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      Intensive care unit versus high-dependency care unit for mechanically ventilated patients with pneumonia: a nationwide comparative effectiveness study

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          Abstract

          Background

          Many mechanically ventilated patients in Japan are treated in high-dependency care units (HDUs) rather than intensive care units (ICUs). HDUs can provide intermediate-level care with reduced costs; however, there is limited evidence on whether mechanically ventilated patients should be treated in the ICU or HDU.

          Methods

          This was a comparative effectiveness study using a nationwide administrative database in Japan. We identified mechanically ventilated patients with pneumonia in ICU or HDU on the day of admission in the Japanese Diagnosis Procedure Combination inpatient database from April 2014 to March 2019. The primary outcome was 30-day in-hospital mortality. Propensity score matching analysis was performed to compare this outcome between patients treated in the ICU and HDU. The robustness of the analyses was evaluated with multivariable regression, overlap weighting, and instrumental variable analyses.

          Findings

          Of 14,859 mechanically ventilated patients with pneumonia, 7,528 (51%) were treated in the ICU and 7,331 (49%) were treated in the HDU. After propensity score matching, patients treated in the ICU had significantly lower 30-day in-hospital mortality than did those treated in the HDU (24.0% vs. 31.2%; difference, −7.2%; 95% confidence interval, −10.0% to −4.4%). The multivariable regression, overlap weighting, and instrumental variable analyses showed a similar direction and magnitude of association.

          Interpretation

          Critical care for mechanically ventilated patients with pneumonia in the ICU was associated with a 7.2% decrease in 30-day in-hospital mortality vs. care in the HDU. Residual confounding may still play a role in the effect estimates.

          Funding

          This study received funding from Ministry of Health, Labour and Welfare, Japan, and Ministry of Education, Culture, Sports, Science and Technology, Japan.

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          Most cited references36

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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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            Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples

            The propensity score is a subject's probability of treatment, conditional on observed baseline covariates. Conditional on the true propensity score, treated and untreated subjects have similar distributions of observed baseline covariates. Propensity-score matching is a popular method of using the propensity score in the medical literature. Using this approach, matched sets of treated and untreated subjects with similar values of the propensity score are formed. Inferences about treatment effect made using propensity-score matching are valid only if, in the matched sample, treated and untreated subjects have similar distributions of measured baseline covariates. In this paper we discuss the following methods for assessing whether the propensity score model has been correctly specified: comparing means and prevalences of baseline characteristics using standardized differences; ratios comparing the variance of continuous covariates between treated and untreated subjects; comparison of higher order moments and interactions; five-number summaries; and graphical methods such as quantile–quantile plots, side-by-side boxplots, and non-parametric density plots for comparing the distribution of baseline covariates between treatment groups. We describe methods to determine the sampling distribution of the standardized difference when the true standardized difference is equal to zero, thereby allowing one to determine the range of standardized differences that are plausible with the propensity score model having been correctly specified. We highlight the limitations of some previously used methods for assessing the adequacy of the specification of the propensity-score model. In particular, methods based on comparing the distribution of the estimated propensity score between treated and untreated subjects are uninformative. Copyright © 2009 John Wiley & Sons, Ltd.
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              The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine.

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                Author and article information

                Contributors
                Journal
                Lancet Reg Health West Pac
                Lancet Reg Health West Pac
                The Lancet Regional Health: Western Pacific
                Elsevier
                2666-6065
                05 July 2021
                August 2021
                05 July 2021
                : 13
                : 100185
                Affiliations
                [1 ]Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 1130033, Japan
                [2 ]Data Science Centre, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, Tochigi Prefecture, 3290498, Japan
                Author notes
                [* ]Corresponding author: Hiroyuki Ohbe, Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 1130033, Japan, Tel: +81-3-5841-1887; Fax: +81-5841-1888 hohbey@ 123456gmail.com
                Article
                S2666-6065(21)00094-8 100185
                10.1016/j.lanwpc.2021.100185
                8350066
                34527980
                76690165-110c-4ee4-aa61-eb236905f5b2
                © 2021 The Author(s). Published by Elsevier Ltd.

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 18 February 2021
                : 13 May 2021
                : 26 May 2021
                Categories
                Research Paper

                high-dependency care unit,intensive care unit,mechanical ventilation,pneumonia,comparative effectiveness

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