Background: Sepsis recognition in older emergency department (ED) patients is difficult due to atypical symptom presentation. We therefore investigated whether the prognostic and discriminative performance of the five most commonly used disease severity scores were appropriate for risk stratification of older ED sepsis patients (≥70 years) compared to a younger control group (<70 years).
Methods: This was an observational multi-centre study using an existing database in which ED patients who were hospitalized with a suspected infection were prospectively included. Patients were stratified by age < 70 and ≥70 years. We assessed the association with in-hospital mortality (primary outcome) and the area under the curve (AUC) with receiver operator characteristics of the Predisposition, Infection, Response, Organ dysfunction (PIRO), quick Sequential Organ Failure Assessment (qSOFA), Mortality in ED Sepsis (MEDS), and the Modified and National Early Warning (MEWS and NEWS) scores.
Results: In-hospital mortality was 9.5% ((95%-CI); 7.4-11.5) in the 783 included older patients, and 4.6% (3.6-5.7) in the 1497 included younger patients. In contrast to younger patients, disease severity scores in older patients associated poorly with mortality. The AUCs of all disease severity scores were poor and ranged from 0.56 to 0.64 in older patients, significantly lower than the good AUC range from 0.72 to 0.86 in younger patients. The MEDS had the best AUC (0.64 (0.57-0.71)) in older patients. In older and younger patients, the newly proposed qSOFA score (Sepsis 3.0) had a lower AUC than the PIRO score (sepsis 2.0).
Conclusion: The prognostic and discriminative performance of the five most commonly used disease severity scores was poor and less useful for risk stratification of older ED sepsis patients.
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http://dx.doi.org/10.1186/s13049-017-0436-3 | DOI Listing |
BMC Med Inform Decis Mak
January 2025
Institute of Mathematical Sciences Centre for Health Analytics and Modelling (CHaM), Strathmore University, Nairobi, Kenya.
Background: Measures of diagnostic test accuracy provide evidence of how well a test correctly identifies or rules-out disease. Commonly used diagnostic accuracy measures (DAMs) include sensitivity and specificity, predictive values, likelihood ratios, area under the receiver operator characteristic curve (AUROC), area under precision-recall curves (AUPRC), diagnostic effectiveness (accuracy), disease prevalence, and diagnostic odds ratio (DOR) etc. Most available analysis tools perform accuracy testing for a single diagnostic test using summarized data.
View Article and Find Full Text PDFBMC Cancer
January 2025
Oncology Unit, Surgery Department, University College Hospital, Ibadan, Nigeria.
Background: Breast cancer is the leading cause of cancer among women globally and the most common cancer among women in Sierra Leone. This study aimed to evaluate the patterns of clinical presentation, management and outcomes among breast cancer patients who presented at the Connaught Teaching Hospital Complex in Sierra Leone.
Method: A retrospective, cross-sectional study was conducted at the specialist outpatient clinic at the Connaught Hospital.
Sci Rep
January 2025
Department of Burns and Plastic Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, No. 321, Zhongshan Road, Nanjing, 210008, Jiangsu, China.
Pyoderma, commonly known as impetigo, is a bacterial skin infection causing pus formation, prevalent globally, especially in resource-poor areas. It affects both children and adults, including those with conditions like diabetes. Despite its significant impact and economic burden, research on its global epidemiology is limited.
View Article and Find Full Text PDFNat Commun
January 2025
School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China.
Heatwaves are commonly simplified as binary variables in epidemiological studies, limiting the understanding of heatwave-mortality associations. Here we conduct a multi-country study across 28 East Asian cities that employed the Cumulative Excess Heatwave Index (CEHWI), which represents excess heat accumulation during heatwaves, to explore the potentially nonlinear associations of daytime-only, nighttime-only, and day-night compound heatwaves with mortality from 1981 to 2010. Populations exhibited high adaptability to daytime-only and nighttime-only heatwaves, with non-accidental mortality risks increasing only at higher CEHWI levels (75th-90th percentiles).
View Article and Find Full Text PDFEnviron Health Prev Med
January 2025
Department of Disease Control and Prevention, The Seventh Medical Center of Chinese PLA General Hospital.
Background: Hypertension is a serious chronic disease that can significantly lead to various cardiovascular diseases, affecting vital organs such as the heart, brain, and kidneys. Our goal is to predict the risk of new onset hypertension using machine learning algorithms and identify the characteristics of patients with new onset hypertension.
Methods: We analyzed data from the 2011 China Health and Nutrition Survey cohort of individuals who were not hypertensive at baseline and had follow-up results available for prediction by 2015.
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