Predictor Of Mortality Research Articles

Role of lymphocyte-to-monocyte ratio as a predictive marker for diabetic coronary artery disease: A cross-sectional study

BACKGROUND The lymphocyte to monocyte ratio (LMR) is considered a marker of systemic inflammation in cardiovascular disease and acts as predictor of mortality in coronary artery disease. AIM To investigate the predictive role of LMR in diabetic coronary artery disease patients. METHODS This cross-sectional study was conducted at tertiary care super-specialty hospital at New Delhi, India. A total of 200 angiography-proven coronary artery disease (CAD) patients were enrolled and grouped into two categories: Group I [CAD patients with type 2 diabetes mellitus (T2DM) and glycated hemoglobin (HbA1c) levels ≥ 6.5%], and Group II (CAD patients without T2DM and HbA1c levels < 6.5%). Serum lipoproteins, HbA1c, and complete blood count of enrolled patients were analyzed using fully automatic analyzers. RESULTS The logistic regression analysis showed an odds ratio of 1.48 (95%CI: 1.28-1.72, P < 0.05) for diabetic coronary artery disease patients (Group I) in unadjusted model. After adjusting for age, gender, diet, smoking, and hypertension history, the odds ratio increased to 1.49 (95%CI: 1.29-1.74, P < 0.01) in close association with LMR. Further adjustment for high cholesterol and triglycerides yielded the same odds ratio of 1.49 (95%CI: 1.27-1.75, P < 0.01). Receiver operating characteristic curve analysis revealed 74% sensitivity, 64% specificity, and 0.74 area under the curve (95%CI: 0.67-0.80, P < 0.001), suggesting moderate predictive accuracy for diabetic CAD patients. CONCLUSION LMR showed positive association with diabetic coronary artery disease, with moderate predictive accuracy. These findings have implications for improving CAD management in diabetics, necessitating further research and targeted interventions.

Mortality Risk Assessment Using Deep Learning-Based Frequency Analysis of EEG and EOG in Sleep

Abstract Study Objectives To assess whether the frequency content of electroencephalography (EEG) and electrooculography (EOG) during nocturnal polysomnography (PSG) can predict all-cause mortality. Methods Power spectra from PSGs of 8,716 participants, included from the MrOS Sleep Study and the Sleep Heart Health Study (SHHS), were analyzed in deep learning-based survival models. The best-performing model was further examined using SHapley Additive Explanation (SHAP) for data-driven sleep-stage specific definitions of power bands, which were evaluated in predicting mortality using Cox Proportional Hazards models. Results Survival analyses, adjusted for known covariates, identified multiple EEG frequency bands across all sleep stages predicting all-cause mortality. For EEG, we found an all-cause mortality hazard ratio (HR) of 0.90 (CI95% 0.85–0.96) for 12–15 Hz in N2, 0.86 (CI95% 0.82–0.91) for 0.75–1.5 Hz in N3, and 0.87 (CI95% 0.83–0.92) for 14.75–33.5 Hz in REM sleep. For EOG, we found several low-frequency effects including an all-cause mortality HR of 1.19 (CI95% 1.11–1.28) for 0.25 Hz in N3, 1.11 (CI95% 1.03–1.21) for 0.75 Hz in N1, and 1.11 (CI95% 1.03–1.20) for 1.25–1.75 Hz in Wake. The gain in the concordance index (C-index) for all-cause mortality is minimal, with only a 0.24% increase: The best single mortality predictor was EEG N3 (0-0.5 Hz) with C-index of 77.78% compared to 77.54% for confounders alone. Conclusion Spectral power features, possibly reflecting abnormal sleep microstructure, are associated with mortality risk. These findings add to a growing literature suggesting that sleep contains incipient predictors of health and mortality.

Prevalence and short-term clinical impacts of new-onset diabetes mellitus among patients with COVID-19 in jazan region, Saudi Arabia

BackgroundDiabetes Mellitus is a major predictor for severity and mortality that is increased by 50% in COVID-19 infection. The aim of this study is to estimate the prevalence of new-onset DM among patients with COVID-19 and examined the short clinical outcomes of the disease.MethodThis is a retrospective study of revising electronic medical records to assess the prevalence of new-onset DM in COVID-19 patients and its impact on the severity of the disease. Adult patients with confirmed COVID-19 during the period from June 2020 to December 2021 were enrolled.Results725 patients were included. 53.8% of them were males and 46.2 were females, the mean age was 43.35 ± 16.76. 13.2% were diabetics; 2.2% with preexisting DM and 11.0% had new-onset DM. 6.34% had coexisting medical conditions. DKA at presentation was observed in 6 patients (0.8%) of newly diagnosed DM. There is a significant correlation between age and family history (FH), and BMI and new-onset DM (P < 0.05). The overall mortality rate was 2.2%, and it was significantly higher in diabetics in comparison to non-diabetics (P < 0.001). 8.6% had persistent hyperglycemia after 4 months of follow-up.ConclusionThe prevalence of COVID-19 related new-onset DM was correlated significantly with disease severity and mortality rate. Age, FH, and BMI, were the major predictors. We recommend that frequent monitoring of blood glucose for patients with COVID-19 infections to detect DM, therefore, prompt treatment can be initiated.

Cerebrospinal fluid lactate levels as a prognostic indicator in HIV-negative patients with cryptococcal meningitis: a retrospective cohort study

Abstract Background Cryptococcal meningitis (CM) is a severe central nervous system infection. In patients with human immunodeficiency virus (HIV) infections and coexisting CM, elevated baseline cerebrospinal fluid (CSF) lactate levels can predict increased mortality. However, the CSF lactate level’s significance in HIV-negative patients with CM remains unclear, necessitating further investigation to elucidate the potential distinctions and enhance patient management. This study investigated the CSF lactate level significance in HIV-negative patients with CM. Methods This retrospective study utilized data from the clinical databases of patients who underwent lumbar punctures at a medical center in Kaohsiung City, Southern Taiwan. Demographic data, CSF lactate levels, routine CSF analyses, and hematological and neurological findings were evaluated. The optimal CSF lactate threshold value was determined using the Youden index. Results This retrospective study included 70 patients with CM, among whom 44 (63%) and 26 (37%) tested negative and positive for HIV, respectively. The group without HIV exhibited higher CSF lactate levels, with an optimal CSF lactate cut-off point for predicting 90-day mortality of 7.935 mmol/L, resulting in significant predictive accuracies (area under the curve, 0.755; sensitivity, 57.1%; specificity, 100%); this value was an independent mortality predictor in HIV-negative patients. In HIV-negative patients with CM, CSF lactate levels ≥7.935 mmol/L correlated with higher mortality rates but without statistical significance. All HIV-negative patients with CM and CSF lactate levels ≥7.935 mmol/L died within 3 months of admission. Conclusions HIV-negative patients with CM had elevated CSF lactate levels that correlated with adverse outcomes, enabling early identification of high-risk individuals.

Galectin-3 Predicts Long-Term Risk of Cerebral Disability and Mortality in Out-of-Hospital Cardiac Arrest Survivors

Background: Out-of-hospital cardiac arrest (OHCA) is associated with high mortality and cerebral disability in survivors. Current models of risk prediction and survival are mainly based on resuscitation duration. We examined the prognostic value of circulating biomarkers in predicting mortality and severe cerebral disability for OHCA survivors, alongside traditional clinical risk indicators. Methods: Biomarkers including BNP, troponin I, and galectin-3 were measured at hospital admission in resuscitated OHCA patients. Prognostic significance for mortality and cerebral disability involving circulating biomarkers, resuscitation duration, demographics, and laboratory and clinical characteristics was examined via univariate and multivariate Cox proportional hazards regression models. The incremental prognostic value of the index covariates was examined through model diagnostics, focusing on the Akaike information criterion (AIC) and Harrell’s concordance statistic (c-statistic). Results: In a combinatorial analysis of 144 OHCA survivors (median follow-up 5.7 years (IQR 2.9–6.6)), BNP, galectin-3, arterial pH, and resuscitation time were significant predictors of all-cause death and severe cerebral disability, whereas troponin I levels were not. Multivariate regression, adjusting for BNP, arterial pH, and resuscitation time, identified galectin-3 as an independent predictor of long-term mortality. Multiple linear regression models also confirmed galectin-3 as the strongest predictor of cerebral disability. The incorporation of galectin-3 into models for predicting mortality and cerebral disability enhanced fit and discrimination, demonstrating the incremental value of galectin-3 beyond traditional risk predictors. Conclusions: Galectin-3 is a significant, independent long-term risk predictor of cerebral disability and mortality in OHCA survivors. Incorporating galectin-3 into current risk stratification models may enhance early prognostication and guide targeted clinical interventions.

Bladder transitional cell carcinoma anatomic primary site as a predictor of survival and mortality: a population-based retrospective cohort study

Background: Bladder cancer is a heterogeneous disease with varying prognostic outcomes based on the primary tumor site within the bladder. This study aims to evaluate the impact of tumor location on overall survival and cancer-specific survival in bladder cancer patients. Methods: We conducted a retrospective cohort study using data from the Surveillance, Epidemiology, and End Results database. Patients with primary transitional cell carcinoma of the bladder were categorized based on their tumor locations. Survival outcomes were assessed using Kaplan-Meier analysis and Cox proportional hazards regression models, adjusted for age, sex, race, cancer stage, and treatment modalities. Additionally, binary logistic regression models were employed to predict overall mortality (OM) and cancer-specific mortality (CSM) at 1, 5, and 10 years. Results: The study included 107,909 patients diagnosed with primary bladder cancer between 2000 and 2021. Significant differences in survival outcomes were observed across different tumor sites. Bladder cancer originating in the urachus had the worst OS before 100 months and the worst CSS overall. Tumors in the anterior wall showed the worst OS after 100 months. In the Cox multivariable analysis, anterior wall tumors were associated with a 1.513-fold increased risk of death compared to lateral wall tumors. The binary logistic regression models showed that anterior wall tumors predicted the highest OM and CSM at 1 year, while urachal tumors had the worst outcomes at 5 and 10 years. Conclusion: The primary site of bladder cancer is a significant predictor of survival outcomes, with tumors in the urachus and anterior wall associated with poorer prognosis. These findings underscore the importance of considering tumor location in the prognosis and management of bladder cancer. Future studies should aim to validate these findings in more diverse populations and explore the underlying biological mechanisms that drive these differences.

Assessing the Predictive Utility of the C-Reactive Protein-to-Lymphocyte Ratio for Mortality in Isolated Traumatic Brain Injury: A Single-Center Retrospective Analysis

Introduction: Early identification of high-risk traumatic brain injury (TBI) patients is crucial for optimizing treatment strategies and improving outcomes. The C-reactive protein-to-lymphocyte ratio (CLR) reflects systemic immunology and inflammation function and serves as a new biomarker for patient stratification. This study aimed to assess the predictive value of the CLR for mortality in patients with isolated moderate to severe TBI. Methods: A retrospective analysis of trauma registry data from 2009 to 2022 was conducted, including 1641 adult patients with isolated moderate to severe TBI. Patient demographics, the CLR, injury characteristics, and outcomes were compared between deceased and surviving patients. Univariate and multivariate analyses were performed to identify mortality risk factors. The optimal CLR cut-off value for predicting mortality was determined using receiver operating characteristic (ROC) curve analysis. Results: The CLR was significantly higher in deceased patients compared to survivors (60.1 vs. 33.9, p &lt; 0.001). The optimal CLR cut-off value for predicting mortality was 54.5, with a sensitivity of 0.328 and a specificity of 0.812. The area under the ROC curve was 0.566, indicating poor discriminative ability. In the multivariate analysis, the CLR was not a significant independent predictor of mortality (OR 1.03, p = 0.051). After propensity score matching to attenuate the difference in baseline characteristics, including sex, age, comorbidities, conscious level, and injury severity, the high-CLR group (CLR ≥ 54.5) did not have significantly higher mortality compared to the low-CLR group (CLR &lt; 54.5). Conclusion: While the CLR was associated with mortality in TBI patients, it demonstrated poor discriminative ability as a standalone predictor. The association between a high CLR and worse outcomes may be primarily due to other baseline patient and injury characteristics, rather than the CLR itself.

Relationship between weight-adjusted-waist index and all-cause and cardiovascular mortality in individuals with type 2 diabetes.

To investigate the relationship between the weight-adjusted-waist index (WWI) and all-cause mortality as well as cardiovascular mortality in individuals with type 2 diabetes. We used data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018 and the UK Biobank database. Restricted cubic spline curves and Cox proportional hazards models were employed to assess hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause mortality. In the UK Biobank database, compared with the lowest WWI quartile, the HR for all-cause and cardiovascular death in the highest quartile was 1.846 (95% CI 1.687-2.019) and 2.118 (95% CI 1.783-2.517), respectively, in the fully adjusted model. In the NHANES database, compared with the lowest WWI quartile, the highest quartile had an HR of 1.727 (95% CI 1.378-2.163) for all-cause death and 1.719 (95% CI 1.139-2.595) for cardiovascular death in the fully adjusted model. Our study indicates that WWI has a long-term synergistic negative impact on all-cause mortality and cardiovascular mortality in individuals with type 2 diabetes. The WWI is an independent predictor of mortality in individuals with type 2 diabetes.

Efficacy of Double Valve Replacement/Repair in Patients with Reduced Left Ventricular Ejection Fractions

Introduction: A reduced left ventricular ejection fraction (LVEF) is a known risk factor for double valve replacement or aortic valve replacement in combination with concomitant mitral valve repair (DVR) and is associated with high morbidity and mortality rates. In this study, we sought to analyze the 30-day mortality and long-term survival rates of patients with reduced LVEFs. Methods: A multicenter, retrospective, observational cohort study of patients who underwent DVR was performed at four centers from January 2016 to December 2021. LVEFs were categorized as 41%–50% (n = 120) or ≤40% (n = 58). For the effects of risk factors on 30-day mortality, binary logistic regression was performed. Survival rates were assessed with the Kaplan–Meier method. Results: A total of 178 patients who underwent DVR were included in this study, of whom 67.42% (n = 120) had LVEFs ranging from 41–50% and 32.58% (n = 58) had LVEFs ≤40%. More mechanical valves and tricuspid valve-forming rings were applied in the LVEF ≤40% group (68.97% versus 53.33%, p = 0.047; 31.03% versus 10.83%, p = 0.001). The 30-day mortality rates of DVR patients with LVEFs ranging from 41–50% and ≤40% were 8.33% and 17.24%, respectively (p = 0.078). During the follow-up period, there were no significant differences in long-term survival (log rank p = 0.75). On multivariable logistic regression analysis, age &gt;65 years [odds ratio (OR): 5.559, 95% confidence interval (CI): 1.668–18.524, p = 0.005] and cardiopulmonary bypass (CPB) duration &gt;200 min (OR: 5.031, 95% CI: 1.773–14.277, p = 0.002) were significantly associated with the likelihood of 30-day mortality. Conclusions: Although the differences in 30-day mortality and long-term survival rates between DVR patients with LVEFs ranging from 41–50% and ≤40% were not statistically significant in our cohort, an age &gt;65 years and a CPB duration &gt;200 min were predictors of 30-day mortality.

The critical role of cardiorespiratory fitness in disease prevention.

Cardiorespiratory fitness (CRF) has been increasingly recognized in recent years as an important predictor of risk for adverse outcomes in numerous chronic conditions. In fact, a growing body of epidemiological and clinical evidence demonstrates that CRF is a potentially stronger predictor of mortality than established risk factors such as smoking, hypertension, hyperlipidemia, and type 2 diabetes. Moreover, adding CRF to these traditional risk factors significantly improves the reclassification of risk for adverse outcomes. The utility of CRF now extends far beyond all-cause and cardiovascular mortality to include the prevention and treatment of numerous other chronic conditions; CRF has been demonstrated to have a mitigating influence in as many as 40 such conditions. Herein we discuss the impact of CRF in the prevention of chronic disease in both adults and children. This discussion includes recent data on interactions between CRF and aging, obesity, statin use, incidence of diabetes, and the impact of CRF and physical activity patterns in adolescents including mental health, scholastic achievement, and cardiometabolic health. Finally, we discuss how CRF, as an essential vital sign, can be implemented in clinical practice.

Physician–patient racial concordance and newborn mortality

The racial gap in infant mortality is a pressing public-health concern, and [B. N. Greenwood et al., Proc. Natl. Acad. Sci. U.S.A. 117, 21194-21200 (2020), 10.1073/pnas.1913405117] suggest that Black newborns are more likely to survive if cared for by Black physicians after birth, even in models that control for numerous variables, including hospital and physician fixed effects, and the 65 most common comorbidities affecting newborns (as described by International Classification of Disease codes). We acquired the data used in the study, covering Florida hospital discharges from 1992 through the third quarter of 2015, to replicate and extend the analysis. We find that the magnitude of the concordance effect is substantially reduced after controlling for diagnoses indicating very low birth weight (<1,500 g), which are a strong predictor of neonatal mortality but not among the 65 most common comorbidities. In fact, the estimated effect is near zero and statistically insignificant in the expanded specifications that control for very low birth weight and include hospital and physician fixed effects.

Association between triglyceride glucose-body mass index and all-cause mortality in critically ill patients with acute pancreatitis

This study delves into the correlation between the triglyceride glucose-body mass index (TyG-BMI) index upon hospital admission and clinical outcomes among this patient population. We investigated the association between TyG-BMI at hospital admission and clinical outcomes in this patient group, and analyzed data from the Medical Information Mart for Intensive Care IV database, identifying acute pancreatitis (AP) patients admitted to ICUs and stratifying them by TyG-BMI quartiles. We assessed the relationship between TyG-BMI and mortality (both in-hospital and ICU) using Cox proportional hazards regression and restricted cubic splines. The cohort included 419 patients, average age 56.34 ± 16.62 years, with a majority being male (61.58%). Hospital and ICU mortality rates were 11.93% and 7.16%, respectively. Higher TyG-BMI was positively correlated with increased all-cause mortality. Patients in the highest TyG-BMI quartile had significantly greater risks of in-hospital and ICU mortality. An S-shaped curve in the spline analysis indicated a threshold effect at a TyG-BMI of 243 for increased in-hospital mortality risk. TyG-BMI is a reliable predictor of both in-hospital and ICU mortality in severely ill AP patients, suggesting its utility in enhancing risk assessment and guiding clinical interventions for this vulnerable population.

Outcomes after SynCardia® temporary total artificial heart implantation: A 20-year single-center experience in 196patients.

The SynCardia® temporary total artificial heart (TAH) serves as a mechanical circulatory support device for patients suffering from irreversible biventricular failure. This retrospective study analyzed 196 consecutive patients who underwent TAH implantation at our center from 2001 to 2021. We assessed survival rates and all-cause mortality during TAH support, including survival post-heart transplantation. The median age of patients was 55 years, with 88% being male. The primary diagnoses included cardiomyopathy (43.9%), acute myocardial infarction (26.5%), and postcardiotomy heart failure (15.5%). At implantation, 87.2% of patients were classified as INTERMACS Profile 1. The median duration of support was 96 days (IQR: 23-227). Survival rates at 1, 6, and 12 months were 72%, 41%, and 34%, respectively. Postoperative rethoracotomy was necessary in 44.4% of patients; 39.3% experienced neurological events and 24.6% developed gastrointestinal bleeding. Overall, 64.8% of patients died while on support, primarily due to multiple organ failure (55.9%). Factors such as older age, higher bilirubin levels, postcardiotomy and specific underlying diagnoses were independent predictors of mortality during TAH support. On a positive note, 35.2% of patients underwent successful heart transplants, with 1-, 5-, and 10-year posttransplant survival rates of 65%, 58%, and 51%, respectively. While high mortality rates persist among patients with biventricular failure, the SynCardia® TAH offers a viable interim solution for critically ill patients, particularly those who can be successfully bridged to heart transplantation.

Differential prognostic value of residual nodal burden in breast cancer subtypes.

Residual cancer burden (RCB) index after neoadjuvant chemotherapy (NAC) is highly prognostic in patients with breast cancer (BC) but does not account for subtype or the precise impact of residual nodal burden (RNB). We aimed to precisely define the effect of RNB on survival by subtypes. Adult women with non-metastatic BC diagnosed from 2006 to 2021 in the National Cancer Database (NCDB) who received NAC followed by surgery within 8months were included. RNB was also evaluated as a predictor of mortality with multivariable logistic regression. Kaplan-Meier analyses were performed to compare overall survival. 51,917 patients were included. After adjustment, ypN stage was the strongest predictor of mortality, with an odds ratio (OR) of 2.24 (95% CI 2.08-2.41) for ypN1 vs ypN0 and increased with increasing nodal burden-ypN2 vs ypN0 OR 5.03, 95% CI 4.60-5.51 and ypN3 vs ypN0 OR 8.85, 95% CI 7.88-9.93. Stratification of survival curves with higher RNB is most pronounced for triple-negative breast cancer (TNBC) with an absolute difference of 64% in 5-year overall survival between ypN0 and ypN3 patients, and lowest for the ER+/HER2- subtype with a 25% absolute difference in 5-year OS between ypN0 and ypN3 patients. On interaction analysis, ypN status was a stronger predictor of mortality for the TNBC subtype compared to other subtypes. RNB has a significantly different impact on survival by BC subtypes. Future study of optimal therapeutic strategies for patients with residual nodal disease after NAC should account for subtype-specific differences in prognosis.

Evaluating the role of biological age in osteoporosis risk among middle-aged and older adults: A nationwide perspective

ObjectivesThis study aimed to investigate the association between biological age acceleration and osteoporosis (OP) risk in middle-aged and older adults using data from the National Health and Nutrition Examination Survey (NHANES). The research focused on analyzing the relationship between two biological aging metrics, Klemera-Doubal Method Age (KDMAge) and Phenotypic Age (PhenoAge), and OP risk. MethodsThe study analyzed data from NHANES, which included 6550 participants aged 50 and above from survey cycles 2005–2010 and 2017–2018. Linear and logistic regression were used to investigate the relationship between biological age acceleration (KDMAgeAccel and PhenoAgeAccel) and OP. Subgroup analysis was performed by age, gender and other factors. Multivariable Cox regression analysis yielded Hazard Ratios (HRs) relating biological age acceleration to mortality were evaluated. The study also considered the mediating roles of body mass index (BMI). ResultsKDMAgeAccel (odds ratio [OR] = 2.34, 95 % CI, 1.72–3.18) and PhenoAgeAccel (OR = 2.03, 95 % CI, 1.48–2.78) were significantly associated with increased OP risk and reduced bone mineral density (BMD). Specifically, higher KDMAgeAccel and PhenoAgeAccel were linked to higher OP prevalence and lower BMD at multiple sites. Subgroup analyses indicated that the association between accelerated biological age acceleration and OP risk was consistent across different demographics. Mediation analysis revealed that BMI partially mediated the relationship between accelerated biological age and OP, although other mechanisms are likely involved. Statistical analysis indicated that individuals with higher biological age metrics had increased mortality risk related to OP. ConclusionThe findings suggest that accelerated biological age is a robust predictor of OP risk and related mortality. KDMAgeAccel and PhenoAgeAccel could serve as valuable biomarkers for identifying individuals at high risk for OP, guiding preventive strategies.

Local social vulnerability as a predictor for cancer-related mortality among US counties.

Local social vulnerability as a predictor for cancer-related mortality among US counties.

Predicting mortality in geriatric patients with fever in the emergency departments: a prospective validation study

ObjectiveEmergency physicians are always faced with the challenge of choosing the appropriate disposition for elderly patients in order to ensure an acceptable care plan and effective use of resources. A clinical decision rule, Geriatric Fever Score (GFS) has been proposed but not validated to help ED physicians with decision-making. This rule employs leukocytosis, severe coma, and thrombocytopenia as predictors of 30-day mortality. Through our study determines the performance of this clinical prediction rule in a prospective study in a setting different from where it was developed.Method and materialsIn this prospective cohort study in a 1200-bed tertiary care, patients older than 65 years old who visited the ED with fever were enrolled. All elements of the rule were collected and the total score was calculated for each patient. Patients were also categorized as low risk (score 0–1) or high risk (score ≥ 2). Thirty-day follow-up was performed to determine the patient outcome (survival or mortality).ResultsA total of 296 patients were included in our final analysis. The mortality rate was 33.1% for patients with a Score of 0, 42.1% for a score of 1, 57.1% for a score of 2, and 100% for a score of 3. When divided into two risk groups, patients’ mortality rates were as follows: low risk group 37.9% and high-risk group 40.5%.ConclusionOur study showed that elderly patients who present to ED with fever and have a score of 2 or higher on the Geriatric Fever Score are at higher risk of mortality at 30 days.

The influence of comorbidities on treatment outcomes in patients with tuberculosis

Aim. To study the association of comorbidities and treatment outcomes in tuberculosis (TB) patients. Materials and methods. A retrospective study includes all TB patients aged 18 years and older registered for treatment in Moscow in period 2021 the end of the 3rd quarter of 2022 using data of regional epidemiological TB monitoring system, a total of 3039 patients. The frequency and spectrum of comorbidities, its impact on the risk of adverse treatment outcome (ATO) and mortality using univariate and regression analysis were assessed. Results. Comorbidities were identified in 1528 (50.3%) patients (95% confidence interval – CI 48.5–52.1); HIV infection (18.0%), chronic nonspecific lung disease (9.6%) and cardiovascular disease (8.2%) were predominant. The presence of comorbid pathology increased the odds of uneffective treatment (odds ratio – OR 2.56, 95% CI 2.22–3.03) and death (OR 2.45, 95% СI 1.67–3.59). Independent risk factors for ATO were HIV infection (OR 4.10, 95% CI 3.36–5.10), substance use (OR 2.57, 95% CI 1.70–3.66), chronic nonspecific lung disease (OR 1.39, 95% CI 1.04–1.88), diabetes mellitus (OR 1.69, 95% CI 1.15–2.48), liver pathology (OR 2.10, 95% CI 1.46–3.03), mental illness (OR 2.01, 95% CI 1.32–3.06). The death rate was 13.4%; the most significant predictors of mortality were HIV infection (OR 3.89, 95% CI 2.42–6.22) and liver disease (OR 1.90, 95% CI 1.27–2.82). A comorbidome model was constructed to assess the importance of different comorbidities for patient prognosis. Conclusion. The presence of comorbidity (predominantly HIV infection and liver disease) is a significant risk factor for ATO and mortality in TB patients, which should be taken into account when organizing and providing TB care to comorbid patients.

Stability and Volatility in the Contextual Predictors of Working-Age Mortality in the United States.

The contextual predictors of mortality in the United States are well documented, but the COVID-19 pandemic may have upended those associations. Informed by the social history of disease framework (SHDF), this study examined how the importance of county contexts on adult deaths from all causes, drug poisonings, and COVID-19-related causes fluctuated during the pandemic. Using 2018 to 2021 vital statistics data, for each quarter, we estimated associations between county-level deaths among adults ages 25 to 64 and prepandemic county-level contexts (economic conditions, racial-ethnic composition, population health profile, and physician supply). The pandemic significantly elevated the importance of county contexts-particularly median household income and counties' preexisting health profile-on all-cause and drug poisoning deaths. The elevated importance of household income may be long-lasting. Contextual inequalities in COVID-19-related deaths rose and then fell, as the SHDF predicts, but rose again along with socio-political disruptions. The findings support and extend the SHDF.

Clinical impact of deep learning-derived intravascular ultrasound characteristics in patients with deferred coronary artery

Prognostic markers for long-term outcomes are lacking in patients with deferred (nonculprit) coronary artery lesions. This study aimed to identify the morphological criteria for predicting adverse outcomes and validate their clinical impact.Using deep learning models, we extracted geometrical parameters and maximal attenuation (or calcium) burden index (ABI-max or CBI-max) from the intravascular ultrasound (IVUS) images of nonculprit vessels in 1115 patients. The endpoints included cardiac death, myocardial infarction, and target vessel revascularization of nonculprit vessel.Cardiac death occurred in 27 (2.4 %) patients at 3 years and 39 (3.5 %) patients at 5 years. At 5 years, the cardiac death-free survival rate was significantly lower with ABP-max ≥11.37 % vs. < 11.37 % (90.0 % vs. 98.7 %), CBI-max ≥13.40 % vs. < 13.40 % (92.8 % vs. 98.4 %), and percent atheroma volume ≥ 51.35 % vs. < 51.35 % (94.0 % vs. 97.7) (all log-rank p < 0.001). The independent predictors of 5-year cardiovascular mortality were age (hazard ratio [HR] 1.21), female sex (HR 0.33), history of heart failure (HR 6.06), chronic kidney disease (HR 18.28), ABI-max (HR 1.04), and CBI-max (HR 1.05). The independent determinants of 5-year target vessel revascularization of nonculprit vessel were fractional flow reserve (HR 0.95 per 0.01 increase), minimal lumen area (HR 0.63), and plaque burden (HR 1.15).In patients with nonculprit coronary artery lesions, a large burden of attenuated or calcified plaques predicted cardiac mortality, while IVUS geometry was associated with repeat revascularization. Thus, deep learning–based IVUS analysis of the whole target vessel may help clinicians identify high-risk lesions.