Risk factors associated with worse outcomes in COVID-19: a retrospective study in Saudi Arabia

Khan, Anas; Althunayyan, Saqer M; Alsofayan, Yousef M.; Alotaibi, Raied; Mubarak, Abdullah; Arafat, Mohammed; Assiri, Abdullah; Jokhdar, Hani

doi:10.26719/emhj.20.130

Cited by 53 publications

(64 citation statements)

References 17 publications

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“… 50 Reportedly, SARS-CoV-2 has negatively influenced the outcome of anemic patients by interacting with hemoglobin either by attacking heme group on 1-beta chain leading to hemolysis or by hepcidin-mimetic action of a spike protein causing hyperferritinemia. 65 , 66 Cardiac and chronic respiratory diseases have also been identified as risk factors associated with worse outcomes in COVID-19 patients 67 while lung and chronic kidney diseases were also recorded as risk factors in an independent study. 68 We also observed that neurological comorbidities contribute significantly to mortality among the hospitalized patients in line with some previous studies which reported cerebrovascular diseases leads to severe outcomes in COVID-19 cases.…”

Section: Discussionmentioning

confidence: 99%

Comorbidities and Risk Factors for Severe Outcomes in COVID-19 Patients in Saudi Arabia: A Retrospective Cohort Study

Shaikh¹,

Aldhafferi²,

Buker³

et al. 2021

JMDH

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Purpose The first novel coronavirus disease-19 (COVID-19) case in the Kingdom of Saudi Arabia (KSA) was reported in Qatif in March 2020 with continual increase in infection and mortality rates since then. In this study, we aim to determine risk factors which effect severity and mortality rates in a cohort of hospitalized COVID-19 patients in KSA. Method We reviewed medical records of hospitalized patients with confirmed COVID-19 positive results via reverse-transcriptase-polymerase-chain-reaction (RT-PCR) tests at Prince Mohammed Bin Abdulaziz Hospital, Riyadh between May and August 2020. Data were obtained for patient’s demography, body mass index (BMI), and comorbidities. Additional data on patients that required intensive care unit (ICU) admission and clinical outcomes were recorded and analyzed with Python Pandas. Results A total of 565 COVID-19 positive patients were inducted in the study out of which, 63 (11.1%) patients died while 101 (17.9%) patients required ICU admission. Disease incidences were significantly higher in males and non-Saudi nationals. Patients with cardiovascular, respiratory, and renal diseases displayed significantly higher association with ICU admissions (p<0.001) while mortality rates were significantly higher in COVID-19 patients with cardiovascular, respiratory, renal and neurological diseases. Univariate cox proportional hazards regression model showed that COVID-19 positive patients requiring ICU admission [Hazard’s ratio, HR=4.2 95% confidence interval, CI 2.5–7.2); p <0.001] with preexisting cardiovascular [HR=4.1 (CI 2.5–6.7); p <0.001] or respiratory [HR=4.0 (CI 2.0–8.1); p =0.010] diseases were at significantly higher risk for mortality among the positive patients. There were no significant differences in mortality rates or ICU admissions among males and females, and across different age groups, BMIs and nationalities. Hospitalized patients with cardiovascular comorbidity had the highest risk of death (HR=2.9, CI 1.7–5.0; p =0.020). Conclusion Independent risk factors for critical outcomes among COVID-19 in KSA include cardiovascular, respiratory and renal comorbidities.

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Section: Discussionmentioning

confidence: 99%

Comorbidities and Risk Factors for Severe Outcomes in COVID-19 Patients in Saudi Arabia: A Retrospective Cohort Study

Shaikh¹,

Aldhafferi²,

Buker³

et al. 2021

JMDH

View full text Add to dashboard Cite

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“…The results from a multi-center, retrospective, cross-sectional study, performed from March 1, 2020, to March 31, 2020, across all parts of the country, revealed a high percentage of diabetes among the COVID-19 positive patients (from the 220 reported comorbidities, 83 had diabetes) [ 29 ]. From a retrospective study in March 2020 done on 648 COVID-19 patients in healthcare facilities across all parts of Saudi Arabia, 73 (11.3 %) COVID-19 patients were found to have diabetes [ 30 ]. In another retrospective, a single-center study was performed at Al Noor Specialist Hospital, Mecca, using 150 COVID-19 patients (from March 12 to 31 of 2020).…”

Section: Why Diabetes Is Important?mentioning

confidence: 99%

COVID-19 among people with diabetes mellitus in Saudi Arabia: Current situation and new perspectives

Robert

Saeed

Dawish

2021

Diabetes & Metabolic Syndrome: Clinical Research & Revi

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Background and aim This review aims to report the current status of COVID-19 among people with diabetes, newly diagnosed diabetes, diabetic ketoacidosis, and programmatic efforts including vaccinations. Methods We conducted a literature search using PubMed, Google, and Scopus until July 15, 2021. Results In Saudi Arabia, most studies have reported diabetes as one of the highly prevalent comorbidities among patients with COVID-19. Currently, there are limited studies from Saudi Arabia on the newly diagnosed diabetes and diabetic ketoacidosis caused by COVID-19. The Saudi ministry has taken several measures to control the impact of COVID-19 among people with diabetes, including comprehensive guidelines and prioritized vaccinations. During the COVID-19 pandemic, the use of telehealth services dramatically increased in diabetes clinics in Saudi Arabia. Conclusions Focused and evidence-based interventions are essential to control the impact of COVID-19 among people with diabetes.

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“…Around 170 million confirmed cases and more than 3.54 million deaths were registered worldwide, with a Case Fatality Rate (CFR) of 2 as of May 31, 2020, [5]. In the same time interval, the Kingdom of Saudi Arabia has registered a lower CFR 1.7 similar to the international clinical manifestation and risk factors of COVID-19 [6,7,8].…”

Section: Introductionmentioning

confidence: 99%

An ICU Admission Predictive Model for COVID-19 Patients in Saudi Arabia

Ghandorh¹,

Khan²,

Alsufyani³

et al. 2021

IJACSA

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Globally, COVID-19 already emerged in around 170 million confirmed cases of infected people and, as of May 31, 2021, affected more than 3.54 million deaths. This pandemic has given rise to numerous public health and socioeconomic issues, emphasizing the significance of unraveling the epidemic's history and forecasting the disease's potential dynamics. A variety of mathematical models have been proposed to obtain a deeper understanding of disease transmission mechanisms. Machine Learning (ML) models have been used in the last decade to identify patterns and enhance prediction efficiency in healthcare applications. This paper proposes a model to predict COVID-19 patients admission to the intensive care unit (ICU). The model is built upon robust known classification algorithms, including classic Machine Learning Classifiers (MLCs), an Artificial Neural Network (ANN) and ensemble learning. This model's strength in predicting COVID-19 infected patients is shown by performance analysis of various MLCs and error metrics. Among other used ML models, the ANN model resulted in the highest accuracy, 97.9% over other models. Mean Squared Error showed that the ANN method had the lowest error (0.0809). In conclusion, this paper could be beneficial to ICU staff to predict ICU admission based on COVID-19 patients' clinical characteristics.

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Risk factors associated with worse outcomes in COVID-19: a retrospective study in Saudi Arabia

Cited by 53 publications

References 17 publications

Comorbidities and Risk Factors for Severe Outcomes in COVID-19 Patients in Saudi Arabia: A Retrospective Cohort Study

Comorbidities and Risk Factors for Severe Outcomes in COVID-19 Patients in Saudi Arabia: A Retrospective Cohort Study

COVID-19 among people with diabetes mellitus in Saudi Arabia: Current situation and new perspectives

An ICU Admission Predictive Model for COVID-19 Patients in Saudi Arabia

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