Fall Patterns Predict Mortality After Hip Fracture in Older Adults, Independent of Age, Sex, and Comorbidities.

Falls are the most frequent cause of hip fracture. We aimed to investigate whether specific fall patterns have predictive value for mortality after hip fracture. In this cohort study, data of individuals presented to the Severance Hospital, Seoul, Korea, between 2005 and 2019 due to fragility hip fracture (n = 1986) were analyzed. Fall patterns were defined as causes, activities leading to falls, and a combination of both, based on electronic medical records using pre-specified classification from a prior study on video-captured falls. Mean age of study subjects were 77 years (71% women) and 211 patients (10.6%) died during follow-up (median 544 days). Indoor falls at home had a higher mortality than outdoor falls (11.9 vs. 8.0%, p = 0.009). Among 16 fall patterns, incorrect weight shift while sitting down (adjusted hazard ratio [aHR] 4.03) or getting up (aHR 2.01), collapse during low-risk activity (aHR 2.39), and slipping while walking (aHR 2.90, p < 0.01 for all) were associated with increased mortality compared to outdoor falls, after adjustment for age, sex, and Charlson comorbidity index (CCI), constituting a high-risk pattern. High-risk fall patterns were associated with a higher risk of mortality (aHR 2.56, p < 0.001) than low-risk patterns (aHR 1.37, p = 0.080) and outdoor falls (referent; log rank p < 0.001), which improved mortality prediction when added to a base model including age, sex, and CCI (integrative area under receiver-operating characteristics curve 0.675 to 0.698, p < 0.001). Specific fall patterns were associated with higher mortality in older adults with hip fracture, independent of age, sex, and comorbidities.

Inference of a causal relation between low-density lipoprotein cholesterol and hypertension using mendelian randomization analysis.

BACKGROUND: It is known in some studies that higher the LDL-C, the greater the risk of developing cardiovascular disease. However, studies of the causal effects between LDL-C and hypertension are limited by their observational study design, and genetic epidemiology studies of associations between LDL-C and hypertension are lacking, as are studies using data for Koreans. In this study, we confirmed the causal effect of LDL-C on hypertension using Korean chip data. METHOD: The epidemiology and genotype data were collected from the Korean Genome and Epidemiology Study conducted by the Korea National Institute of Health and covered 20,701 subjects. Single-nucleotide polymorphisms associated with LDL-C were selected (p-value < 5 × 10- 8) from the Global Lipids Genetics Consortium database, and Mendelian randomization analysis (MRA) was performed with counted genetic risk scores and weighted genetic risk scores (WGRSs) for 24 single-nucleotide polymorphisms. RESULT: The assumptions for MRA were statistically confirmed, and WGRSs showed a strong association with LDL-C. Interestingly, while the relationship between LDL-C and hypertension was not statistically significant in the observational study, MRA study demonstrated that the risk of hypertension increased as LDL-C increased in both men and women. CONCLUSIONS: The results of this study confirmed that the relationship between LDL-C and hypertension is greatly influenced by genetic information.