Panel of COVID-19 phenotypes: systematic review protocol


 Background The pandemic caused by the SARS-CoV-2 virus, called coronavirus disease 2019 (COVID-19), had an unexpected impact on much of the world, especially Brazil. People diagnosed with the virus manifest different levels of respiratory symptoms, ranging from mild to severe, and may need mechanical ventilation support. The interaction different factors lead to the development of a spectrum of time-related diseases in different phenotypes. Methods This review will consider observational studies published from December 2019 to July 2021, without language restrictions. Studies involving human subjects, adult participants (18 years and older), with subjects who have received a COVID-19 diagnosis using the reverse transcriptase polymerase chain reaction (RT-PCR) test as a reference for the detection of the SARS- CoV-2 virus, according to World Health Organization (WHO) guidance. The databases to be searched will include PubMed/MEDLINE, EMBASE, and CINAHL. The grey literature will also be searched for published research and unpublished studies, using Google Scholar. wo reviewers will independently screen all citations, full-text articles and abstract data. Potential conflicts will be resolved through discussion. Findings will be reported using a narrative synthesis of the results will be carried out around the prevalence, severity of the disease, mortality and risk among the different phenotypes of COVID-19. The I 2 statistic will be used to examine the heterogeneity between the studies, if possible, the meta-analysis will be conducted using the RStudio® statistical software package, and the data will be displayed using forest graphics. Discussion This review will disclose a panel of the different manifestations of the disease COVID-19, and to identify the real risk factor for the most serious phenotypes. Systematic review registration This protocol has been registered within the International Prospective Register of Systematic Reviews (PROSPERO)(CRD42020211439)


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The pandemic caused by the severe acute respiratory syndrome coronavirus 2 62 The interaction between these factors leads to the development of a spectrum of 71 time-related diseases in different phenotypes. Like Richard Dawkins, he extrapolated the 72 concept of Extended Phenotype, not merely being a product of the genotype, but 73 influenced to varying degrees by the environment and the possible interaction between 74 the two (3). It is possible through good assessment tools to identify these phenotypes (4). 75

SARS-CoV
The tool of importance and prominence in the diagnosis of COVID-19, is the Computed 76 Tomography (CT) of the chest, however, it cannot alone confirm it or exclude it. When 77 the reverse-transcriptase polymerase chain reaction (RT-PCR) is used as a reference for 78 the detection of the virus, chest CT has high sensitivity (97%), but low specificity (25%), 79 given the overlap of findings with pulmonary infections of different etiologies. Above all, 80 multiple articles were published reporting the tomographic findings of this condition, 81 even in patients with negative RT-PCR results, emphasizing the role of CT in the current 82 clinical setting (5). 83 Tomographic findings, pathophysiological mechanisms, and possible 84 mechanisms of disease progression are being divided into stages by different authors. In 85 fibrosis arising from the fibrous exudation of the alveolar cavity with multiple irregular 94 consolidations (7). 95 In addition, increased levels of inflammatory biomarkers such as C-reactive 96 protein (CRP), ferritin, Interleukin-6 (IL-6), Interleukin-1 (IL-1) and D-dimer are 97 associated with the development of acute respiratory distress syndrome (ARDS) and a 98 course unfavorable clinical outcome (8). The stages of the disease and its broad clinical 99 spectrum, allows the description of specific individual phenotypes, considering 100 hypoxemia as the severity marker (9). Rello et all describes 3 phenotypes based on 101 respiratory symptoms, CT, hypoxemia, respiratory rate (RF), peripheral oxygen 102 saturation (SpO2) by pulse oximetry, in addition to interleukin-6 (IL-6) to differentiate 103 phenotype 2 from 3 , due to the high inflammatory pattern of viral disease of completely 104 unexpected evolution (9). 105 With respect to patients requiring mechanical ventilation, three respiratory 106 phenotypes are named and explained by different authors (2,7,9). Indicators such as lung 107 weight, CT, ventilation / perfusion ratio (V / Q), pulmonary compliance and elastance, 108 fraction of cardiac output, right-to-left shunt and alveolar recruitment capacity are 109 discussed among the authors, but with inconclusive outcomes. It is believed that the 110 underlying pathophysiological mechanisms differ significantly between the phenotypes, 111 thus requiring careful evaluation, different treatments and different results. The 112 interaction between these factors leads to the development of a spectrum of time-related 113 diseases in different phenotypes. Phenotype is not merely a product of genotype, but is 114 influenced to varying degrees by the environment, and the possible interactions between 115 the two. 116 The primary objective of this systematic review is to address a gap, summarizing 117 the evidence from observational studies, randomized and cluster-randomized clinical The studies selected for this review will assess the different clinical manifestations 171 of the study period, study population, characteristics of participants (symptoms, CT 172 findings, blood tests, hypoxemia, treatment, hospitalization days) individual or group and 173 outcomes in Table 1

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Details on the intervention administered and comparison, the duration of 178 prognostic indicators, mortality, primary results, incidence, prevalence, morbid, will be 179 the second stage of da analyses the articles. 180 181

Exclusion criteria 182
We will exclude studies including participants under the age of 18 or those 183 diagnosed with end-stage chronic disease or in palliative care will be excluded. The search strategy will be designed to identify published and unpublished 187 studies. An initial limited search of PubMed/MEDLINE was conducted to identify 188 articles on this topic, followed by an analysis of the text words contained in the titles and 189 abstracts, and the index terms used to describe those articles.
The grey literature will also be searched for published research and unpublished studies, 192 using Google Scholar. 193 The search terms to be used will be as follows: 194 Step 1: "sars cov2" with Boolean OR for "covid 19" with Boolean AND for "prevalence", 195 "incidence".
Step 2: "sars cov2" with Boolean OR for "covid 19" with Boolean AND for 196 "risk factor", "symptoms" and "phenotype". (Additional file 2). London, UK) and duplicates will be removed. The screening process will be in two steps. 202 The first step will involve the first author (LCS) and a second reviewer each 203 independently screening the title and abstract of all retrieved citations for eligibility based 204 on the specified inclusion and exclusion criteria. This will then be reviewed by the rest of 205 the research team and, on consensus, move to the next step where relevant citations will 206 be included in the full-text review. The first author (LCS) and a second reviewer will 207 independently review the full texts to assess eligibility using the specified criteria. The 208 rest of the research team will again review this process until full consensus is attained. If 209 disagreements arise between (LCS) and a second reviewer at both stages of the screening 210 process, a third reviewer (RSS) will be brought in as a moderator and make the final 211 decision. The studies that meet the inclusion criteria will be recovered in full and their 212 details extracted. The full texts of the selected studies will be submitted to a critical 213 evaluation process. The critical evaluation will be carried out by two independent 214 reviewers (LCS and YCSM) using the standardized critical evaluation instruments from 215 the Joanna Briggs Institute (JBI) -Critical Appraisal Tools for the specifically studies 216 found (13,14). 217 218

Stage 4: Extracting and charting the data 219
A data extraction form will be designed and used to extract equivalent information 220 from each study. Data extraction forms will be piloted initially on a small number of 221 included studies. Subsequently, each of the included studies will be abstracted by two 222 reviewers, independently, and potential conflicts will be resolved through discussion. A 223 panel will be developed that addresses the research questions and the aim of the review.
For the epidemiological studies, will use the Strengthening the Reporting of 225

Observational Studies in Epidemiology (STROBE) checklist (15). 226
The data extracted will be discussed by the research team then summarized and 227 tabulated in themes that address the research questions. Data to be extracted will include, 228 but not be limited to study design, country, study setting, population characteristics, 229 sampling and recruitment of participants, data collection, exposure and outcome variables 230 of interest, characteristics of study participants, identified environmental risk factors, con-231 founders and important conclusions reached from the study. The study selection process will be epitomized in a flow chart adapted from the 235 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 236 Statement (11). The data from each study (e.g. study characteristics, context, participants, 237 outcomes, limitations) will be used to build evidence tables of an overall description of 238 included studies. A qualitative synthesis to assess the methodological quality of the 239 studies will be carried out and will proceed to the quantitative synthesis (meta-analysis). 240 For the application of the most appropriate meta-analytical model and obtaining 241 the combined estimate, the I 2 test will be used to estimate the proportion of total 242 variability in point estimates attributed to heterogeneity different from that due to chance. 243 The data will be grouped according to the level of heterogeneity between the studies, 244 using the following strategy: 245 • I 2 <25%, meta-analysis of fixed effects to estimate the common prevalence (CI95%), 246 assuming that the variability between all or most of the study is due to chance; 247 • I 2 25-75%, meta-analysis of random effects to estimate mean prevalence (CI95%); 248 • I 2 > 75%, very large heterogeneity for the summary estimate to be calculated. 249 RStudio® software was used to group the results of the included studies. 250 After this test, thematic analysis and visual representations including maps or 251 diagrams will be made available. We will use our results to (1) determine the panel of This review will contribute to the literature by summarizing the evidence to report 259 the different existing phenotypes for COVID-19, and the real risk factors for the disease, 260 together with their incidence and prevalence. To correlate the results of our study with 261 the findings of different studies, facilitating discussion about the problem and its possible 262 solution. The divergences in the data published by researchers in relation to mortality 263 rates in risk groups, as well as the prevalence of the disease and its manifestations in parts 264 of the population will be considered. This review will disclose the true etiology of the 265 progression of the severity of the disease, as well as comparisons between severities in 266 people in the same group, will also be elucidated. It is hoped that it will be possible to 267 assemble a panel of the different manifestations of the disease COVID-19, and to identify 268 the real risk factor for the most serious phenotypes. 269 At a larger review level, we anticipate that some outcomes may not have been 270 sufficiently studied, resulting in inconclusive review results. As part of our review, we 271 will identify knowledge strengths and gaps related to this area of inquiry. The findings of 272 this review will be shared through peer-reviewed publications in academic journals,

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Availability of data and materials 305 All data generated or analyzed during this study will be included in the published review article and 306 will be available upon request.