The British journal of surgery
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Meta Analysis Comparative Study
Observational versus antibiotic treatment for uncomplicated diverticulitis: an individual-patient data meta-analysis.
Two RCTs (AVOD and DIABOLO) demonstrated no difference in recovery or adverse outcomes when antibiotics for acute uncomplicated diverticulitis were omitted. Both trials showed non-significantly higher rates of complicated diverticulitis and surgery in the non-antibiotic groups. This meta-analysis of individual-patient data aimed to explore adverse outcomes and identify patients at risk who may benefit from antibiotic treatment. ⋯ Observational management of acute uncomplicated diverticulitis is safe. Some statistical uncertainty remains, depending on the thresholds of clinical relevance, owing to small differences, but no subgroup that would benefit from antibiotic treatment was apparent.
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Multicenter Study Observational Study
Perioperative intravenous contrast administration and the incidence of acute kidney injury after major gastrointestinal surgery: prospective, multicentre cohort study.
This study aimed to determine the impact of preoperative exposure to intravenous contrast for CT and the risk of developing postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. ⋯ There was no association between preoperative intravenous contrast administered for CT up to 7 days before surgery and postoperative AKI. Risk of contrast-induced nephropathy should not be used as a reason to avoid contrast-enhanced CT.
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Smoking at the time of surgery is associated with postoperative complications. Quitting smoking before surgery is linked to fewer complications during the hospital stay. This work analysed whether a smoking cessation intervention before surgery is economically worthwhile when funded by the National Health System (NHS) in Spain. ⋯ From the perspective of the Spanish NHS, the benefit of funding smoking cessation before surgery, in terms of healthcare cost savings, appears to greatly outweigh the costs.
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Observational Study
Prehospital triage of acute aortic syndrome using a machine learning algorithm.
Acute aortic syndrome (AAS) comprises a complex and potentially fatal group of conditions requiring emergency specialist management. The aim of this study was to build a prediction algorithm to assist prehospital triage of AAS. ⋯ A machine learning prediction model performed well in discriminating AAS and could be clinically useful in prehospital triage of patients with suspected AAS.
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Conditional survival accounts for the time already survived after surgery and may be of additional informative value. The aim was to assess conditional survival in patients with oesophageal cancer and to create a nomogram predicting the conditional probability of survival after oesophagectomy. ⋯ The probability of achieving 5-year overall survival after oesophagectomy for cancer increases with each additional year survived. The proposed nomogram predicts survival in patients after oesophagectomy, taking the years already survived into account.