Background: The aim was to identify fall predictors in elderly suffering from chronic pain (CP) and to test their applicability among patients with other chronic conditions.
Methods: 1,379 non-institutionalized patients aged 65 years and older who were suffering from CP (S.AGE CP sub-cohort) were monitored every 6 months for 1 year. Socio-demographic, clinical and pain data and medication use were assessed at baseline for the association with falls in the following year. Falls were assessed retrospectively at each study visit. Logistic regression analyses were performed to identify fall predictors. The derived model was applied to two additional S.AGE sub-cohorts: atrial fibrillation (AF) (n = 1,072) and type-2 diabetes mellitus (T2DM) (n = 983).
Results: Four factors predicted falls in the CP sub-cohort: fall history (OR: 4.03, 95 % CI 2.79-5.82), dependency in daily activities (OR: 1.81, 95 % CI 1.27-2.59), age ≥75 (OR: 1.53, 95 % CI 1.04-2.25) and living alone (OR: 1.73, 95 % CI 1.24-2.41) (Area Under the Curve: AUC = 0.71, 95 % CI 0.67-0.75). These factors were relevant in AF (AUC = 0.71, 95 % CI 0.66-0.75) and T2DM (AUC = 0.67, 95 % CI 0.59-0.73) sub-cohorts. Fall predicted probability in CP, AF and T2DM sub-cohorts increased from 7, 7 and 6 % in patients with no risk factors to 59, 66 and 45 % respectively, in those with the four predictors. Fall history was the strongest predictor in the three sub-cohorts.
Conclusion: Fall history, dependency in daily activities, age ≥75 and living alone are independent fall predictors in CP, AF and T2DM patients.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s40520-015-0319-2 | DOI Listing |
Sci Rep
January 2025
Department of Biological Sciences, California State University Los Angeles, 5151 State University Dr, Los Angeles, CA, 90032, USA.
The moss Syntrichia caninervis Mitt. is distributed throughout drylands globally, and often anchors ecologically significant communities known as biological soil crusts (biocrusts). The species occupies a variety of dryland habitats with varying levels of drought and temperature stress, suggesting the potential for ecological specialization within S.
View Article and Find Full Text PDFWe examined how generalized and mathematics-specific language skills predicted the word-problem performance of students with mathematics difficulty. Participants included 325 third-grade students in the southwestern United States who performed at or below the 25th percentile on a word-problem measure. We assessed generalized language skills in word reading, passage comprehension, and vocabulary knowledge.
View Article and Find Full Text PDFBMC Geriatr
January 2025
Department of Nursing, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, 322000, China.
Background: Existing fall risk assessment tools in clinical settings often lack accuracy. Although an increasing number of fall risk prediction models have been developed for hospitalized older patients in recent years, it remains unclear how useful these models are for clinical practice and future research.
Objectives: To systematically review published studies of fall risk prediction models for hospitalized older adults.
Eur J Trauma Emerg Surg
January 2025
Division of Trauma, Emergency Surgery, and Surgical Critical Care, Department of Surgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Purpose: This study aims to identify predictors of discharge to post-acute care in geriatric emergency general surgery (EGS) patients.
Methods: This is a retrospective study of geriatric emergency general surgery (EGS) patients at a tertiary care facility between 2017 and 2018. Inclusion criteria were ≥ 65 years old and presented directly from home.
JMIR Hum Factors
January 2025
Department of Medical Safety, Shizuoka General Hospital, Shizuoka, Japan.
Background: Falls in hospitalized patients are a serious problem, resulting in physical injury, secondary complications, impaired activities of daily living, prolonged hospital stays, and increased medical costs. Establishing a fall prediction scoring system to identify patients most likely to fall can help prevent falls among hospitalized patients.
Objectives: This study aimed to identify predictive factors of falls in acute care hospital patients, develop a scoring system, and evaluate its validity.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!