ArticleBMC geriatrics2026
The interaction between frailty and patient characteristics and its association with hospital-related adverse events in older adults.
Article in BMC geriatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFrailty is a state of increased vulnerability to stressors that predisposes individuals to adverse outcomes. Hospital-related adverse events (AEs) are complications not directly caused by patients' pre-existing conditions. While age has been widely studied, less is known about the effect of frailty and its interaction with patient demographic and clinical characteristics on the risk of having at least one adverse event (AE) among acutely admitted older adults.
methodsIn this study, AEs were operationally defined as Datix-reported patient safety incidents with the potential to cause harm. Poisson regression models were used to estimate Relative Risk (RRs) and 95% Confidence Intervals (CIs) for the association between frailty and the likelihood of experiencing at least one AE during admission. Frailty was assessed at the Emergency Department (ED) using the Clinical Frailty Scale (CFS) and modelled as the primary predictor. Individual models were then used to assess crude associations for age, gender, ethnicity, ED wait time, and In-patient (IP) Length of Stay (LOS). Interaction terms between frailty and each characteristic were tested using likelihood ratio tests. Backward stepwise elimination was used to obtain a multivariable model retaining only variables that significantly improved model fit (p < 0.01).
resultsA total of 158,470 hospital admissions with a recorded frailty score were included. Statistically significant interactions were found between frailty and age, ED wait time, and IP LOS in relation to the risk of experiencing at least one AE (all p < 0.01). Multivariable modelling showed that the interaction between frailty and IP LOS was the only interaction that significantly improved model fit.
conclusionThe risk of AEs was associated with increasing frailty, and this association varied with IP LOS. Frailty assessment may help identify patients at increased risk of Datix-reported patient safety incidents, although the observed interaction with IP LOS does not imply causation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.