ArticleBMC ophthalmology2025
Evaluation of different fall risk screening tools for risk prediction of ophthalmology inpatients.
Article in BMC ophthalmology, 2025. 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
6 authors.
Funding
Abstract
AIMS AND
objectivesTo evaluate the risk factors for falls in adult ophthalmic inpatients and compare the accuracy and predictability of fall risk screening tools.
methodsA prospective cross-sectional study was conducted on a total of 1102 hospitalised patients in ophthalmology ward. Fall risk screening was performed within 8 h of admission using the following tools: Falling Risk Assessment Tool in Ophthalmology Inpatients (FRAT), Morse Fall Scale (MFS), Johns Hopkins fall-risk Assessment Tool (JHFRAT), St Thomas Risk Assessment Tool (STRATIFY), and Hendrich II fall-risk Model (HFRM). Taking the occurrence of falls or the occurrence of falls as a positive standard. The sensitivity, specificity, positive predictive value, negative predictive value and area under the curve of the risk assessment tool were calculated to determine accuracy and predictability.
resultsIn this study, 1102 met the inclusion criteria. The mean age was 56.81(58.00) and 536(48.6) were females. 61(5.54%) experienced falling or falling status. STRATIFY had the highest sensitivity(85.2%), followed by FRAT(70.5%). The specificity of MFS was the highest(91.7%), followed by FRAT(69.5%). However, in clinical practice, risk assessment tools are difficult to have high sensitivity and high specificity, so they are more inclined to high-sensitivity assessment tools to avoid missing high-risk groups. According to the evaluation results, FRAT has both good sensitivity and specificity. Furthermore, we identified significant risk factors for falls in ophthalmic patients, such as fall history, visual acuity, age, excretion and gait.
conclusionsFRAT was the most suitable fall assessment tool and was essential for reliable screening of people at high risk of ophthalmic falls. PATIENT OR PUBLIC CONTRIBUTION: After explaining the purpose, the patients received our fall risk assessment and answered the corresponding questionnaire questions.
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.