ABSTRACT
Background: Coronavirus disease 2019 (COVID-19) neurologic symptoms such as anosmia and ageusia are considered the most challenging issues for patients in the first steps of viral infection. Herein, we aimed to investigate the olfactory and gustatory dysfunction and their association with prognostic factors in patients with COVID-19. Material(s) and Method(s): The current retrospective study was performed on patients admitted to a hospital with a definite diagnosis of COVID-19 between March and November 2020. Based on the study criteria, information of 150 eligible participants (89 males and 61 females) was collected entirely. The olfactory and gustatory symptoms, including anosmia, hyposmia, ageusia, and dysgeusia, were assessed, and five main COVID-19 prognostic factors, including the level of D-dimer, C-reactive protein (CRP), lymphocyte count (LC), lactic acid dehydrogenase (LDH) and COVID-19 related lung involvement was measured. Result(s): Among all patients, 102 (68%) participants were treated entirely, and 48 (32%) died. All prognostic factors, including CRP, LDH, LC, D-dimer, and lung involvement, were significantly higher in death cases compared to treated patients. We found that 97 (64.7%) patients experienced at least one olfactory or gustatory dysfunction. The level of CRP, LC, D-dimer, and lung involvement showed a better prognosis among patients with at least one sensory dysfunction. Moreover, a better outcome was observed in patients with sensory dysfunction. Conclusion(s): It can be concluded the evaluation of CRP, LDH, D-dimer, and LC, together with the HRCT scan score, contributes to a better prognosis in COVID-19 patients with sensory dysfunction. Copyright © 2022 The authors.
ABSTRACT
Background: A novel coronavirus led to a rapidly spreading outbreak of COVID-19, which caused morbidity and mortality world-wide. Appropriate case definitions can help diagnose COVID-19. Objectives: This study aimed to evaluate the COVID-19 clinical symptoms and their potential patterns using latent class analysis (LCA) for identifying confirmed COVID-19 cases among hospitalized patients in northern Iran according to the syndromic surveil-lance system data. Methods: This cross-sectional study was conducted on patients with COVID-19 admitted to hospitals in Mazandaran Province, Iran. Respiratory specimens were collected by nasopharyngeal swabs from the patients and tested for COVID-19 using reverse transcrip-tion polymerase chain reaction (RT-PCR). Latent class analysis was used to identify patterns of the symptoms. The sensitivity, speci-ficity, and area under the receiver operating characteristic (ROC) curve (AUC) of each symptom pattern were compared and plotted. Also, multiple logistic regression was used to determine the odds ratio for each symptom pattern for predicting COVID-19 infection by adjusting for gender and age groups. Results: Among 13,724 hospitalized patients tested for COVID-19 and included in the analyses, 4,836 (35, 2%) had RT-PCR confirmed COVID-19. The symptoms of fever, chills, cough, shortness of breath, fatigue, myalgia, sore throat, diarrhea, nausea or vomiting, headache, and arthralgia were significantly more common in patients positive for COVID-19 than in other patients and were used in LCA. Latent class analysis suggested six classes (patterns) of clinical symptoms. The AUC of symptom patterns was poor, being 0.43 for class 5, comprising patients without any symptoms, and 0.53 for class 3, comprising patients with fever, chills, and cough. Also, multiple logistic regression showed that class 1, comprising patients with fever, chills, cough, shortness of breath, sore throat, and arthralgia, had an odds ratio of 2.87 (1.39, 3.43) relative to class 5 (patients without any symptoms) for positive COVID-19. Conclusions: This study showed that the clinical symptoms might help diagnose COVID-19. However, the defined clinical symptoms suggested in the surveillance system of COVID-19 in Iran during this time were not appropriate for identifying COVID-19 cases.
ABSTRACT
Backgrounds: Coronavirus disease 2019 (COVID-19) pandemic is considered as a global health challenge, and Iran is among the top ten countries with the highest mortality rate. This study aimed to analyze epidemiological, clinical, and laboratory features of hospitalized SARS-CoV-2 infected patients and identify the risk factors of mortality among them to facilitate the prioritization of resources and vaccine allocation in the population using data available in a large university hospital in Tehran, Iran. Materials & Methods: From February 20 to May 14, 2020, a total of 684 COVID-19 confirmed cases were admitted to Imam Hossein University hospital in Tehran and enrolled in this retrospective observational study. Findings: The mean age of the participants was 59.48±16.65 years, and 55.8% were male. Compared to survivors, non-survivors (n=127, 18.57%) were older (69.09±14.16 vs. 57.29±16.40), had higher average number of comorbidities, and more frequently suffered from dyspnea, convulsion, loss of consciousness (LOC), tachycardia, tachypnea, and hypoxia. They also had higher levels of leukocytes, neutrophil count, C-reactive protein (CRP), creatine phosphokinase (CPK), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), international normalized ratio (INR), prothrombin time (PT), partial thromboplastin time (PTT), urea, and serum creatinine (p<.05). Serum potassium (K), lymphocyte count, hemoglobin, HCO3, and serum sodium (Na) were significantly lower in non-survivors. Multivariable logistic regression analysis results revealed that nine variables were positively associated with mortality. Conclusion: Among COVID-19 patients admitted to the hospital, having more than two or three comorbidities, loss of consciousness, SpO2 < 90%, increased CRP, CPK, urea, and serum potassium, were associated with mortality. © 2021, TMU Press.