A5040823635- COVID-19 Clinical Research Studies
- Long-Term Effects of COVID-19
- Cardiac Structural Anomalies and Repair
- Nutritional Studies and Diet
- Pharmacovigilance and Adverse Drug Reactions
- Coronary Artery Anomalies
- COVID-19 and healthcare impacts
- Antibiotic Use and Resistance
- Cancer Genomics and Diagnostics
- Diet, Metabolism, and Disease
- Respiratory Support and Mechanisms
- Diabetes Management and Research
- Patient Satisfaction in Healthcare
- Kawasaki Disease and Coronary Complications
- COVID-19 and Mental Health
- Diet and metabolism studies
- SARS-CoV-2 and COVID-19 Research
- Intravenous Infusion Technology and Safety
- Ethics in Clinical Research
- Hyperglycemia and glycemic control in critically ill and hospitalized patients
- Colorectal Cancer Treatments and Studies
- Lung Cancer Treatments and Mutations
- Emergency and Acute Care Studies
McMaster University
2022-2024
Impact
2022-2024
Weatherford College
2023
To evaluate the impact of COVID-19 pandemic on patterns antimicrobial use and incidence pathogens in primary secondary healthcare settings Northern Ireland.Data were collected antibiotic Gram-positive Gram-negative from Ireland for period before (January 2015-March 2020) during (April 2020-December 2021) pandemic. Time series intervention analysis methods utilized.In hospital setting, mean total consumption was 1864.5 defined daily doses (DDDs) per 1000 occupied-bed days (OBD), showing no...
This study aimed to assess the risk factors for COVID-19 mortality among hospitalized patients in Jordan. All admitted a tertiary hospital Jordan from September 20, 2020, August 8, 2021, were included this study. Demographics, clinical characteristics, comorbidities, and laboratory results extracted patients’ electronic records. Multivariable logistic machine learning (ML) methods used variable importance. Out of 1,613 patients, 1,004 (62.2%) discharged (survived), while 609 (37.8%) died....
To identify early indicators for invasive mechanical ventilation utilization among COVID-19 patients.This retrospective study evaluated patients who were admitted to hospital from 20 September 2020, 8 August 2021. Multivariable logistic regression and machine learning (ML) methods employed assess variable significance.Among 1,613 confirmed patients, 365 (22.6%) received (IMV). Factors associated with IMV included older age >65 years (OR,1.46; 95%CI, 1.13-1.89), current smoking status (OR,...
e20092 Background: EGFR mutations with exon 20 insertions (Exon20ins) have emerged as a distinct subset significant clinical implications. Their prevalence is approximately 10%. Patients Exon20ins fewer available treatment options compared to common mutations. We therefore aimed evaluate progression-free survival (PFS) in advanced and recurrent non-small cell lung cancer (NSCLC) patients harboring treated inhibitors. Methods: searched the OpenCase database for stage III-IV NSCLC mutation...
The current study sets out to develop and validate a robust machine-learning model utilizing electronic health records (EHR) forecast the risk of hypoglycemia among ICU patients in Jordan.
Coronavirus Disease 2019 (COVID-19) long-term effect is the new challenge facing healthcare providers that should be further assessed. We aim to describe characteristics and patterns of consequences COVID-19 among recovered patients. patients baseline data was extracted from hospital records alive filled self-reported symptoms questionnaires. A follow-up chest X-ray (CXR) then scored based on lung abnormalities compared with CXR images. Six hundred ninety-four were included for questionnaire...
<h3>Background</h3> The United States Food and Drug Administration Adverse Event Reporting System (FAERS), EudraVigilance the World Health Organization's VigiBase are global gold standards for reporting of adverse events (AEs). However, these platforms rely on spontaneous limited by under-reporting, time-lag between event occurrence discovery as well lack drug-event causality. Peer reviewed published case reports a high quality source AE reports. breadth use this data is poorly understood,...