), serum albumin (p = .020) and prolonged PTT (partial thromboplastin time) (p = .001).

CONCLUSIONS

We were able to identify additional parameters that had previously not been included in existing scores to predict the risk of UGIB, the need for therapeutic endoscopy and mortality in ICU patients. Therefore, an extension of these scores is necessary. Further validation of identified parameters in multicenter trials is needed to improve risk scores for ICU patients.

The Glasgow Prognostic Score Predicts Survival Outcomes in Neuroendocrine Neoplasms of the Gastro-Entero-Pancreatic (GEP-NEN) System

Background: Across a variety of solid tumors, prognostic implications of nutritional and inflammation-based risk scores have been identified as a complementary resource of risk stratification. Methods: In this retrospective study, we performed a comparative analysis of several established risk scores and ratios, such as the Glasgow Prognostic Score (GPS), in neuroendocrine neoplasms of the gastro−entero−pancreatic (GEP-NEN) system with respect to their prognostic capabilities. Clinicopathological and treatment-related data for 102 GEP-NEN patients administered to the participating institutions between 2011 and 2021 were collected. Scores/ratios significantly associated with overall or progression-free survival (OS, PFS) upon univariate analysis were subsequently included in a Cox-proportional hazard model for the multivariate analysis. Results: The median age was 62 years (range 18−95 years) and the median follow-up period spanned 51 months. Pancreatic or intestinal localization at the initial diagnosis were present in 41 (40.2%) and 44 (43.1%) cases, respectively. In 17 patients (16.7%), the primary manifestation could not be ascertained (NNUP; neuroendocrine neoplasms of unknown primary). Histological grading (HG) revealed 24/102 (23.5%) NET/NEC (poorly differentiated; high grade G3) and 78/102 (76.5%) NET (highly or moderately differentiated; low−high grade G1−G2). In total, 53/102 (51.9%) patients presented with metastatic disease (UICC IV), 11/102 (10.7%) patients presented with multifocal disease, and 56/102 (54.9%) patients underwent a primary surgical or endoscopic approach, whereas 28 (27.5%) patients received systemic cytoreductive treatment. The univariate analysis revealed the GPS and PI (prognostic index), as well as UICC-stage IV, HG, and the Charlson comorbidity index (CCI) to predict both the PFS and OS in GEP-NEN patients. However, the calculation of the survival did not separate GPS subgroups at lower risk (GPS 0 versus GPS 1). Upon the subsequent multivariate analysis, GPS was the only independent predictor of both OS (p < 0.0001; HR = 3.459, 95% CI = 1.263−6.322) and PFS (p < 0.003; HR = 2.119, 95% CI = 0.944−4.265). Conclusion: In line with previous results for other entities, the present study revealed the GPS at baseline to be the only independent predictor of survival across all stages of GEP-NEN, and thus supports its clinical utility for risk stratification in this group of patients.

A novel intubation prediction model for patients hospitalized with COVID-19: the OTO-COVID-19 scoring model

OBJECTIVE

The method for predicting the risk of intubation in patients with coronavirus disease 2019 (COVID-19) is yet to be standardized. This study aimed to introduce a new disease prognosis scoring model that may predict the intubation risk based on the symptoms, signs, and laboratory tests of patients hospitalized with the diagnosis of COVID-19.

METHOD

This cross-sectional retrospective study analyzed the intubation status of 733 patients hospitalized with COVID-19 diagnosis between March and December 2020 at Ondokuz Mayıs University Faculty of Medicine, Turkey, based on 33 variables. Binary logistic regression analysis was used to select the variables that significantly affect intubation, which constitute the risk factors. The Chi-square Automatic Interaction Detection algorithm, one of the data mining methods, was used to determine the threshold values of the important variables for intubation classification.

RESULTS

The following variables found were mostly associated with intubation: C-reactive protein, lactate dehydrogenase, neutrophil-to-lymphocyte ratio, age, lymphocyte count, and malignancy. The logistic function based on these variables correctly predicted 81.13% of intubated (sensitivity), 99.52% of nonintubated (specificity), and 96.86% of both intubated and nonintubated (accurate classification rate) patients. The scoring model revealed the following risk statuses for the intubated patients: very high risk, 75.47%; moderate risk, 20.75%; and very low risk, 3.77%.

CONCLUSIONS

On the basis of certain variables measured at admission, the OTO-COVID-19 scoring model may help clinicians identify patients at the risk of intubation and subsequently provide a prompt and effective treatment at the earliest.

The polytomous discrimination index for prediction involving multistate processes under intermittent observation

With the increasing importance of predictive modeling in health research comes the need for methods to rigorously assess predictive accuracy. We consider the problem of evaluating the accuracy of predictive models for nominal outcomes when outcome data are coarsened at random. We first consider the problem in the context of a multinomial response modeled by polytomous logistic regression. Attention is then directed to the motivating setting in which class membership corresponds to the state occupied in a multistate disease process at a time horizon of interest. Here, class (state) membership may be unknown at the time horizon since disease processes are under intermittent observation. We propose a novel extension to the polytomous discrimination index to address this and evaluate the predictive accuracy of an intensity-based model in the context of a study involving patients with arthritis from a registry at the University of Toronto Centre for Prognosis Studies in Rheumatic Diseases.

Clinical Score for Predicting the Risk of Poor Ambulation at Discharge in Fragility Femoral Neck Fracture Patients: A Development Study

Surgical treatment in patients with fragility femoral neck fractures often leads to a longer length of hospital stay (LOS) and higher costs. Intensive rehabilitation is one of the choices to reduce LOS, but patient selection criteria are controversial. We intended to develop a clinical score to predict the risk of poor ambulation at discharge. This study was based on a retrospective cohort of patients diagnosed with fragility femoral neck fractures surgically managed from January 2010 to December 2019 at Chiang Mai University (CMU) Hospital. Pre-, intra-, and post-operative factors that affect rehabilitation training were candidate predictors. All patients were categorized into able or unable groups based on their ability to bear self-weight at discharge. Logistic regression was used for score derivation. Five hundred and nine patients were included in this study. Male sex, end-stage kidney disease (ESRD), cerebrovascular disease, psychiatric disorders, pre-fracture ambulation with gait aids, concomitant fracture, post-operative intensive care unit (ICU) admission or ventilator use, and urinary catheter use at second day post-operation were identified as the prognostic factors. The score showed an AuROC of 0.84 with good calibration. The score can be used for risk stratification on the second day post-operation. External validation is encouraged before clinical implementation.

Tenofovir is superior to entecavir in reducing HCC for patients with HBV-related compensated cirrhosis at high HCC risk scores

Background:

Both tenofovir disoproxil fumarate (TDF) and entecavir (ETV) are known to reduce the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). This study aimed to compare the difference in HCC risk reduction between TDF and ETV in treatment-naïve patients with CHB-related compensated cirrhosis.

Methods:

Patients with compensated cirrhosis initially treated with TDF or ETV at nine Chinese hospitals between June 2014 and March 2021 were enrolled in this retrospective study. The cumulative HCC incidence rates for the two drugs were compared for the entire cohort, and a subgroup analysis was performed according to the HCC risk scores. Propensity score matching (PSM) was used to control confounding biases.

Results:

The analysis included 1453 patients (TDF group, n = 188; ETV group, n = 1265). Ninety-five patients developed HCC, with a median follow-up period of 26.1 months. The 3-year HCC incidence was 2.0% in the TDF group and 7.5% in the ETV group (log-rank p = 0.005). TDF treatment was associated with a lower risk of HCC than ETV treatment [hazard ratio (HR) = 0.222, 95% confidence interval (CI), 0.070–0.702, p = 0.010] but was similar after PSM (HR = 0.483, 95% CI, 0.144–1.626, p = 0.240; log-rank p = 0.230). However, subgroup analysis showed that the cumulative HCC incidence was lower in the TDF group than in the ETV group among patients with a modified PAGE-B score (mPAGE-B) ⩾9, either before or after PSM (log-rank p = 0.048 and p = 0.023, respectively).

Conclusion:

Among patients with an mPAGE-B score ⩾9, TDF is associated with a lower HCC incidence than ETV in patients with CHB-related compensated cirrhosis.

Framingham and American College of Cardiology/American Heart Association Pooled Cohort Equations, High-Sensitivity Troponin T, and N-Terminal Pro-Brain-Type Natriuretic Peptide for Predicting Atherosclerotic Cardiovascular Events Across the Spectrum of Kidney Dysfunction

Background

Contemporary guidelines recommend using atherosclerotic cardiovascular disease screening tools to guide primary prevention. The performance of these scores is not well known in patients with moderate to advanced chronic kidney disease, particularly in combination with clinically available cardiac biomarkers including N‐terminal pro–brain‐type natriuretic peptide and high‐sensitivity troponin T (hsTnT).

Methods and Results

We studied 1027 participants from the Chronic Renal Insufficiency Cohort without self‐reported atherosclerotic cardiovascular disease who were not taking aspirin or statins at enrollment. Framingham Risk Score, Pooled Cohort Equation, N‐terminal pro–brain‐type natriuretic peptide, and hsTnT were measured at baseline. Outcomes included fatal and nonfatal myocardial infarction, stroke, and cardiac death. We calculated 10‐fold cross‐validated Harrell’s C‐indices for each risk score and cardiac biomarker alone and in combination. The C‐index (95% CI) for discrimination of atherosclerotic cardiovascular disease was 0.72 (0.67, 0.77) for the Framingham Risk Score, and 0.72 (0.67, 0.76) for the Pooled Cohort Equation. HsTnT had comparable discrimination to each risk score, and improved the discrimination of each (change in Framingham 0.029, 95% CI 0.003, 0.055; change in Pooled Cohort Equation 0.027, 95% CI 0.002, 0.052). N‐terminal pro–brain‐type natriuretic peptide had poorer discrimination than the risk scores and did not significantly improve their discrimination (change in Framingham 0.009, 95% CI −0.001, 0.018; change in Pooled Cohort Equation 0.011, 95% CI −0.001, 0.024).

Conclusions

The Framingham Risk Score and Pooled Cohort Equation demonstrated moderate discrimination for atherosclerotic cardiovascular disease in patients with chronic kidney disease. HsTnT, but not N‐terminal pro–brain‐type natriuretic peptide, improved their discrimination overall. Until chronic kidney disease–specific atherosclerotic cardiovascular disease risk scores can be developed, it may be worth considering how to incorporate hsTnT into existing clinical risk scores.