Objective: This study assessed the associations between hospital volume, resection rate and survival of oesophageal and gastric cancer patients in England.
Design: 62,811 patients diagnosed with oesophageal or gastric cancer between 2004 and 2008 were identified from a national population-based cancer registration and Hospital Episode Statistics-linked dataset. Cox regression analyses were used to assess all-cause mortality according to hospital volume and resection rate, adjusting for case-mix variables (sex, age, socioeconomic deprivation, comorbidity and type of cancer). HRs and 95% CIs, according to hospital volume, were evaluated for three predefined periods following surgery: <30, 30-365, and >365 days. Analysis of mortality in relation to resection rate was performed among all patients and among the 13 189 (21%) resected patients.
Results: Increasing hospital volume was associated with lower mortality (p trend=0.0001; HR 0.87, 95% CI 0.79 to 0.95 for hospitals resecting 80+ and compared with <20 patients a year). In relative terms, the association between increasing hospital volume and lower mortality was particularly strong in the first 30 days following surgery (p trend<0.0001; HR 0.52, (0.39 to 0.70)), but a clinically relevant association remained beyond 1 year (p trend=0.0011; HR 0.82, (0.72 to 0.95)). Increasing resection rates were associated with lower mortality among all patients (p trend<0.0001; HR 0.86, (0.84 to 0.89) for the highest, compared with the lowest resection quintile).
Conclusions: With evidence of lower short-term and longer-term mortality for patients resected in high-volume hospitals, this study supports further centralisation of oesophageal and gastric cancer surgical services in England.
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http://dx.doi.org/10.1136/gutjnl-2012-303008 | DOI Listing |
Aliment Pharmacol Ther
January 2025
Gastrointestinal and Liver Theme, National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre (BRC), Nottingham University Hospitals NHS Trust and the University of Nottingham, School of Medicine, Queen's Medical Centre, Nottingham, UK.
Background: Colorectal cancer (CRC) is the third most common cancer in the United Kingdom and the second largest cause of cancer death.
Aim: To develop and validate a model using available information at the time of faecal immunochemical testing (FIT) in primary care to improve selection of symptomatic patients for CRC investigations.
Methods: We included all adults (≥ 18 years) referred to Nottingham University Hospitals NHS Trust between 2018 and 2022 with symptoms of suspected CRC who had a FIT.
Circ Cardiovasc Imaging
January 2025
Cardiovascular Center Aalst, Onze-Lieve-Vrouwziekenhuis (OLV) Clinic, Aalst, Belgium (M. Belmonte, P.P., M.M.V., M. Beles, H.O., R.S., G.E., M.S., R.D., W.H., J.V.K., J.B., M.V.).
Background: Coronary computed tomography angiography (CCTA) is emerging as a valuable tool for noninvasive surveillance of cardiac allograft vasculopathy (CAV) in patients with heart transplant (HTx). We assessed the diagnostic performance of a comprehensive CCTA-based approach compared with the invasive reference, which includes invasive coronary angiography, intravascular ultrasound, and fractional flow reserve, for detecting CAV.
Methods: This was a multicenter prospective study including 37 patients with HTx who underwent CCTA, invasive coronary angiography, intravascular ultrasound, and fractional flow reserve.
Anaesthesia
January 2025
Department of Anaesthesia and Intensive Care, Hospices Civils de Lyon, Femme Mère Enfant Hospital, Bron, France.
Introduction: The diagnostic accuracy of gastric ultrasound in children has not been assessed thoroughly. We aimed to determine the sensitivity and specificity in children of a qualitative ultrasound examination of the gastric antrum in the supine 45° semi-recumbent position and a clinical algorithm for detecting a gastric fluid volume > 1.25 ml.
View Article and Find Full Text PDFWorld J Clin Cases
January 2025
Department of Gastroenterology, Laiko General Hospital, National and Kapodistrian University of Athens, Athens 11527, Greece.
Machine learning (ML) is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis, thus creating machines that can complete tasks otherwise requiring human intelligence. Among its various applications, it has proven groundbreaking in healthcare as well, both in clinical practice and research. In this editorial, we succinctly introduce ML applications and present a study, featured in the latest issue of the .
View Article and Find Full Text PDFCureus
December 2024
General Surgery, Sri Devaraj Urs Medical College, Kolar, IND.
Introduction Acute appendicitis is a common surgical emergency that requires a timely and accurate diagnosis to prevent complications. Several laboratory markers have been assessed to improve the diagnostic accuracy of acute appendicitis, including C-reactive protein (CRP), white blood cell (WBC) count, and cytokines like interleukins and tumor necrosis factor-alpha. One less commonly used but potentially valuable marker is the mean platelet volume (MPV), which indicates the size of circulating platelets and has the potential to serve as a biomarker for inflammatory conditions.
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