BackgroundNational Early Warning Score (NEWS) is increasingly used in UK hospitals. However, there is only limited evidence to support the use of pre-hospital early warning scores. We hypothesised that pre-hospital NEWS was associated with death or critical care escalation within the first 48 h of hospital stay.MethodsPlanned secondary analysis of a prospective cohort study at a single UK teaching hospital. Consecutive medical ward admissions over a 20-day period were included in the study. Data were collected from ambulance report forms, medical notes and electronic patient records. Pre-hospital NEWS was calculated retrospectively. The primary outcome was a composite of death or critical care unit escalation within 48 h of hospital admission. The secondary outcome was length of hospital stay.Results189 patients were included in the analysis. The median pre-hospital NEWS was 3 (IQR 1–5). 13 patients (6.9%) died or were escalated to the critical care unit within 48 h of hospital admission. Pre-hospital NEWS was associated with death or critical care unit escalation (OR, 1.25; 95% CI, 1.04–1.51; p = 0.02), but NEWS on admission to hospital was more strongly associated with this outcome (OR, 1.52; 95% CI, 1.18–1.97, p < 0.01). Neither was associated with hospital length of stay.ConclusionPre-hospital NEWS was associated with death or critical care unit escalation within 48 h of hospital admission. NEWS could be used by ambulance crews to assist in the early triage of patients requiring hospital treatment or rapid transport. Further cohort studies or trials in large samples are required before implementation.
NEWS on admission is superior to PARS for identifying patients at risk of death or critical care admission within the first 2 days of hospital stay. Current guidelines advocate a threshold of 5 for triggering a clinical review. However, since a score of 3 or more was associated with a poor outcome, this recommendation should be reviewed. Both scores were poor predictors of hospital length of stay.
ObjectiveTo describe the characteristics and outcomes of patients with a clinical diagnosis of COVID-19 and false-negative SARS-CoV-2 reverse transcription-PCR (RT-PCR), and develop and internally validate a diagnostic risk score to predict risk of COVID-19 (including RT-PCR-negative COVID-19) among medical admissions.DesignRetrospective cohort study.SettingTwo hospitals within an acute NHS Trust in London, UK.ParticipantsAll patients admitted to medical wards between 2 March and 3 May 2020.OutcomesMain outcomes were diagnosis of COVID-19, SARS-CoV-2 RT-PCR results, sensitivity of SARS-CoV-2 RT-PCR and mortality during hospital admission. For the diagnostic risk score, we report discrimination, calibration and diagnostic accuracy of the model and simplified risk score and internal validation.Results4008 patients were admitted between 2 March and 3 May 2020. 1792 patients (44.8%) were diagnosed with COVID-19, of whom 1391 were SARS-CoV-2 RT-PCR positive and 283 had only negative RT-PCRs. Compared with a clinical reference standard, sensitivity of RT-PCR in hospital patients was 83.1% (95% CI 81.2%–84.8%). Broadly, patients with false-negative RT-PCR COVID-19 and those confirmed by positive PCR had similar demographic and clinical characteristics but lower risk of intensive care unit admission and lower in-hospital mortality (adjusted OR 0.41, 95% CI 0.27–0.61). A simple diagnostic risk score comprising of age, sex, ethnicity, cough, fever or shortness of breath, National Early Warning Score 2, C reactive protein and chest radiograph appearance had moderate discrimination (area under the receiver–operator curve 0.83, 95% CI 0.82 to 0.85), good calibration and was internally validated.ConclusionRT-PCR-negative COVID-19 is common and is associated with lower mortality despite similar presentation. Diagnostic risk scores could potentially help triage patients requiring admission but need external validation.
BackgroundEpidemiological data on malaria in Bangladesh are sparse, particularly on severe and fatal malaria. This hampers the allocation of healthcare provision in this resource-poor setting. Over 85% of the estimated 150,000-250,000 annual malaria cases in Bangladesh occur in Chittagong Division with 80% in the Chittagong Hill Tracts (CHT). Chittagong Medical College Hospital (CMCH) is the major tertiary referral hospital for severe malaria in Chittagong Division.MethodsMalaria screening data from 22,785 inpatients in CMCH from 1999–2011 were analysed to investigate the patterns of referral, temporal trends and geographical distribution of severe malaria in Chittagong Division, Bangladesh.ResultsFrom 1999 till 2011, 2,394 malaria cases were admitted, of which 96% harboured Plasmodium falciparum and 4% Plasmodium vivax. Infection was commonest in males (67%) between 15 and 34 years of age. Seasonality of malaria incidence was marked with a single peak in P. falciparum transmission from June to August coinciding with peak rainfall, whereas P. vivax showed an additional peak in February-March possibly representing relapse infections. Since 2007 there has been a substantial decrease in the absolute number of admitted malaria cases. Case fatality in severe malaria was 18% from 2008–2011, remaining steady during this period.A travel history obtained in 226 malaria patients revealed only 33% had been to the CHT in the preceding three weeks. Of all admitted malaria patients, only 9% lived in the CHT, and none in the more remote malaria endemic regions near the Indian border.ConclusionsThe overall decline in admitted malaria cases to CMCH suggests recent control measures are successful. However, there are no reliable data on the incidence of severe malaria in the CHT, the most endemic area of Bangladesh, and most of these patients do not reach tertiary health facilities. Improvement of early treatment and simple supportive care for severe malaria in remote areas and implementation of a referral system for cases requiring additional supportive care could be important contributors to further reducing malaria-attributable disease and death in Bangladesh.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.