Fall predictors in hospitalized patients living with cancer: a case-control study.

Autor: Zeneli A; Istituto Romagnolo Per Lo Studio Dei Tumori 'Dino Amadori' IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy. anita.zeneli@irst.emr.it., Montalti S; Istituto Romagnolo Per Lo Studio Dei Tumori 'Dino Amadori' IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy., Masciangelo I; Istituto Romagnolo Per Lo Studio Dei Tumori 'Dino Amadori' IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy., Manieri G; Istituto Romagnolo Per Lo Studio Dei Tumori 'Dino Amadori' IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy., Golinucci M; Istituto Romagnolo Per Lo Studio Dei Tumori 'Dino Amadori' IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy., Nanni O; Istituto Romagnolo Per Lo Studio Dei Tumori 'Dino Amadori' IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy., Montella MT; Istituto Romagnolo Per Lo Studio Dei Tumori 'Dino Amadori' IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy., Martinelli G; Istituto Romagnolo Per Lo Studio Dei Tumori 'Dino Amadori' IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy., Petracci E; Istituto Romagnolo Per Lo Studio Dei Tumori 'Dino Amadori' IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy.
Jazyk: angličtina
Zdroj: Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer [Support Care Cancer] 2022 Oct; Vol. 30 (10), pp. 7835-7843. Date of Electronic Publication: 2022 Jun 16.
DOI: 10.1007/s00520-022-07208-x
Abstrakt: Purpose: To identify fall predictors and develop an assessment tool to be used for screening hospitalized cancer patients at risk for fall.
Methods: A retrospective case-control study was conducted in 2018 at a cancer center in Northern Italy. The study participants were 448 adult cancer patients admitted to the oncology ward from 2009 to 2013. The case group consisted of 112 patients presenting at least one fall, while controls were randomly chosen by matching each case for age, sex, and admission period with three patients who did not fall. Data for the fall predictors were extracted from the electronic medical records. Conditional logistic regression was used to evaluate the association between patient's characteristics and fall risk.
Results: The overall prevalence of patients having at least one candidate fall predictor was high (98%). Seven of the studied variables showed an independent association with fall risk at multivariate analysis. These were tumor site, the presence of neurologic diseases, gait imbalance disorders, fatigue, and the assumption of certain medications such as diuretics, hypnotics, and opioids (odds ratios and 95% confidence intervals in brackets were 3.78 (1.78-8.13), 2.26 (1.08-4.77), 4.22 (1.87-9.52), 2.76 (1.45-5.26), 2.66 (1.52-4.66), 2.41 (1.20-4.85), and 3.03 (1.68-5.45), respectively).
Conclusions: In this study, we identified falling risk factors in an Italian population of hospitalized cancer patients and developed a new risk assessment tool. An external validation is necessary before implementing our screening tool in clinical practice.
(© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
Databáze: MEDLINE
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