The authors prospectively explored the consequences of hip fracture with regard to discharge placement, functional status, and mortality using the Survey on Assets and Health Dynamics Among the Oldest Old (AHEAD). Data from baseline (1993) AHEAD interviews and biennial follow-up interviews were linked to Medicare claims data from 1993-2005. There were 495 postbaseline hip fractures among 5,511 respondents aged >or=69 years. Mean age at hip fracture was 85 years; 73% of fracture patients were white women, 45% had pertrochanteric fractures, and 55% underwent surgical pinning. Most patients (58%) were discharged to a nursing facility, with 14% being discharged to their homes. In-hospital, 6-month, and 1-year mortality were 2.7%, 19%, and 26%, respectively. Declines in functional-status-scale scores ranged from 29% on the fine motor skills scale to 56% on the mobility index. Mean scale score declines were 1.9 for activities of daily living, 1.7 for instrumental activities of daily living, and 2.2 for depressive symptoms; scores on mobility, large muscle, gross motor, and cognitive status scales worsened by 2.3, 1.6, 2.2, and 2.5 points, respectively. Hip fracture characteristics, socioeconomic status, and year of fracture were significantly associated with discharge placement. Sex, age, dementia, and frailty were significantly associated with mortality. This is one of the few studies to prospectively capture these declines in functional status after hip fracture.
Continuity of care with a PCP, as assessed by two distinct measures, was associated with substantial reductions in long-term mortality.
Objective. To assess the covariate balancing properties of propensity score-based algorithms in which covariates affecting treatment choice are both measured and unmeasured. Data Sources/Study Setting. A simulation model of treatment choice and outcome. Study Design. Simulation. Data Collection/Extraction Methods. Eight simulation scenarios varied with the values placed on measured and unmeasured covariates and the strength of the relationships between the measured and unmeasured covariates. The balance of both measured and unmeasured covariates was compared across patients either grouped or reweighted by propensity scores methods. Principal Findings. Propensity score algorithms require unmeasured covariate variation that is unrelated to measured covariates, and they exacerbate the imbalance in this variation between treated and untreated patients relative to the full unweighted sample. Conclusions. The balance of measured covariates between treated and untreated patients has opposite implications for unmeasured covariates in randomized and observational studies. Measured covariate balance between treated and untreated patients in randomized studies reinforces the notion that all covariates are balanced. In contrast, forced balance of measured covariates using propensity score methods in observational studies exacerbates the imbalance in the independent portion of the variation in the unmeasured covariates, which can be likened to squeezing a balloon. If the unmeasured covariates affecting treatment choice are confounders, propensity score methods can exacerbate the bias in treatment effect estimates. Key Words. Propensity scores, covariate balance, matching, binning, assumptions, simulationThe strength of randomized controlled trials (RCTs) is the assumption that randomized treatment assignment yields a balanced distribution of covariates thought to be related to outcome between the treatment and control groups
The impact of prenatal care use on birth outcomes has been understudied in South American countries. This study assessed the effects of various measures of prenatal care use on birth weight (BW) and gestational age outcomes using samples of infants born without and with common birth defects from Brazil, and evaluated the demand for prenatal care. Prenatal visits improved BW in the group without birth defects through increasing both fetal growth rate and gestational age, but prenatal care visits had an insignificant effect on BW in the group with birth defects when adjusting for gestational age. Prenatal care delay had no effects on BW in both infant groups but increased preterm birth risk in the group without birth defects. Inadequate care versus intermediate care also increased LBW risk in the group without birth effects. Quantile regression analyses revealed that prenatal care visits had larger effects at low compared with high BW quantiles. Several other prenatal factors and covariates such as multivitamin use and number of previous live births had significant effects on the studied outcomes. The number of prenatal care visits was significantly affected by several maternal health and fertility indicators. Significant geographic differences in utilization were observed as well. The study suggests that more frequent use of prenatal care can increase BW significantly in Brazil, especially among pregnancies that are uncomplicated with birth defects but that are at high risk for low birth weight. Further research is needed to understand the effects of prenatal care use for pregnancies that are complicated with birth defects.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.