ArticleJournal of clinical medicine2021
Simplified Decision-Tree Algorithm to Predict Falls for Community-Dwelling Older Adults.
Article in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 6 of them syntheses that pooled it.
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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.
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Who cites it
20 citing papers in PubMed, 6 syntheses or guidelines pooled it, 32 citations in OpenAlex.
- Machine Learning and Deep Learning Models for Predicting Future Falls in Community-Dwelling Older Adults: Systematic Review and Meta-Analysis of Longitudinal Evidence.Journal of medical Internet research · 2026Pooled it
- Interpretable and explainable artificial intelligence for wearable sensor-based fall risk assessment in older adults: a systematic review with considerations for prosthetics and orthotics.Frontiers in computational neuroscience · 2026Pooled it
- Sarcopenia-related traits and risk of falls in older adults: results from meta-analysis of cohort studies and Mendelian randomization analyses.Aging clinical and experimental research · 2025Pooled it
- Developing an HIV-specific falls risk prediction model with a novel clinical index: a systematic review and meta-analysis method.BMC infectious diseases · 2024Pooled it
- A systematic review of fall prediction models for community-dwelling older adults: comparison between models based on research cohorts and models based on routinely collected data.Age and ageing · 2024Pooled it
- The risk of falls among the aging population: A systematic review and meta-analysis.Frontiers in public health · 2022Pooled it
- Factors associated with falls in older adults: A secondary analysis of a 12-month randomized controlled trial.Archives of gerontology and geriatrics · 2023Trial
- Electronic Strategies for Tailored Exercise to Prevent Falls: Evaluating Implementation in Primary Care.Applied clinical informatics · 2026Article
- The interplay of risk factors for future falls and fall-related injuries among community-dwelling older adults: a Bayesian network analysis.BMC public health · 2026Article
- Distribution and Characteristics of Fall Risk Index-21 Scores in Patients with Fall-Related Hip Fractures.Journal of bone metabolism · 2026Article
- Quality of Life in European Adults and Older with All-Over Pain: Relationship with Frequency of Moderate and Vigorous Physical Activity and Decision Prediction Models with Cross-Sectional Data.Healthcare (Basel, Switzerland) · 2025Article
- A scoping review of machine learning models to predict risk of falls in elders, without using sensor data.Diagnostic and prognostic research · 2025Review
- Association between willingness to exercise and incident disability in older adults: a prospective longitudinal cohort study.European geriatric medicine · 2024Article
- [Development of a fall prediction model for community-dwelling older adults in South Korea using machine learning: a secondary data analysis].Journal of Korean biological nursing science · 2024Article
- Development and validation of a machine learning-based fall-related injury risk prediction model using nationwide claims database in Korean community-dwelling older population.BMC geriatrics · 2023Article
- CNN-Based Self-Attention Weight Extraction for Fall Event Prediction Using Balance Test Score.Sensors (Basel, Switzerland) · 2023Article
- Assessment of fall-associated risk factors in the Muslim community-dwelling older adults of Peshawar, Khyber Pakhtunkhwa, Pakistan.BMC geriatrics · 2023Article
- Article
- Artificial intelligence for falls management in older adult care: A scoping review of nurses' role.Journal of nursing management · 2022Article
- Explainable Fall Risk Prediction in Older Adults Using Gait and Geriatric Assessments.Frontiers in digital health · 2022Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
The present study developed a simplified decision-tree algorithm for fall prediction with easily measurable predictors using data from a longitudinal cohort study: 2520 community-dwelling older adults aged 65 years or older participated. Fall history, age, sex, fear of falling, prescribed medication, knee osteoarthritis, lower limb pain, gait speed, and timed up and go test were assessed in the baseline survey as fall predictors. Moreover, recent falls were assessed in the follow-up survey. We created a fall-prediction algorithm using decision-tree analysis (C5.0) that included 14 nodes with six predictors, and the model could stratify the probabilities of fall incidence ranging from 30.4% to 71.9%. Additionally, the decision-tree model outperformed a logistic regression model with respect to the area under the curve (0.70 vs. 0.64), accuracy (0.65 vs. 0.62), sensitivity (0.62 vs. 0.50), positive predictive value (0.66 vs. 0.65), and negative predictive value (0.64 vs. 0.59). Our decision-tree model consists of common and easily measurable fall predictors, and its white-box algorithm can explain the reasons for risk stratification; therefore, it can be implemented in clinical practices. Our findings provide useful information for the early screening of fall risk and the promotion of timely strategies for fall prevention in community and clinical settings.
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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.