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Prevalence of and characteristics associated with in-hospital mortality in a Ugandan neurology ward.

ABSTRACT: BACKGROUND:While the burden of neurologic illness in developing countries is increasing, less is known about mortality among patients admitted to sub-Saharan African hospitals with neurologic disease. We sought to characterize the rate and patient-level predictors of in-hospital mortality in a Ugandan Neurology ward.cc. METHODS:Data was prospectively collected on 335 patients admitted to the Neurology ward of Mulago Hospital, Kampala, Uganda. Kaplan-Meier survival curves and multivariate COX proportional hazard modeling were used to assess survival. RESULTS:Within our sample (n = 307), 35.8% received no diagnosis at time of hospital admission. Stroke (27.3%), head trauma (19.6%), and malaria (16.0%) were the most common diagnoses. Among the 56 (18.5%) patients who died during the index hospitalization, the most common diagnosis at admission and at death was stroke. Adjusted regression analysis showed that patients without a diagnosis at time of death (HR = 7.01 [2.42-20.35], p < .001) and those with diagnoses of infections (HR = 5.21 [2.16-12.58], p = <.001), stroke (HR = 2.69 [1.20-6.04], p = .017), or head trauma (HR = 3.39, [1.27-9.07], p = 0.15) had worse survival. CONCLUSIONS:In-hospital mortality affected nearly 20% of the cohort, with worse survival among those without a diagnosis and with infections, stroke, head trauma. Future work should identify reasons for increased mortality among these high-risk groups and implement targeted interventions.

SUBMITTER: Diaz MM

PROVIDER: S-EPMC6995141 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Prevalence of and characteristics associated with in-hospital mortality in a Ugandan neurology ward.

Diaz Monica M MM Hu Xin X Fenton Brenda T BT Kimuli Ivan I Lee Allison A Lindsey Hayley H Bigelow Jeffrey K JK Maiser Samuel S Altalib Hamada H HH Sico Jason J JJ

BMC neurology 20200131 1

<h4>Background</h4>While the burden of neurologic illness in developing countries is increasing, less is known about mortality among patients admitted to sub-Saharan African hospitals with neurologic disease. We sought to characterize the rate and patient-level predictors of in-hospital mortality in a Ugandan Neurology ward.cc.<h4>Methods</h4>Data was prospectively collected on 335 patients admitted to the Neurology ward of Mulago Hospital, Kampala, Uganda. Kaplan-Meier survival curves and multi ...[more]

PMID: 32005185

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Project description:The COVID-19 pandemic caused unprecedented pressure over health care systems worldwide. Hospital-level data that may influence the prognosis in COVID-19 patients still needs to be better investigated. Therefore, this study analyzed regional socioeconomic, hospital, and intensive care units (ICU) characteristics associated with in-hospital mortality in COVID-19 patients admitted to Brazilian institutions. This multicenter retrospective cohort study is part of the Brazilian COVID-19 Registry. We enrolled patients ≥ 18 years old with laboratory-confirmed COVID-19 admitted to the participating hospitals from March to September 2020. Patients' data were obtained through hospital records. Hospitals' data were collected through forms filled in loco and through open national databases. Generalized linear mixed models with logit link function were used for pooling mortality and to assess the association between hospital characteristics and mortality estimates. We built two models, one tested general hospital characteristics while the other tested ICU characteristics. All analyses were adjusted for the proportion of high-risk patients at admission. Thirty-one hospitals were included. The mean number of beds was 320.4 ± 186.6. These hospitals had eligible 6556 COVID-19 admissions during the study period. Estimated in-hospital mortality ranged from 9.0 to 48.0%. The first model included all 31 hospitals and showed that a private source of funding (β = - 0.37; 95% CI - 0.71 to - 0.04; p = 0.029) and location in areas with a high gross domestic product (GDP) per capita (β = - 0.40; 95% CI - 0.72 to - 0.08; p = 0.014) were independently associated with a lower mortality. The second model included 23 hospitals and showed that hospitals with an ICU work shift composed of more than 50% of intensivists (β = - 0.59; 95% CI - 0.98 to - 0.20; p = 0.003) had lower mortality while hospitals with a higher proportion of less experienced medical professionals had higher mortality (β = 0.40; 95% CI 0.11-0.68; p = 0.006). The impact of those association increased according to the proportion of high-risk patients at admission. In-hospital mortality varied significantly among Brazilian hospitals. Private-funded hospitals and those located in municipalities with a high GDP had a lower mortality. When analyzing ICU-specific characteristics, hospitals with more experienced ICU teams had a reduced mortality.

Project description:IntroductionFrailty is a common and clinically significant condition in geriatric populations, associated with adverse health outcomes such as hospitalisation, disability and mortality. Although there are systematic reviews/meta-analyses assessing the prevalence of frailty in community-dwelling older adults, nursing home residents, and cancer and general surgery patients, there are none assessing the overall prevalence of frailty in geriatric hospital inpatients.Methods and analysisThis review will systematically search and analyse the prevalence of frailty within geriatric hospital inpatients within the literature. A search will be employed on the platforms of Ovid, Web of Science and databases of Cumulative Index to Nursing and Allied Health Literature (CINAHL) Plus, SCOPUS and the Cochrane Library. Any observational or experimental study design which utilises a validated operational definition of frailty, reports the prevalence of frailty, has a minimum age ≥65 years, attempts to assess the whole ward/clinical population and occurs in hospital inpatients, will be included. Title and abstract and full-text screenings will be conducted by three reviewers. Methodological quality of eligible studies will be assessed using the Joanna Briggs Institute critical appraisal tool. Data extraction will be performed by two reviewers. If sufficient data are available, a meta-analysis synthesising pooled estimates of the prevalence of frailty and pre-frailty, as well as the prevalence of frailty stratified by age, sex, operational frailty definition, prevalent morbidities, ward type and location, among older hospitalised inpatients will be conducted. Clinical heterogeneity will be assessed by two reviewers. Statistical heterogeneity will be assessed through a Cochran Q test, and an I2 test performed to assess its magnitude.Ethics and disseminationEthical approval was not required as primary data will not be collected. Findings will be disseminated through publication in peer reviewed open access scientific journals, public engagement events, conference presentations and social media.Prospero registration number79202.

Project description:BackgroundThis paper describes a model for estimating COVID-19 related excess deaths that are a direct consequence of insufficient hospital ward bed and intensive care unit (ICU) capacity.MethodsCompartmental models were used to estimate deaths under different combinations of ICU and ward care required and received in England up to late April 2021. Model parameters were sourced from publicly available government information and organisations collating COVID-19 data. A sub-model was used to estimate the mortality scalars that represent increased mortality due to insufficient ICU or general ward bed capacity. Three illustrative scenarios for admissions numbers, 'Optimistic', 'Middling' and 'Pessimistic', were modelled and compared with the subsequent observations to the 3rd February.ResultsThe key output was the demand and capacity model described. There were no excess deaths from a lack of capacity in the 'Optimistic' scenario. Several of the 'Middling' scenario applications resulted in excess deaths-up to 597 deaths (0.6% increase) with a 20% reduction compared to best estimate ICU capacity. All the 'Pessimistic' scenario applications resulted in excess deaths, ranging from 49,178 (17.0% increase) for a 20% increase in ward bed availability, to 103,735 (35.8% increase) for a 20% shortfall in ward bed availability. These scenarios took no account of the emergence of the new, more transmissible, variant of concern (b.1.1.7).ConclusionsMortality is increased when hospital demand exceeds available capacity. No excess deaths from breaching capacity would be expected under the 'Optimistic' scenario. The 'Middling' scenario could result in some excess deaths-up to a 0.7% increase relative to the total number of deaths. The 'Pessimistic' scenario would have resulted in significant excess deaths. Our sensitivity analysis indicated a range between 49,178 (17% increase) and 103,735 (35.8% increase). Given the new variant, the pessimistic scenario appeared increasingly likely and could have resulted in a substantial increase in the number of COVID-19 deaths. In the event, it would appear that capacity was not breached at any stage at a national level with no excess deaths. it will remain unclear if minor local capacity breaches resulted in any small number of excess deaths.

Dataset Information

Prevalence of and characteristics associated with in-hospital mortality in a Ugandan neurology ward.

Publications

Prevalence of and characteristics associated with in-hospital mortality in a Ugandan neurology ward.

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