Predictor Of All-cause Mortality Research Articles

Impact of Pre-Diagnostic Risk Factors on Short- and Long-Term Ovarian Cancer Survival Trajectories: A Longitudinal Observational Study.

Tumor- and treatment-related factors are established predictors of ovarian cancer survival. New studies suggest a differential impact of exposures on ovarian cancer survival trajectories (i.e., rapidly fatal to long-term disease). This study examined the impact of pre-diagnostic risk factors on short- and long-term ovarian cancer survival trajectories in the Canadian context. This population-based longitudinal observational study included women diagnosed with invasive epithelial ovarian cancer from 1995 to 2004 in Ontario. Data were obtained from medical records, interviews, and the provincial cancer registry. Extended Cox proportional hazard models estimated the association between risk factors and all-cause and ovarian cancer-specific mortality by survival time intervals (<3 years (i.e., short-term survival), 3 to <6 years, 6 to <10 years, and ≥10 years (i.e., long-term survival)). Among 1421 women, histology, stage, and residual disease were the most important predictors of all-cause mortality in all survival trajectories, particularly for short-term survival. Reproductive and lifestyle factors did not strongly impact short-term overall survival but were associated with long-term overall survival. As such, among long-term survivors, history of breastfeeding significantly decreased the risk of all-cause mortality (HR 0.65; 95% CI 0.46, 0.93; p < 0.05), whereas smoking history (HR 1.75; 95% CI 1.27, 2.40; p < 0.05) and obesity (HR 1.81; 95% CI 1.24, 2.65; p < 0.05) significantly increased the risk of all-cause mortality. The findings were consistent with ovarian cancer-specific mortality. These findings suggest that pre-diagnostic exposures differentially influence survival time following a diagnosis of ovarian cancer.

Risk factors for short-term all-cause mortality in patients with end stage renal disease: a scoping review

ObjectivesThere is a lack of prognostic information to guide the prediction of short-term all-cause mortality in patients with end-stage renal disease (ESRD). The aim was to review the risk factors that influenced the risk of short-term all-cause mortality in patients with ESRD.MethodsMEDLINE, Embase, PubMed, CINAHL, the Cochrane Library and Web of Science databases were searched for articles published between 2000 and 2020. Articles describing risk factors predicting short-term mortality (≤ 3 years) in patients with ESRD were included. Four reviewers independently performed title, abstract, full text screening and data extraction. Assessment of risk of bias was assessed using the Quality In Prognosis Studies (QUIPS) tool checklist.Results20,840 articles were identified and 113 papers were included for this review. Of the 113 papers, 6.2% included only peritoneal dialysis (PD) patients, 67.3% included only hemodialysis (HD) patients, 20.4% included both PD and HD patients, with the remaining papers featuring patients on conservative management or awaiting renal transplant. Risk factors were categorised into 13 domains: 1)demographics/ lifestyle, 2) comorbidities 3)intradialytic blood pressure, 4)biomarkers, 5)cardiovascular measurements, 6)frailty status, 7)medications, 8)treatment related indicators, 9)renal related parameters, 10)health status, 11)cause of ESRD, 12)access to healthcare care/ information and, 13)proxy measures for poor health. C-reactive protein(CRP), age, and functional status were observed to have higher percentage of instances of being significantly associated with all-cause mortality.ConclusionCommonly examined risk factors observed from this review may be used to build a general prognostic model for patients with ESRD, with specific treatment related risk factors added on to enhance the accuracy of the models.

Association of pulmonary hypertension with the outcome in patients undergoing edge-to-edge mitral valve repair

ObjectivesThe association of pulmonary hypertension (PH) with the outcome after mitral transcatheter edge-to-edge repair (M-TEER) focusing on the new ESC/ERS guidelines definition for PH.BackgroundPH is frequently found in patients with...

Predictive ability of both the healthy aging index and the frailty index for all-cause mortality.

We aimed to develop and assess a modified healthy aging index (HAI) among Chileans aged 60years and older and compare its predictive ability for all-cause mortality risk with the frailty index (FI). This prospective study analyzed data from the Chilean National Health Survey (CNHS) conducted in 2009-2010. We included 847 adults with complete data to construct the HAI and FI. The HAI comprised five indicators (lung function, systolic blood pressure, fasting glucose, cognitive status, and glomerular filtration rate), while the FI assessed frailty using a 36-item scale. HAI scores were calculated by summing the indicator scores, ranging from 0 to 10, with higher scores indicating poorer health. Receiver operating curves (ROC) and area under the curve (AUC) were used to assess predictive validity. Associations with all-cause mortality were assessed using Cox proportional hazard models adjusted by confounders. The mean HAI score was 4.06, while the FI score was 0.24. The AUC for mortality was higher for the HAI than the FI (0.640, 95% confidence interval (CI) 0.601 to 0.679 vs. 0.586, 95% CI 0.545 to 0.627). After adjusting for confounders, the FI showed a higher mortality risk compared to the HAI (2.63, 95% CI 1.76 to 3.51 vs. 1.16, 95% CI 1.08 to 1.26). The FI and HAI were valid predictors for all-cause mortality in the Chilean population. Integrating these indices into research and clinical practice can significantly enhance our capacity to identify at-risk individuals.

Prognostic impact of polypharmacy and discharge medications in octogenarians and nonagenarian patients with acute heart failure.

With the increasing frequency of heart failure (HF) in elderly patients, polypharmacy has become a major concern owing to its adverse outcomes. However, reports on the clinical impact of polypharmacy and discharge medications in hospitalized super-aged patients with acute HF are rare. Data from 682 patients aged 80years or older, hospitalized for treating acute HF, were analyzed. We recorded the number of medications at discharge and classified them into three groups: HF, non-HF cardiovascular, and non-cardiovascular medications. We investigated the correlation of polypharmacy, defined as daily administration of 10 or more medications at discharge, and the use of discharge medications with post-discharge prognosis. Polypharmacy was recorded in 24.3% of enrolled patients. Polypharmacy was not an independent predictor of all-cause mortality, the incidence of cardiac-related death, or HF-associated rehospitalization; however, the number of non-cardiovascular medications, multiple usage of potentially inappropriate medications, use of mineralocorticoid receptor antagonists, and doses of loop diuretics were associated with poor prognosis. Polypharmacy was significantly associated with higher mortality in patients with Barthel index ≥ 60 at discharge; hence, physical function at discharge was useful for the stratification of prognostic impacts of polypharmacy. The current study demonstrated that polypharmacy was not essentially associated with poor prognosis in super-aged patients with acute HF. Appropriate medications that consider the patient's physical function, rather than polypharmacy itself, are important for the management of HF.

Effect of Neutrophil-to-Lymphocyte Ratio on Post-TAVR Mortality and Periprocedural Pulmonary Hypertension.

To evaluate the impact of neutrophil-to-lymphocyte ratio (NLR) on periprocedural pulmonary hypertension (PH) and 3-month all-cause mortality in patients with aortic stenosis (AS) who underwent transcatheter aortic valve replacement (TAVR) and to develop a nomogram for predicting the mortality for these patients. 124 patients undergoing TAVR were categorized into three groups according to systolic pulmonary artery pressure (sPAP): Group I (no PH, n = 61) consisted of patients with no pre- and post-TAVR PH; Group II (improved PH, n = 35) consisted of patients with post-TAVR systolic pulmonary artery pressure (sPAP) decreased by more than 10 mmHg compared to pre-TAVR levels; and Group III (persistent PH, n = 28) consisted of patients with post-TAVR sPAP no decrease or less than 10 mmHg, or new-onset PH after the TAVR procedure. The risk of all-cause mortality within 3 months tended to be higher in Group II (11.4%) and Group III (14.3%) compared to Group I (3.3%) (P=0.057). The multinomial logistic regression analysis demonstrated a positive correlation between NLR and both improved PH (OR: 1.182, 95% CI: 1.036-1.350, P=0.013) and persistent PH (OR: 1.181, 95% CI: 1.032-1.352, P=0.016). Kaplan-Meier analysis revealed a significant association between higher NLR and increased 3-month all-cause mortality (16.1% vs. 3.1% in lower NLR group, P=0.021). The multivariable Cox regression analysis confirmed that NLR was an independent predictor for all-cause mortality within 3 months, even after adjusting for clinical confounders. A nomogram incorporating five factors (BNP, heart rate, serum total bilirubin, NLR, and comorbidity with coronary heart disease) was developed. ROC analysis was performed to discriminate the ability of the nomogram, and the AUC was 0.926 (95% CI: 0.850-1.000, P < 0.001). Patients with higher baseline NLR were found to be at an increased risk of periprocedural PH and all-cause mortality within 3 months after TAVR.

'Evaluation of beta-2-microglobulin and neuron-specific enolase as prognostic factors in patients over 65 years of age with frailty syndrome hospitalized for acute coronary syndrome'.

The aim of the study is to assess the value of beta-2-microglobulin (B2M) and neuron-specific enolase (NSE) as prognostic factors in the population of patients over 65 years of age with frailty hospitalized due to acute coronary syndrome (ACS). Patients aged ≥65 years with ACS were included. Assessment of frailty was carried out using the FRAIL scale. The measurement of NSE and B2M was carried out three times during hospitalization: (1) at the time of admission, (2) on the second day of hospitalization, (3) on the seventh day of hospitalization, or the day of discharge if it was before the seventh day. The primary endpoint was all-cause mortality, and the secondary endpoint was unscheduled rehospitalization. Of the 127 patients, frailty was identified in 39.3%. Multivariate analysis of variance showed significantly higher levels of NSE ( P = 0.012) and B2M ( P < 0.001) in patients with frailty compared to the nonfrail group and significant changes in marker levels during hospitalization - decreased NSE ( P < 0.001) and increased B2M levels ( P < 0.001). Elevated B2M-1 level was an independent marker of the occurrence of frailty [odds ratio (OR), 1.98 (1.09-4.00); P = 0.044], and the optimal cutoff point for the diagnosis of frailty was 2.85 mg/l [area under the curve (AUC), 0.718 (0.632-0.795)] with sensitivity 52% and specificity 84.4% ( P < 0.001). Elevated NSE-3 level was associated with all-cause mortality, and each 1 ng/ml increase in NSE-3 increased the risk of death by 1.07-fold [OR, 1.07 (1.03-1.10]). Meanwhile, elevated B2M-3 level was associated with unscheduled rehospitalization, and each 1 mg/l increase in B2M-3 increased the risk of unscheduled rehospitalization by 1.21-fold [OR, 1.21 (1.03-1.42)]. The Harrell's C-index for all-cause mortality was higher for NSE-3 [0.820 (95% confidence interval {CI}, 0.706-0.934)] compared to frailty assessed by the FRAIL scale [0.715 (95% CI, 0.580-0.850)], which means that additional NSE-3 assessment may improve the prediction of all-cause mortality. However, Uno's C-Statistic analysis showed that the difference was not statistically significant (Pr>chi-square 0.556). Harrell's C-index for unscheduled rehospitalization was higher for frailty assessed by the FRAIL scale compared to B2M-3. Monitoring NSE and B2M marker levels in patients over 65 years of age with frailty and ACS does not provide additional benefits in terms of prognostic ability compared to tests assessing frailty. B2M, assessed upon hospital admission and monitoring NSE and B2M levels during hospitalization may be considered in the diagnosis of frailty and risk stratification in a group of patients for whom currently available frailty diagnostic tools cannot be used.

Impact of Frailty on Heart Failure Prognosis: Is Sex Relevant?

Heart failure (HF) is one of the most frequent causes of hospital admission in elderly patients, especially in women, who present a high prevalence of geriatric syndromes like frailty. Studies have suggested that frailty and its impact may also differ between males and females. Understanding how frailty may differently affect HF patients depending on sex is therefore imperative for providing personalized care. The aim of this review is to summarize the role of sex in the prognostic impact of frailty in HF patients. Numerous studies have identified frailty as a significant predictor of all-cause mortality and hospital readmissions. A recent study of elderly HF out-patients demonstrated that while women had a higher prevalence of frailty, it was an independent predictor of mortality and readmission only in men. Moreover, another study revealed that physical frailty was associated with time to first clinical event among men but not among women. These results raise the question about why frailty affects differently HF prognosis in men and women. Women with HF present a higher prevalence of frailty, especially when it is considered as physical decline. Nevertheless, frailty affects differently HF prognosis in men and women. Women with HF present lower mortality than men and frailty is related with prognosis only in men. The different severity of HF between men and women and other hormonal, psychosocial, and clinical factors might be involved in this fact.

Prognostic value of native T1 and extracellular volume in patients with immunoglubin light-chain amyloidosis

BackgroundCardiac involvement in patients with immunoglubin light-chain amyloidosis (AL) is a major determinant of treatment choice and prognosis, and early identification of high-risk patients can initiate intensive treatment strategies to achieve better survival. This study aimed to investigate the prognostic value of native T1 and ECV in patients with AL-cardiac amyloidosis (CA).MethodsA total of 38 patients (mean age 59 ± 11 years) with AL diagnosed histopathologically from July 2017 to October 2021 were collected consecutively. All patients were performed 3.0-T cardiac magnetic resonance (CMR) including cine, T1 mapping, and late gadolinium enhancement (LGE). Pre- and post-contrast T1 mapping images were transferred to a dedicated research software package (CVI42 v5.11.3) to create parametric T1 and ECV values. In addition, clinical and laboratory data of all patients were collected, and patients or their family members were regularly followed up by telephone every 3 months. The starting point of follow-up was the time of definitive pathological diagnosis, and the main endpoint was all-cause death. Kaplan-Meier analysis and Cox proportional risk model were used to evaluate the association between native T1 and ECV and death in patients with CA.ResultsAfter a median follow-up of 27 (16, 37) months, 12 patients with CA died. Kaplan-Meier analysis showed that elevated native T1 and ECV were closely associated with poor prognosis in patients with CA. The survival rate of patients with ECV > 44% and native T1 > 1389ms were significantly lower than that of patients with ECV ≤ 44% and native T1 ≤ 1389ms (Log-rank P < 0.001), and was not associated with the presence of LGE. After adjusting for clinical risk factors and CMR measurements in a stepwise multivariate Cox regression model, ECV [risk ratio (HR):1.37, 95%CI: 1.09–1.73, P = 0.008] and native T1 (HR:1.01, 95%CI: 1.00-1.02, P = 0.037) remained independent predictors of all-cause mortality in patients with CA.ConclusionsBoth native T1 and ECV were independently prognostic for mortality in patients with CA, and can be used as important indicators for clinical prognosis assessment of AL.

Physical activity and Physical fitness in Prediction of all-cause Mortality and Age at Death in European Extinct Cohorts of middle-aged men followed for 60 Years.

A study of the power of physical activity (Phyac) and physical fitness (Fitscore) in predicting very long-term all-cause mortality and age at death (AD) is missing. A total of 5,482 middle-aged men were examined with measurement of several risk factors and followed for 60 years until virtual extinction of cohorts. Phyac in 3 classes was estimated from their type of work while Fitscore was derived from the linear combinations of levels of arm circumference, heart rate and vital capacity computed as a factor score by principal components analysis. Predictive power of these characteristics (adjusted for 5 traditional cardiovascular risk factors) was made by Cox models (for all-cause mortality) and multiple linear regression models (for AD). Single levels of the 3 indicators of fitness were highly related to the 3 levels of Phyac and of Fitscore. High levels of both Phyac and of Fitscore forced into the same models were associated with lower all-cause mortality and higher AD. Predictive power of Fitscore was systematically better than that of Phyac. Hazard ratios (high versus low) for all-cause mortality were 0.85 (Phyac) and 0.70 (Fitscore). Coefficients (all significant) were 2.25 years (Phyac) and 3.79 of AD by Fitscore. Fitscore was independently and significantly predictive of all-cause mortality for both first and second 30-year follow-up periods. Phyac and Fitscore are related and both showed important predictive power for all-cause mortality and AD. The role of Fitscore was more powerful and both characteristics seem to be expressions of health status.

Social frailty as a predictor of all-cause mortality and functional disability: a systematic review and meta-analysis

The association between social frailty and adverse health outcomes, especially mortality and functional disability, which are essential health outcomes, has not been systematically summarized or meta-analyzed. In this study, we conducted a systematic review and meta-analysis of the impact of social frailty on all-cause mortality and functional disability, while addressing the components of social frailty. In this study, social frailty was operationally defined in alignment with the previous literature, as follows: “a state of increased vulnerability to the interactive back-and-forth of the community, including general resources, social resources, social behaviors, and needs.” Hazard ratios or odds ratios described in each selected literature were used as the meta-analytic results. Considering the impact of social frailty on all-cause mortality, the hazard ratio was 1.96 (95% CI 1.20–3.19), indicating a significant association between the two but high heterogeneity. The hazard and odds ratios for the impact of social frailty on functional disability were 1.43 (95% CI 1.20–1.69) and 2.06 (95% CI 1.55–2.74), respectively. A significant association was found between social frailty and functional disability; both hazard and odds ratios were found, and low heterogeneity between these articles was observed. These results highlight the importance of assessing social frailty using more standardized methods and examining its effects on various health outcomes.

Performance in a Balance Test and Prediction of All-Cause Mortality in Community-Dwelling Elderly Ambulatory Individuals: A Systematic Review and Meta-analysis.

Objective: This systematic review and meta-analysis was performed to evaluate the association between an inability to perform a static balance test and mortality in community-dwelling older ambulatory individuals. Methods: PubMed, Embase, and Scopus were searched for relevant cohort studies. Hazard ratios (HR) were pooled (random-effect model). Meta-regression was performed with independent demographic variables (PROSPERO ID: CRD42022381137). Results: A total of 11,713 articles were screened and 15 were included. An inability to perform a static balance test was significantly associated with a higher risk of mortality irrespective of whether confounding variables were considered [HR, 1.14 (95% CI: 1.07-1.21); p < .001; i2, 87.96% (p < .01)] or not [HR, 1.11 (95% CI: 1.03-1.20); p = .01; i2, 95.28% (p < .01)] (both moderate GRADE evidence). Also, this association was correlated with progressive age. Conclusion: An inability to successfully complete a static balance test was significantly associated with a higher risk of mortality among community-dwelling older ambulatory individuals.

Epicardial adipose tissue as an independent predictor of long-term outcome in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement.

Accurate risk stratification is important to improve patient selection and outcome of patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). As epicardial adipose tissue (EAT) is discussed to be involved in cardiovascular disease, it could be useful as a marker of poor prognosis in patients with severe AS undergoing TAVR. A total of 416 patients diagnosed with severe AS by transthoracic echocardiography were assigned for TAVR and enrolled for systematic assessment. Patients underwent clinical surveys and 5-year long-term follow-up, with all-cause mortality as the primary endpoint. EAT volume was quantified on pre-TAVR planning CTs. Patients were retrospectively dichotomized at the median of 74 cm3 of EAT into groups with low EAT and high EAT volumes. Mortality rates were compared using Kaplan-Meyer plots and uni- and multivariable cox regression analyses. A total number of 341 of 416 patients (median age 80.9years, 45% female) were included in the final analysis. Patients with high EAT volumes had similar short-term outcome (p = 0.794) but significantly worse long-term prognosis (p = 0.023) compared to patients with low EAT volumes. Increased EAT volumes were associated with worse long-term outcome (HR1.59; p = 0.031) independently from concomitant cardiovascular risk factors, general type of AS, and functional echocardiography parameters of AS severity (HR1.69; p = 0.013). Increased EAT volume is an independent predictor of all-cause mortality in patients with severe AS undergoing TAVR. It can be easily obtained from pre-TAVR planning CTs and may thus qualify as a novel marker to improve prognostication and management of patient with severe AS. DRKS, DRKS00024479.

Albumin-bilirubin score as a predictor of all-cause mortality in patients with hepatitis B virus infection: An analysis of National Health and Nutrition Examination Survey (NHANES) 1999–2018

ObjectivesThe Albumin-Bilirubin (ALBI) score has been widely used to assess the prognosis in patients with cirrhosis and hepatocellular carcinoma. This study aimed to analyze the relationship between ALBI score and all-cause mortality in patients with hepatitis B virus (HBV) infection in general. MethodsPatients aged ≥ 18 years with previous or current HBV infection from the National Health and Nutrition Examination Survey (NHANES) in the United States between 1999 and 2018 were enrolled in this retrospective cohort study. Weight univariate and multivariate Cox regression models were used to assess the relationship between ALBI score and all-cause mortality. The area under the receiver operating characteristic curve (AUC) was utilized to assess the predictive effect of ALBI score for all-cause mortality. ResultsA total of 3,666 patients were included, of whom 925 (23.53 %) patients died. Compared with ALBI score ≤ -2.6, HBV-infected patients with ALBI score > -2.6 [hazard ratio (HR) = 1.75; 95 % confidence interval (CI): 1.43–2.14] were corrected with a higher all-cause mortality risk after adjusting for confounders. Stratified analyses showed that higher ALBI score was related to a higher risk of all-cause mortality in different patients with HBV infection (All P < 0.05). Furthermore, the ALBI score had good predictive ability for 1-year (AUC = 0.816, 95 %CI: 0.754–0.878), 3-year (AUC = 0.808, 95 %CI: 0.775–0.841), 5-year (AUC = 0.809, 95 %CI: 0.783–0.835), and 10-year (AUC = 0.806, 95 %CI: 0.784–0.827) all-cause mortality. ConclusionHigher ALBI score was related to a higher risk of all-cause mortality in patients with HBV infection, and the ALBI score showed a good predictive effect for short- and long-term all-cause mortality.

Do LUTS Predict Mortality? An Analysis Using Random Forest Algorithms.

To evaluate a random forest (RF) algorithm of lower urinary tract symptoms (LUTS) as a predictor of all-cause mortality in a population-based cohort. A population-based cohort of 3143 men born in 1924, 1934, and 1944 was evaluated using a mailed questionnaire including the Danish Prostatic Symptom Score (DAN-PSS-1) to assess LUTS as well as questions on medical conditions and behavioral and sociodemographic factors. Surveys were repeated in 1994, 1999, 2004, 2009 and 2015. The cohort was followed-up for vital status until the end of 2018. RF uses an ensemble of classification trees for prediction with a good flexibility and without overfitting. RF algorithms were developed to predict the five-year mortality using LUTS, demographic, medical, and behavioral factors alone and in combinations. A total of 2663 men were included in the study, of whom 917 (34%) died during follow-up (median follow-up time 15.0 years). The LUTS-based RF algorithm showed an area under the curve (AUC) 0.60 (95% CI 0.52-0.69) for five-year mortality. An expanded RF algorithm, including LUTS, medical history, and behavioral and sociodemographic factors, yielded an AUC 0.73 (0.65-0.81), while an algorithm excluding LUTS yielded an AUC 0.71 (0.62-0.78). An exploratory RF algorithm using LUTS can predict all-cause mortality with acceptable discrimination at the group level. In clinical practice, it is unlikely that LUTS will improve the accuracy to predict death if the patient's background is well known.

High-sensitivity C-reactive protein is a predictor of all-cause mortality in a rural Japanese population.

High-sensitivity C-reactive protein (hsCRP) is a sensitive marker of inflammation. This study aimed to determine whether increased hsCRP levels are associated with all-cause mortality rate. We examined data for participants from the 2002 Nomura Cohort Study who attended follow-ups for 20 years (follow-up rate: 93.3%). Of these, 793 were male (aged 61 ± 14 years) and 1040 were female (aged 63 ± 11 years). The Japanese Basic Resident Registry provided data on adjusted relative hazards for all-cause mortality. The data were subjected to a Cox regression analysis using a time variable of age and confounding risk factors. The median (interquartile range) follow-up period was 6548 days (6094-7452 days). The follow-up confirmed that there were 632 (34.8%) deaths, of which 319 were male (40.2% of all males) and 313 were female (30.6% of all females). Multivariable-adjusted hazard ratio(1.27; 95% confidence interval, 1.01-1.59) in the highest hsCRP category was also significantly higher compared with reference. A higher hsCRP was associated with a greater risk of all-cause mortality in male participants aged ≥65 years, a BMI < 25 kg/m2 , and no history of CVD or diabetes, and this association was particularly significant among participants with both of the latter two risk factors (p = 0.004 and 0.022 for interaction, respectively). Our results indicate a significant association between hsCRP levels and all-cause mortality in a rural Japanese population. Specifically, hsCRP appears to be a crucial biomarker for predicting long-term survival, particularly among older persons.

Abstract TP120: Racial Disparities and Predictors of All-Cause Mortality in Postmenopausal Women Hospitalized for Stroke: A Nationwide Analysis, 2019

Background: Racial disparities in stroke prevalence and outcomes have been well documented in previous studies, but there is not sufficient data based on post-menopausal women. In this study, we aim to analyze stroke hospitalization rates and subsequent mortality rates by race among females aged 55 years and older. We also sought to identify independent predictors of mortality based on race. Methods: We queried the 2019 National Inpatient Sample to identify stroke hospitalizations in women aged &gt;55 years by using ICD-10 CM codes. Demographics were analyzed after stratifying the population by race. Multivariable regression analysis was performed taking stroke admission rates and mortality by race as a primary outcome of interest and the co-primary outcome was independent predictors of mortality by race. Results: A total of 140,805 patients with a median age of 76 [67-85] were included in the study of which 66.9% were white, 16.5% black, 7.5% Hispanic, 3.6% Asian/Pacific Islander 0.6% Native Americans, and 2.5% in the other race category. Blacks (52.8%) and Native Americans (47.9%) were significantly present in the lowest national household income quartile compared to Asians/Pacific Islanders (26.1%). COPD (OR: 1.19 95%, p- 0.017), cancer (OR: 1.27 p - 0.030), and age at admission (OR: 1.02 p &lt;0.001) were independent positive predictors for all-cause mortality in whites, while complicated hypertension (OR: 2.64 p - 0.039), and age at admission (OR: 1.04 p - 0.004) were the independent positive predictors for the Asian population. Conclusion: Among post-menopausal women hospitalized with stroke, all-cause mortality was the highest in Asians, followed by whites and Hispanics. Interventions and targeted strategies can be developed to address these disparities, further studies should be conducted to investigate the causes and etiologies of these disparities.

Respiratory-related leg movement index as a predictor of all-cause mortality: the MrOS sleep study

Respiratory-related leg movement index as a predictor of all-cause mortality: the MrOS sleep study

Prognosis of pacing-dependent patients with cardiovascular implantable electronic devices.

Data on the prognostic significance of pacing dependency in patients with cardiovascular implantable electronic devices (CIEDs) are sparse. The prognostic significance of pacing dependency defined as absence of an intrinsic rhythm ≥ 30 bpm was determined in 786 patients with CIEDs at the authors' institution using univariate and multivariate regression analysis to identify predictors of all-cause mortality. During 49months median follow-up, death occurred in 63 of 130 patients with pacing dependency compared to 241 of 656 patients without pacing dependency (48% versus 37%, hazard ratio [HR] 1.34; 95% confidence interval [CI]: 1.02-1.78, P = 0.04). Using multivariate regression analysis, predictors of all-cause mortality included age (HR 1.07; 95% CI: 1.05-1.08, P < 0.01), history of atrial fibrillation (HR 1.32, 95% CI: 1.03-1.69, P < 0.01), chronic kidney disease (HR 1.28; 95% CI: 1.00-1.63, P = 0.048) and New York Heart Association (NYHA) class ≥ III (HR 2.00; 95% CI: 1.52-2.62, P < 0.01), but not pacing dependency (HR 1.15; 95% CI: 0.86-1.54, P = 0.35). In contrast to age, atrial fibrillation, chronic kidney disease and heart failure severity as indexed by NYHA functional classIII orIV, pacing dependency does not appear to be an independent predictor of all-cause mortality in patients with CIEDs.

Machine Learning Multicenter Risk Model to Predict Right Ventricular Failure After Mechanical Circulatory Support

The existing models predicting right ventricular failure (RVF) after durable left ventricular assist device (LVAD) support might be limited, partly due to lack of external validation, marginal predictive power, and absence of intraoperative characteristics. To derive and validate a risk model to predict RVF after LVAD implantation. This was a hybrid prospective-retrospective multicenter cohort study conducted from April 2008 to July 2019 of patients with advanced heart failure (HF) requiring continuous-flow LVAD. The derivation cohort included patients enrolled at 5 institutions. The external validation cohort included patients enrolled at a sixth institution within the same period. Study data were analyzed October 2022 to August 2023. Study participants underwent chronic continuous-flow LVAD support. The primary outcome was RVF incidence, defined as the need for RV assist device or intravenous inotropes for greater than 14 days. Bootstrap imputation and adaptive least absolute shrinkage and selection operator variable selection techniques were used to derive a predictive model. An RVF risk calculator (STOP-RVF) was then developed and subsequently externally validated, which can provide personalized quantification of the risk for LVAD candidates. Its predictive accuracy was compared with previously published RVF scores. The derivation cohort included 798 patients (mean [SE] age, 56.1 [13.2] years; 668 male [83.7%]). The external validation cohort included 327 patients. RVF developed in 193 of 798 patients (24.2%) in the derivation cohort and 107 of 327 patients (32.7%) in the validation cohort. Preimplant variables associated with postoperative RVF included nonischemic cardiomyopathy, intra-aortic balloon pump, microaxial percutaneous left ventricular assist device/venoarterial extracorporeal membrane oxygenation, LVAD configuration, Interagency Registry for Mechanically Assisted Circulatory Support profiles 1 to 2, right atrial/pulmonary capillary wedge pressure ratio, use of angiotensin-converting enzyme inhibitors, platelet count, and serum sodium, albumin, and creatinine levels. Inclusion of intraoperative characteristics did not improve model performance. The calculator achieved a C statistic of 0.75 (95% CI, 0.71-0.79) in the derivation cohort and 0.73 (95% CI, 0.67-0.80) in the validation cohort. Cumulative survival was higher in patients composing the low-risk group (estimated <20% RVF risk) compared with those in the higher-risk groups. The STOP-RVF risk calculator exhibited a significantly better performance than commonly used risk scores proposed by Kormos et al (C statistic, 0.58; 95% CI, 0.53-0.63) and Drakos et al (C statistic, 0.62; 95% CI, 0.57-0.67). Implementing routine clinical data, this multicenter cohort study derived and validated the STOP-RVF calculator as a personalized risk assessment tool for the prediction of RVF and RVF-associated all-cause mortality.