Background: Rates of hospital admissions for bronchiolitis vary seasonally and geographically across England; however, seasonal differences by area remain unexplored. We sought to describe spatial variation in the seasonality of hospital admissions for bronchiolitis and its association with local demographic characteristics.
Methods: Singleton children born in English National Health Service hospitals between 2011 and 2016 (n=3 727 013) were followed up for 1 year. Poisson regression models with harmonic functions to model seasonal variations were used to calculate weekly incidence rates and peak timing of bronchiolitis admissions across English regions and clinical commissioning groups (CCGs). Linear regression was used to estimate the joint association of population density and deprivation with incidence and peak timing of bronchiolitis admissions at the CCG level.
Results: Bronchiolitis admission rates ranged from 30.9 per 1000 infant-years (95% CI 30.4 to 31.3) in London to 68.7 per 1000 (95% CI 67.9 to 69.5) in the North West. Across CCGs, there was a 5.3-fold variation in incidence rates and the epidemic peak ranged from week 49.3 to 52.2. Admission rates were positively associated with area-level deprivation. CCGs with earlier peak epidemics had higher population densities, and both high and low levels of deprivation were associated with earlier peak timing.
Conclusions: Approximately one quarter of the variation in admission rates and two-fifths of the variation in peak timing of hospital admissions for bronchiolitis were explained by local demographic characteristics. Implementation of an early warning system could help to prepare hospitals for peak activity and to time public health messages.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7105391 | PMC |
http://dx.doi.org/10.1136/thoraxjnl-2019-213764 | DOI Listing |
J Med Internet Res
January 2025
Department of Anesthesiology, Daping Hospital, Army Medical University, Chongqing, China.
Background: Recent research has revealed the potential value of machine learning (ML) models in improving prognostic prediction for patients with trauma. ML can enhance predictions and identify which factors contribute the most to posttraumatic mortality. However, no studies have explored the risk factors, complications, and risk prediction of preoperative and postoperative traumatic coagulopathy (PPTIC) in patients with trauma.
View Article and Find Full Text PDFJAMA Netw Open
January 2025
Division of Geriatrics, School of Medicine, University of California San Francisco.
Importance: The Walter Index is a widely used prognostic tool for assessing 12-month mortality risk among hospitalized older adults. Developed in the US in 2001, its accuracy in contemporary non-US contexts is unclear.
Objective: To evaluate the external validity of the Walter Index in predicting posthospitalization mortality risk in Brazilian older adult inpatients.
JAMA Surg
January 2025
Department of Surgery, State University of New York, Downstate Health Sciences University, Brooklyn.
Importance: Chronic limb-threatening ischemia (CLTI) is a major public health issue that requires considerable human and physical resources to provide optimal patient care. It is essential to characterize the disease severity and resource needs of patients with CLTI presenting to facilities of varying resource capacities.
Objective: To investigate the association between facility-level Medicaid payer proportions and the incidence of nonelective admissions among patients admitted for CLTI.
JAMA Surg
January 2025
Department of Anesthesiology, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, New York.
Importance: In the US, traumatic injuries are a leading cause of mortality across all age groups. Patients with severe trauma often require time-sensitive, specialized medical care to reduce mortality; air transport is associated with improved survival in many cases. However, it is unknown whether the provision of and access to air transport are influenced by factors extrinsic to medical needs, such as race or ethnicity.
View Article and Find Full Text PDFHeart Vessels
January 2025
Medical Faculty Mannheim, Department of Cardiology, Angiology, Haemostaseology and Medical Intensive Care, University Medical Centre Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Germany.
This study investigates the prognosis of acute decompensated heart failure (ADHF) on admission (i.e., primary ADHF) as compared to ADHF onset during course of hospitalization (i.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!