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      Development and Validation of a Clinical Score to Predict Neurological Outcomes in Patients With Out-of-Hospital Cardiac Arrest Treated With Extracorporeal Cardiopulmonary Resuscitation

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      , MD 1 , 2 , , MD, PhD 1 , 3 , , MD, PhD 4 , , MD, PhD 5 , , MD, PhD 6 , , MD 7 , , MD, PhD 8 , , MD, PhD 9 , , MD, PhD 10 , , MD, PhD 11 , , MD 12 , , MD, PhD 13 , , MD, PhD 14 , , MD, PhD 15 , , MD 16 , , MD 17 , , MD 18 , , MD, PhD 19 , , MD 1 , , MD, PhD 1 , , MD 20 , , MD, MPH 20 , , MD 1 , , MD, MPH 1 , , MD, PhD 4 , , MD, PhD 2 , , MD, MSc, DPH 20 , , MD, MPH, PhD 1 ,
      JAMA Network Open
      American Medical Association

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          Key Points

          Question

          Can the neurological outcome of patients with out-of-hospital cardiac arrest and shockable rhythm who are treated with extracorporeal cardiopulmonary resuscitation (ECPR) be predicted using accessible information?

          Findings

          In this prognostic study of 916 patients, a model using time to hospital arrival, pH in initial blood gas assessment, shockable rhythm on hospital arrival, and being younger than 65 years was developed to predict survival with good neurological outcome. The model had good performance and was well calibrated.

          Meaning

          These findings suggest that this model may be useful for predicting the neurological outcomes of patients with out-of-hospital cardiac arrest and shockable rhythm treated with ECPR.

          Abstract

          This prognostic study develops and validates a prediction model for neurological outcomes of patients with out-of-hospital cardiac arrest with shockable rhythm treated with extracorporeal cardiopulmonary resuscitation.

          Abstract

          Importance

          Extracorporeal cardiopulmonary resuscitation (ECPR) is expected to improve the neurological outcomes of patients with refractory cardiac arrest; however, it is invasive, expensive, and requires substantial human resources. The ability to predict neurological outcomes would assist in patient selection for ECPR.

          Objective

          To develop and validate a prediction model for neurological outcomes of patients with out-of-hospital cardiac arrest with shockable rhythm treated with ECPR.

          Design, Setting, and Participants

          This prognostic study analyzed data from the Japanese Association for Acute Medicine Out-of-Hospital Cardiac Arrest registry, a multi-institutional nationwide cohort study that included 87 emergency departments in Japan. All adult patients with out-of-hospital cardiac arrest and shockable rhythm who were treated with ECPR between June 2014 and December 2017 were included. Patients were randomly assigned to the development and validation cohorts based on the institutions. The analysis was conducted between November 2019 and August 2020.

          Exposures

          Age (<65 years), time from call to hospital arrival (≤25 minutes), initial cardiac rhythm on hospital arrival (shockable), and initial pH value (≥7.0).

          Main Outcomes and Measures

          The primary outcome was 1-month survival with favorable neurological outcome, defined by Cerebral Performance Category 1 or 2. In the development cohort, a simple scoring system was developed to predict this outcome using a logistic regression model. The diagnostic ability and calibration of the scoring system were assessed in the validation cohort.

          Results

          A total of 916 patients were included, 458 in the development cohort (median [interquartile range {IQR}] age, 61 [47-69] years, 377 [82.3%] men) and 458 in the validation cohort (median [IQR] age, 60 [49-68] years; 393 [85.8%] men). The cohorts had the same proportion of favorable neurological outcome (57 patients [12.4%]). The prediction scoring system was developed, attributing a score of 1 for each clinical predictor. Patients were divided into 4 groups, corresponding to their scores on the prediction model, as follows: very low probability (score 0), low probability (score 1), middle probability (score 2), and high probability (score 3-4) of good neurological outcome. The mean predicted probabilities in the groups stratified by score were as follows: very low, 1.6% (95% CI, 1.6%-1.6%); low, 4.4% (95% CI, 4.2%-4.6%); middle, 12.5% (95% CI, 12.1%-12.8%); and high, 30.8% (95% CI, 29.1%-32.5%). In the validation cohort, the C statistic of the scoring system was 0.724 (95% CI, 0.652-0.786). The predicted probability was evaluated as well calibrated to the observed favorable outcome in both cohorts by visual assessment of the calibration plot.

          Conclusions and Relevance

          In this study, the scoring system had good discrimination and calibration performance to predict favorable neurological outcomes of patients with out-of-hospital cardiac arrest and shockable rhythm who were treated with ECPR.

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          Most cited references36

          • Record: found
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          Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration

          The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org.
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            Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement

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              Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study.

              W S Lim (2003)
              In the assessment of severity in community acquired pneumonia (CAP), the modified British Thoracic Society (mBTS) rule identifies patients with severe pneumonia but not patients who might be suitable for home management. A multicentre study was conducted to derive and validate a practical severity assessment model for stratifying adults hospitalised with CAP into different management groups. Data from three prospective studies of CAP conducted in the UK, New Zealand, and the Netherlands were combined. A derivation cohort comprising 80% of the data was used to develop the model. Prognostic variables were identified using multiple logistic regression with 30 day mortality as the outcome measure. The final model was tested against the validation cohort. 1068 patients were studied (mean age 64 years, 51.5% male, 30 day mortality 9%). Age >/=65 years (OR 3.5, 95% CI 1.6 to 8.0) and albumin 7 mmol/l, Respiratory rate >/=30/min, low systolic( /=65 years (CURB-65 score) based on information available at initial hospital assessment, enabled patients to be stratified according to increasing risk of mortality: score 0, 0.7%; score 1, 3.2%; score 2, 3%; score 3, 17%; score 4, 41.5% and score 5, 57%. The validation cohort confirmed a similar pattern. A simple six point score based on confusion, urea, respiratory rate, blood pressure, and age can be used to stratify patients with CAP into different management groups.
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                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                24 November 2020
                November 2020
                24 November 2020
                : 3
                : 11
                : e2022920
                Affiliations
                [1 ]Department of Preventive Services, School of Public Health, Kyoto University, Kyoto, Japan
                [2 ]Department of Primary Care and Emergency Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
                [3 ]Critical Care and Trauma Center, Osaka General Medical Center, Osaka, Japan
                [4 ]Department of Traumatology and Acute Critical Medicine, Osaka University Graduate School of Medicine, Suita, Japan
                [5 ]Emergency and Critical Care Medical Center, Osaka Police Hospital, Osaka, Japan
                [6 ]Department of Emergency and Critical Care Medicine, Kansai Medical University, Takii Hospital, Moriguchi, Japan
                [7 ]Department of Emergency Medicine, Tane General Hospital, Osaka, Japan
                [8 ]Department of Critical Care Medicine, Osaka City University, Osaka, Japan
                [9 ]Department of Emergency and Critical Care Medicine, Kindai University School of Medicine, Osaka-Sayama, Japan
                [10 ]Osaka Mishima Emergency Critical Care Center, Takatsuki, Japan
                [11 ]Senshu Trauma and Critical Care Center, Osaka, Japan
                [12 ]Senri Critical Care Medical Center, Saiseikai Senri Hospital, Suita, Japan
                [13 ]Traumatology and Critical Care Medical Center, National Hospital Organization Osaka National Hospital, Osaka, Japan
                [14 ]Emergency and Critical Care Medical Center, Osaka City General Hospital, Osaka, Japan
                [15 ]Department of Pediatrics, Osaka Red Cross Hospital, Osaka, Japan
                [16 ]Emergency and Critical Care Medical Center, Kishiwada Tokushukai Hospital, Osaka, Japan
                [17 ]Department of Emergency and Critical Care Medicine, Kansai Medical University, Hirakata, Osaka, Japan
                [18 ]Department of Emergency Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan
                [19 ]Division of Environmental Medicine and Population Sciences, Department of Social and Environmental Medicine, Graduate School of Medicine, Osaka University, Osaka, Japan
                [20 ]Public Health, Department of Social and Environmental Medicine, Osaka University Graduate School of Medicine, Osaka, Japan
                Author notes
                Article Information
                Accepted for Publication: August 23, 2020.
                Published: November 24, 2020. doi:10.1001/jamanetworkopen.2020.22920
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Okada Y et al. JAMA Network Open.
                Corresponding Author: Taku Iwami, MD, MPH, PhD, Department of Preventive Services, School of Public Health, Kyoto University, Yoshidahonmachi, Sakyo, Kyoto, 606-8501, Japan ( iwami.taku.8w@ 123456kyoto-u.ac.jp ).
                Author Contributions: Drs Okada and Iwami had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Okada, Kiguchi, Kitamura, Iwami.
                Acquisition, analysis, or interpretation of data: Kiguchi, Irisawa, Yamada, Yoshiya, Park, Nishimura, Ishibe, Yagi, Kishimoto, Inoue, Hayashi, Sogabe, Morooka, Sakamoto, Suzuki, Nakamura, Matsuyama, Nishioka, Kobayashi, Matsui, Hirayama, Yoshimura, Kimata, Shimazu, Ohtsuru, Kitamura, Iwami.
                Drafting of the manuscript: Okada, Kiguchi, Yoshiya, Kitamura.
                Critical revision of the manuscript for important intellectual content: Kiguchi, Irisawa, Yamada, Park, Nishimura, Ishibe, Yagi, Kishimoto, Inoue, Hayashi, Sogabe, Morooka, Sakamoto, Suzuki, Nakamura, Matsuyama, Nishioka, Kobayashi, Matsui, Hirayama, Yoshimura, Kimata, Shimazu, Ohtsuru, Kitamura, Iwami.
                Statistical analysis: Okada, Yoshiya, Nishioka, Hirayama.
                Obtained funding: Kitamura, Iwami.
                Administrative, technical, or material support: Okada, Kiguchi, Irisawa, Yamada, Park, Nishimura, Ishibe, Yagi, Kishimoto, Inoue, Hayashi, Sogabe, Morooka, Sakamoto, Suzuki, Nakamura, Matsuyama, Kobayashi, Matsui, Hirayama, Yoshimura, Kimata, Shimazu, Ohtsuru, Iwami.
                Supervision: Kiguchi, Irisawa, Yamada, Yoshiya, Nishimura, Ishibe, Yagi, Kishimoto, Inoue, Sogabe, Morooka, Nakamura, Matsuyama, Nishioka, Kobayashi, Matsui, Kimata, Ohtsuru, Kitamura, Iwami.
                Conflict of Interest Disclosures: None reported.
                Funding/Support: This study was supported by the Ministry of Education, Culture, Sports, Science and Technology of Japan (grant Nos. 15H05006 and 19K09393).
                Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Article
                zoi200768
                10.1001/jamanetworkopen.2020.22920
                7686862
                33231635
                c1464c8e-ae8e-4f53-920c-5fed70f48ad0
                Copyright 2020 Okada Y et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 1 June 2020
                : 23 August 2020
                Categories
                Research
                Original Investigation
                Online Only
                Emergency Medicine

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