key: cord-289522-7u3d6nfc authors: Ebrahimi, Mina; Malehi, Amal Saki; Rahim, Fakher title: COVID-19 Patients: A Systematic Review and Meta-Analysis of Laboratory Findings, Comorbidities, and Clinical Outcomes Comparing Medical Staff versus the General Population date: 2020-10-17 journal: Osong Public Health Res Perspect DOI: 10.24171/j.phrp.2020.11.5.02 sha: doc_id: 289522 cord_uid: 7u3d6nfc This review compared coronavirus disease 2019 (COVID-19) laboratory findings, comorbidities, and clinical outcomes in patients from the general population versus medical staff to aid diagnosis of COVID-19 in a more timely, efficient, and accurate way. Electronic databases were searched up to 23(rd) March, 2020. The initial search yielded 6,527 studies. Following screening, 24 studies were included [18 studies (11,564 cases) of confirmed COVID-19 cases in the general public, and 6 studies (394 cases) in medical staff] in this review. Significant differences were observed in white blood cell counts (p < 0.001), lymphocyte counts (p < 0.001), platelet counts (p = 0.04), procalcitonin levels (p < 0.001), lactate dehydrogenase levels (p < 0.001), and creatinine levels (p = 0.03) when comparing infected medical staff with the general public. The mortality rate was higher in the general population than in medical staff (8% versus 2%). This review showed that during the early stages of COVID-19, laboratory findings alone may not be significant predictors of infection and may just accompany increasing C-reactive protein levels, erythrocyte sedimentation rates, and lactate dehydrogenase levels. In the symptomatic stage, the lymphocyte and platelet counts tended to decrease. Elevated D-dimer fibrin degradation product was associated with poor prognosis. Coronavirus disease 2019 (COVID- 19) was first detected in Wuhan, China, before rapidly affecting 199 countries and territories around the world. According to the World Health Organization, as of the 24 th March, 2020, the total number of patients with COVID-19 was 537,881 with 24,293 deaths [1] . USA, China, Italy, Spain, Germany, and Iran have the most reported laboratory-confirmed COVID-19 cases and deaths [2] . Genetic studies revealed that Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus has an 88% similarity with severe acute respiratory syndrome (SARS), and 50% similarity with Middle East respiratory syndrome (MERS) [3] . Compared with SARS, MERS, and pneumonia, SARS-CoV-2 has a longer incubation time, greater pathogenicity and rapid transmission [4] . Currently there is no vaccine or specific treatment for COVID-19. SARS-CoV-2 infects people of all ages and may cause the respiratory system to rapidly develop acute respiratory distress syndrome (ARDS), cardiovascular complications, and acute kidney injury [5] [6] [7] . A fever, cough, Studies which were just molecular reports, studies that reported laboratory results as percentages, case reports, and commentaries were excluded. Two reviewers separately extracted the data from included studies, considering key characteristics including author, publication year, country, type of study, sample size, laboratory findings, comorbidities, and final clinical outcomes. Quality appraisal checklist and the critical appraisal methodological index for non-randomized studies were used as tools for bias risk assessment [13] . The funnel-plot and Egger's regression test were used to assess publication bias [14] . Cochran, Chi-square test, and I 2 were used to assess heterogeneity amongst studies. A fixed-effects model was used when I 2 < 50%, and when I 2 > 50%, a random-effects model was selected. The fixed-model assumed that the population effect sizes were the same for all studies [15] . In contrast the random-effects model attempted to generalize findings beyond the included studies by assuming that the selected studies were random samples from a larger population [16] . If there was statistical heterogeneity amongst the results, a further sensitivity analysis was conducted to determine the source of heterogeneity. After significant clinical heterogeneity was excluded, the randomized effects model was used for metaanalysis. When p < 0.05 the result was considered statistically significant (2-sided). All data were analyzed using the STAT 15 software (IBM, NY, USA). The initial search yielded 6,527 studies, with duplicate studies removed resulting in 1,759 studies remaining. Following the inclusion exclusion criteria 24 studies were selected. This included 11,950 confirmed cases of COVID-19 and comprised of 18 studies (11,556 cases) of patients from the general population, and 6 studies (394 cases) where medical staff were the patients ( Figure 1 ). The 24 selected studies obtained from the systematic review are presented in Table 1 . Of these, 41.7% [17] were case-control studies [6, 8, 9, [18] [19] [20] [21] [22] [23] , and 58.3% [20] were cross-sectional design studies [5, 18, [24] [25] [26] [27] [28] . There was 1 study that investigated the association between coagulation abnormalities and prognosis in COVID-19 patients [20] . Just 2 studies had a sample size greater than 1,000 [25, 29] (Table 1 ). All eligible studies that evaluated medical staff who had contracted COVID-19 were selected. Of these 6 studies there were 394 infected medical staff [19, 24, 26] (Table 1) . Other details of the data are available in Table S1 . The result of laboratory finding analysis in the general public showed, lymphocytopenia (0. (Table 2) . Further statistical tests revealed that the laboratory variables in infected medical staff were significantly different to the general public who were infected. A lower WBC (p < 0.001), a higher lymphocyte count (p < 0.001), platelet count (p = 0.04 ), and PCT (p < 0.001), a lower LDH (p < 0.001), and creatinine (p = 0.03) were observed in infected medical staff ( Table 2 ). The detailed data are available in Table S2 and S3. The most reported clinical findings for all cases in this review were a fever 77% (95% CI: 63-89%), a cough 60% (95% CI: 53-68%), and fatigue 38% (95% CI: 28-48%). Further analysis revealed the frequency of clinical manifestations in infected medical staff were similar to patients in the general public (Table 3) . Egger test results revealed there was no publication bias in the studies (Table 3) . Af ter investigating comorbidities, it was reveale d that patients with hypertension 17% (95% CI: 12-23%), cardiovascular disease (CVD) 0.8% (95% CI: 0.4-12%), or diabetes 10% (95% CI: 0.7-13%) were more susceptible to COVID-19 (Table 4 ). As shown in Table 5 , these frequencies were lower amongst infected medical staff. The clinical outcome showed that the mortality rate was higher in patients from the general population [8% (95% CI: 4-13%)] than patients who were medical staff [2% (95% CI: 0-10%)]. There were 51% (95% CI: 27-75%) of patients from the general population who required hospitalization. Medical staffs had shorter number of days in hospital than patients with relative frequency of 73% (95% CI: 38-97%) (Table S4 ). The absence of specific laboratory findings and clinical manifestations during the early stages of COVID-19 in patients complicated early diagnosis of the disease. Additional to the rapid progression in late-stage COVID-19, development of ARDS was more severe than ARDS observed with other virus infections which occur routinely [30] . There are several systematic and meta-analysis studies of COVID-19 which mainly discussed comorbidities, clinical manifestations, and treatments [31] [32] [33] [34] [35] . In this current review, laboratory abnormality interpretations in early and late stage disease were considered. In this regard, 24 studies, including 11,556 general patients and 394 infected medical staff were evaluated. Like other viral infections, a fever, a cough, and fatigue were the most commonly observed clinical findings in COVID-19 patients, but the absence of these clinical characteristics cannot rule out infection. In this regard, Hu et al [9] reported just 20.8% of infected patients developed these symptoms during hospitalization. Despite the typical symptom of SARS and MERS infections being diarrhea, it has a low prevalence in COVID-19 [36] . It has been reported in a case without typical COVID-19 clinical characteristics and laboratory results, that the virus was detected in the stool sample suggesting that suspected cases of COVID-19 where diarrhea was present but no laboratory abnormalities are observed should be considered for follow up COVID-19 testing [37] . Additionally, this review supports other data to show that COVID-19 in patients with underlying disease, mainly hypertension, diabetes, and CVD, results in these patients being hospitalized Wang et al [8] showed that patients admitted to the intensive care unit (ICU) had more comorbidities compared with patients not treated in the ICU. The main mechanism for inflammation and organ damage associated with COVID-19 appears to be attributable to [21, 39, 42] . This could be an explanation of normal laboratory findings related to the liver in the early stages of COVID-19. Hypoxia is another pathogenesis associated with COVID-19, which is one of the main causes of sudden death in patients, hence increasing creatine kinase may be due to hypoxia and must be causally interpreted [22] . A critical issue not discussed in earlier systematic and metaanalysis studies are coagulation parameters. Inflammatory cytokine activation of monocytes and endothelial cells, tissue factor expression, and secretion of Von Willebrand clotting factor protein causes the development of and dissemination of intravascular coagulation [21] . It was demonstrated that SARS infection is accompanied by dysregulation of the urokinase pathway, activation of fibrinolysis, increasing fibrin degradation products (FDP), and is associated with poor prognosis [20, 43] . The findings of this review indicated that elevated D-dimer was associated with COVID-19. It was demonstrated that disease progression was accompanied by coagulation parameters increasing thus, increasing D-dimer and FDP were observed in patients admitted to ICU [8, 20, 22] . In the present study, SARS-CoV-2 infected medical staff were compared with SARS-CoV-2 infected patients from the general public and the mean laboratory results showed that medical staff had milder symptoms with slightly less disease severity than the patients from the general population. The clinical outcome analysis revealed 51% of patients from the general population required hospitalization, and the mortality rate was 8%. Whereas in patients who were medical staff, mortality and hospitalization rates were lower, and the discharge rate was higher. This could be due to a lower rate of comorbidities, as well as timely access to diagnostic tools and care [9, 19, 26] . [45] , mortality was reported as high thus, the possible reason could be that the mean age and comorbidities were higher than in the other studies. The findings of this COVID-19 meta-analysis review revealed that the normal or abnormal outcome of a patient's laboratory results may shed light on the stage of the disease and its progression. In asymptomatic patients, in the early stages of Supplementary data is available at http://www.kcdcphrp.org. The authors have no conflicts of interest to declare. World Health Organization. Coronavirus disease Cross-country comparison of case fatality rates of Covid-19/SARS-CoV-2 A Novel Coronavirus from Patients with Pneumonia in China Laboratory abnormalities in patients with COVID-2019 infection Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China Laboratory findings, signs and symptoms, clinical outcomes of Patients with COVID-19 Infection: An updated systematic review and meta-analysis Clinical Characteristics of 138 Hospitalized Patients with 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China Clinical characteristics of 24 asymptomatic infections with COVID-19 screened among close contacts in Nanjing Clinical characteristics of fatal and recovered cases of coronavirus disease 2019 in Wuhan, China: A retrospective study Clinical characteristics of novel coronavirus cases in tertiary hospitals in Hubei Province Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement Methodological index for nonrandomized studies (Minors): Development and validation of a new instrument Statistical aspects of the analysis of data from retrospective studies of disease Conducting a meta-analysis: Basics and good practices Prevalence of all-cause mortality and suicide among bariatric surgery cohorts: A meta-analysis Clinical characteristics and intrauterine vertical transmission potential of COVID-19 infection in nine pregnant women: A retrospective review of medical records Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study Association of Cardiovascular Manifestations with In-hospital Outcomes in Patients with COVID-19: A Hospital Staff Data Abnormal Coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72314 Cases From the Chinese Center for Disease Control and Prevention Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China A comparative study on the clinical features of COVID-19 pneumonia to other pneumonias Clinical Characteristics of 54 medical staff with COVID-19: A retrospective study in a single center in Wuhan Clinical Characteristics of Coronavirus Disease 2019 in China Epidemiological, Clinical Characteristics and Outcome of Me dical Staf f Infecte d with COVID-19 in Wuhan, China: A Retrospective Case Series Analysis Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: Retrospective case series Initial clinical features of suspected Coronavirus Disease 2019 in two emergency departments outside of Hubei Epidemiology Committee TUoMS: Epidemiological report of covid patients 19 in Hospitals covered by Tehran University of Personal knowledge on novel coronavirus pneumonia Novel Coronavirus Patients' Clinical Characteristics, Discharge Rate and Fatality Rate of Meta-Analysis Clinical Characteristics, Laboratory Findings, Radiographic Signs and Outcomes of 52,251 Patients with Confirmed COVID-19 Infection: A Systematic Review and Metaanalysis Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 infection Prevalence of comorbidities in the novel Wuhan coronavirus (COVID-19) infection: A systematic review and metaanalysis SARS and other coronaviruses as causes of pneumonia Detection of Novel Coronavirus by RT-PCR in Stool Specimen from Asymptomatic Child Review of the Clinical Characteristics of Coronavirus Disease 2019 (COVID-19) Receptor recognition by novel coronavirus from Wuhan: An analysis based on decade-long structural studies of SARS T-cell immunity of SARS-CoV: Implications for vaccine development against MERS-CoV Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease Specific ACE2 Expression in Cholangiocytes May Cause Liver Damage After 2019-nCoV Infection Mechanisms of severe acute respiratory syndrome coronavirus-induced acute lung injury Clinical characteristics of survivors and nonsurvivors, medical and non-medical staff members with 2019-nCoV pneumonia in Wuhan, China : A descriptive study COVID-19 in a Long-Term Care Facility Time Course of Lung Changes On Chest CT During Recovery From 2019 Novel Coronavirus (COVID-19) Pneumonia Analysis of CT features of 15 Children with 2019 novel coronavirus infection Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: A singlecentered, retrospective, observational study Clinical characteristics of 30 medical workers infected with new coronavirus pneumonia We wish to thank all our colleagues in the Allied Health Sciences School, Ahvaz Jundishapur University of Medical Sciences. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.