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      Risk factors for mortality in postoperative peritonitis in critically ill patients

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          Abstract

          AIM

          To identify the risk factors for mortality in intensive care patients with postoperative peritonitis (POP).

          METHODS

          This was a retrospective analysis using a prospective database that includes all patients hospitalized in a surgical intensive care unit for POP from September 2006 to August 2011. The data collected included demographics, comorbidities, postoperative severity parameters, bacteriological findings, adequacy of antimicrobial therapy and surgical treatments. Adequate source control was defined based on a midline laparotomy, infection source control and intraoperative peritoneal lavage. The number of reoperations needed was also recorded.

          RESULTS

          A total of 201 patients were included. The overall mortality rate was 31%. Three independent risk factors for mortality were identified: The Simplified Acute Physiological II Score (OR = 1.03; 95%CI: 1.02-1.05, P < 0.001), postoperative medical complications (OR = 6.02; 95%CI: 1.95-18.55, P < 0.001) and the number of reoperations (OR = 2.45; 95%CI: 1.16-5.17, P = 0.015). Surgery was considered as optimal in 69% of the cases, but without any significant effect on mortality.

          CONCLUSION

          The results from the large cohort in this study emphasize the role of the initial postoperative severity parameters in the prognosis of POP. No predefined criteria for optimal surgery were significantly associated with increased mortality, although the number of reoperations appeared as an independent risk factor of mortality.

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          Most cited references32

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          A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study.

          To develop and validate a new Simplified Acute Physiology Score, the SAPS II, from a large sample of surgical and medical patients, and to provide a method to convert the score to a probability of hospital mortality. The SAPS II and the probability of hospital mortality were developed and validated using data from consecutive admissions to 137 adult medical and/or surgical intensive care units in 12 countries. The 13,152 patients were randomly divided into developmental (65%) and validation (35%) samples. Patients younger than 18 years, burn patients, coronary care patients, and cardiac surgery patients were excluded. Vital status at hospital discharge. The SAPS II includes only 17 variables: 12 physiology variables, age, type of admission (scheduled surgical, unscheduled surgical, or medical), and three underlying disease variables (acquired immunodeficiency syndrome, metastatic cancer, and hematologic malignancy). Goodness-of-fit tests indicated that the model performed well in the developmental sample and validated well in an independent sample of patients (P = .883 and P = .104 in the developmental and validation samples, respectively). The area under the receiver operating characteristic curve was 0.88 in the developmental sample and 0.86 in the validation sample. The SAPS II, based on a large international sample of patients, provides an estimate of the risk of death without having to specify a primary diagnosis. This is a starting point for future evaluation of the efficiency of intensive care units.
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            Association between frailty and short- and long-term outcomes among critically ill patients: a multicentre prospective cohort study.

            Frailty is a multidimensional syndrome characterized by loss of physiologic and cognitive reserves that confers vulnerability to adverse outcomes. We determined the prevalence, correlates and outcomes associated with frailty among adults admitted to intensive care. We prospectively enrolled 421 critically ill adults aged 50 or more at 6 hospitals across the province of Alberta. The primary exposure was frailty, defined by a score greater than 4 on the Clinical Frailty Scale. The primary outcome measure was in-hospital mortality. Secondary outcome measures included adverse events, 1-year mortality and quality of life. The prevalence of frailty was 32.8% (95% confidence interval [CI] 28.3%-37.5%). Frail patients were older, were more likely to be female, and had more comorbidities and greater functional dependence than those who were not frail. In-hospital mortality was higher among frail patients than among non-frail patients (32% v. 16%; adjusted odds ratio [OR] 1.81, 95% CI 1.09-3.01) and remained higher at 1 year (48% v. 25%; adjusted hazard ratio 1.82, 95% CI 1.28-2.60). Major adverse events were more common among frail patients (39% v. 29%; OR 1.54, 95% CI 1.01-2.37). Compared with nonfrail survivors, frail survivors were more likely to become functionally dependent (71% v. 52%; OR 2.25, 95% CI 1.03-4.89), had significantly lower quality of life and were more often readmitted to hospital (56% v. 39%; OR 1.98, 95% CI 1.22-3.23) in the 12 months following enrolment. Frailty was common among critically ill adults aged 50 and older and identified a population at increased risk of adverse events, morbidity and mortality. Diagnosis of frailty could improve prognostication and identify a vulnerable population that might benefit from follow-up and intervention.
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              The ACCP-SCCM consensus conference on sepsis and organ failure.

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                Author and article information

                Journal
                World J Crit Care Med
                WJCCM
                World Journal of Critical Care Medicine
                Baishideng Publishing Group Inc
                2220-3141
                4 February 2017
                4 February 2017
                : 6
                : 1
                : 48-55
                Affiliations
                Yoann Launey, Benjamin Duteurtre, Raphaëlle Larmet, Nicolas Nesseler, Audrey Tawa, Yannick Mallédant, Philippe Seguin, Anesthésie Réanimation 1, Centre Hospitalier Universitaire de Rennes, F-35000 Rennes, France
                Author notes

                Author contributions: Launey Y, Mallédant Y and Seguin P contributed to study design/planning; Launey Y, Duteurtre B, Nesseler N, Tawa A, Mallédant Y and Seguin P contributed to study conduct; Launey Y, Duteurtre B, Nesseler N, Mallédant Y and Seguin P contributed to data analysis; Launey Y, Duteurtre B, Mallédant Y and Seguin P contributed to writing paper; all authors contributed to revising paper.

                Correspondence to: Philippe Seguin, MD, PhD, Professor, Anesthésie Réanimation 1, Centre Hospitalier Universitaire de Rennes, Inserm U991, F-35000 Rennes, France. philippe.seguin@ 123456chu-rennes.fr

                Telephone: +33-2-99289371 Fax: +33-2-99282421

                Article
                jWJCCM.v6.i1.pg48
                10.5492/wjccm.v6.i1.48
                5295169
                28224107
                34007337-5a69-4818-a53a-bc00296309a2
                ©The Author(s) 2017. Published by Baishideng Publishing Group Inc. All rights reserved.

                This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.

                History
                : 19 August 2016
                : 14 November 2016
                : 7 December 2016
                Categories
                Retrospective Study

                mortality,postoperative peritonitis,risk factors,surgery

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