Clinical features, laboratory characteristics and risk factors for mortality of COVID-19 patients in a secondary hospital in Oman during the first wave of the SARS-CoV-2 pandemic

Assessment of the hematological profiles among COVID-19 patients during the first and second waves in Ethiopia: A multicenter retrospective cohort study

Background

The coronavirus disease 2019 is highly infectious and patients with coronavirus diseases demonstrated a series of clinical symptoms caused by severe acute respiratory syndrome coronavirus-2. Without a break of the wave's hematological profile of the patients is still ambiguous and differs from wave to wave.

Objective

This study aimed to assess the hematological profile among coronavirus disease 2019 patients during the first and the second waves in Ethiopia.

Methods

A multi-centered facility-based retrospective cohort study design was conducted at six coronavirus disease 2019 treatment centers. A total of 538 study participants were enrolled in the selected coronavirus disease 2019 treatment centers during the first and second waves of the pandemic. The demographic characteristics, underlying diseases, symptoms, and hematological parameters of patients were recorded. Data were entered into Epi-Data Manager 4.6 and analyzed using STATA 14.2. An independent sample t-test was used to assess the mean differences in hematological parameters across waves. Associations between categorical variables across waves were also determined using Chi-square and Fisher exact tests.

Results

Among the total study participants, 240 (44.6%) and 298 (55.4%) patients were taken from wave-1 and wave-2, respectively. The average age of the study participants was 56.44 ± 16.25 years. The most frequent comorbidities in this study were hypertension, diabetes mellitus, ischemic heart disease, and asthma. The most presenting symptoms of COVID-19 infection across the two waves were presented. In the first wave, dry cough 166 (69.2%), fatigue 153 (63.75%), shortness of breath 148 (61.67%), and fever accounted 116 (48.33%), while during the second wave, dry cough 242 (81.2%), fatigue 244 (81.88%) shortness of breath 204 (68.47%) and fever account 180 (60.40%). White blood cells (WBC), neutrophils, and lymphocytes had shown increment during the first wave. Platelet count and platelet distribution width (p < 0.001) had significant mean differences across the two waves, while the other had no significant mean difference.

Conclusion

In the present study, dry cough, fatigue, shortness of breath, and fever were found to be the most presenting symptoms of COVID-19 infection across the two waves. Only the platelet count and platelet distribution width had significant mean differences across the two waves, while the other had no significant mean difference across waves.

Transmission dynamics, responses, and clinical features for the first 1100 COVID-19 cases in South Batinah, Oman: Major lessons from a provincial perspective

Objectives

This study was aimed at exploring and analyzing the epidemiological profile, surveillance, and response to COVID-19, including transmission dynamics and cluster formation.

Methodology

This was a retrospective analysis of surveillance data, including contact tracing, risk factors, and clinical information. Binary logistic regressions were used to assess the likelihood of admission, cluster formation, and of each individual being an index patient. Clusters were demonstrated through geographic data systems, network analysis, and visualization software.

Results

A total of 1100 COVID-19 cases were diagnosed from 20 March to 7 June 2020, of which 144 (13.1%) were asymptomatic. The median time from symptom onset to admission was 7 days (IQR, 4.5-10), and the median symptom duration was 5 days (IQR, 3-9). Eighty-nine clusters containing 736 patients were identified. The surveillance and control actions were divided into three phases. Clusters began to form in phase 2 and became more pronounced in phase 3. Patients ≥50 years of age and patients presenting with fever had relatively higher odds of admission: OR = 12.85 (95% CI 5.13-32.19) and 2.53 (95% CI 1.24-5.17), respectively. Cluster formation was observed among females, asymptomatic patients, and people living in Awabi: OR = 2.3 (95% CI 1.7-3.1), 6.39 (95% CI 2.33-17.2), and 3.54 (95% CI 2.06-6.07), respectively. Patients working in the police and defense sectors had higher odds of being an index patient: OR = 7.88 (95% CI 3.35-18.52).

Conclusion

Case-based interventions should be supported by population-wide measures, particularly movement restrictions. Establishing prevention teams or district units, or primary care will be crucial for the control of future pandemics. Prevention should always be prioritized for vulnerable populations.

Epidemiological, Clinical, and Laboratory Findings of 235 Hospitalized COVID-19 Adult Patients (Survivors and Non-Survivors) at Sohar Hospital in Oman

OBJECTIVES

The aim of this study was to describe the epidemiological and clinical characteristics and laboratory findings of coronavirus disease 2019 (COVID-19) patients at the Sohar Hospital, Sohar, Oman.

METHODS

This retrospective study of admitted COVID-19 patients at Sohar Hospital in Oman was carried out from March to October 2020. Demographics and laboratory data of 19 tests for 235 COVID-19 patients, of which 202 were survivors and 33 were non-survivors, were collected from the hospital information system after ethics approval.

RESULTS

Thirteen factors were significantly correlated with in-hospital mortality, including older age, having chronic disease, high neutrophil count, high troponin T, high creatinine, low albumin (p < 0.0001), high white blood cell (WBC) count, low hemoglobin, high D-dimer (p < 0.001), high C-reactive protein (CRP) (p < 0.002), low lymphocyte count (p < 0.003), high alkaline phosphatase (ALP) enzyme (p < 0.007) and high ferritin (p < 0.045). The most common laboratory blood test abnormalities that were highly correlated with mortality were increased values of CRP (100% of non-survivors), D-dimer (94.1% of non-survivors), ferritin (88.2% of non-survivors), and troponin T (85% of non-survivors) and reduced lymphocyte count (73.9% of non-survivors).

CONCLUSION

These findings could help in categorizing COVID-19 patients for risk-based assessment and early identification of patients with poor prognosis.

Risk Factors for Mortality of Hospitalized Adult Patients with COVID-19 Pneumonia: A Two-Year Cohort Study in a Private Tertiary Care Center in Mexico

During the COVID-19 pandemic, the high prevalence of comorbidities and the disparities between the public and private health subsystems in Mexico substantially contributed to the severe impact of the disease. The objective of this study was to evaluate and compare the risk factors at admission for in-hospital mortality of patients with COVID-19. A 2-year retrospective cohort study of hospitalized adult patients with COVID-19 pneumonia was conducted at a private tertiary care center. The study population consisted of 1258 patients with a median age of 56 ± 16.5 years, of whom 1093 recovered (86.8%) and 165 died (13.1%). In the univariate analysis, older age (p < 0.001), comorbidities such as hypertension (p < 0.001) and diabetes (p < 0.001), signs and symptoms of respiratory distress, and markers of acute inflammatory response were significantly more frequent in non-survivors. The multivariate analysis showed that older age (p < 0.001), the presence of cyanosis (p = 0.005), and previous myocardial infarction (p = 0.032) were independent predictors of mortality. In the studied cohort, the risk factors present at admission associated with increased mortality were older age, cyanosis, and a previous myocardial infarction, which can be used as valuable predictors for patients' outcomes. To our knowledge, this is the first study analyzing predictors of mortality in COVID-19 patients attended in a private tertiary hospital in Mexico.