Predictive Risk Model for Serious Falls Among Older Persons Living With HIV.

BACKGROUND: Older (older than 50 years) persons living with HIV (PWH) are at elevated risk for falls. We explored how well our algorithm for predicting falls in a general population of middle-aged Veterans (age 45-65 years) worked among older PWH who use antiretroviral therapy (ART) and whether model fit improved with inclusion of specific ART classes. METHODS: This analysis included 304,951 six-month person-intervals over a 15-year period (2001-2015) contributed by 26,373 older PWH from the Veterans Aging Cohort Study who were taking ART. Serious falls (those falls warranting a visit to a health care provider) were identified by external cause of injury codes and a machine-learning algorithm applied to radiology reports. Potential predictors included a fall within the past 12 months, demographics, body mass index, Veterans Aging Cohort Study Index 2.0 score, substance use, and measures of multimorbidity and polypharmacy. We assessed discrimination and calibration from application of the original coefficients (model derived from middle-aged Veterans) to older PWH and then reassessed by refitting the model using multivariable logistic regression with generalized estimating equations. We also explored whether model performance improved with indicators of ART classes. RESULTS: With application of the original coefficients, discrimination was good (C-statistic 0.725; 95% CI: 0.719 to 0.730) but calibration was poor. After refitting the model, both discrimination (C-statistic 0.732; 95% CI: 0.727 to 0.734) and calibration were good. Including ART classes did not improve model performance. CONCLUSIONS: After refitting their coefficients, the same variables predicted risk of serious falls among older PWH nearly and they had among middle-aged Veterans.

Brief Report: Are Serious Falls Associated With Subsequent Fragility Fractures Among Veterans Living With HIV?

BACKGROUND: The extensive research on falls and fragility fractures among persons living with HIV (PWH) has not explored the association between serious falls and subsequent fragility fracture. We explored this association. SETTING: Veterans Aging Cohort Study. METHODS: This analysis included 304,951 6-month person- intervals over a 15-year period (2001-2015) contributed by 26,373 PWH who were 50+ years of age (mean age 55 years) and taking antiretroviral therapy (ART). Serious falls (those falls significant enough to result in a visit to a health care provider) were identified by the external cause of injury codes and a machine learning algorithm applied to radiology reports. Fragility fractures were identified using ICD9 codes and included hip fracture, vertebral fractures, and upper arm fracture and were modeled with multivariable logistic regression with generalized estimating equations. RESULTS: After adjustment, serious falls in the previous year were associated with increased risk of fragility fracture [odds ratio (OR) 2.10; 95% confidence interval (CI): 1.83 to 2.41]. The use of integrase inhibitors was the only ART risk factor (OR 1.17; 95% CI: 1.03 to 1.33). Other risk factors included the diagnosis of alcohol use disorder (OR 1.49; 95% CI: 1.31 to 1.70) and having a prescription for an opioid in the previous 6 months (OR 1.40; 95% CI: 1.27 to 1.53). CONCLUSIONS: Serious falls within the past year are strongly associated with fragility fractures among PWH on ART-largely a middle-aged population-much as they are among older adults in the general population.

Polypharmacy, Hazardous Alcohol and Illicit Substance Use, and Serious Falls Among PLWH and Uninfected Comparators.

BACKGROUND: Medication classes, polypharmacy, and hazardous alcohol and illicit substance abuse may exhibit stronger associations with serious falls among persons living with HIV (PLWH) than with uninfected comparators. We investigated whether these associations differed by HIV status. SETTING: Veterans Aging Cohort Study. METHODS: We used a nested case-control design. Cases (N = 13,530) were those who fell. Falls were identified by external cause of injury codes and a machine-learning algorithm applied to radiology reports. Cases were matched to controls (N = 67,060) by age, race, sex, HIV status, duration of observation, and baseline date. Risk factors included medication classes, count of unique non-antiretroviral therapy (non-ART) medications, and hazardous alcohol and illicit substance use. We used unconditional logistic regression to evaluate associations. RESULTS: Among PLWH, benzodiazepines [odds ratio (OR) 1.24; 95% confidence interval (CI) 1.08 to 1.40] and muscle relaxants (OR 1.29; 95% CI: 1.08 to 1.46) were associated with serious falls but not among uninfected (P > 0.05). In both groups, key risk factors included non-ART medications (per 5 medications) (OR 1.20, 95% CI: 1.17 to 1.23), illicit substance use/abuse (OR 1.44; 95% CI: 1.34 to 1.55), hazardous alcohol use (OR 1.30; 95% CI: 1.23 to 1.37), and an opioid prescription (OR 1.35; 95% CI: 1.29 to 1.41). CONCLUSION: Benzodiazepines and muscle relaxants were associated with serious falls among PLWH. Non-ART medication count, hazardous alcohol and illicit substance use, and opioid prescriptions were associated with serious falls in both groups. Prevention of serious falls should focus on reducing specific classes and absolute number of medications and both alcohol and illicit substance use.

Prevalence of kidney stones in the United States.

BACKGROUND: The last nationally representative assessment of kidney stone prevalence in the United States occurred in 1994. After a 13-yr hiatus, the National Health and Nutrition Examination Survey (NHANES) reinitiated data collection regarding kidney stone history. OBJECTIVE: Describe the current prevalence of stone disease in the United States, and identify factors associated with a history of kidney stones. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional analysis of responses to the 2007-2010 NHANES (n=12 110). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Self-reported history of kidney stones. Percent prevalence was calculated and multivariable models were used to identify factors associated with a history of kidney stones. RESULTS AND LIMITATIONS: The prevalence of kidney stones was 8.8% (95% confidence interval [CI], 8.1-9.5). Among men, the prevalence of stones was 10.6% (95% CI, 9.4-11.9), compared with 7.1% (95% CI, 6.4-7.8) among women. Kidney stones were more common among obese than normal-weight individuals (11.2% [95% CI, 10.0-12.3] compared with 6.1% [95% CI, 4.8-7.4], respectively; p<0.001). Black, non-Hispanic and Hispanic individuals were less likely to report a history of stone disease than were white, non-Hispanic individuals (black, non-Hispanic: odds ratio [OR]: 0.37 [95% CI, 0.28-0.49], p<0.001; Hispanic: OR: 0.60 [95% CI, 0.49-0.73], p<0.001). Obesity and diabetes were strongly associated with a history of kidney stones in multivariable models. The cross-sectional survey design limits causal inference regarding potential risk factors for kidney stones. CONCLUSIONS: Kidney stones affect approximately 1 in 11 people in the United States. These data represent a marked increase in stone disease compared with the NHANES III cohort, particularly in black, non-Hispanic and Hispanic individuals. Diet and lifestyle factors likely play an important role in the changing epidemiology of kidney stones.