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      Clinical Examination for the Prediction of Mortality in the Critically Ill: The Simple Intensive Care Studies-I

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          Abstract

          Supplemental Digital Content is available in the text.

          Objectives:

          Caregivers use clinical examination to timely recognize deterioration of a patient, yet data on the prognostic value of clinical examination are inconsistent. In the Simple Intensive Care Studies-I, we evaluated the association of clinical examination findings with 90-day mortality in critically ill patients.

          Design:

          Prospective single-center cohort study.

          Setting:

          ICU of a single tertiary care level hospital between March 27, 2015, and July 22, 2017.

          Patients:

          All consecutive adults acutely admitted to the ICU and expected to stay for at least 24 hours.

          Interventions:

          A protocolized clinical examination of 19 clinical signs conducted within 24 hours of admission.

          Measurements Main Results:

          Independent predictors of 90-day mortality were identified using multivariable logistic regression analyses. Model performance was compared with established prognostic risk scores using area under the receiver operating characteristic curves. Robustness of our findings was tested by internal bootstrap validation and adjustment of the threshold for statistical significance. A total of 1,075 patients were included, of whom 298 patients (28%) had died at 90-day follow-up. Multivariable analyses adjusted for age and norepinephrine infusion rate demonstrated that the combination of higher respiratory rate, higher systolic blood pressure, lower central temperature, altered consciousness, and decreased urine output was independently associated with 90-day mortality (area under the receiver operating characteristic curves = 0.74; 95% CI, 0.71–0.78). Clinical examination had a similar discriminative value as compared with the Simplified Acute Physiology Score-II (area under the receiver operating characteristic curves = 0.76; 95% CI, 0.73–0.79; p = 0.29) and Acute Physiology and Chronic Health Evaluation-IV (using area under the receiver operating characteristic curves = 0.77; 95% CI, 0.74–0.80; p = 0.16) and was significantly better than the Sequential Organ Failure Assessment (using area under the receiver operating characteristic curves = 0.67; 95% CI, 0.64–0.71; p < 0.001).

          Conclusions:

          Clinical examination has reasonable discriminative value for assessing 90-day mortality in acutely admitted ICU patients. In our study population, a single, protocolized clinical examination had similar prognostic abilities compared with the Simplified Acute Physiology Score-II and Acute Physiology and Chronic Health Evaluation-IV and outperformed the Sequential Organ Failure Assessment score.

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          Most cited references26

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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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            Hemodynamic variables related to outcome in septic shock.

            To assess the impact of hemodynamic variables on the outcome of critically ill patients in septic shock and to identify the optimal threshold values related to outcome with special reference to continuously monitored mean arterial pressure (MAP) and mixed venous oxygen saturation (SvO2). Retrospective cohort study in a university hospital intensive care unit (ICU). All consecutive 111 patients with septic shock treated in our ICU between 1 Jan. 1999 and 30 Jan. 2002. The data on the hemodynamic and respiratory monitoring and circulation-related laboratory tests over the first 48 h of treatment in the ICU were collected from the clinical data management system. Data from 6 h and 48 h were analyzed separately. The 30-day mortality rate was 33% (36 of 111). Univariate analysis and forward stepwise logistic regression analysis were performed using the 30-day mortality as the primary endpoint. Mean MAP and lactate on arrival during 6 h, while mean MAP, the area of SvO2 under 70%, and mean CVP during 48 h were independently associated with mortality. MAP level of 65 mmHg and SvO2 of 70% had the highest areas under receiver characteristics curves. MAP, SvO2, CVP, and initial lactate were independently associated with mortality in septic shock, with threshold values supporting those published in recent guidelines.
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              Oliguria is an early predictor of higher mortality in critically ill patients.

              Oliguria is a valuable marker of kidney function and a criterion for diagnosing and staging acute kidney injury (AKI). However, the utility of urine output as a specific metric for renal dysfunction is somewhat controversial. To study this issue further we tested whether urine output is a sensitive, specific, and early measure for diagnosing and staging AKI in 317 critically ill patients in a prospective observational study. Urine output was assessed every hour and serum creatinine every 12 to 24  h. The sensitivity and specificity of different definitions of oliguria for the diagnosis of AKI were compared with the Acute Kidney Injury Network serum creatinine criterion. The incidence of AKI increased from 24%, based solely on serum creatinine, to 52% by adding the urine output as a diagnostic criterion. Oliguric patients without a change in serum creatinine had an intensive care unit mortality rate (8.8%) significantly higher than patients without AKI (1.3%), and similar to oliguric patients with an increase in serum creatinine (10.4%). The diagnosis of AKI occurred earlier in oliguric than in non-oliguric patients. Oliguria of more than 12  h and oliguria of 3 or more episodes were associated with an increased mortality rate. Thus, urine output is a sensitive and early marker for AKI and is associated with adverse outcomes in intensive care unit patients.
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                Author and article information

                Journal
                Crit Care Med
                Crit. Care Med
                CCM
                Critical Care Medicine
                Lippincott Williams & Wilkins
                0090-3493
                1530-0293
                October 2019
                13 September 2013
                : 47
                : 10
                : 1301-1309
                Affiliations
                [1 ]Department of Critical Care, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
                [2 ]Department of Anesthesiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
                [3 ]Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
                [4 ]Department of Intensive Care, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.
                [5 ]Centre for Research in Intensive Care, Department 7831, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
                [6 ]Division of Intensive Care Medicine, Department of Anesthesiology, Intensive Care and Pain Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
                [7 ]The Copenhagen Trial Unit, Centre for Clinical Intervention Research, Department 7812, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
                Author notes
                For information regarding this article, E-mail: b.hiemstra01@ 123456umcg.nl
                Article
                00003
                10.1097/CCM.0000000000003897
                6750157
                31356472
                9d13cb7c-c831-403b-b12c-0b1c6d681547
                Copyright © 2019 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine and Wolters Kluwer Health, Inc.

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

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                clinical examination,critical illness,intensive care unit,mortality,observational study,prognostic modeling

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