ABSTRACT
BACKGROUND: Conceptual models are abstract representations of the real world. They are used to refine medical and nonmedical health care scopes of service. During the COVID-19 pandemic, numerous analytic predictive models were generated aiming to evaluate the impact of implemented policies on mitigating the spread of the virus. The models also aimed to examine the psychosocial factors that might govern the general population's adherence to these policies and to identify factors that could affect COVID-19 vaccine uptake and allocation. The outcomes of these analytic models helped set priorities when vaccines were available and predicted readiness to resume non-COVID-19 health care services. OBJECTIVE: The objective of our research was to implement a descriptive-analytical conceptual model that analyzes the data of all COVID-19-positive cases admitted to our hospital from March 1 to May 31, 2020, the initial wave of the pandemic, the time interval during which local policies and clinical guidelines were constantly updated to mitigate the local effects of COVID-19, minimize mortality, reduce intensive care unit (ICU) admission, and ensure the safety of health care providers. The primary outcome of interest was to identify factors that might affect mortality and ICU admission rates and the impact of the implemented policy on COVID-19 positivity among health care providers. The secondary outcome of interest was to evaluate the sensitivity of the COVID-19 visual score, implemented by the Saudi Arabia Ministry of Health for COVID-19 risk assessment, and CURB-65 (confusion, urea, respiratory rate, blood pressure, and age >65 years) scores in predicting ICU admission or mortality among the study population. METHODS: This was a cross-sectional study. The relevant attributes were constructed based on research findings from the first wave of the pandemic and were electronically retrieved from the hospital database. Analysis of the conceptual model was based on the International Society for Pharmacoeconomics and Outcomes Research guidelines and the Society for Medical Decision-Making. RESULTS: A total of 275 individuals tested positive for COVID-19 within the study design interval. The conceptualization model revealed a low-risk population based on the following attributes: a mean age of 42 (SD 19.2) years; 19% (51/275) of the study population being older adults ≥60 years of age; 80% (220/275) having a CURB-65 score <4; 53% (147/275) having no comorbidities; 5% (13/275) having extreme obesity; and 20% (55/275) having a significant hematological abnormality. The overall rate of ICU admission for the study population was 5% (13/275), and the overall mortality rate was 1.5% (4/275). The multivariate correlation analysis revealed that a high-selectivity approach was adopted, resulting in patients with complex medical problems not being sent to MOH isolation facilities. Furthermore, 5% of health care providers tested positive for COVID-19, none of whom were health care providers allocated to the COVID-19 screening areas, indicating the effectiveness of the policy implemented to ensure the safety of health care providers. CONCLUSIONS: Based on the conceptual model outcome, the selectivity applied in retaining high-risk populations within the hospital might have contributed to the observed low mortality rate, without increasing the risk to attending health care providers.
ABSTRACT
Diagnosis of tuberculosis was affected during the coronavirus disease 2019 (COVID-19) pandemic. Several studies have shown an association between tuberculosis reactivation and COVID-19, but disseminated tuberculosis was rare. We present a case of a 17-year-old male hospitalized due to a fever of unknown origin for two weeks. The patient recovered from COVID-19 five weeks ago, and his nasopharyngeal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) polymerase chain reaction (PCR) was negative on current hospitalization. After investigations, diagnosis of disseminated tuberculosis was made by lymph node biopsy and radiological features. The patient was treated with four anti-tuberculosis medications and had a favorable outcome.
ABSTRACT
INTRODUCTION: Adult Still's disease (ASD) is an uncommon inflammatory disorder characterized by fevers, a salmon-colored rash, and arthritis. Cytokines storm syndrome related to Coronavirus-19 (COVID-19) usually occur in acute period of COVID-19 and can mimic clinical features of ASD. CASE REPORT: We present a case of a 27-year-old male who was hospitalized in July 2020 due to fever, sore throat, multiple joint pain, and body rash for 2 weeks. Patient recovered from COVID-19 8 weeks ago but his nasopharyngeal SARS CoV-2 PCR was still positive on current hospitalization. Post COVID-19 cytokines storm syndrome post COVID-19 was suspected but after further assessment and investigations, diagnosis of ASD was established and patient was treated with corticosteroids therapy and had favorable outcome. CONCLUSION: During COVID-19 pandemic, diagnosis of many other diseases either were delayed or missed. We encourage all clinicians to have a broader differential diagnosis to improve patient care and outcome.
ABSTRACT
Data on multisystem inflammatory syndrome in children (MIS-C) related to coronavirus disease-19 (COVID-19) is increasing in the current COVID-19 pandemic. We present a 16 year old male who was hospitalized in July 2020 under adult medical service due to Kawasaki-like disease symptoms. Diagnosis of MIS-C related to COVID-19 was established by clinical features, elevated inflammatory markers, and positive SARS-COV 2 immunoglobulin G. We encourage all clinicians especially who practice adult medicine to be familiar with signs and symptoms of MIS-C to avoid delayed diagnosis and complications.