55 research outputs found

    Model for predicting short-term mortality of severe sepsis

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    International audienceABSTRACT: INTRODUCTION: To establish a prognostic model for predicting 14-day mortality in ICU patients with severe sepsis overall and according to place of infection acquisition and to sepsis episode number. METHODS: In this prospective multicentre observational study on a multicentre database (OUTCOMEREA) including data from 12 ICUs, 2268 patients with 2737 episodes of severe sepsis were randomly divided into a training cohort (n=1458) and a validation cohort (n=810). Up to four consecutive severe sepsis episodes per patient occurring within the first 28 ICU days were included. We developed a prognostic model for predicting death within 14 days after each episode, based on patient data available at sepsis onset. RESULTS: Independent predictors of death were logistic organ dysfunction (OR, 1.22 per point, p<10-4), septic shock (OR, 1.40; p=0.01), rank of severe sepsis episode (1 reference, 2: OR, 1.26; p=0.10 [greater than or equal to]3: OR, 2.64 ;10-3), multiple sources of infection (OR; 1.45, p=0.03), simplified acute physiology score II (OR, 1.02 per point; p<10-4), McCabe score ([greater than or equal to]2)(OR, 1.96; p<10-4), and number of chronic co-morbidities (1: OR, 1.75; p=10-3, [greater than or equal to]2: OR, 2.24, p= 10-3). Validity of the model was good in whole cohorts (AUC-ROC, 0.76; 95%CI [0.74; 0.79] and HL Chi-square: 15.3 (p=0.06) for all episodes pooled). CONCLUSIONS: In ICU patients, a prognostic model based on a few easily obtained variables is effective in predicting death within 14 days after the first to fourth episode of severe sepsis complicating community-, hospital-, or ICU-acquired infection

    Multiple-center evaluation of mortality associated with acute kidney injury in critically ill patients: a competing risks analysis

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    International audienceINTRODUCTION: In this study, we aimed to assess the association between acute kidney injury (AKI) and mortality in critically ill patients using an original competing risks approach. METHODS: Unselected patients admitted between 1997 and 2009 to 13 French medical or surgical intensive care units were included in this observational cohort study. AKI was defined according to the RIFLE criteria. The following data were recorded: baseline characteristics, daily serum creatinine level, daily Sequential Organ Failure Assessment (SOFA) score, vital status at hospital discharge and length of hospital stay. Patients were classified according to the maximum RIFLE class reached during their ICU stay. The association of AKI with hospital mortality with "discharge alive" considered as a competing event was assessed according to the Fine and Gray model. RESULTS: Of the 8,639 study patients, 32.9% had AKI, of whom 19.1% received renal replacement therapy. Patients with AKI had higher crude mortality rates and longer lengths of hospital stay than patients without AKI. In the Fine and Gray model, independent risk factors for hospital mortality were the RIFLE classes Risk (sub-hazard ratio (SHR) 1.58 and 95% confidence interval (95% CI) 1.32 to 1.88; P < 0.0001), Injury (SHR 3.99 and 95% CI 3.43 to 4.65; P < 0.0001) and Failure (SHR 4.12 and 95% CI 3.55 to 4.79; P < 0.0001); nonrenal SOFA score (SHR 1.19 per point and 95% CI 1.18 to 1.21; P < 0.0001); McCabe class 3 (SHR 2.71 and 95% CI 2.34 to 3.15; P < 0.0001); and respiratory failure (SHR 3.08 and 95% CI 1.36 to 7.01; P < 0.01). CONCLUSIONS: By using a competing risks approach, we confirm in this study that AKI affecting critically ill patients is associated with increased in-hospital mortality

    Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

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    Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P &lt; 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

    Tracheostomy does not improve the outcome of patients requiring prolonged mechanical ventilation: a propensity analysis.

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    International audienceOBJECTIVE: To examine the association between the performance of a tracheostomy and intensive care unit and postintensive care unit mortality, controlling for treatment selection bias and confounding variables. DESIGN: Prospective, observational, cohort study. SETTING: Twelve French medical or surgical intensive care units. PATIENTS: Unselected patients requiring mechanical ventilation for > or =48 hrs enrolled between 1997 and 2004. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Two models of propensity scores for tracheostomy were built using multivariate logistic regression. After matching on these propensity scores, the association of tracheostomy with outcomes was assessed using multivariate conditional logistic regression. Results obtained with the two models were compared. Of the 2,186 patients included, 177 (8.1%) received a tracheostomy. Both models led to similar results. Tracheostomy did not improve intensive care unit survival (model 1: odds ratio, 0.94; 95% confidence interval, 0.63-1.39; p = .74; model 2: odds ratio, 1.12; 95% confidence interval, 0.75-1.67; p = .59). There was no difference whether tracheostomy was performed early (within 7 days of ventilation) or late (after 7 days of ventilation). In patients discharged free from mechanical ventilation, tracheostomy was associated with increased postintensive care unit mortality when the tracheostomy tube was left in place (model 1: odds ratio, 3.73; 95% confidence interval, 1.41-9.83; p = .008; model 2: odds ratio, 4.63; 95% confidence interval, 1.68-12.72, p = .003). CONCLUSIONS: Tracheostomy does not seem to reduce intensive care unit mortality when performed in unselected patients but may represent a burden after intensive care unit discharge
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