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Development of a prediction model for postoperative pneumonia: A multicentre prospective observational study.

dc.contributor.authorRussotto, V
dc.contributor.authorSabaté, S
dc.contributor.authorCanet, J
dc.contributor.authorCarmona, C, et al.
dc.date.accessioned2019-05-17T08:47:49Z
dc.date.available2019-05-17T08:47:49Z
dc.date.issued2019
dc.description.abstractBACKGROUND: Postoperative pneumonia is associated with increased morbidity, mortality and costs. Prediction models of pneumonia that are currently available are based on retrospectively collected data and administrative coding systems. OBJECTIVE: To identify independent variables associated with the occurrence of postoperative pneumonia. DESIGN: A prospective observational study of a multicentre cohort (Prospective Evaluation of a RIsk Score for postoperative pulmonary COmPlications in Europe database). SETTING: Sixty-three hospitals in Europe. PATIENTS: Patients undergoing surgery under general and/or regional anaesthesia during a 7-day recruitment period. MAIN OUTCOME MEASURE: The primary outcome was postoperative pneumonia. DEFINITION: the need for treatment with antibiotics for a respiratory infection and at least one of the following criteria: new or changed sputum; new or changed lung opacities on a clinically indicated chest radiograph; temperature more than 38.3 °C; leucocyte count more than 12 000 μl. RESULTS: Postoperative pneumonia occurred in 120 out of 5094 patients (2.4%). Eighty-two of the 120 (68.3%) patients with pneumonia required ICU admission, compared with 399 of the 4974 (8.0%) without pneumonia (P < 0.001). We identified five variables independently associated with postoperative pneumonia: functional status [odds ratio (OR) 2.28, 95% confidence interval (CI) 1.58 to 3.12], pre-operative SpO2 values while breathing room air (OR 0.83, 95% CI 0.78 to 0.84), intra-operative colloid administration (OR 2.97, 95% CI 1.94 to 3.99), intra-operative blood transfusion (OR 2.19, 95% CI 1.41 to 4.71) and surgical site (open upper abdominal surgery OR 3.98, 95% CI 2.19 to 7.59). The model had good discrimination (c-statistic 0.89) and calibration (Hosmer-Lemeshow P = 0.572). CONCLUSION: We identified five variables independently associated with postoperative pneumonia. The model performed well and after external validation may be used for risk stratification and management of patients at risk of postoperative pneumonia.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationEur J Anaesthesiol. 2019 Feb;36(2):93-104pt_PT
dc.identifier.doi10.1097/EJA.0000000000000921pt_PT
dc.identifier.issn1365-2346
dc.identifier.urihttp://hdl.handle.net/10400.10/2257
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherLippincott, Williams & Wilkinspt_PT
dc.subjectAnesthesiapt_PT
dc.subjectPostoperative complicationspt_PT
dc.subjectRespiratory insufficiencypt_PT
dc.subjectPneumoniapt_PT
dc.subjectHospital Mortalitypt_PT
dc.titleDevelopment of a prediction model for postoperative pneumonia: A multicentre prospective observational study.pt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceCambridgept_PT
oaire.citation.titleEuropean Journal of Anaesthesiologypt_PT
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT

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