All articles that can be used to assess clinical severity in obese patients with or without comorbidity infected by 2019-nCoV, will be included. There will be no time limit for searching the articles. Studies in any environment or country will be considered.
Protocol
This research will be completed following the methods outlined by the Joanna Briggs Institute's Method Manual for Scoping Review(12). These types of reviews are useful for examining emerging evidence when it is not yet clear and other more specific issues that can be reliably posed and addressed (JBI). The protocol of this Scope Review will be prepared in accordance with the recommendations of the Prisma-P guidelines(13). The protocol was reviewed by the members of the research team. To conduct the research, we will ask for help from another expert to work in collaboration with their librarian, using the PRESS(14) (peer-review of search strategies) checklist.
Framework
The structure will be based on the following points: identify the research question and the relevant studies; select and evaluate the results. This research aims to evaluate the severity of clinical outcomes in obese patients with COVID-19. Recent studies have associated a higher mortality rate and the need for advanced medical care in obese patients.
Eligibility criteria
Any evidence that meets the PICOCS(15) criteria (population, intervention, comparison, outcomes, context, study design) will be included in this review:
Population
- Obese patients (no age limit) infected with COVID-19, with or without comorbidities.
Intervention:
- No intervention is required
Comparison:
- Patients with normal weight
Outcomes:
- Articles that report the severity of clinical outcomes in obese patients, with or without comorbidity, related to SARS-CoV-2 infection.
Context
- Articles published in English, Portuguese and Spanish will be included. There will be no restrictions on the date or range of the publication, because the purpose of the review is to map the existing evidence.
Study design
- This review will consider the designs of experimental studies, including randomized clinical trials, non-randomized clinical trials, expert opinion, cohort study and cross-sectional studies. In addition, analytical observational studies will be considered, including prospective and retrospective cohort studies, case control studies, and cross-sectional analytical studies. This research will also consider descriptive observational study projects, including case series, individual case reports, and descriptive cross-sectional studies, for inclusion. Futhermore, editorials, opinion articles, reviews, systematic reviews, and gray literature will be considered for inclusion.
Exclusion criteria
Articles or studies will be excluded if they cannot be obtained in full-text or if they are not in English, Portuguese and Spanish.
Research strategy
The studies available in the scientific literature will be identified without time limitations using the following databases: PubMed/MEDLINE; Latin American Literature on Health Sciences (Lilacs); Online Scientific Electronic Library (Scielo); Scopus, ScienceDirect, Web of Science,Embase and Cochrane. For identification, a research was conducted with the terms MESH and DECS with the following descriptors: ("covid-19" OR "covid-19 virus infection" OR "SARS-CoV-2 infection" OR "COVID-19 virus disease" OR "severe respiratory acute" OR "syndrome coronavirus 2" OR "severe acute respiratory syndrome coronavirus 2" OR "2019-nCoV" OR "SARS-CoV-2" OR coronavirus) AND (mortality or hospital mortality or hospital) And comorbid* and obes*. The manual search analyzing the references of the included articles will also be done.
Search process
The titles, abstracts, and articles in full will be evaluated by two independent reviewers. Three categories were used in the selection of the title and abstract and text in full: 'yes', 'no' and 'maybe'. In case of doubts (category 'maybe'), the study will be selected for evaluation of the full text, at this stage, the divergences will be resolved by consensus between the two reviewers. The strategy will be sent to an online platform known as Google Forms. Google Forms will allow authors to collaborate simultaneously. The review team will have training on how to use Google Forms before the study begins to ensure calibration of collection methods. The full search of the data will proceed only with x > 75% agreement across the team. If it is found below the value, the doubts will be clarified and the training exercise will be repeated. Conflicts will be resolved by a third reviewer. For this stage, it will be carried out a pilot of 20 studies to calibrate the collection method and the level of agreement. The research will be in accordance with the recommendations of PRESS 2015 guidelines(14), according to the following variables: translation of the research question; boolean operators and proximity; subject titles (database-specific); word text search; limits and filters.
Risk of bias assessment
The assessment of the risk of bias will not be carried out because this is a Scoping Review. Our method is in accordance with the Joanna Briggs Institute Manual for Scoping Review(12) on health-related topics.
Data collect
The reviewers are experts in electronic research, systematic review, and Scoping Review. From this action, a collection of studies will be created to be evaluated by the reviewers. Selection divergences will be resolved through a third reviewer and consensus building. Cohen's kappa statistics will be used to measure reliability among evaluators. The information to be extracted will be:
- Identification of studies: place of publication, date of publication;
- Study methodology: study design; when and where it was performed, analysis of the data used, duration of the study and authors.
- Variables collected: body mass index; comorbidities; severe acute respiratory syndrome; renal failure; acute myocardial infarction; invasive mechanical ventilation; liver failure; death;
Statistical analysis
The statistical program SPSS version 17.0 will be used to calculate the kappa index to verify agreement in the selection of studies included among the authors, reducing the chance of a study loss and the possibility of bias.