Nahid Abdulhamid Qushmaq
Research Subjects
Nahid Abdulhamid Qushmaq has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Ahmad Ali Alharbi
Department of Basic Medical Sciences, College of Medicine, Majmaah University, Majmaah 11952, Saudi Arabia
1 shared publication - Ebtisam Bakhsh
Department of Internal Medicine, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia
1 shared publication - Ekremah A. Alzarea
Hematopathology, Department of Pathology, College of Medicine, Jouf University, Sakaka 72388, Saudi Arabia
1 shared publication - Ezeldine K. Abdalhabib
Department of Clinical Laboratory Sciences, College of Applied Medical Sciences-AlQurayyat, Jouf University, Saudi Arabia
1 shared publication - Hadeer Ahmed Ali Esmaeil
Faculty of Medicine, Minia University, Minia 2431436, Egypt
1 shared publication - May AlMoshary
Department of Basic Science, College of Medicine, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia
1 shared publication
Latest Publications
- Open Access
- 14 July 2026
- Published by MDPI AG in Healthcare
- Vol. 14 (14) , 2112
Factors Associated with Delayed Diagnosis of Iron Deficiency Anemia in Egyptian Patients: A Retrospective Cohort Study
Background/Objectives: Iron deficiency anemia (IDA) remains the most prevalent nutritional deficiency worldwide and a leading cause of years lived with disability, particularly in low-income countries. In Egypt, the burden is substantial and compounded by regional socioeconomic, nutritional, and parasitic factors. Despite this, the predictors of diagnostic delay within the Egyptian healthcare system remain poorly characterized. This study aimed to quantify the extent of diagnostic delay among Egyptian patients with IDA and to identify the sociodemographic and clinical risk factors independently associated with prolonged time to diagnostic confirmation. Methods: A single-center retrospective cohort study was conducted at Al-Minia University Hospital, Egypt, between March and April 2026, enrolling 350 adults with confirmed IDA diagnosed between 2015 and 2025. “Diagnostic delay” was defined as the interval in days from the index date (the first documented abnormal complete blood count) to laboratory confirmation of iron deficiency by serum ferritin and/or transferrin saturation. Secondary outcomes included patient delay, system/testing delay, and etiology work-up delay. Time-to-event analysis was performed using Kaplan–Meier curves and Cox proportional hazards regression. All analyses were conducted in R version 4.4.0. Results: The cohort comprised 213 females (60.9%) and 137 males (39.1%), with a median age of 39 and 36 years, respectively. The median primary diagnostic delay was 76.0 days (IQR: 38.0, 182.8), with patient delay accounting for a median of 26.5 days and system/testing delay for 21.0 days. Overall, 155 patients (44.3%) experienced a diagnostic delay of more than 90 days. In the multivariable Cox model, urban residence (aHR = 0.69, 95% CI [0.53, 0.99], p = 0.045) was independently associated with a slower rate of diagnostic confirmation. Conclusions: Diagnostic delay in IDA is substantial in Egypt, driven by both patient-level symptom normalization and counterintuitive systemic bottlenecks. Urban residence was independently associated with prolonged time to diagnostic confirmation; ordering of iron studies at the first visit was associated with delay in bivariate analysis only and was not an independent predictor after multivariable adjustment. Targeted public health education, restructured primary care pathways, and improved laboratory turnaround times are essential to reduce this burden.
- 14 July 2026
- Published by MDPI AG in Healthcare
- Vol. 14 (14) , 2112
Open AccessFactors Associated with Delayed Diagnosis of Iron Deficiency Anemia in Egyptian Patients: A Retrospective Cohort Study
Background/Objectives: Iron deficiency anemia (IDA) remains the most prevalent nutritional deficiency worldwide and a leading cause of years lived with disability, particularly in low-income countries. In Egypt, the burden is substantial and compounded by regional socioeconomic, nutritional, and parasitic factors. Despite this, the predictors of diagnostic delay within the Egyptian healthcare system remain poorly characterized. This study aimed to quantify the extent of diagnostic delay among Egyptian patients with IDA and to identify the sociodemographic and clinical risk factors independently associated with prolonged time to diagnostic confirmation. Methods: A single-center retrospective cohort study was conducted at Al-Minia University Hospital, Egypt, between March and April 2026, enrolling 350 adults with confirmed IDA diagnosed between 2015 and 2025. “Diagnostic delay” was defined as the interval in days from the index date (the first documented abnormal complete blood count) to laboratory confirmation of iron deficiency by serum ferritin and/or transferrin saturation. Secondary outcomes included patient delay, system/testing delay, and etiology work-up delay. Time-to-event analysis was performed using Kaplan–Meier curves and Cox proportional hazards regression. All analyses were conducted in R version 4.4.0. Results: The cohort comprised 213 females (60.9%) and 137 males (39.1%), with a median age of 39 and 36 years, respectively. The median primary diagnostic delay was 76.0 days (IQR: 38.0, 182.8), with patient delay accounting for a median of 26.5 days and system/testing delay for 21.0 days. Overall, 155 patients (44.3%) experienced a diagnostic delay of more than 90 days. In the multivariable Cox model, urban residence (aHR = 0.69, 95% CI [0.53, 0.99], p = 0.045) was independently associated with a slower rate of diagnostic confirmation. Conclusions: Diagnostic delay in IDA is substantial in Egypt, driven by both patient-level symptom normalization and counterintuitive systemic bottlenecks. Urban residence was independently associated with prolonged time to diagnostic confirmation; ordering of iron studies at the first visit was associated with delay in bivariate analysis only and was not an independent predictor after multivariable adjustment. Targeted public health education, restructured primary care pathways, and improved laboratory turnaround times are essential to reduce this burden.