ORCID Profile
0000-0003-4713-8536
Current Organisation
Johns Hopkins University
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Publisher: Future Science Ltd
Date: 07-2021
Publisher: Hindawi Limited
Date: 13-11-2020
DOI: 10.1111/IJCP.13777
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 12-2020
Publisher: F1000 Research Ltd
Date: 19-04-2021
Publisher: International Scientific Information, Inc.
Date: 18-03-2021
DOI: 10.12659/AJCR.930200
Publisher: Informa UK Limited
Date: 10-2020
DOI: 10.2147/IJGM.S273900
Publisher: Informa UK Limited
Date: 03-08-2022
DOI: 10.1080/17476348.2022.2108796
Abstract: To identify early indicators for invasive mechanical ventilation utilization among COVID-19 patients. This retrospective study evaluated COVID-19 patients who were admitted to hospital from 20 September 2020, to 8 August 2021. Multivariable logistic regression and machine learning (ML) methods were employed to assess variable significance. Among 1,613 confirmed COVID-19 patients, 365 patients (22.6%) received invasive mechanical ventilation (IMV). Factors associated with IMV included older age >65 years (OR,1.46 95%CI, 1.13-1.89), current smoking status (OR, 1.71 95%CI, 1.22-2.41), critical disease at admission (OR, 1.97 95%CI, 1.28-3.03), and chronic kidney disease (OR, 2.07 95%CI, 1.37-3.13). Laboratory abnormalities that were associated with increased risk for IMV included high leukocyte count (OR, 2.19 95%CI, 1.68-2.87), low albumin (OR, 1.76 95%CI, 1.33-2.34) and high AST (OR, 1.71 95%CI, 1.31-2.22). Our study suggests that there are several factors associated with the increased need for IMV among COVID-19 patients. These findings will help in early identification of patients at high risk for IMV and reallocation of hospital resources toward patients who need them the most to improve their outcomes.
Publisher: Informa UK Limited
Date: 09-2022
DOI: 10.2147/IJWH.S360465
Publisher: Hindawi Limited
Date: 16-08-2022
DOI: 10.1155/2022/9617319
Abstract: This study aimed to assess the risk factors for COVID-19 mortality among hospitalized patients in Jordan. All COVID-19 patients admitted to a tertiary hospital in Jordan from September 20, 2020, to August 8, 2021, were included in this study. Demographics, clinical characteristics, comorbidities, and laboratory results were extracted from the patients’ electronic records. Multivariable logistic and machine learning (ML) methods were used to study variable importance. Out of 1,613 COVID-19 patients, 1,004 (62.2%) were discharged from the hospital (survived), while 609 (37.8%) died. Patients who were of elderly age ( years) (OR, 2.01 95% CI, 1.28–3.16), current smokers (OR, 1.61 95%CI, 1.17–2.23), and had severe or critical illness at admission ((OR, 1.56 95%CI, 1.05–2.32) (OR, 2.94 95%CI, 2.02–4.27) respectively), were at higher risk of mortality. Comorbidities including chronic kidney disease (OR, 2.90 95% CI, 1.90–4.43), deep venous thrombosis (OR, 2.62 95% CI, 1.08–6.35), malignancy (OR, 2.22 95% CI, 1.46–3.38), diabetes (OR, 1.31 95% CI, 1.04–1.65), and heart failure (OR, 1.51 95% CI, 1.02–2.23) were significantly associated with increased risk of mortality. Laboratory abnormalities associated with mortality included hypernatremia (OR, 11.37 95% CI, 4.33–29.81), elevated aspartate aminotransferase (OR, 1.81 95% CI, 1.42–2.31), hypoalbuminemia (OR, 1.75 95% CI, 1.37–2.25), and low platelets level (OR, 1.43 95% CI, 1.05–1.95). Several demographic, clinical, and laboratory risk factors for COVID-19 mortality were identified. This study is the first to examine the risk factors associated with mortality using ML methods in the Middle East. This will contribute to a better understanding of the impact of the disease and improve the outcome of the pandemic worldwide.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 12-2020
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 02-2021
No related grants have been discovered for Abdel-Hameed Al-Mistarehi.