Near-term Mortality Research Articles

Patients with dementia or frailty undergoing major limb amputation have poor outcomes

ObjectiveMajor lower limb amputation is a disfiguring operation associated with impaired mobility and high near-term mortality. Informed decision-making regarding amputation requires outcomes data. Despite the co-occurrence of both chronic limb-threatening ischemia (CLTI) and Alzheimer’s disease and related dementias (ADRD), there is sparse data on the outcomes of major limb amputation in this population and the impact of frailty. We sought to determine mortality, complications, readmissions, revisions, intensive interventions (eg, cardiopulmonary resuscitation), and other outcomes after amputation for CLTI in patients living with ADRD looking at the modifying effects of frailty. MethodsWe examined Medicare fee-for-service claims data from January 1, 2016, to December 31, 2020. Patients with CLTI undergoing amputation at or proximal to the ankle were included. Along with demographic information, dementia status, and comorbid conditions, we measured frailty using a claims-based frailty index. We dichotomized dementia and frailty (pre-frail/robust = “non-frail” vs moderate/severe frailty = “frail”) to create four groups: non-frail/non-ADRD, frail/non-ADRD, non-frail/ADRD, and frail/ADRD. We used linear and logistic regression via generalized estimating equations in addition to performing selected outcomes analyses with death as a competing risk to understand the association between dementia status, frailty status, and 1-year mortality as our primary outcome in addition to the postoperative outcomes outlined above. ResultsAmong 46,930 patients undergoing major limb amputation, 11,465 (24.4%) had ADRD and 24,790 (52.8%) had frailty. Overall, 55.9% of amputations were below-knee. Selected outcomes among frail/ADRD patients undergoing amputation (n = 10,153) were: 55.3% 1-year mortality 29.6% readmissions at 30 days, and 32.3% amputation revision/reoperation within 1 year. Of all four groups, those in the frail/ADRD had the worst outcomes only for 1-year mortality. ConclusionsFirst, patients with ADRD or moderate/severe frailty suffer an array of very poor outcomes after major limb amputation for CLTI, including high mortality, readmissions, revision, and risks of discharge to higher levels of care. Second, there is a complex relationship between outcome severity and ADRD/frailty status. Specifically, frailty is more often than ADRD associated with the poorest results for any given outcome. These data provide important outcomes data to help align decision-making with health care values and goals.

The influence of air masses on human mortality in the contiguous United States.

Temperature-related mortality is the leading cause of weather-related deaths in the United States. Herein, we explore the effect of air masses (AMs) - a relatively novel and holistic measure of environmental conditions - on human mortality across 61 cities in the United States. Geographic and seasonal differences in the effects of each AM on deseasonalized and detrended anomalous lagged mortality are examined using simple descriptive statistics, one-way analyses of variance, relative risks of excess mortality, and regression-based artificial neural network (ANN) models. Results show that AMs are significantly related to anomalous mortality in most US cities, and in most seasons. Of note, two of the three cool AMs (Cool and Dry-Cool) each show a strong, but delayed mortality response in all seasons, with peak mortality 2 to 4days after they occur, with the Dry-Cool AM having nearly a 15% increased risk of excess mortality. Humid-Warm (HW) air masses are associated with increases in deaths in all seasons 0 to 1days after they occur. In most seasons, these near-term mortality increases are offset by reduced mortality for 1-2weeks afterwards; however, in summer, no such reduction is noted. The Warm and Dry-Warm AMs show slightly longer periods of increased mortality, albeit slightly less intensely as compared with HW, but with a similar lag structure by season. Meanwhile, the most seasonally consistent results are with transitional weather, whereby passing cold fronts are associated with a significant decrease in mortality 1day after they occur, while warm fronts are associated with significant increases in mortality at that same lag time. Finally, ANN modeling reveals that AM-mortality relationships gleaned from a combined meta-analysis can actually lead to more skillful modeling of these relationships than models trained on some individual cities, especially in the cities where such relationships might be masked due to low average daily mortality.

Esophageal oxyhemoglobin saturation as a resuscitative metric in hemorrhagic shock

BackgroundMixed venous saturation (SvO2) is considered the gold standard to assess the adequacy of tissue oxygen delivery (DO2) in shock states. However, SvO2 monitoring is challenging as it requires an...

Machine learning models identify predictive features of patient mortality across dementia types

BackgroundDementia care is challenging due to the divergent trajectories in disease progression and outcomes. Predictive models are needed to flag patients at risk of near-term mortality and identify factors contributing to mortality risk across different dementia types.MethodsHere, we developed machine-learning models predicting dementia patient mortality at four different survival thresholds using a dataset of 45,275 unique participants and 163,782 visit records from the U.S. National Alzheimer’s Coordinating Center (NACC). We built multi-factorial XGBoost models using a small set of mortality predictors and conducted stratified analyses with dementiatype-specific models.ResultsOur models achieved an area under the receiver operating characteristic curve (AUC-ROC) of over 0.82 utilizing nine parsimonious features for all 1-, 3-, 5-, and 10-year thresholds. The trained models mainly consisted of dementia-related predictors such as specific neuropsychological tests and were minimally affected by other age-related causes of death, e.g., stroke and cardiovascular conditions. Notably, stratified analyses revealed shared and distinct predictors of mortality across eight dementia types. Unsupervised clustering of mortality predictors grouped vascular dementia with depression and Lewy body dementia with frontotemporal lobar dementia.ConclusionsThis study demonstrates the feasibility of flagging dementia patients at risk of mortality for personalized clinical management. Parsimonious machine-learning models can be used to predict dementia patient mortality with a limited set of clinical features, and dementiatype-specific models can be applied to heterogeneous dementia patient populations.

Designing an Implementable Clinical Prediction Model for Near-Term Mortality and Long-Term Survival in Patients on Maintenance Hemodialysis

The life expectancy of patients treated with maintenance hemodialysis (MHD) is heterogeneous. Knowledge of life-expectancy may focus care decisions on near-term versus long-term goals. The current tools are limited and focus on near-term mortality. Here, we develop and assess potential utility for predicting near-term mortality and long-term survival on MHD. Predictive modeling study. 42,351 patients contributing 997,381 patient months over 11 years, abstracted from the electronic health record (EHR) system of midsize, nonprofit dialysis providers. Demographics, laboratory results, vital signs, and service utilization data available within dialysis EHR. For each patient month, we ascertained death within the next 6 months (ie, near-term mortality) and survival over more than 5 years during receipt of MHD or after kidney transplantation (ie, long-term survival). We used least absolute shrinkage and selection operator logistic regression and gradient-boosting machines to predict each outcome. We compared these to time-to-event models spanning both time horizons. We explored the performance of decision rules at different cut points. All models achieved an area under the receiver operator characteristic curve of≥0.80 and optimal calibration metrics in the test set. The long-term survival models had significantly better performance than the near-term mortality models. The time-to-event models performed similarly to binary models. Applying different cut points spanning from the 1st to 90th percentile of the predictions, a positive predictive value (PPV) of 54% could be achieved for near-term mortality, but with poor sensitivity of 6%. A PPV of 71% could be achieved for long-term survival with a sensitivity of 67%. The retrospective models would need to be prospectively validated before they could be appropriately used as clinical decision aids. A model built with readily available clinical variables to support easy implementation can predict clinically important life expectancy thresholds and shows promise as a clinical decision support tool for patients on MHD. Predicting long-term survival has better decision rule performance than predicting near-term mortality. Clinical prediction models (CPMs) are not widely used for patients undergoing maintenance hemodialysis (MHD). Although a variety of CPMs have been reported in the literature, many of these were not well-designed to be easily implementable. We consider the performance of an implementable CPM for both near-term mortality and long-term survival for patients undergoing MHD. Both near-term and long-term models have similar predictive performance, but the long-term models have greater clinical utility. We further consider how the differential performance of predicting over different time horizons may be used to impact clinical decision making. Although predictive modeling is not regularly used for MHD patients, such tools may help promote individualized care planning and foster shared decision making.

Recent death early warning value of ECG changes in patients with NSCLC.

We aimed to explore the predictive value of abnormal electrocardiogram (ECG) changes in non-small-cell lung carcinoma non-small cell lung cancer (NSCLC) patients for near-term mortality. Seventy-eight NSCLC patients hospitalized in Chaohu Hospital Affiliated to Anhui Medical University from October 2017 to August 2021 were selected as the observation group. Baseline medical history and type of ECG abnormalities were the same. Seventy-eight patients were included in the control group. To compare the difference in mortality within 3 months between the observation group and the control group after the occurrence of the same type of electrocardiogram abnormalities, and to explore the value of electrocardiogram abnormalities in the early warning of NSCLC patients recent death. When the average ventricular rate of patients in the observation group was ≥100 beats/minute, ST-segment depression ≥0.05 mm, QRS voltage decrease ≥0.5 mm, new atrial fibrillation and other electrocardiogram changes, all patients died within 3 months. The control group with the same abnormal ECG had no death within 3 months (P < .05). In the resting 12-lead synchronous ECG in NSCLC patients, when the average ventricular rate ≥100 beats/minute, QRS wave voltage significantly decreased ≥0.5 mm, ST segment depression ≥0.05 mm, new atrial fibrillation appeared, it suggested that the patients' cardiac function decreased and the potential for near-term adverse outcomes is high.

Abstract 18561: Trends Among Patients Undergoing Transvenous Lead Extraction: A Single Center Experience

Background: In recent years there has been an increase in cardiac device-related infections and the need for transvenous lead extraction (TLE). Limited data exist on secular trends in baseline characteristics and outcome measures among patients undergoing this high-risk procedure. Objective: To examine secular trends in baseline characteristics and outcomes for patients undergoing lead extraction procedure at our institution. Methods: We conducted a retrospective chart review of patients undergoing TLE from 2010 to 2021, at a tertiary academic institution. Patients were divided into three epochs (2010-2013, 2014-2017 and 2018-2021). Baseline characteristics in hospital length of stay (LOS) and survival were compared between groups. Results: A total of 794 patients, with a mean age of 64±16 years, were analyzed. 481 (60%) patients had infection as the indication for TLE. On average, 2 ± 1 leads were extracted per patient. The longest lead dwell time was 6.5 ± 4.8 years. Significant progressive increase in baseline comorbidity over time is noted (Table 1). A concomitant increase in infection indication versus lead management was also noted. There was a significant increase in the median hospital LOS across epochs; 3.88 IQR (1.26-10.06) for epoch 1 vs 7.34 IQR (2.25-13.35) for epoch 2, vs 9.06 IQR (5.78-14.05) for epoch 3 (P &lt; 0.0001). While there was no difference in long term survival curves (log rank p =0.4), between group analysis showed higher risk for 30 day [RR 2.24(1.08-4.66) p=0.0306] and 1 year mortality [RR 1.44 (1.004-2.05) p=0.0478] between epoch 3 vs epoch 1. Conclusion: Across epochs, the number of TLE procedures performed decreased while patient morbidity increased with a notable increase in infection indication for the procedure. This corresponded to a progressive increase in hospital LOS and an emergent signal toward increased near-term mortality.

Anthropometric deficits and the associated risk of death by age and sex in children aged 6-59 months: A meta-analysis.

Risk of death from undernutrition is thought to be higher in younger than in older children, but evidence is mixed. Research also demonstrates sex differences whereby boys have a higher prevalence of undernutrition than girls. This analysis described mortality risk associated with anthropometric deficits (wasting, underweight and stunting) in children 6-59 months by age and sex. We categorised children into younger (6-23 months) and older (24-59 months) age groups. Age and sex variations in near-term (within 6months) mortality risk, associated with individual anthropometric deficits were assessed in a secondary analysis of multi-country cohort data. A random effects meta-analysis was performed. Data from seven low-or-middle-income-countries collected between 1977 and 2013 were analysed. One thousand twenty deaths were recorded for children with anthropometric deficits. Pooled meta-analysis estimates showed no differences by age in absolute mortality risk for wasting (RR 1.08, p = 0.826 for MUAC < 125 mm; RR 1.35, p = 0.272 for WHZ < -2). For underweight and stunting, absolute risk of death was higher in younger (RR 2.57, p < 0.001) compared with older children (RR 2.83, p < 0.001). For all deficits, there were no differences in mortality risk for girls compared with boys. There were no differences in the risk of mortality between younger and older wasted children, supporting continued inclusion of all children under-five in wasting treatment programmes. The risk of mortality associated with underweight and stunting was higher among younger children, suggesting that prevention programmes might be justified in focusing on younger children where resources are limited. There were no sex differences by age in mortality risk for all deficits.

Worldwide physical activity trends since COVID-19 onset

The COVID-19 pandemic has disrupted nearly all aspects of daily life worldwide. Public health interventions necessary to curb disease spread could have unintended consequences that adversely influence long-term health outcomes beyond near-term mortality.1 For example, step counts—a proxy for physical activity2—were markedly lower early in the COVID-19 pandemic than pre-pandemic.3 As the global pandemic persists despite vaccines, understanding its long-term ramifications on physical activity—an important determinant of health4—is crucial, and might help to inform public health and regional policy decisions.

Dynamic prediction of mortality in COVID-19 patients in the intensive care unit: A retrospective multi-center cohort study

BackgroundThe COVID-19 pandemic continues to overwhelm intensive care units (ICUs) worldwide, and improved prediction of mortality among COVID-19 patients could assist decision making in the ICU setting. In this work, we report on the development and validation of a dynamic mortality model specifically for critically ill COVID-19 patients and discuss its potential utility in the ICU. MethodsWe collected electronic medical record (EMR) data from 3222 ICU admissions with a COVID-19 infection from 25 different ICUs in the Netherlands. We extracted daily observations of each patient and fitted both a linear (logistic regression) and non-linear (random forest) model to predict mortality within 24 h from the moment of prediction. Isotonic regression was used to re-calibrate the predictions of the fitted models. We evaluated the models in a leave-one-ICU-out (LOIO) cross-validation procedure. ResultsThe logistic regression and random forest model yielded an area under the receiver operating characteristic curve of 0.87 [0.85; 0.88] and 0.86 [0.84; 0.88], respectively. The recalibrated model predictions showed a calibration intercept of −0.04 [−0.12; 0.04] and slope of 0.90 [0.85; 0.95] for logistic regression model and a calibration intercept of −0.19 [−0.27; −0.10] and slope of 0.89 [0.84; 0.94] for the random forest model. DiscussionWe presented a model for dynamic mortality prediction, specifically for critically ill COVID-19 patients, which predicts near-term mortality rather than in-ICU mortality. The potential clinical utility of dynamic mortality models such as benchmarking, improving resource allocation and informing family members, as well as the development of models with more causal structure, should be topics for future research.

Simulation of “North Carolina Protocol for Allocating Scarce Inpatient Critical Care Resources in a Pandemic” in a Multi-hospital Health Care System

BACKGROUND An integrated nonprofit health care system with 13 North Carolina medical centers conducted a time-pressured quality improvement simulation of its plan to implement the "North Carolina Protocol for Allocating Scarce Inpatient Critical Care Resources in a Pandemic" attendant to pandemic scenario planning. Simulation objectives included assessing the plan in terms of a) efficiency and effectiveness; b) comorbidity scoring validity; c) impact by race/ethnicity, gender, age, and payer status; and d) simulation participant impressions of potential impact on clinicians.METHOD The simulation scenario involved scoring 14 patients with the constraint that only 10 could be afforded critical care resources. Also included were independent scoring validation by four clinicians, structured debriefs with simulation participants and observers, and tracking patient outcomes for 30 days.RESULTS Triage scoring was identical among four triage teams. Lack of concordance in clinician comorbidity scoring did not alter patient prioritization for withdrawal of treatment in this small cohort. Protocol scoring was not correlated with resource utilization or near-term mortality.LIMITATIONS The simulation sample was small and selected when COVID-19 census was temporarily waning. No protocol for pediatric patients was tested.CONCLUSIONS The simulation yielded resource allocation concordance using comorbidity scoring by attending physicians, which significantly accelerated triage team decision-making and did not result in notable disparities by race/ethnicity, gender, or advanced age. Qualitative findings surfaced tensions in balancing de-identified data with individualized assessment and in trusting the clinical judgments of other physicians. Additional research is needed to validate the protocol's predictive value related to patient outcomes.

Comparative Effectiveness of Surgical Approaches for Lung Cancer

BackgroundThe magnitude of association and quality of evidence comparing surgical approaches for lung cancer resection has not been analyzed. This has resulted in conflicting information regarding the relative superiority of the different approaches and disparate opinions on the optimal surgical treatment. We reviewed and systematically analyzed all published data comparing near- (30-d) and long-term mortality for minimally invasive to open surgical approaches for lung cancer. MethodsComprehensive search of EMBASE, MEDLINE, and the Cochrane Library, from January 2009 to August 2019, was performed to identify the studies and those that passed bias assessment were included in the analysis utilizing propensity score matching techniques. Meta-analysis was performed using random-effects and fixed-effects models. Risk of bias was assessed via the Newcastle–Ottawa Scale and the ROBINS-I tool. The study was registered in PROSPERO (CRD42020150923) prior to analysis. ResultsOverall, 1382 publications were identified but 19 studies were included encompassing 47,054 patients after matching. Minimally invasive techniques were found to be superior with respect to near-term mortality in early and advanced-stage lung cancer (risk ratio 0.45, 95% confidence interval [CI] 0.21-0.95, I2 = 0%) as well as for elderly patients (odds ratio 0.45, 95% CI 0.31-0.65, I2 = 30%), but did not demonstrate benefit for high-risk patients (odds ratio 0.74, 95% CI 0.06-8.73, I2 = 78%). However, no difference was found in long-term survival. ConclusionsWe performed the first systematic review and meta-analysis to compare surgical approaches for lung cancer which indicated that minimally invasive techniques may be superior to thoracotomy in near-term mortality, but there is no difference in long-term outcomes.

Development and validation of a machine learning-based prediction model for near-term in-hospital mortality among patients with COVID-19

ObjectivesTo develop and validate a model for prediction of near-term in-hospital mortality among patients with COVID-19 by application of a machine learning (ML) algorithm on time-series inpatient data from electronic...

Management of Penetrating Traumatic Brain Injury: Operative versus Non-Operative Intervention

BackgroundPenetrating traumatic brain injury (pTBI) is the most lethal form of TBI, with mortality rates as high as 90%. This high mortality rate leads many providers to feel that the treatment of pTBI is futile. Contrary to this point of view, several studies have shown that victims of pTBI who present with a Glasgow Coma Scale (GCS) ≥6 have a reasonable chance of a meaningful outcome. This study sought to investigate outcomes of pTBI patients based on GCS score who underwent neurosurgical intervention (craniotomy or craniectomy) and compare them with patients who did not undergo surgical intervention. Materials and methodsThe study represents a secondary analysis of the data that were collected from 2006 to 2016 from 17 institutions as part of a multi-center study, investigating clinical outcomes for adult patients sustaining pTBI and surviving >72 h. Patients were divided into those with GCS 3-5 and those with GCS ≥6. Within these groups, patients were stratified by whether they received surgical intervention, compared with standard non-surgical care. Patient level data (age and gender), clinical data (Injury Severity Score and Abbreviated Injury Score), GCS on admission, post-op infection rates, and outcomes data (mortality, length of stay [LOS], intensive care unit LOS) were collected. Both groups were compared using independent sample t-test or chi-squared test. ResultsSeven hundred twenty patients with pTBI were identified over 11 y, out of which 336 (46.7%) underwent surgery. The mean Injury Severity Score and Abbreviated Injury Score on admission were higher in the surgical intervention group than their non-surgical counterpart in patients with a GCS ≥6 (P < 0.0001). Patients with GCS of 3-5 with surgical intervention demonstrated a higher survival rate than non-surgical patients (P < 0.0001). In the GCS ≥6 group, surgical intervention did not impact near-term mortality. Intensive care unit LOS was significantly longer in the surgical intervention group in patients with GCS ≥ 6 (P < 0.0001) and GCS of 3-5 (P < 0.0001), as was total hospital LOS (P < 0.0001). Patients with a GCS 3-5 and ≥6 who underwent surgical intervention were more likely to develop a central nervous system infection (P = 0.016; P = 0.017). ConclusionsSurgical intervention in pTBI patients with GCS 3-5 results in improved mortality but comes at a cost of increased resource utilization in the form of longer LOS and higher infection rate. On the other hand, in patients with GCS ≥6, surgery does not provide significant benefits in patient survival. Future prospective studies providing insight as to the impact of surgery on the resource utilization and quality of survival would be beneficial in determining the need for surgical intervention in this population.

Improving screening for malnourished children at high risk of death: a study of children aged 6-59 months in rural Senegal.

To investigate whether children with concurrent wasting and stunting require therapeutic feeding and to better understand whether multiple diagnostic criteria are needed to identify children with a high risk of death and in need of treatment. Community-based cohort study, following 5751 children through time. Each child was visited up to four times at 6-month intervals. Anthropometric measurements were taken at each visit. Survival was monitored using a demographic surveillance system operating in the study villages. Niakhar, a rural area of the Fatick region of central Senegal.ParticipantsChildren aged 6-59 months living in thirty villages in the study area. Weight-for-age Z-score (WAZ) and mid-upper arm circumference (MUAC) were independently associated with near-term mortality. The lowest WAZ threshold that, in combination with MUAC, detected all deaths associated with severe wasting or concurrent wasting and stunting was WAZ &lt;-2·8. Performance for detecting deaths was best when only WAZ and MUAC were used. Additional criteria did not improve performance. Risk ratios for near-term death in children identified using WAZ and MUAC suggest that children identified by WAZ &lt;-2·8 but with MUAC≥115 mm may require lower-intensity treatment than children identified using MUAC &lt;115 mm. A combination of MUAC and WAZ detected all near-term deaths associated with severe anthropometric deficits including concurrent wasting and stunting. Therapeutic feeding programmes may achieve higher impact if WAZ and MUAC admission criteria are used.

Stroke Severity and Cognitive Impairment as Predictors of Near-Term Mortality in the Mayo Clinic Florida Familial Cerebrovascular Diseases Registry (S14.008)

Stroke Severity and Cognitive Impairment as Predictors of Near-Term Mortality in the Mayo Clinic Florida Familial Cerebrovascular Diseases Registry (S14.008)

21THE MALE-FEMALE HEALTH-SURVIVAL PARADOX IN HOSPITALISED OLDER ADULTS

Abstract Objectives To determine whether the ‘male-female health-survival paradox’ is present in older hospitalised adults and to examine whether sex differences in the ‘lethality’ of acute medical conditions influence the relationship between sex and mortality. Study design and outcome measures This study was a secondary analysis of prospective cohort data collected from 1418 Australian inpatients aged 70 years and over. Frailty was measured using a 39-variable Frailty Index (FI-AC). Analyses examined the relationship between sex, age, FI-AC and 28-day mortality. Survival models were adjusted for ‘lethality’ of acute conditions (high versus low mortality risk). Results The FI-AC had a normal distribution in both sexes (female mean = 0.34 (±0.13); male mean = 0.31 (± 0.15)). When adjusted for age, females had similar FI-AC scores to males (β coefficient = 0.014, 95% confidence interval (CI) = 0.00-0.028, p = 0.056). There were 80 deaths in the sample, with females facing a significantly lower mortality risk than males of the same FI-AC and age (HR = 0.39, 95% CI = 0.25–0.63, p Conclusion The male-female health-survival paradox was not demonstrated in this study of older inpatients. Whilst females faced a significantly lower risk of near-term mortality, the sexes were found to have similar levels of frailty on admission to hospital. The sex mortality gap was not explained by sex differences in the ‘lethality’ of acute medical conditions.

Abstract 21108: Early Evidence That the Female Genome Does Matter for Acute Coronary Syndrome Risk

Introduction: Women of all ethnicities have the highest rates of Acute Coronary Syndrome (ACS) misdiagnosis, delayed treatment, and ACS-related near-term mortality. Known physiologic differences and traditional risk factors have failed to fully explain these ACS disparities among women. Our knowledge gap of genomic variation underlying women’s unique ACS phenotypes means that there is no female-derived ACS risk biomarker that reflects female-specific biology and phenotype features. Among 510 women, we previously identified 122 SNPs within 14 genomic regions that significantly predicted ‘survivorship in CAD’ (all-cause mortality among coronary artery disease cases; p&lt;10-5); none of which were significant in males or controls. Given the recent recognition of sex as a biological variable, our purpose was to identify female-specific genomic markers that predict ACS case status. Methods: We performed secondary case-control analysis for 1,382 females (796 ACS cases/586 non-ACS controls) of the Duke Catheterization Genetics (CATHGEN) Study (Illumina Human Infinium 1.0 platform). ACS was defined as having no previous MI history plus either documented unstable angina pain type or incident myocardial infarction. We employed logistic regression models of ACS case status for each SNP separately, assuming additive genetic models, and controlling for age and 3 PCAs of ethnicity. Results: Twenty-three SNPs among 3 biologically relevant candidates ( LPAGT1 , SLC9A9 , &amp; RAP1GAP2 ) significantly predicted women’s ACS (range p=7.43x10 -5 - 0.05) with positive and negative odds ratios observed. LPGAT1 is involved in cardiolipin synthesis; SLC9A9 is involved in endosome recycling; and, RAP1GAP2 regulates secretion of dense granules from platelets at endothelial damage sites. Additionally, 74 SNPs within the 11 novel survivorship with CAD candidates significantly predicted ACS (p&lt;0.05). Conclusions: We demonstrate proof of principal for unique , female-specific genomic effects on ACS case status; and, shared genomic variation with ACS and survivorship in CAD among women. Validation of this work is required. Future research is needed to identify female-derived genomic markers that may uniquely characterize women’s ACS and coronary disease expression.

The male-female health-survival paradox in hospitalised older adults

ObjectivesTo determine whether the ‘male-female health-survival paradox’ is present in older hospitalised adults and to examine whether sex differences in the ‘lethality’ of acute medical conditions influence the relationship between sex and mortality. Study design and outcome measuresThis study was a secondary analysis of prospective cohort data collected from 1418 Australian inpatients aged 70 years and over. Frailty was measured using a 39-variable Frailty Index (FI-AC). Analyses examined the relationship between sex, age, FI-AC and 28-day mortality. Survival models were adjusted for ‘lethality’ of acute conditions (high versus low mortality risk). ResultsThe FI-AC had a normal distribution in both sexes (female mean=0.34 (±0.13); male mean=0.31 (±0.15)). When adjusted for age, females had similar FI-AC scores to males (β coefficient=0.014, 95% confidence interval (CI)=0.00-0.028, p=0.056). There were 80 deaths in the sample, with females facing a significantly lower mortality risk than males of the same FI-AC and age (HR=0.39, 95% CI=0.25–0.63, p<0.001). Females were less likely than males to be admitted with a high-risk acute condition. Even so, this did not significantly reduce their survival advantage (HR=0.46, 95% CI=0.29-0.73, p=0.001). ConclusionThe male-female health-survival paradox was not demonstrated in this study of older inpatients. Whilst females faced a significantly lower risk of near-term mortality, the sexes were found to have similar levels of frailty on admission to hospital. The sex mortality gap was not explained by sex differences in the ‘lethality’ of acute medical conditions.

Treatment-Related Mortality Among Early-Stage NSCLC Patients Undergoing Surgery Versus SBRT

The comparative effectiveness of stereotactic body radiotherapy (SBRT) versus surgery for early-stage non-small cell lung cancer (esNSCLC) continues to be debated. Perioperative surgical mortality may give SBRT patients an early survival advantage. We endeavored to compare near-term mortality in a large esNSCLC population between patients undergoing surgery or SBRT in an analysis of the National Cancer Database (NCDB). NCDB was queried for patients with T1-T2a N0 M0 NSCLC diagnosed from 2004 to 2013 undergoing either SBRT or surgery. Thirty-day and 90-day post-treatment mortality was calculated by subtracting the time from diagnosis to treatment initiation from duration of follow-up and compared between SBRT and various surgical approaches. Patients were segmented into similarly sized age quartiles. Multivariate logistic regression (MVA) was performed to determine associations between odds of mortality and demographic, facility-specific, and clinical factors. Propensity-score matching (PSM) was also performed to derive a 3:1 (surgery:SBRT) matched cohort in order to compare odds of mortality between surgery and SBRT by univariate logistic regression. We identified 76,623 surgery patients, of whom 77.7% received lobectomy, and 8,216 SBRT patients, who received a median dose of 51 Gy. Surgical patients experienced increased mortality as compared to those undergoing SBRT at both 30 days (2.1% vs 0.7%) and 90 days (3.6% vs 2.9%), differences most pronounced among patients older than 75 (Table 1). On MVA, each surgical modality was associated with increased mortality versus SBRT at 30 days (odds ratio [OR] for sublobar resection 2.76, 95% CI 2.08-3.68; OR for lobectomy 3.52, 95% CI 2.70-4.60; OR for pneumonectomy 14.1, 95% CI 10.1-19.8; all P < 0.001) and at 90 days (OR for sublobar resection 1.36, 95% CI 1.16-1.61; OR for lobectomy 1.58, 95% CI 1.37-1.83; OR for pneumonectomy 5.59, 95% CI 4.46-7.01; all P < 0.001). Among a PSM cohort of 28,248 patients, surgical patients continued to experience increased mortality at both 30 days (2.5% vs 0.7%; OR 3.43, 95% CI 2.57-4.56; P < 0.001) and 90 days (4.2% vs 2.8%; OR 1.53, 95% CI 1.31-1.79; P < 0.001). We identified greater mortality in the near-term post-treatment period in a modern cohort of esNSCLC patients undergoing surgery versus SBRT. These findings may guide management of esNSCLC, particularly for older patients and those at greatest risk of perioperative morbidity, and underscore the importance of multidisciplinary evaluation.Abstract 1154; Table 1Age QuartileSublobar ResectionLobectomyPneumonectomyAll SurgerySBRT30-Day Mortality Rates (%)<620.70.85.31.00.762-681.31.47.21.50.469-751.72.410.92.40.8>752.93.913.83.70.890-Day Mortality Rates (%)<621.31.48.11.62.762-682.32.411.02.61.969-753.24.216.04.22.7>755.46.521.36.43.5 Open table in a new tab