Objectives The aim of this study was to systematically collate and appraise the available evidence regarding the associations between small, dense low-density lipoprotein (sdLDL) and incident coronary heart disease (CHD), focusing on cholesterol concentration (sdLDL-C) and sdLDL particle characteristics (presence, density, and size). Background Coronary heart disease (CHD) is the leading cause of death worldwide. Small, dense low-density lipoprotein (sdLDL) has been hypothesized to induce atherosclerosis and subsequent coronary heart disease (CHD). However, the etiological relevance of lipoprotein particle size (sdLDL) versus cholesterol content (sdLDL-C) remains unclear. Methods PubMed, MEDLINE, Web of Science, and EMBASE were systematically searched for studies published before February 2020. CHD associations were based on quartile comparisons in eight studies of sdLDL-C and were based on binary categorization in fourteen studies of sdLDL particle size. Reported hazards ratios (HR) and odds ratios (OR) with 95% confidence interval (CI) were standardized and pooled using a random-effects meta-analysis model. Results Data were collated from 21 studies with a total of 30,628 subjects and 5,693 incident CHD events. The average age was 67 years, and 53% were men. Higher sdLDL and sdLDL-C levels were both significantly associated with higher risk of CHD. The pooled estimate for the high vs. low categorization of sdLDL was 1.36 (95% CI: 1.21, 1.52) and 1.07 (95% CI: 1.01, 1.12) for comparing the top quartiles versus the bottom of sdLDL-C. Several studies suggested a dose response relationship. Conclusions The findings show a positive association between sdLDL or sdLDL-C levels and CHD, which is supported by an increasing body of genetic evidence in favor of its causality as an etiological risk factor. Thus, the results support sdLDL and sdLDL-C as a risk marker, but further research is required to establish sdLDL or sdLDL-C as a potential therapeutic marker for incident CHD risk reduction.

We assessed district-level geospatial trends in precision weighted prevalence and absolute wealth disparity in stunting, underweight, wasting, low birthweight, and anemia among children under five in India. The largest wealth disparities were found for anthropometric failures and substantial variation existed across states. We identified statistically significant (p < 0.001) geospatial patterns in district-wide wealth disparities for all outcomes, which differed from geospatial patterns for the overall prevalence. We characterized each district as either a “Disparity”, “Pitfall”, “Intensity”, or “Prosperity” area based on its overall burden and wealth disparity, as well as discuss the importance of considering both measures for geographically-targeted public health interventions to improve health equity.

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Compared to White patients, Black heart transplant recipients have a higher rate of all-cause mortality and graft failure, 1,2,3 and are considered at high risk of acute rejection. 4 Current treatment guidelines suggest that patients at high risk of acute rejection may benefit from immunosuppressive induction with anti-thymocyte globulin. 5 Induction immunosuppression is a prophylactic treatment used during the peri-transplant period which in theory, is expected to lower the risk of acute rejection, 6 though its effect on long-term outcomes is not clear.In a previous analysis of Scientific Registry of Transplant Recipients (SRTR) data, consistent with recent findings by Maredia et al., 2 we found that Black heart transplant recipients had a 28% higher odds of

Background The conventional indicators of infant and under-five mortality are aggregate deaths occurring in the first year and the first five years, respectively. Monitoring deaths by <1 month (neonatal), 1-11 months (post-neonatal), and 12-59 months (child) can be more informative given various etiological causes that may require different interventions across these three mutually exclusive periods. For optimal resource allocation, it is also necessary to track progress in robust estimates of child survival at a smaller geographic and administrative level. Methods Data on 259 627 children came from the 2015-2016 Indian National Family Health Survey. We used a random effects model to account for the complex survey design and sampling variability, and predicted district-specific probabilities of neonatal, post-neonatal, and child mortality. The resulting precision-weighted estimates are more reliable as they pool information and borrow strength from other districts that share the same state membership. The Pearson correlation and Spearman’s rank correlation were assessed for the three mortality estimates, and the Moran’s I measure was used to detect spatial clustering of high burden districts for each outcome. Results The majority of under-five deaths was disproportionately concentrated in the neonatal period. Across all districts, the predicted probability of neonatal, post-neonatal, and child mortality varied from 6.0 to 63.9 deaths, 3.8 to 47.6 deaths, and 1.7 to 11.8 deaths per 1000 live births, respectively. The overall correlation between district-wide probabilities of mortality for the three mutually exclusive periods was moderate (Pearson correlation = 0.47-0.58, Spearman’s rank correlation = 0.58-0.64). For each outcome, a relatively strong spatial clustering was detected across districts that transcended state boundaries (Moran’s I = 0.61-0.76). Conclusions Sufficiently breaking down the under-five mortality to distinct age groups and using the precision-weighted estimations to monitor performances at smaller geographic and administrative units can inform more targeted interventions and foster accountability to improve child survival.

Objective In this nationwide retrospective study, the authors aimed to identify demographic, clinical, and baseline health risk factors predictive of a prolonged length of stay (PLOS) for patients with pituitary adenomas (PAs). Methods The National Inpatient Sample dataset from 2016 to 2019 was utilized to identify all included hospitalizations for PA resection as identified by the appropriate diagnosis-related group code. Comorbidities were classified based on the Charlson Comorbidity Index mapping of ICD-10 codes, and PLOS was identified as any stay longer than 3 days. Univariable and multivariable logistic regression models, accounting for the sample design, were built to determine factors associated with PLOS and emergent surgery. Results Overall, 30 945 patients were included in this study with 10 535 patients having PLOS. Female patients experienced an increased odds of PLOS (odds ratio [OR]: 1.29; P < .001). Black patients (OR: 1.49; P < .001) and Hispanic patients (OR: 1.30; P = .003) had 1.49 times and 1.30 times the odds of PLOS compared to White patients, respectively. Compared to patients insured by Medicare, patients insured by Medicaid had an increased odds of PLOS (OR: 1.36; P = .007) as well as emergent surgery (OR: 5.40; P < .001). When stratified by emergent surgeries, Black patients (OR: 1.89; P < .001), Hispanic patients, (OR: 2.14; P < .001), and patients on Medicaid insurance (OR: 1.71; P < .001) were at an increased risk of emergent procedures. However, female sex (OR: 0.65; P < .001), upper third quartile (OR: 0.73; P = .017), and fourth quartile (OR: 0.69; P = .014) of patients categorized by zip code income were at decreased odds of an emergent procedure. Conclusions Black and Hispanic patients, patients with Medicaid insurance, and patients of low socioeconomic status patients are at significantly higher risk of emergent PA resection and PLOS. Efforts to prevent emergent surgeries and shorten hospitalization after pituitary surgery may need to primarily focus on patient groups with select sociodemographic characteristics.

BACKGROUND: Recent advances in treatment of malignant brain tumors have improved outcomes. However, patients continue to experience significant disability. Palliative care helps patients with advanced illnesses improve their quality of life. There is a paucity of clinical studies examining palliative care usage among patients with malignant brain tumors. OBJECTIVE: To assess if there were any patterns in palliative care utilization among patients hospitalized with malignant brain tumors. METHODS: A retrospective cohort representing hospitalizations for malignant brain tumors was created from The National Inpatient Sample (2016-2019). Palliative care utilization was identified by ICD-10 code. Univariable and multivariable logistic regression models, accounting for the sample design, were built to evaluate the demographic variables associated with palliative care consultation in all patients and fatal hospitalizations. RESULTS: 375 010 patients admitted with a malignant brain tumor were included in this study. Over the whole cohort, 15.0% of patients used palliative care. In fatal hospitalizations, Black and Hispanic patients had 28% lower odds of receiving a palliative care consultation compared with White patients (odds ratio for both = 0.72; P = .02). For fatal hospitalizations, patients insured privately were 34% more likely to use palliative care services compared with patients insured with Medicare (odds ratio = 1.34, P = .006). CONCLUSION: Palliative care is underutilized among all patients with malignant brain tumors. Within this population, disparities in utilization are exacerbated by sociodemographic factors. Prospective studies investigating utilization disparities across race and insurance status are necessary to improve access to palliative care services for this population.

37With overall global improvements in life expectancy, one important concern is whether 38 there is cross-country convergence in life expectancy at various ages. Insights in convergence 39 patterns can help realign research priorities help governments better structure health investments 40 across various age groups. We reveal global patterns in life expectancy improvements and 41 identify convergent clubs in life expectancy at various ages for 201 countries / areas between 42 1950 and 2015. In the case of life expectancy at younger ages, most countries are moving in the 43 same direction, but we observe significant cross-country variation for older adults and the 44 elderly. Further, we observe increasing variance in life expectancy for older adults and elderly 45 across countries. Increasing global heterogeneity in survival experience of older adults and the 46 elderly population thus has remained a neglected aspect in the discussions on global life 47