Acute Kidney Injury in Subarachnoid Hemorrhage: Exploring its Clinical Significance and Prognostic Implications.

OBJECTIVES: Subarachnoid hemorrhage (SAH) from spontaneous rupture of an aneurysm is a debilitating condition with high morbidity and mortality. Patients with SAH remain understudied, particularly concerning the evaluation of incidence and consequences of subsequent acute kidney injury (AKI). In this study, we aim to explore the risk factors and outcomes of AKI in patients with SAH. MATERIALS AND METHODS: International Classification of Diseases, 9th Edition and 10th Edition (ICD-10-CM) codes were used to query the National Inpatient Sample (NIS) for patients with a diagnosis of SAH between 2010-2019. Subgroup analysis was stratified by AKI diagnosis during the same hospitalization. AKI and non-AKI groups were assessed for baseline clinical characteristics, interventions, complications, and outcomes. Descriptive statistics, multivariate regressions, and propensity score-matching were performed using IBM SPSS 28. NEED TO MENTION NIH-SSS RESULTS: Of 76,553 patients diagnosed with nontraumatic SAH between 2010-2019, 10,634 (13.89%) had a comorbid diagnosis of AKI. Patients with AKI were older (p<0.01) and more often obese (p < 0.01), compared to the non-AKI group. A multivariate regression found the diagnosis of AKI to be independently correlated with poor functional outcome (p<0.001), above average length of stay (p < 0.001), and in-hospital mortality (p < 0.001) when controlling for age, SAH severity, and other comorbidities. CONCLUSIONS: This study showed significant association between AKI and adverse outcomes in SAH patients, and a correlation between AKI and heightened complication rates, poor functional outcome, extended hospital stays, and elevated mortality rates. Early detection of AKI in SAH patients is vital to enhance their chances of recovery.

Initial combination therapy with macitentan and tadalafil in patients with pulmonary arterial hypertension, with and without cardiac comorbidities.

AIMS: According to current guidelines, initial monotherapy should be considered for pulmonary arterial hypertension (PAH) patients with cardiopulmonary comorbidities. This analysis of combined data from the TRITON and REPAIR clinical trials, assesses efficacy and safety of initial double combination therapy in patients without vs. with 1-2 cardiac comorbidities. METHODS AND RESULTS: Data were combined for patients from TRITON (NCT02558231) and REPAIR (NCT02310672) on initial macitentan and tadalafil double combination therapy (overall set, n = 148) and two subgroups defined as patients without cardiac comorbidities (n = 62) and those with 1-2 cardiac comorbidities (n = 78). Patients with ≥3 comorbidities were excluded from these studies. For the overall set, the median (Q1-Q3) duration of combined macitentan and tadalafil exposure was 513.0 (364.0-778.0) days, and was similar between subgroups. Change from baseline to Week 26 for pulmonary vascular resistance was -55% and -50% for patients without and with 1-2 cardiac comorbidities, respectively; marked improvements in other hemodynamic and functional parameters were also observed, although functional parameters improved to a lesser extent in patients with comorbidities. At Week 26, the majority of patients had improved PAH risk status, according to the non-invasive four-strata and REVEAL Lite 2.0 methods. The safety profile of initial macitentan plus tadalafil combination therapy was consistent with the known profiles of the two drugs, and similar between the subgroups. CONCLUSIONS: Initial double combination therapy with macitentan plus tadalafil is efficacious in patients with PAH with 1-2 cardiac comorbidities and those without, with similar safety and tolerability profiles between the two groups.

Predictors of Paroxysmal Atrial Fibrillation in Patients With a Cryptogenic Stroke: Selecting Patients for Long-Term Rhythm Monitoring.

BACKGROUND: After a cryptogenic stroke, patients will often require prolonged cardiac monitoring; however, the subset of patients who would benefit from long-term rhythm monitoring is not clearly defined. OBJECTIVE: Using significant predictors of AF using age, sex, comorbidities, baseline 12-lead electrocardiogram, short term rhythm monitoring and echocardiogram data, we created a risk score and compared it to previously published risk scores. METHODS: Patients admitted to Montefiore Medical Center between May 2017 and June 2022 with a primary diagnosis of cryptogenic stroke or TIA who underwent long-term rhythm monitoring with an implantable cardiac monitor were retrospectively analyzed. RESULTS: Variables positively associated with a diagnosis of clinically significant atrial fibrillation include age (p < 0.001), race (p = 0.022), diabetes status (p = 0.026), and COPD status (p = 0.012), the presence of atrial runs (p = 0.003), the number of atrial runs per 24 hours (p < 0.001), the total number of atrial run beats per 24 hours (p < 0.001) and the number of beats in the longest atrial run (p < 0.001), LA enlargement (p = 0.007) and at least mild mitral regurgitation (p = 0.009). We created a risk stratification score for our population, termed the "ACL score." The ACL score demonstrated superiority to the CHA2DS2-VASc score and comparability to the C2HEST score for predicting device-detected AF. CONCLUSION: The ACL score enables clinicians to better predict which patients are more likely to be diagnosed with device-detected AF after a cryptogenic stroke.

Performance of HAS-BLED and DOAC scores to predict major bleeding events in atrial fibrillation patients treated with direct oral anticoagulants: A report from a prospective European observational registry.

BACKGROUND: The DOAC score has been recently proposed for bleeding risk stratification of patients with atrial fibrillation treated with direct oral anticoagulants (DOAC). OBJECTIVE: To compare the performance of HAS-BLED and DOAC score in predicting major bleeding events in a contemporary cohort of European AF patients treated with DOAC. METHODS: We included patients derived from a prospective observational registry of European AF patients. HAS-BLED and DOAC scores were calculated as per the original schemes. Our primary endpoint was major bleeding events. Receiver operating characteristic (ROC) curves were used to compare the predictive ability of the scores. RESULTS: A total of 2834 AF patients (median age [IQR] 69 [62-77] years; 39.6 % female) treated with DOAC were included in the analysis. According to the HAS-BLED score, 577 patients (20.4 %) were categorized as very low risk of bleeding, as compared to 1276 (45.0 %) according to DOAC score. A total of 55 major bleeding events occurred with an overall incidence of 1.04 per 100 patient-years. Both scores showed only a modest ability for the prediction of bleeding events (HAS-BLED area under the curve [AUC], 0.65, 95 % confidence interval [CI] 0.55-0.70; DOAC score AUC 0.62, 95 % CI 0.59-0.71, p for difference = 0.332]. At calibration analysis, the DOAC score showed modest calibration, especially for patients at high risk, when compared to HAS-BLED. CONCLUSION: In a contemporary cohort of DOAC-treated AF patients, both HAS-BLED and DOAC scores only modestly predicted the occurrence of major bleeding events. Our results do not support the preferential use of DOAC score over HAS-BLED.

Association of Thrombocytopenia With Disease Burden, High-Risk Cytogenetics, and Survival in Newly Diagnosed Multiple Myeloma Patients Treated With Novel Therapies.

BACKGROUND: The effect of thrombocytopenia has not been studied in the era of novel treatments in multiple myeloma (MM). OBJECTIVE: To evaluate the clinical characteristics and outcomes in MM patients presenting with thrombocytopenia. MATERIALS: Newly diagnosed MM patients between 2008 and 2018 who received at least 2 novel agents at induction. Thrombocytopenia was defined as a platelet count of less than < 150,000/mm3. RESULTS: A total of 648 patients were identified. Thrombocytopenia was found in 120 patients (18.5%). Baseline disease characteristics associated with higher rates of thrombocytopenia at baseline included IgA myeloma, P < .01, ISS 3 versus 1 or 2, P < .01, R-ISS 3 versus 1 or 2, P < .01, renal failure (CrCl < 30 mL/min), P < .01, hypercalcemia (Ca > 11.5 mg/dL), P < .01, elevated LDH, P < .03, anemia (Hb < 10 g/dL), P < .01, higher serum monoclonal protein, P < .02, and > 60% plasma cells in the bone marrow, P < .01. Thrombocytopenia was more prevalent across patients with t(4;14) and t(14;16), but was not associated with an overall high-risk fluorescence in situ hybridization (FISH) classification. Median OS was significantly lower among patients with thrombocytopenia (64.4 vs. 145.0 months, P < .01). In multivariable Cox regression, thrombocytopenia was associated with mortality (HR = 2.45, 95% CI, 1.7-3.6) independently of age, sex, high-risk FISH, ISS stage, response at induction, percentage of plasma cells in the BM, and anemia. CONCLUSION: We found that thrombocytopenia was seen among one-fifth of MM patients and was more common in patients with (t[4; 14] and t[14; 16]). Thrombocytopenia had an independent association with worse survival.

The role of biomarkers in the prognosis and risk stratification in heart failure: A systematic review.

Acute heart failure (AHF) episodes are marked by high rates of morbidity and mortality during the episode and minimal advancements in its care. Multiple biomarker monitoring is now a crucial supplementary technique in the therapy of AHF. A scientific literature search was conducted by assessing and evaluating the most pertinent research that has been published, including original papers and review papers with the use of PubMed, Medline, and Cochrane databases. Established biomarkers like natriuretic peptides (BNP, NT-proBNP) and cardiac troponins play crucial roles in diagnostic and prognostic evaluation. Emerging biomarkers such as microRNAs, osteopontin, galectin-3, ST2, and GDF-15 show promise in enhancing risk stratification and predicting adverse outcomes in HF. However, while these biomarkers offer valuable insights, their clinical utility requires further validation and integration into practice. Continued research into novel biomarkers holds promise for early HF detection and risk assessment, potentially mitigating the global burden of HF. Understanding the nuances of biomarker utilization is crucial for their effective incorporation into clinical practice, ultimately improving HF management and patient care.

The wolf in sheep's clothing: vasovagal syncope in acute aortic dissection.

BACKGROUND: The presentation of acute aortic dissection can pose a challenge for emergency physicians, as it may occur without pain. Atypical presentations can lead to significant delays in diagnosis and increased mortality rates. CASE DESCRIPTION: Our case illustrates that isolated painless syncope can be a rare presenting symptom of acute aortic dissection type A. What is unique about our case is the limited extension of the dissection tear and the availability of Holter monitoring during the syncopal episode. CONCLUSION: This constellation provides insight into the pathophysiological mechanism of the syncope in this patient. Mechanisms of syncope related to acute aortic dissection are diverse. We show that vasovagal activation not related to pain can be the underlying mechanism of syncope in acute aortic dissection type A. Although excessive vasovagal tone in the setting of aortic dissection has been hypothesized in the past, it has never been as clearly illustrated as in the present case. This also highlights the challenge in risk stratification of syncope in the emergency department.

Improving the Risk Prediction of the 2015 ATA Recurrence Risk Stratification in Papillary Thyroid Cancer.

BACKGROUND: Various prognostic factors are expected to refine the American Thyroid Association (ATA) recurrence risk stratification for patients with papillary thyroid cancer (PTC). However, it remains unclear to what extent integrating these factors improves patient treatment decision-making. METHODS: We developed two predictive models for structural incomplete response (SIR) at the one-year follow-up visit, based on comprehensive clinical data from a retrospective cohort of 2539 patients. Model 1 included the recurrence risk stratification and lymph node features (i.e., number and ratio of metastatic lymph nodes, N stage). Model 2 further incorporated preablation stimulated thyroglobulin (s-Tg). An independent cohort of 746 patients was used for validation analysis. We assessed the models' predictive performance compared to the recurrence risk stratification using the integrated discrimination improvement (IDI) and the continuous net reclassification improvement (NRI). The clinical utility of the models was evaluated using decision curve analysis. RESULTS: Both Model 1 and Model 2 outperformed the recurrence risk stratification in predicting SIR, with improved correct classification rates (Model 1: IDI=0.02, event NRI=42.31%; Model 2: IDI=0.07, event NRI=53.54%). The decision curves indicated that both models provided greater benefits over the risk stratification system in clinical decision-making. In the validation set, Model 2 maintained similar performance while Model 1 did not significantly improve correct reclassification. CONCLUSION: The inclusion of lymph node features and s-Tg showed potential to enhance the predictive accuracy and clinical utility of the existing risk stratification system for PTC patients.

Risk-stratified analysis of long-term clinical outcomes and cumulative costs in Finnish patients with recent acute coronary syndrome or coronary revascularization: a 5-year real-world study using electronic health records.

Aims: Risk assessment is essential in the prevention of cardiovascular disease. In patients with recent acute coronary syndrome (ACS) or coronary revascularization, risk prediction tools, like the European Society of Cardiology guideline recommended SMART-REACH risk score, are increasingly used to predict the risk of recurrent cardiovascular events enabling risk-based personalized prevention. However, little is known about the association between risk stratification and the social and healthcare costs at a population level. This study evaluated the associations between baseline SMART-REACH risk scores, long-term recurrent clinical events, cumulative costs, and post-index event LDL-C goal attainment in patients with recent ACS and/or revascularization. Methods and results: This retrospective study used electronic health records and was conducted in the North Karelia region of Finland. The study cohort included all patients aged 45-85 admitted to a hospital for ACS or who underwent percutaneous coronary intervention or coronary artery bypass surgery between 1 January 2017 and 31 December 2021. Patients were divided into quintiles based on their baseline SMART-REACH risk scores to examine the associations between predicted 5-year scores and selected clinical and economic outcomes. In addition, simple age-based stratification was conducted as a sensitivity analysis. The observed 5-year cumulative incidence of recurrent events ranged from 20% in the lowest to 41% in the highest risk quintile, whereas the corresponding predicted risks ranged from 13% to 51%, and cumulative 5-year mean total costs per patient ranged from 15 827 to 46 182€, respectively. Both monitoring and attainment of low LDL-C values were suboptimal. Conclusion: The use of the SMART-REACH quintiles as a population-level risk stratification tool successfully stratified patients into subgroups with different cumulative numbers of recurrent events and cumulative total costs. However, more research is needed to define clinically and economically optimal threshold values for a population-level stratification.

A machine learning clinic scoring system for hepatocellular carcinoma based on the Surveillance, Epidemiology, and End Results database.

Background: Hepatocellular carcinoma (HCC) poses a global threat to life; however, numerical tools to predict the clinical prognosis of these patients remain scarce. The primary objective of this study is to establish a clinical scoring system for evaluating the overall survival (OS) rate and cancer-specific survival (CSS) rate in HCC patients. Methods: From the Surveillance, Epidemiology, and End Results (SEER) Program, we identified 45,827 primary HCC patients. These cases were randomly allocated to a training cohort (22,914 patients) and a validation cohort (22,913 patients). Univariate and multivariate Cox regression analyses, coupled with Kaplan-Meier methods, were employed to evaluate prognosis-related clinical and demographic features. Factors demonstrating prognostic significance were used to construct the model. The model's stability and accuracy were assessed through C-index, receiver operating characteristic (ROC) curves, calibration curves, and clinical decision curve analysis (DCA), while comparisons were made with the American Joint Committee on Cancer (AJCC) staging. Ultimately, machine learning (ML) quantified the variables in the model to establish a clinical scoring system. Results: Univariate and multivariate Cox regression analyses identified 11 demographic and clinical-pathological features as independent prognostic indicators for both CSS and OS using. Two models, each incorporating the 11 features, were developed, both of which demonstrated significant prognostic relevance. The C-index for predicting CSS and OS surpassed that of the AJCC staging system. The area under the curve (AUC) in time-dependent ROC consistently exceeded 0.74 in both the training and validation sets. Furthermore, internal and external calibration plots indicated that the model predictions aligned closely with observed outcomes. Additionally, DCA demonstrated the superiority of the model over the AJCC staging system, yielding greater clinical net benefit. Ultimately, the quantified clinical scoring system could efficiently discriminate between high and low-risk patients. Conclusions: A ML clinical scoring system trained on a large-scale dataset exhibits good predictive and risk stratification performance in the cohorts. Such a clinical scoring system is readily integrable into clinical practice and will be valuable in enhancing the accuracy and efficiency of HCC management.

A systematic review of fall prediction models for community-dwelling older adults: comparison between models based on research cohorts and models based on routinely collected data.

BACKGROUND: Prediction models can identify fall-prone individuals. Prediction models can be based on either data from research cohorts (cohort-based) or routinely collected data (RCD-based). We review and compare cohort-based and RCD-based studies describing the development and/or validation of fall prediction models for community-dwelling older adults. METHODS: Medline and Embase were searched via Ovid until January 2023. We included studies describing the development or validation of multivariable prediction models of falls in older adults (60+). Both risk of bias and reporting quality were assessed using the PROBAST and TRIPOD, respectively. RESULTS: We included and reviewed 28 relevant studies, describing 30 prediction models (23 cohort-based and 7 RCD-based), and external validation of two existing models (one cohort-based and one RCD-based). The median sample sizes for cohort-based and RCD-based studies were 1365 [interquartile range (IQR) 426-2766] versus 90 441 (IQR 56 442-128 157), and the ranges of fall rates were 5.4% to 60.4% versus 1.6% to 13.1%, respectively. Discrimination performance was comparable between cohort-based and RCD-based models, with the respective area under the receiver operating characteristic curves ranging from 0.65 to 0.88 versus 0.71 to 0.81. The median number of predictors in cohort-based final models was 6 (IQR 5-11); for RCD-based models, it was 16 (IQR 11-26). All but one cohort-based model had high bias risks, primarily due to deficiencies in statistical analysis and outcome determination. CONCLUSIONS: Cohort-based models to predict falls in older adults in the community are plentiful. RCD-based models are yet in their infancy but provide comparable predictive performance with no additional data collection efforts. Future studies should focus on methodological and reporting quality.

Serum cystatin C, monocyte/high-density lipoprotein-C ratio, and uric acid for the diagnosis of coronary heart disease and heart failure.

BACKGROUND: Coronary heart disease (CHD) and heart failure (HF) are the major causes of morbidity and mortality worldwide. Early and accurate diagnoses of CHD and HF are essential for optimal management and prognosis. However, conventional diagnostic methods such as electrocardiography, echocardiography, and cardiac biomarkers have certain limitations, such as low sensitivity, specificity, availability, and cost-effectiveness. Therefore, there is a need for simple, noninvasive, and reliable biomarkers to diagnose CHD and HF. AIM: To investigate serum cystatin C (Cys-C), monocyte/high-density lipoprotein cholesterol ratio (MHR), and uric acid (UA) diagnostic values for CHD and HF. METHODS: We enrolled 80 patients with suspected CHD or HF who were admitted to our hospital between July 2022 and July 2023. The patients were divided into CHD (n = 20), HF (n = 20), CHD + HF (n = 20), and control groups (n = 20). The serum levels of Cys-C, MHR, and UA were measured using immunonephelometry and an enzymatic method, respectively, and the diagnostic values for CHD and HF were evaluated using receiver operating characteristic (ROC) curve analysis. RESULTS: Serum levels of Cys-C, MHR, and UA were significantly higher in the CHD, HF, and CHD + HF groups than those in the control group. The serum levels of Cys-C, MHR, and UA were significantly higher in the CHD + HF group than those in the CHD or HF group. The ROC curve analysis showed that serum Cys-C, MHR, and UA had good diagnostic performance for CHD and HF, with areas under the curve ranging from 0.78 to 0.93. The optimal cutoff values of serum Cys-C, MHR, and UA for diagnosing CHD, HF, and CHD+HF were 1.2 mg/L, 0.9 × 109, and 389 µmol/L; 1.4 mg/L, 1.0 × 109, and 449 µmol/L; and 1.6 mg/L, 1.1 × 109, and 508 µmol/L, respectively. CONCLUSION: Serum Cys-C, MHR, and UA are useful biomarkers for diagnosing CHD and HF, and CHD+HF. These can provide information for decision-making and risk stratification in patients with CHD and HF.

Optimizing Total Hip and Knee Arthroplasty Among an Underserved Population: Lessons Learned From a Quality-Improvement Initiative.

Background: Under-represented minorities and those with noncommercial insurance have higher medical comorbidities and complications following elective total joint arthroplasty (TJA). In an effort to bridge this gap, our center implemented a preoperative optimization protocol for TJA in a Medicaid Clinic (Clinic). The purpose of this study is to assess the effectiveness of that protocol and highlight challenges associated with caring for this patient population. Methods: This retrospective analysis included 117 patients undergoing TJA between January 2015 and January 2020. In 2015, the protocol was implemented as a mandatory practice prior to TJA. A contemporary control cohort from the private office was also analyzed. Patient demographics, American Society of Anesthesiologists score, and postoperative complications were collected. Results: Within the clinic group, 52.5% (62) patients identified as Hispanic with 46.6% (55) Spanish-speaking as primary language, compared to 9.3% (11) and 8.5% (10) in the office group (P = .0001), respectively. Clinic group patients were significantly more likely to experience a complication compared to office patients (20 vs 7, respectively). There was no difference in complication or reoperation rate between clinic patients who underwent the optimization protocol and those who did not. Conclusions: The findings from this study highlight the demographic and comorbidities profile of an underserved population, and report on results of a quality improvement initiative among that population, which failed to improve postoperative outcomes. These results underscore the need for further study in this population to improve outcomes and health equity.

Mortality Risk Assessment Using the REVEAL 2.0 Score in Pulmonary Hypertension Secondary to Left Heart Disease.

Background: Pulmonary hypertension (PH) frequently complicates the course of patients with left heart disease (PH-LHD) and is associated with worse clinical outcomes. Mortality calculators for PH-LHD are lacking, and it is unclear whether any risk prediction tools originally derived from other forms of PH can accurately predict outcomes in patients with PH-LHD. Methods: We retrospectively analyzed data from 161 patients diagnosed with PH-LHD referred to our pulmonary hypertension center from 2016 to 2022. We calculated the Registry to Evaluate Early and Long-Term PAH Disease Management (REVEAL 2.0) risk score and categorized patients as low, intermediate, or high-risk. We assessed survival at 1 and 3 years using Kaplan-Meier and Cox proportional hazards, as well as classification performance using a concordance index. Results: At the first outpatient visit, 15% of patients were stratified as low-risk, 27% as intermediate, and 57% as high-risk. Cumulative 1-year survival rates were 100%, 94%, and 91% for the low, intermediate, and high-risk strata, respectively. Cumulative 3-year survival rates were 96%, 89%, and 70% for the low, intermediate, and high-risk strata, respectively. We found no difference in outcomes at 1 year between risk groups. High-risk patients had an increased risk of death at 3 years using REVEAL 2.0 (HR 5.32, p < 0.001). However, while REVEAL 2.0 accurately discriminated high-risk patients, the hazard ratio was not statistically different between patients classified as intermediate-risk compared to low-risk. Conclusion: REVEAL 2.0 accurately predicted 3-year survival in PH-LHD patients with high-risk features. However, the mortality risk between patients classified as intermediate-risk was not different from the low-risk stratum, suggesting inaccurate classification for this group of patients.

Integration of two-dimensional echocardiography: A novel risk indicator for ST-segment elevation myocardial infarction.

AIMS: We aim to integrate the parameters of two-dimensional (2D) echocardiography and identify the high-risk population for all-cause mortality in patients with acute ST-segment elevation myocardial infarction (STEMI) undergoing percutaneous coronary intervention (PCI). METHODS: The study involved a retrospective cohort population with STEMI who were admitted to Yongchuan Hospital of Chongqing Medical University between January 2016 and January 2019. Baseline data were collected, including 2D echocardiography parameters and left ventricular ejection fraction (LVEF). The parameters of 2D echocardiography were subjected to cluster analysis. Logistic regression models were employed to assess univariate and multivariate adjusted odds ratios (ORs) of cluster information in relation to all-cause mortality. Four logistic regression models were generated, utilizing cluster information, clinical variables, clinical variables in conjunction with LVEF, and clinical variables in conjunction with LVEF and cluster information as predictive variables, respectively. The area under the curve (AUC) were utilized to evaluate the incremental risk stratification value of cluster information. RESULTS: The study included 633 participants with 28.8% female, a mean age of 65.68 ± 11.98 years. Over the course of a 3-year follow-up period, 108 (17.1%) patients experienced all-cause mortality. Utilizing cluster analysis of 2D echocardiography parameters, the patients were categorized into two distinct clusters, with statistically significant differences observed in most clinical variables, echocardiography, and survival outcomes between the clusters. Multivariate regression analysis revealed that cluster information was independently associated with the risk of all-cause mortality with adjusted OR 7.33 (95% confidence interval [CI] 3.99-14.06, P < 0.001). The inclusion of LVEF enhanced the predictive capacity of the model utilized with clinical variables with AUC 0.848 (95% CI 0.809-0.888) versus AUC 0.872 (95% CI 0.836-0.908) (P < 0.001), and the addition of cluster information further improved its predictive performance with AUC 0.906 (95% CI 0.878-0.934, P < 0.001). This cluster analysis was translated into a free available online calculator (https://app-for-mortality-prediction-cluster.streamlit.app/). CONCLUSIONS: The 2D echocardiographic diagnostic information based on cluster analysis had good prognostic value for STEMI population, which was helpful for risk stratification and individualized intervention.

A risk-scoring model based on endobronchial ultrasound multimodal imaging for predicting metastatic lymph nodes in lung cancer patients.

Background and Objectives: Endobronchial ultrasound (EBUS) imaging is a valuable tool for predicting lymph node (LN) metastasis in lung cancer patients. This study aimed to develop a risk-scoring model based on EBUS multimodal imaging (grayscale, Doppler mode, elastography) to predict LN metastasis in lung cancer patients. Patients and Methods: This retrospective study analyzed 350 metastatic LNs in 314 patients with lung cancer and 124 reactive LNs in 96 patients with nonspecific inflammation. The sonographic findings were compared with the final pathology results and clinical follow-up. Univariate and multivariate logistic regression analyses were performed to evaluate the independent risk factors of metastatic LNs. According to the ß coefficients of corresponding indicators in logistic regression analysis, a risk-scoring model was established. Receiver operating characteristic curve was applied to evaluate the predictive capability of model. Results: Multivariate analysis showed that short axis >10 mm, distinct margin, absence of central hilar structure, presence of necrosis, nonhilar vascularity, and elastography score 4 to 5 were independent predictors of metastatic LNs. Both short axis and margin were scored 1 point, and the rest of independent predictors were scored 2 points. The combination of 3 EBUS modes had the highest area under the receiver operating characteristic and accuracy of 0.884 (95% confidence interval, 0.846-0.922) and 87.55%, respectively. The risk stratification was as follows: 0 to 2 points, malignancy rate of 11.11%, low suspicion; 3 to 10 points, malignancy rate of 86.77%, high suspicion. Conclusions: The risk-scoring model based on EBUS multimodal imaging can effectively evaluate metastatic LNs in lung cancer patients to support clinical decision making.

Characteristics and risk profiles of patients with pulmonary arterial or chronic thromboembolic pulmonary hypertension living permanently at >2500 m of high altitude in Ecuador.

Over 80 Mio people worldwide live >2500 m, including at least as many patients with pulmonary vascular disease (PVD), defined as pulmonary arterial or chronic thromboembolic pulmonary hypertension (PAH/CTEPH), as elsewhere (estimated 0.1‰). Whether PVD patients living at high altitude have altered disease characteristics due to hypobaric hypoxia is unknown. In a cross-sectional study conducted at the Hospital Carlos Andrade Marin in Quito, Ecuador, located at 2840 m, we included 36 outpatients with PAH or CTEPH visiting the clinic from January 2022 to July 2023. We collected data on diagnostic right heart catheterization, treatment, and risk factors, including NYHA functional class (FC), 6-min walk distance (6MWD), and NT-brain natriuretic peptide (BNP) at baseline and at last follow-up. Thirty-six PVD patients (83% women, 32 PAH, 4 CTEPH, mean ± SD age 44 ± 13 years, living altitude 2831 ± 58 m) were included and had the following baseline values: PaO2 8.2 ± 1.6 kPa, PaCO2 3.9 ± 0.5 kPa, SaO2 91 ± 3%, mean pulmonary artery pressure 53 ± 16 mmHg, pulmonary vascular resistance 16 ± 4 WU, 50% FC II, 50% FC III, 6MWD 472 ± 118 m, BNP 490 ± 823 ng/L. Patients were treated for 1628 ± 1186 days with sildenafil (100%), bosentan (33%), calcium channel blockers (33%), diuretics (69%), and oxygen (nocturnal 53%, daytime 11%). Values at last visit were: FC (II 75%, III 25%), 6MWD of 496 ± 108 m, BNP of 576 ± 5774 ng/L. Compared to European PVD registries, ambulatory PVD patients living >2500 m revealed similar blood gases and relatively low and stable risk factor profiles despite severe hemodynamic compromise, suggesting that favorable outcomes are achievable for altitude residents with PVD. Future studies should focus on long-term outcomes in PVD patients dwelling >2500 m.

Right ventricular-pulmonary arterial coupling in patients with first acute myocardial infarction: An emerging post-revascularization triage tool.

BACKGROUND: Tricuspid annular plane systolic excursion/pulmonary artery systolic pressure (TAPSE/PASP) is a non-invasive surrogate of right ventricular-pulmonary arterial (RV-PA) coupling, studied in chronic RV pressure overload syndromes. However, its prognostic utility in patients with acute myocardial infarction (AMI) that may cause acute RV pressure overload remains unexplored. OBJECTIVES: To determine predictors of RV-PA uncoupling in patients with first AMI and examine whether it could improve risk stratification for cardiovascular in-hospital mortality after revascularization. METHODS: Three-hundred consecutive patients with first AMI were prospectively studied (age 61.2±11.8, 24% females). An echocardiogram was performed 24 hours after successful revascularization and TAPSE/PASP was evaluated. Cardiovascular in-hospital mortality was recorded. RESULTS: The optimal cutoff value of TAPSE/PASP to determine cardiovascular in-hospital mortality was 0.49 mm/mmHg. RV-PA uncoupling was considered for patients with TAPSE/PASP ≤0.49 mm/mmHg. Left ventricular ejection fraction (LVEF) was independently associated with RV-PA uncoupling. A total of 23 (7.7%) patients died in-hospital despite successful revascularization. TAPSE/PASP was independently associated with in-hospital mortality, after adjustment for Global Registry of Cardiovascular Events (GRACE) risk score and LVEF (Odds Ratio 0.14, 95% Confidence Intervals [0.03-0.56], P-value 0.007). The prognostic value of a baseline model including GRACE risk score and NT-pro-BNP (χ2 26.55) was significantly improved by adding LVEF ≤40 % (χ2 44.71, P-value <0.001), TAPSE ≤17 mm (χ2 75.42, P-value <0.001) and TAPSE/PASP ≤0.49 mm/mmHg (χ2 101.74, P-value <0.001) for predicting cardiovascular in-hospital mortality. CONCLUSIONS: RV-PA uncoupling, assessed by echocardiographic TAPSE/PASP ≤0.49 mm/mmHg 24 hours after revascularization, may improve risk stratification for cardiovascular in-hospital mortality post first AMI.

Development and Validation of PRE-SARC (PREdiction of SARCopenia Risk in Community Older Adults) Sarcopenia Prediction Model.

OBJECTIVE: Reliable identification of high-risk older adults who are likely to develop sarcopenia is essential to implement targeted preventive measures and follow-up. However, no sarcopenia prediction model is currently available for community use. Our objective was to develop and validate a risk prediction model for calculating the 1-year absolute risk of developing sarcopenia in an aging population. METHODS: One prospective population-based cohort of non-sarcopenic individuals aged 60 years or older were used for the development of a sarcopenia risk prediction model and model validation. Sarcopenia was defined according to the 2019 Asian Working Group for Sarcopenia consensus. Stepwise logistic regression was used to identify risk factors for sarcopenia incidence within a 1-year follow-up. Model performance was evaluated using the area under the receiver operating characteristics curve (AUROC) and calibration plot, respectively. RESULTS: The development cohort included 1042 older adults, among whom 87 participants developed sarcopenia during a 1-year follow-up. The PRE-SARC (PREdiction of SARCopenia Risk in community older adults) model can accurately predict the 1-year risk of sarcopenia by using 7 easily accessible community-based predictors. The PRE-SARC model performed well in predicting sarcopenia, with an AUROC of 87% (95% CI, 0.83-0.90) and good calibration. Internal validation showed minimal optimism, with an adjusted AUROC of 0.85. The prediction score was categorized into 4 risk groups: low (0%-10%), moderate (>10%-20%), high (>20%-40%), and very high (>40%). The PRE-SARC model has been incorporated into an online risk calculator, which is freely accessible for daily clinical applications (https://sarcopeniariskprediction.shinyapps.io/dynnomapp/). CONCLUSIONS: In community-dwelling individuals, the PRE-SARC model can accurately predict 1-year sarcopenia incidence. This model serves as a readily available and free accessible tool to identify older adults at high risk of sarcopenia, thereby facilitating personalized early preventive approaches and optimizing the utilization of health care resources.

Prognoses and risk stratification of thrombus-associated events in heart failure patients without atrial fibrillation.

AIMS: We aim to assess the risk of thrombus-associated events (TAE) in patients with heart failure (HF) without atrial fibrillation (AF) and develop an effective scoring system for a risk stratification model. METHODS AND RESULTS: This retrospective study included 450 patients (median age 64.0 years, interquartile range [55.0, 75.0]; 31.6% women) hospitalized for HF without AF and atrial flutter, but with a left ventricular ejection fraction (LVEF) ≤ 55% and New York Heart Association (NYHA) functional class of III-IV. A median follow-up of 47 months was conducted. In the present study, TAE during follow-up was independently associated with both all-cause death [hazard ratio (HR) 1.756, 95% confidence interval (CI) 1.324-2.328, P < 0.001] and readmission for HF (HR 1.574, 95% CI 1.122-2.208, P = 0.009) after adjustment for covariates. Hypertension (HR 1.573, 95% CI 1.018-2.429, P = 0.041), atrial arrhythmia excluding AF (AAexAF) (HR 2.041, 95% CI 1.066-3.908, P = 0.031), previous ischaemic stroke (HR 2.469, 95% CI 1.576-3.869, P < 0.001), and vascular disease (HR 1.658, 95% CI 1.074-2.562, P = 0.023) were independently associated with TAE. Age (HR 1.021, 95% CI 1.008-1.033, P = 0.001), previous ischaemic stroke (HR 1.685, 95% CI 1.248-2.274, P = 0.001), LVEF ([10, 25] vs. [40, 55]) HR 1.925, 95% CI 1.311-2.826, P = 0.001; (25, 40] vs. (40, 55] HR 1.084, 95% CI 0.825-1.424, P = 0.563), and creatinine clearance rate (Ccr) (HR 0.991, 95% CI 0.986-0.996, P = 0.001) were independently associated with composite events of TAE and death (TAE-D). CHA2DS2VASc modestly predicted 5-year TAE [area under the receiver operating characteristic curves (AUC) 0.660, P < 0.001 compared with 0.5] and TAE-D (AUC 0.639, P < 0.001 compared with 0.5). (C)ACE, formed by incorporating AAexAF, LVEF, and Ccr into CHA2DS2VASc, had higher AUC for predicting 5-year TAE (0.694 vs. 0.660, P = 0.018) and TAE-D (0.708 vs. 0.639, P < 0.001) compared with CHA2DS2VASc. In patients with HF with reduced ejection fraction (HFrEF), (C)ACE and (C)ACEN [formed by incorporating NYHA into (C)ACE] had higher AUC compared with CHA2DS2VASc in predicting 5-year TAE (0.700 and 0.707 vs. 0.649, P = 0.013 and 0.030, respectively) and TAE-D (0.712 and 0.713 vs. 0.622, P < 0.001 and <0.001, respectively). The AUC did not improve statistically from (C)ACE to (C)ACEN (0.700 vs. 0.707, P = 0.600 for TAE; 0.712 vs. 0.713, P = 0.917 for TAE-D). CONCLUSIONS: In HF without AF, TAE during follow-up was associated with adverse prognoses. The independent risk factors of TAE or TAE-D improved CHA2DS2-VASc predictive ability, especially in patients with HFrEF. Our findings provide new evidence for TAE risk stratification in HF without AF, potentially guiding prophylactic anticoagulation.