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Intensive care
Protocol
Systematic review of the effect of metabolic syndrome on outcomes due to acute respiratory distress syndrome: a protocol
  1. Gregory Stone1,
  2. Andre Sisk2,
  3. Margo Brown2,
  4. Amy Corder3,
  5. Kevin Tea2,
  6. Yuanhao Zu4,
  7. Jeff Shaffer4,
  8. Rahul Kashyap5,
  9. Nida Qadir6,
  10. Joshua Lee Denson2
  1. 1Department of Internal Medicine, UCLA, Los Angeles, California, USA
  2. 2Section of Pulmonary Diseases, Critical Care, and Environmental Medicine, John W. Deming Department of Medicine, Tulane University School of Medicine, New Orleans, Louisiana, USA
  3. 3Rudolph Matas Library of the Health Sciences, Tulane University, New Orleans, Louisiana, USA
  4. 4Department of Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
  5. 5Department of Research, WellSpan Health, York, Pennsylvania, USA
  6. 6Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, UCLA, Los Angeles, California, USA
  1. Correspondence to Joshua Lee Denson; Jdenson{at}tulane.edu

Abstract

Introduction Acute respiratory distress syndrome (ARDS) is a life-threatening condition commonly seen in the intensive care unit. COVID-19 has dramatically increased the incidence of ARDS—with this rise in cases comes the ability to detect predisposing factors perhaps not recognised before, such as metabolic syndrome (MetS) and its associated conditions (hypertension, obesity, dyslipidaemia and type 2 diabetes mellitus). In this systematic review, we seek to describe the complex relationship between MetS, its associated conditions and ARDS (including COVID-19 ARDS).

Methods and analysis A systematic search of PubMed, Embase, Cochrane Central Register of Controlled Trials, CINAHL and Web of Science will be conducted. The population of interest is adults with ARDS and MetS (as defined according to the study author recognising that MetS definitions vary) or any MetS-associated condition. The control group will be adult patients with ARDS without MetS or any individual MetS-associated condition. We will search studies published in English, with a date restriction from the year 2000 to June 2023 and employ the search phrases ‘metabolic syndrome’, ‘acute respiratory distress syndrome’ and related terms. Search terms including ‘dyslipidaemia’, ‘hypertension’, ‘diabetes mellitus’ and ‘obesity’ will also be utilised. Outcomes of interest will include mortality (in-hospital, ICU, 28-day, 60-day and 90-day), days requiring mechanical ventilation and hospital and/or ICU length of stay. Study bias will be assessed using the NIH Bias Scale.

Ethics and dissemination Ethical approval is not required because this study includes previously published and publicly accessible data. Findings from this review will be disseminated via publication in a peer-reviewed journal.

PROSPERO registration number CRD42023405816.

  • COVID-19
  • DIABETES & ENDOCRINOLOGY
  • Adult intensive & critical care
  • Respiratory Distress Syndrome
  • RESPIRATORY MEDICINE (see Thoracic Medicine)
  • Systematic Review
http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article 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, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi-org.ezproxy.u-pec.fr/10.1136/bmjopen-2023-076036

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    STRENGTHS AND LIMITATIONS OF THIS STUDY

    • This investigation will provide, for the first time, a systematic review of metabolic syndrome and acute respiratory distress syndrome both related and unrelated to COVID-19.

    • The review will be conducted under the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines.

    • The reliability of the results will largely depend on the comprehensiveness and the methodological quality of the primary studies included in this review.

    Introduction

    Acute respiratory distress syndrome (ARDS) is a life-threatening condition commonly seen in the intensive care unit (ICU), accounting for roughly 10% of ICU admissions prior to the COVID-19 disease pandemic.1 2 ARDS develops as part of a systemic inflammatory response precipitated by conditions such as sepsis, pneumonia, aspiration, trauma or transfusions.3 COVID-19 has dramatically increased the incidence of ARDS—with this rise in cases comes the ability to detect predisposing factors perhaps not recognised before, such as metabolic syndrome (MetS) and its associated conditions (hypertension, obesity, dyslipidaemia and type 2 diabetes mellitus).

    The presentation, diagnosis and clinical course of ARDS remain heterogeneous with continued difficulty discerning who is most at-risk for adverse outcomes and who is most likely to benefit from targeted treatments.4 5 Obesity, a condition associated with MetS, has historically been associated with an increased risk of developing non-COVID-19 ARDS,6 whereas diabetes mellitus, which is also associated with MetS, has not been demonstrated to confer this risk.7 8 Furthermore, though obesity carries an increased risk of ARDS, it may be protective against mortality.9 Given conflicting data, it is unclear how poor metabolic health, identified by MetS, impacts non-COVID-19 ARDS. Furthermore, emerging data following the COVID-19 pandemic has highlighted an association between MetS and an increased risk for COVID-19-related ARDS and subsequent mortality.10 11 In this systematic review, we seek to describe the complex relationship between MetS, its associated conditions (obesity, hypertension, dyslipidaemia and type 2 diabetes mellitus) and ARDS (including COVID-19 ARDS).

    Methods and analysis

    The Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) 2020 statement12 will be utilised to conduct this systematic review. Study design began in February 2023. We anticipate data analysis will conclude in December 2023.

    Patient and public involvement

    Patients and/or the public were not involved in this research.

    Objectives

    The primary objective is to determine the association between MetS and outcomes due to ARDS. The secondary objective is to determine an association between MetS-associated conditions (obesity, hypertension, dyslipidaemia and diabetes mellitus) and outcomes due to ARDS. The tertiary objective is to identify the difference between outcomes due to COVID-19 and non-COVID-19-related ARDS in those with MetS as compared with those without. Outcomes due to ARDS will include mortality (in-hospital, ICU, 28-day, 60-day and 90-day), days requiring mechanical ventilation, organ failure-free days and hospital and/or ICU length of stay. We will also compare baseline characteristics of patients with and without MetS, including demographics, comorbidities, degree of hypoxia and severity of illness.

    Review question

    What is the impact of MetS, and individual MetS-associated conditions, on outcomes due to ARDS in adult patients?

    Eligibility criteria

    All studies meeting the following criteria will be considered: (1) involve only adult patients (18+-years-old); (2) include patients with ARDS; (3) compare patients with MetS or individual MetS-associated conditions (obesity, hypertension or high blood pressure, insulin resistance or type 2 diabetes mellitus and dyslipidaemia) to those without; (4) studies published in English; (5) studies published during or after the year 2000. Studies with the following attributes were excluded: (1) systematic reviews and meta-analyses on related topics; (2) case reports or case series; (3) comorbidities of study patients not listed; (4) inclusion of patients <18-years-old; (5) studies published earlier than 1 January 2000 and (6) studies that did not have fulltext availability.

    Search strategy

    In June 2023, a librarian (AC) conducted the search in PubMed and translated it to the following databases: Embase.com, Cochrane Central Register of Controlled Trials (CENTRAL), CINAHL and Web of Science. Search results were restricted by studies published in English and from the year 2000 to June 2023. Search phrases include ‘metabolic syndrome’, ‘acute respiratory distress syndrome’ and related terms. To assess an association between MetS-related conditions and outcomes due to ARDS, search terms including ‘dyslipidaemia’, ‘hypertension’, ‘diabetes mellitus’ and ‘obesity’ were also employed. Our search strategy is detailed in online supplemental 1.

    Population of interest

    Adult patients with ARDS and MetS (as defined according to the study author recognising that MetS definitions vary) is the main population of interest. Subgroup analyses will be conducted in patients with ARDS and any MetS-associated condition, including obesity, hypertension or high blood pressure, insulin resistance or type 2 diabetes mellitus and dyslipidaemia. Subgroup analysis will also be conducted between patients with MetS, or any MetS-associated condition, with COVID-related ARDS compared with non-COVID-related ARDS.

    ARDS will be defined according to the study in question and commonly accepted criteria, which would be the Berlin13 or American-European Consensus Conference14 definition depending on the date of the study in question. Although a new ARDS definition was proposed in July 2023,15 because our study search extends to June 2023, we do not anticipate that any study will have incorporated the new 2023 ARDS definition. We therefore will not stratify studies by these ARDS definitions.

    Comparator

    Adult patients with ARDS without MetS or any individual MetS-associated condition.

    Main outcomes

    The primary outcome of interest is 28-day mortality. Secondary outcomes include in-hospital, ICU, 60-day and 90-day mortality; days requiring mechanical ventilation; organ failure-free days; and hospital and/or ICU length of stay.

    Study selection method

    Studies will be reviewed for inclusion by three investigators (GS, MB and AS). Studies will be first reviewed for inclusion by title and abstract organised on Microsoft Excel. Once all searches are conducted, the full text of selected studies will be examined for final selection. Full-text manuscripts that are not available for free, with our academic institutional access or after request were excluded. To track search results, digital object identifier numbers were collected and stored in Microsoft Excel.

    Data extraction

    Two authors will independently extract data. Information collected from studies will include: (1) study information (year of publication, study design); (2) sample size, including the number of patients with the exposure of interest (MetS or MetS associated condition(s)) and number of control (non-MetS or without MetS association condition(s)) patients and (3) outcome frequency and/or percentages, including the type of outcome (in-hospital, ICU, 28-day, 60-day and 90-day), days requiring mechanical ventilation and hospital and/or ICU length of stay.

    Quality assessment of studies

    The NIH Bias Scale will be used by two authors independently (AS and MB) to assess the quality of the studies. The instrument scores cohort studies in several domains including clarity of study design, patient inclusion factors, exposure parameters and sample size, and assigns a quality rating of ‘Good’, ‘Fair’ or ‘Poor’. Given the anticipated small number of included studies, we will not exclude low-quality studies.

    Data synthesis and analysis

    Data synthesis and analysis will be conducted in SAS V.9.4 (SAS institute), and figures will be generated using GraphPad Prism V.10.0.3 (GraphPad software). Study characteristics and findings will be summarised in tabular form. We will use the total patients in each case and control group and their respective outcome to calculate pooled OR/HR for dichotomous outcomes and mean differences for continuous outcomes along with 95% CI. This will be plotted as a forest plot. Study heterogeneity will be measured using both χ2 and I2 statistics. I2 values, which represent the proportion of inter-study variability attributable to heterogeneity rather than chance, of less than 25%, 25%–50% and more than 50% will be considered low, moderate and high estimates, respectively.16 In case of higher heterogeneity, we will do sensitivity analysis. To generate pooled effects across studies, random-effects or fixed-effects modelling with inverse-variance weighting will be used depending on study heterogeneity. If heterogeneity is not statistically significant, as determined by a I2< 50% and χ2 > 0.1, fixed-effects modelling will be employed. If heterogeneity is statistically significant, mixed-effects modelling will be utilised. Additionally, meta-regression will be conducted.

    Ethics and dissemination

    Ethical approval is not required because this study includes previously published and publicly accessible data. Findings from this review will be disseminated via publication in a peer-reviewed journal.

    Ethics statements

    Patient consent for publication

    References

    1. ↵
      1. Rubenfeld GD,
      2. Caldwell E,
      3. Peabody E, et al
      . Incidence and outcomes of acute lung injury. N Engl J Med 2005;353:1685–93. doi:10.1056/NEJMoa050333
      OpenUrlCrossRefPubMedWeb of Science
    2. ↵
      1. Bellani G,
      2. Laffey JG,
      3. Pham T, et al
      . Epidemiology, patterns of care, and mortality for patients with acute respiratory distress syndrome in intensive care units in 50 countries. JAMA 2016;315:788–800. doi:10.1001/jama.2016.0291
      OpenUrlCrossRefPubMed
    3. ↵
      1. Eworuke E,
      2. Major JM,
      3. Gilbert McClain LI
      . National incidence rates for acute respiratory distress syndrome (ARDS) and ARDS cause-specific factors in the United States (2006-2014). J Crit Care 2018;47:192–7. doi:10.1016/j.jcrc.2018.07.002
      OpenUrlCrossRef
    4. ↵
      1. Calfee CS,
      2. Delucchi K,
      3. Parsons PE, et al
      . Subphenotypes in acute respiratory distress syndrome: latent class analysis of data from two randomised controlled trials. Lancet Respir Med 2014;2:611–20. doi:10.1016/S2213-2600(14)70097-9
      OpenUrlCrossRef
    5. ↵
      1. Wilson JG,
      2. Calfee CS
      . ARDS subphenotypes: understanding a heterogeneous syndrome. Crit Care 2020;24:102. doi:10.1186/s13054-020-2778-x
    6. ↵
      1. Karnatovskaia LV,
      2. Lee AS,
      3. Bender SP, et al
      . US critical illness and injury trials group: lung injury prevention study investigators (USCIITG–LIPS). Obstructive sleep apnea, obesity, and the development of acute respiratory distress syndrome. J Clin Sleep Med JCSM Off Publ Am Acad Sleep Med 2014;10:657–62. doi:10.5664/jcsm.3794
      OpenUrl
    7. ↵
      1. Boyle AJ,
      2. Madotto F,
      3. Laffey JG, et al
      . Identifying associations between diabetes and acute respiratory distress syndrome in patients with acute hypoxemic respiratory failure: an analysis of the LUNG SAFE database. Crit Care Lond Engl 2018;22:268. doi:10.1186/s13054-018-2158-y
    8. ↵
      1. Ji M,
      2. Chen M,
      3. Hong X, et al
      . The effect of diabetes on the risk and mortality of acute lung injury/acute respiratory distress syndrome: a meta-analysis. Medicine 2019;98:e15095. doi:10.1097/MD.0000000000015095
    9. ↵
      1. Soto GJ,
      2. Frank AJ,
      3. Christiani DC, et al
      . Body mass index and acute kidney injury in the acute respiratory distress syndrome. Crit Care Med 2012;40:2601–8. doi:10.1097/CCM.0b013e3182591ed9
      OpenUrlCrossRefPubMed
    10. ↵
      1. Xie J,
      2. Zu Y,
      3. Alkhatib A, et al
      . Metabolic syndrome and COVID-19 mortality among adult black patients in New Orleans. Diabetes Care 2020;44:188–93. doi:10.2337/dc20-1714
      OpenUrl
    11. ↵
      1. Denson JL,
      2. Gillet AS,
      3. Zu Y, et al
      . Metabolic syndrome and acute respiratory distress syndrome in hospitalized patients with COVID-19. JAMA Netw Open 2021;4:e2140568. doi:10.1001/jamanetworkopen.2021.40568
    12. ↵
      1. Page MJ,
      2. McKenzie JE,
      3. Bossuyt PM, et al
      . The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi:10.1136/bmj.n71
    13. ↵
      1. ARDS Definition Task Force,
      2. Ranieri VM,
      3. Rubenfeld GD, et al
      . Acute respiratory distress syndrome: the Berlin definition. JAMA 2012;307:2526–33. doi:10.1001/jama.2012.5669
      OpenUrlCrossRefPubMedWeb of Science
    14. ↵
      1. Bernard GR,
      2. Artigas A,
      3. Brigham KL, et al
      . The American-European consensus conference on ARDS. definitions, mechanisms, relevant outcomes, and clinical trial coordination. Am J Respir Crit Care Med 1994;149(3 Pt 1):818–24. doi:10.1164/ajrccm.149.3.7509706
      OpenUrlCrossRefPubMedWeb of Science
    15. ↵
      1. Matthay MA,
      2. Arabi Y,
      3. Arroliga AC, et al
      . A new global definition of acute respiratory distress syndrome. Am J Respir Crit Care Med July 24, 2023. doi:10.1164/rccm.202303-0558WS
    16. ↵
      1. Higgins JPT,
      2. Thomas J,
      3. Chandler J
      , eds. Cochrane Handbook for systematic reviews of interventions version 6.4. 2023. Available: www.Training.Cochrane.Org/Handbook

    Supplementary materials

    • Supplementary Data

      This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

    Footnotes

    • Contributors GS, AS and MB will search databases and extract and organise data from collected articles. AC will assist with expanding the database search. YZ and JS will perform statistical analysis. GS and KT drafted the manuscript. RK, NQ and JLD provided overarching guidance and mentorship and study direction, formulated the research question and edited manuscript drafts.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting or dissemination plans of this research.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.