The Relation of Serum Vitamin C Concentrations with Alzheimer's Disease Mortality in a National Cohort of Community-Dwelling Elderly Adults.

The relation of vitamin C with Alzheimer's disease (AD) is equivocal. The aim of this study was to assess the relation of serum vitamin C levels with AD-related mortality, and to evaluate the threshold beyond which the potential benefits of higher serum concentrations of vitamin C for AD mortality ceases. The cohort consisted of 4504 adults aged ≥60 years enrolled in the National Health and Nutrition Examination Survey who had serum measures of vitamin C and no cognitive impairment at baseline (1988-1994) and were followed-up for mortality until 2019. Vitamin C was assayed from fasting blood samples using isocratic high-performance liquid chromatography. At baseline, the mean age of participants was 70 years, with 42.7% being men. At the end of follow-up (median: 15 years), the AD mortality rate was 2.4 per 1000 person-years. In the Cox regression models, compared to participants in the lowest tertile of serum vitamin C (<0.56 mg/dL), those in the highest tertile (>0.98 mg/dL) had a lower risk of AD mortality (hazard ratio: 0.44, 95% confidence intervals: 0.25-0.77) after adjusting for sociodemographic factors, behavior/lifestyle factors, prevalent health conditions, and dietary vitamin C intake. In dose-response analysis using restricted cubic splines, vitamin C concentrations beyond 2.3 mg/dL were associated with the elevated risk of AD-related mortality. The findings from this national sample of community-dwelling elderly adults suggest that higher levels of serum vitamin C are associated with slower AD disease progression, although levels beyond the normal reference values were associated with a higher risk of AD mortality.

BGLM: big data-guided LOINC mapping with multi-language support.

Motivation: Mapping internal, locally used lab test codes to standardized logical observation identifiers names and codes (LOINC) terminology has become an essential step in harmonizing electronic health record (EHR) data across different institutions. However, most existing LOINC code mappers are based on text-mining technology and do not provide robust multi-language support. Materials and methods: We introduce a simple, yet effective tool called big data-guided LOINC code mapper (BGLM), which leverages the large amount of patient data stored in EHR systems to perform LOINC coding mapping. Distinguishing from existing methods, BGLM conducts mapping based on distributional similarity. Results: We validated the performance of BGLM with real-world datasets and showed that high mapping precision could be achieved under proper false discovery rate control. In addition, we showed that the mapping results of BGLM could be used to boost the performance of Regenstrief LOINC Mapping Assistant (RELMA), one of the most widely used LOINC code mappers. Conclusions: BGLM paves a new way for LOINC code mapping and therefore could be applied to EHR systems without the restriction of languages. BGLM is freely available at https://github.com/Bin-Chen-Lab/BGLM.

Staffing and Protective Equipment Access Mitigated COVID-19 Penetration and Spread in US Nursing Homes During the Third Surge.

OBJECTIVES: During the last quarter of 2020-despite improved distribution of personal protective equipment (PPE) and knowledge of COVID-19 management-nursing homes experienced the greatest increases in cases and deaths since the pandemic's beginning. We sought to update COVID-19 estimates of cases, hospitalization, and mortality and to evaluate the association of potentially modifiable facility-level infection control factors on odds and magnitude of COVID-19 cases, hospitalizations, and deaths in nursing homes during the third surge of the pandemic. DESIGN: Cross-sectional analysis. SETTING AND PARTICIPANTS: Facility-level data from 13,156 US nursing home facilities. METHODS: Two series of multivariable logistic regression and generalized linear models to examine the association of infection control factors (personal protective equipment and staffing) on incidence and magnitude, respectively, of confirmed COVID-19 cases, hospitalizations, and deaths in nursing home residents reported in the last quarter of 2020. RESULTS: Nursing homes experienced steep increases in COVID-19 cases, hospitalizations, and deaths during the final quarter of 2020. Four-fifths (80.51%; n = 10,592) of facilities reported at least 1 COVID-19 case, 49.44% (n = 6504) reported at least 1 hospitalization, and 49.76% (n = 6546) reported at least 1 death during this third surge. N95 mask shortages were associated with increased odds of at least 1 COVID-19 case [odds ratio (OR) 1.21, 95% confidence interval (CI) 1.05-1.40] and hospitalization (1.26, 95% CI 1.13-1.40), as well as larger numbers of hospitalizations (1.11, 95% CI 1.02-1.20). Nursing aide shortages were associated with lower odds of at least 1 COVID-19 death (1.23, 95% CI 1.12-1.34) and higher hospitalizations (1.09, 95% CI 1.01-1.17). The number of nursing hours per resident per day was largely insignificant across all outcomes. Of note, smaller (<50-bed) and midsized (50- to 150-bed) facilities had lower odds yet higher magnitude of all COVID outcomes. Bed occupancy rates >75% increased odds of experiencing a COVID-19 case (1.48, 95% CI 1.35-1.62) or death (1.25, 95% CI 1.17-1.34). CONCLUSIONS AND IMPLICATIONS: Adequate staffing and PPE-along with reduced occupancy and smaller facilities-mitigate incidence and magnitude of COVID-19 cases and sequelae. Addressing shortcomings in these factors is critical to the prevention of infections and adverse health consequences of a next surge among vulnerable nursing home residents.