Frailty and mortality among older patients in a tertiary hospital in Nigeria

Adebusoye, Lawrence A.; Cadmus, Eniola Olubukola; Owolabi, Mayowa; Ogunniyi, Adesola

doi:10.4314/gmj.v53i3.5

Cited by 16 publications

(29 citation statements)

References 21 publications

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“…Geriatric syndromes such as frailty, delirium, falls, dementia, depression, functional impairment, or malnutrition, have been consistently reported as factors of increased risk of death in several studies [10][11][12][13][14][15][16][17]. In our study, older adults with functional impairment or depression were twice as likely as those without these geriatric syndromes to die within the 3 months after hospitalization.…”

Section: Discussionsupporting

confidence: 49%

“…Also, high mortality rates have been reported among hospitalized older adults, ranging from 5% during hospital stay to 20-30% within 1 year following hospital discharge [7]. In the literature, main risk factors for hospital mortality among older adults are age, length of stay [9,10], health conditions such as cardiovascular diseases, diabetes, stroke, cancer, and lung diseases [10], and geriatric syndromes such as fall, inappropriate drug use, malnutrition, frailty, functional impairment, and depression [10][11][12][13][14][15][16][17]. Assessing these predictors is important as some of them can be prevented through appropriate interventions.…”

Section: Introductionmentioning

confidence: 99%

“…In sub-Saharan Africa (SSA), few studies have reported hospital mortality data among older adults. Hospital mortality rates in these studies ranged from 15.1% in South Africa [ 9 ] to 22.0% in Nigeria [ 13 ] . In Togo, the proportion of older adults ≥60 years is expected to increase from 5.2% in 2010 to 6.7% by 2030 [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

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Predictors of three-month mortality among hospitalized older adults in Togo

et al. 2020

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Background Assessing hospital mortality and its predictors is important as some of these can be prevented through appropriate interventions. Few studies have reported hospital mortality data among older adults in sub-Saharan Africa. The objective of this study was to assess the mortality and associated factors among hospitalized older adults in Togo. Methods We conducted a prospective cohort study from February 2018 to September 2019 among patients ≥50 years admitted in medical and surgical services of six hospitals in Togo. Data were recorded during hospitalization and through telephone follow-up survey within 90 days after admission. The main outcome was all-cause mortality at 3 months. Survival curves were estimated using the Kaplan-Meier method and Cox regression analyses were performed to assess predictors of mortality. Results The median age of the 650 older adults included in the study period was 61 years, IQR: [55–70] and at least one comorbidity was identified in 59.7% of them. The all-cause mortality rate of 17.2% (95%CI: 14.4–20.4) and the majority of death (93.7%) occurred in hospital. Overall survival rate was 85.5 and 82.8% after 30 and 90 days of follow-up, respectively. Factors associated with 3-month mortality were the hospital level in the health pyramid, hospitalization service, length of stay, functional impairment, depression and malignant diseases. Conclusion Togolese health system needs to adjust its response to an aging population in order to provide the most effective care.

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Section: Discussionsupporting

confidence: 49%

Section: Introductionmentioning

confidence: 99%

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Predictors of three-month mortality among hospitalized older adults in Togo

et al. 2020

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“…The measurement of intrinsic capacity in frail individuals may provide additional information to formulate a personalized care program to address deficits associated with frailty and to tailor health promoting strategies to attenuate losses and foster wellbeing (Belloni & Cesari, 2019). Patients who are frail based on the FRS-NF definitions are at higher risk for in-hospital mortality compared to patients who are less frail, which calls for prompt identification and management to improve survival (Adebusoye et al, 2019). Identification of frail patients as demonstrated in this study enables nurses and other healthcare providers to enhance various aspects of care, including instituting increased monitoring, applying more intensive, individualized resources to high-risk patients, and initiating more informed discussions with patients and their families about treatment options and discharge planning.…”

Section: Discussionmentioning

confidence: 99%

Frailty and In-Hospital Mortality Risk Using EHR Nursing Data

Lekan

McCoy

Jenkins

et al. 2021

Biological Research For Nursing

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Purpose The purpose of this study was to evaluate four definitions of a Frailty Risk Score (FRS) derived from EHR data that includes combinations of biopsychosocial risk factors using nursing flowsheet data or International Classification of Disease, 10th revision (ICD-10) codes and blood biomarkers and its predictive properties for in-hospital mortality in adults ≥50 years admitted to medical-surgical units. Methods In this retrospective observational study and secondary analysis of an EHR dataset, survival analysis and Cox regression models were performed with sociodemographic and clinical covariates. Integrated area under the ROC curve (iAUC) across follow-up time based on Cox modeling was estimated. Results The 46,645 patients averaged 1.5 hospitalizations (SD = 1.1) over the study period and 63.3% were emergent admissions. The average age was 70.4 years (SD = 11.4), 55.3% were female, 73.0% were non-Hispanic White (73.0%), mean comorbidity score was 3.9 (SD = 2.9), 80.5% were taking 1.5 high risk medications, and 42% recorded polypharmacy. The best performing FRS-NF-26-LABS included nursing flowsheet data and blood biomarkers (Adj. HR = 1.30, 95% CI [1.28, 1.33]), with good accuracy (iAUC = .794); the reduced model with age, sex, and FRS only demonstrated similar accuracy. The poorest performance was the ICD-10 code-based FRS. Conclusion The FRS captures information about the patient that increases risk for in-hospital mortality not accounted for by other factors. Identification of frailty enables providers to enhance various aspects of care, including increased monitoring, applying more intensive, individualized resources, and initiating more informed discussions about treatments and discharge planning.

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“…Also, high mortality rates have been reported among hospitalized older adults, ranging from 5% during hospital stay to 20%-30% within one year following hospital discharge [7]. In the literature, main risk factors for hospital mortality among older adults are age, length of stay [9,10], health conditions such as cardiovascular diseases, diabetes, stroke, cancer, and lung diseases [10], and geriatric syndromes such as fall, inappropriate drug use, malnutrition, frailty, functional impairment, and depression [10][11][12][13][14][15][16][17]. Assessing these predictors is important as some of them can be prevented through appropriate interventions.…”

Section: Introductionmentioning

confidence: 99%

Predictors of three-month mortality among hospitalized older adults in Togo

Gbeasor-Komlanvi

Tchankoni

Bakoubayi

et al. 2020

Preprint

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Background: Assessing hospital mortality and its predictors is important as some of these can be prevented through appropriate interventions. Few studies have reported hospital mortality data among older adults in sub-Saharan Africa. The objective of this study was to assess the mortality and associated factors among hospitalized older adults in Togo.Methods: We conducted a prospective cohort study from February 2018 to September 2019 among patients ≥50 years admitted in medical and surgical services of six hospitals in Togo. Data were recorded during hospitalization and through telephone follow-up survey within 90 days after admission. The main outcome was all-cause mortality at 3 months. Survival curves were estimated using the Kaplan-Meier method and Cox regression analyses were performed to assess predictors of mortality.Results: The median age of the 650 older adults included in the study period was 61 years, IQR: [55-70] and at least one comorbidity was identified in 59.7% of them. The all-cause mortality rate of 17.2% (95%CI: 14.4-20.4) and the majority of death (93.7%) occurred in hospital. Overall survival rate was 85.5% and 82.8% after 30 and 90 days of follow-up, respectively. Factors associated with 3-month mortality were the hospital level in the health pyramid, hospitalization service, length of stay, functional impairment, depression and malignant diseases.Conclusion: Togolese health system needs to adjust its response to an aging population in order to provide the most effective care.

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Frailty and mortality among older patients in a tertiary hospital in Nigeria

Cited by 16 publications

References 21 publications

Predictors of three-month mortality among hospitalized older adults in Togo

Predictors of three-month mortality among hospitalized older adults in Togo

Frailty and In-Hospital Mortality Risk Using EHR Nursing Data

Predictors of three-month mortality among hospitalized older adults in Togo

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