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Developing a Scoring Model to Predict the Risk of Injurious Falls in Elderly Patients: A Retrospective Case–Control Study in Multicenter Acute Hospitals

ABSTRACT: Purpose Injurious falls seriously threaten the safety of elderly patients. Identifying risk factors for predicting the probability of injurious falls is an important issue that still needs to be solved urgently. We aimed to identify predictors and develop a nomogram for distinguishing populations at high risk of injurious falls from older adults in acute settings. Patients and Methods A retrospective case–control study was conducted at three hospitals in Shanghai, China. Elderly patients with injurious falls from January 2014 to December 2018 were taken as cases, and control patients who did not have falls were randomly matched based on the admission date and the department. The data were collected through a medical record review and adverse events system. The original data set was randomly divided into a training set and a validation set at a 7:3 ratio. A nomogram was established based on the results of the univariate analysis and multivariate logistic regression analysis, and its discrimination and calibration were verified to confirm the accuracy of the prediction. The cut-off value of risk stratification was determined to help medical staff identify the high-risk groups. Results A total of 115 elderly patients with injurious falls and 230 controls were identified. History of fractures, orthostatic hypotension, functional status, sedative-hypnotics and level of serum albumin were independent risk factors for injurious falls in elderly patients. The C-indexes of the training and validation sets were 0.874 (95% CI: 0.784?0.964) and 0.847 (95% CI: 0.771–0.924), respectively. Calibration curves were drawn and showed acceptable predictive performance. The cut-off values of the training and validation sets were 146.3 points (sensitivity: 73.7%; specificity: 87.5%) and 157.2 points (sensitivity: 69.2%; specificity: 85.5%), respectively. Conclusion The established nomogram facilitates the identification of high-risk populations among elderly patients, providing a new assessment tool to forecast the individual risk of injurious falls.

SUBMITTER: Zhao M

PROVIDER: S-EPMC7522431 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Unassisted falls are more likely to result in injury than assisted falls. However, little is known about risk factors for falling unassisted. Furthermore, rural hospitals, which care for a high proportion of older adults, are underrepresented in research on hospital falls. This study identified risk factors for unassisted and injurious falls in rural hospitals. METHODS:Seventeen hospitals reported 353 falls over 2?years. We categorized falls by type (assisted vs. unassisted) and outcome (injurious vs. non-injurious). We used multivariate logistic regression to determine factors that predicted fall type and outcome. RESULTS:With all other factors being equal, the odds of falling unassisted were 2.55 times greater for a patient aged ?65 than <?65 (95% confidence interval [CI]?=?1.30-5.03), 3.70 times greater for a patient with cognitive impairment than without (95% CI?=?2.06-6.63), and 6.97 times greater if a gait belt was not identified as an intervention for a patient than if it was identified (95% CI?=?3.75-12.94). With all other factors being equal, the odds of an injurious fall were 2.55 times greater for a patient aged ?65 than <?65 (95% CI?=?1.32-4.94), 2.48 times greater if a fall occurred in the bathroom vs. other locations (95% CI?=?1.41-4.36), and 3.65 times greater if the fall occurred when hands-on assistance was provided without a gait belt, compared to hands-on assistance with a gait belt (95% CI?=?1.34-9.97). CONCLUSIONS:Many factors associated with unassisted or injurious falls in rural hospitals were consistent with research conducted in larger facilities. A novel finding is that identifying a gait belt as an intervention decreased the odds of patients falling unassisted. Additionally, using a gait belt during an assisted fall decreased the odds of injury. We expanded upon other research that found an association between assistance during falls and injury by discovering that the manner in which a fall is assisted is an important consideration for risk mitigation.

Project description:BackgroundThis study aimed to determine whether the number of anti-hypertensive medication classes or any change in anti-hypertensive medication were associated with injurious fall among the community-dwelling older population of low socioeconomic status.MethodsUsing data from electronic medical records, we performed a nested case-control study among older Singapore residents (≥60) of low socioeconomic status (N = 210). Controls (n = 162) were matched to each case (n = 48) by age and gender. Variables with p < 0.10 in univariate analysis were included in multivariate analysis. We used conditional logistic regression to assess the associations of the number of anti-hypertensive medication classes and change in anti-hypertensive medication with injurious falls. We also performed stepwise regressions as sensitivity analyses. p < 0.05 was considered statistically significant.ResultsThe mean (±SD) age of participants was 78.1 (± 8.33) years; 127 (60.4%) were female, 189 (90.0%) were Chinese. Those on ≥2 anti-hypertensive medication classes had an increased risk of experiencing an injurious fall compared to those not on any anti-hypertensive medication (OR = 5.45; CI:1.49-19.93; p = 0.01). Among those who were taking anti-hypertensive medication, those who had a change in the medication 180-day prior to injurious fall had a significantly increased risk of experiencing an injurious fall compared to those that did not report any change in anti-hypertensive medication (OR = 3.88; CI:1.23-12.19; p = 0.02). Sensitivity analyses generated consistent findings.ConclusionBoth ≥2 anti-hypertensive medication classes and change in anti-hypertensive medication were associated with an increased risk of experiencing an injurious fall among the older population of low socioeconomic status. Our findings could guide prescribers to exercise caution in the initiation of anti-hypertensive medications or in making medication changes, especially among the older population of low socioeconomic status.

Project description:PURPOSE:To review and update the evidence of the relationship between physical activity, risk of fall-related injury, and physical function in community-dwelling older people that was presented in the 2018 Physical Activity Guidelines Advisory Committee Scientific Report (PAGAC Report). METHODS:Duplicate independent screenings of 1415 systematic reviews and meta-analyses published between 2006 and 2016 identified from PubMed®, Cochrane Library, and CINAHL databases yielded 111 articles used for the PAGAC Report. The PAGAC Aging Subcommittee members graded scientific evidence strength based upon a five-criteria rubric and assigned one of four grades: strong, moderate, limited, or not assignable. An updated search of 368 articles published between January 2017 and March 2018 yielded 35 additional pertinent articles. RESULTS:Strong evidence demonstrated that physical activity reduced the risk of fall-related injuries by 32% to 40%, including severe falls requiring medical care or hospitalization. Strong evidence also supported that physical activity improved physical function and reduced the risk of age-related loss of physical function in an inverse graded manner among the general aging population, and improved physical function in older people with frailty and with Parkinson's disease. Aerobic, muscle-strengthening, and/or multicomponent physical activity programs elicited the largest improvements in physical function in these same populations. Moderate evidence indicated that for older adults who sustained a hip fracture or stroke, extended exercise programs and mobility-oriented physical activity improved physical function. CONCLUSIONS:Regular physical activity effectively helps older adults improve or delay the loss of physical function and mobility while reducing the risk of fall-related injuries. These important public health benefits underscore the importance of physical activity among older adults, especially those living with declining physical function and chronic health conditions.

Project description:ObjectiveTo develop and validate a scoring system to predict mortality among hospitalized patients with COVID-19.MethodsRetrospective cohort study. We analyzed 5,062 analyzed hospitalized patients with COVID-19 treated at two hospitals; one each in Quito and Guayaquil, from February to July 2020. We assessed predictors of mortality using survival analyses and Cox models. We randomly divided the database into two sets: (i) the derivation cohort (n = 2497) to identify predictors of mortality, and (ii) the validation cohort (n = 2565) to test the discriminative ability of a scoring system. After multivariate analyses, we used the final model's β-coefficients to build the score. Statistical analyses involved the development of a Cox proportional hazards regression model, assessment of goodness of fit, discrimination, and calibration.ResultsThere was a higher mortality risk for these factors: male sex [(hazard ratio (HR) = 1.32, 95% confidence interval (95% CI): 1.03-1.69], per each increase in a quartile of ages (HR = 1.44, 95% CI: 1.24-1.67) considering the younger group (17-44 years old) as the reference, presence of hypoxemia (HR = 1.40, 95% CI: 1.01-1.95), hypoglycemia and hospital hyperglycemia (HR = 1.99, 95% CI: 1.01-3.91, and HR = 1.27, 95% CI: 0.99-1.62, respectively) when compared with normoglycemia, an AST-ALT ratio >1 (HR = 1.55, 95% CI: 1.25-1.92), C-reactive protein level (CRP) of >10 mg/dL (HR = 1.49, 95% CI: 1.07-2.08), arterial pH <7.35 (HR = 1.39, 95% CI: 1.08-1.80) when compared with normal pH (7.35-7.45), and a white blood cell count >10 × 103 per μL (HR = 1.76, 95% CI: 1.35-2.29). We found a strong discriminative ability in the proposed score in the validation cohort [AUC of 0.876 (95% CI: 0.822-0.930)], moreover, a cutoff score ≥39 points demonstrates superior performance with a sensitivity of 93.10%, a specificity of 70.28%, and a correct classification rate of 72.66%. The LR+ (3.1328) and LR- (0.0981) values further support its efficacy in identifying high-risk patients.ConclusionMale sex, increasing age, hypoxemia, hypoglycemia or hospital hyperglycemia, AST-ALT ratio >1, elevated CRP, altered arterial pH, and leucocytosis were factors significantly associated with higher mortality in hospitalized patients with COVID-19. A statistically significant Cox regression model with strong discriminatory power and good calibration was developed to predict mortality in hospitalized patients with COVID-19, highlighting its potential clinical utility.

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Developing a Scoring Model to Predict the Risk of Injurious Falls in Elderly Patients: A Retrospective Case–Control Study in Multicenter Acute Hospitals

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