A two-question tool to assess the risk of repeated falls in the elderly

Rodríguez‐Molinero, Alejandro; Gálvez‐Barrón, César; Narvaiza, Leire; Miñarro, Antonio; Ruiz, Jaime E.; Valldosera, Esther; Gonzalo, Natalia; Ng, Thalia; Sanguino, María Jesús; Yuste, Antonio Pérez

doi:10.1371/journal.pone.0176703

Cited by 20 publications

(17 citation statements)

References 26 publications

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“… 39 Regarding developed models (n=6), calibration was found acceptable, but studies did not assess model calibration in new participants. 41 44 47 49 …”

Section: Resultsmentioning

confidence: 99%

Predicting falls in community-dwelling older adults: a systematic review of prognostic models

et al. 2021

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ObjectiveTo systematically review and critically appraise prognostic models for falls in community-dwelling older adults.Eligibility criteriaProspective cohort studies with any follow-up period. Studies had to develop or validate multifactorial prognostic models for falls in community-dwelling older adults (60+ years). Models had to be applicable for screening in a general population setting.Information sourceMEDLINE, EMBASE, CINAHL, The Cochrane Library, PsycINFO and Web of Science for studies published in English, Danish, Norwegian or Swedish until January 2020. Sources also included trial registries, clinical guidelines, reference lists of included papers, along with contacting clinical experts to locate published studies.Data extraction and risk of biasTwo authors performed all review stages independently. Data extraction followed the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist. Risk of bias assessments on participants, predictors, outcomes and analysis methods followed Prediction study Risk Of Bias Assessment Tool.ResultsAfter screening 11 789 studies, 30 were eligible for inclusion (n=86 369 participants). Median age of participants ranged from 67.5 to 83.0 years. Falls incidences varied from 5.9% to 59%. Included studies reported 69 developed and three validated prediction models. Most frequent falls predictors were prior falls, age, sex, measures of gait, balance and strength, along with vision and disability. The area under the curve was available for 40 (55.6%) models, ranging from 0.49 to 0.87. Validated models’ The area under the curve ranged from 0.62 to 0.69. All models had a high risk of bias, mostly due to limitations in statistical methods, outcome assessments and restrictive eligibility criteria.ConclusionsAn abundance of prognostic models on falls risk have been developed, but with a wide range in discriminatory performance. All models exhibited a high risk of bias rendering them unreliable for prediction in clinical practice. Future prognostic prediction models should comply with recent recommendations such as Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis.PROSPERO registration numberCRD42019124021.

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“… 39 Regarding developed models (n=6), calibration was found acceptable, but studies did not assess model calibration in new participants. 41 44 47 49 …”

Section: Resultsmentioning

confidence: 99%

Predicting falls in community-dwelling older adults: a systematic review of prognostic models

et al. 2021

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“…Demographic characteristics of participants, including age, sex, marital status, house type, visual acuity, balance ability, and history of falling in the previous six months [ 30 ], were collected using standardized questionnaires. Visual acuity was assessed using a Snellen chart (“good” being able to read more than half the numbers on the Snellen chart at a distance of 6/12 meters, and “poor” otherwise) [ 20 ], while balance ability was assessed with a one-leg balancing test for 10 seconds (“good” being able to stand on one leg for 10 seconds or longer and “poor” otherwise) [ 31 ].…”

Section: Methodsmentioning

confidence: 99%

Predictive validity of three home fall hazard assessment tools for older adults in Thailand

et al. 2020

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This study aimed to examine the predictive validity of two internationally well-known instruments, the Modified Home Falls and Accidents Screening Tool (Modified HOME FAST) and the Modified Home Falls and Accidents Screening Tool-Self Report (Modified HOME FAST-SR), and the newly developed Thai Home Falls Hazard Assessment Tool (Thai-HFHAT) (69 items) in predicting falls among older Thai adults. It also aimed to examine the predictive validity of the two abbreviated versions (44 and 27 items) of the Thai-HFHAT, which were developed post hoc to accommodate older adults’ limited literacy and poor vision and to facilitate the identification of high-impact home fall hazards that are prevalent in the Thailand context. A prospective cohort study was conducted among 450 participants aged 60 years and above who were assessed by the aforementioned tools at baseline, for which data on fall incidence were then collected during the one-year follow-up. The Cox proportional hazard model was applied to estimate hazard ratios (HRs); then, Harrell’s C-statistics and receiver operating characteristic (ROC) analyses were conducted to identify the best cutoff point, sensitivity and specificity for each instrument. The results showed that the fall hazard rate was 2.04 times per 1,000 person-days. Taking into account both the predictive validity and applicability, the Thai-HFHAT (44 items) was found to be the most suitable screening tool due to its highest sensitivity and specificity (93% and 72%) at the cutoff score of 18. In conclusion, our study showed that these internationally validated home fall hazard assessment tools were quite applicable for Thailand, but further tailoring the tools into a specific local context yielded even more highly valid tools in predicting fall risk among older Thai adults. Although these findings were well reproducible by inferring from the internal validation results, further external validation in the independent population is necessary.

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“…Thus, older adults may have their risk of falling estimated to better target interventions. A recently published systematic review [ 10 ] highlighted models available for predicting falls [ 11 – 17 ]. These models were primarily based on younger participants (65+ years) [ 11 – 13 , 15 – 17 ].…”

Section: Introductionmentioning

confidence: 99%

“…A recently published systematic review [ 10 ] highlighted models available for predicting falls [ 11 – 17 ]. These models were primarily based on younger participants (65+ years) [ 11 – 13 , 15 – 17 ]. Also, methodological limitations were present regarding outcome assessments with long recording intervals and lack of blinding [ 11 – 17 ] which could potentially lead to unreliable predictions.…”

Section: Introductionmentioning

confidence: 99%

Development of a multivariable prognostic PREdiction model for 1-year risk of FALLing in a cohort of community-dwelling older adults aged 75 years and above (PREFALL)

et al. 2021

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Background Falls are the leading cause of fatal and non-fatal injuries in older adults, and attention to falls prevention is imperative. Prognostic models identifying high-risk individuals could guide fall-preventive interventions in the rapidly growing older population. We aimed to develop a prognostic prediction model on falls rate in community-dwelling older adults. Methods Design: prospective cohort study with 12 months follow-up and participants recruited from June 14, 2018, to July 18, 2019. Setting: general population. Subjects: community-dwelling older adults aged 75+ years, without dementia or acute illness, and able to stand unsupported for one minute. Outcome: fall rate for 12 months. Statistical methods: candidate predictors were physical and cognitive tests along with self-report questionnaires. We developed a Poisson model using least absolute shrinkage and selection operator penalization, leave-one-out cross-validation, and bootstrap resampling with 1000 iterations. Results Sample size at study start and end was 241 and 198 (82%), respectively. The number of fallers was 87 (36%), and the fall rate was 0.94 falls per person-year. Predictors included in the final model were educational level, dizziness, alcohol consumption, prior falls, self-perceived falls risk, disability, and depressive symptoms. Mean absolute error (95% CI) was 0.88 falls (0.71–1.16). Conclusion We developed a falls prediction model for community-dwelling older adults in a general population setting. The model was developed by selecting predictors from among physical and cognitive tests along with self-report questionnaires. The final model included only the questionnaire-based predictors, and its predictions had an average imprecision of less than one fall, thereby making it appropriate for clinical practice. Future external validation is needed. Trial registration Clinicaltrials.gov (NCT03608709).

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A two-question tool to assess the risk of repeated falls in the elderly

Cited by 20 publications

References 26 publications

Predicting falls in community-dwelling older adults: a systematic review of prognostic models

Predicting falls in community-dwelling older adults: a systematic review of prognostic models

Predictive validity of three home fall hazard assessment tools for older adults in Thailand

Development of a multivariable prognostic PREdiction model for 1-year risk of FALLing in a cohort of community-dwelling older adults aged 75 years and above (PREFALL)

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