Department of Geriatric Medicine, Aalborg University Hospital, Aalborg, Denmark
Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.
BMJ Open. 2021 May 4;11(5):e044170. doi: 10.1136/bmjopen-2020-044170.
To systematically review and critically appraise prognostic models for falls in community-dwelling older adults.
Prospective 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.
MEDLINE, 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.
Two 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.
After 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.
An 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.
CRD42019124021.
系统回顾和批判性评价社区居住的老年人跌倒的预后模型。
前瞻性队列研究，随访时间不限。研究必须针对社区居住的老年人（60 岁以上）开发或验证多因素跌倒预后模型。模型必须适用于一般人群的筛查。
MEDLINE、EMBASE、CINAHL、The Cochrane Library、PsycINFO 和 Web of Science，检索截至 2020 年 1 月发表在英文、丹麦文、挪威文或瑞典文的研究。来源还包括试验注册处、临床指南、纳入文献的参考文献列表，以及联系临床专家以找到已发表的研究。
两名作者独立进行所有审查阶段。数据提取遵循预测模型研究的批判性评价和数据提取清单。对参与者、预测因素、结局和分析方法的偏倚风险评估遵循预测研究风险评估工具。
在筛选了 11789 项研究后，有 30 项符合纳入标准（n=86369 名参与者）。参与者的中位年龄范围为 67.5 岁至 83.0 岁。跌倒发生率从 5.9%到 59%不等。纳入的研究报告了 69 个开发的和 3 个验证的预测模型。最常见的跌倒预测因素是既往跌倒、年龄、性别、步态、平衡和力量测量值，以及视力和残疾。40 个（55.6%）模型有曲线下面积，范围从 0.49 到 0.87。验证模型的曲线下面积范围从 0.62 到 0.69。所有模型的偏倚风险都很高，主要是由于统计方法、结局评估和限制性纳入标准的局限性。
已经开发了大量关于跌倒风险的预后模型，但预测性能差异很大。所有模型都存在高偏倚风险，使其在临床实践中的预测不可靠。未来的预后预测模型应符合 Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis 等最新建议。
PROSPERO 注册号：CRD42019124021。
