Mustafa H. Khazali

Dr. Mustafa H. Khazali

orcid

Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 September 2026 in Antimicrobial Resistance & Infection Control
Verified
Journal Article
Open access
PDF file
MKMustafa H. Khazali
Mustafa H. Khazali
AGAbdullah Ghrabat
Abdullah Ghrabat
ASAli Soukia
Ali Soukia
OMObada Muayaid
Obada Muayaid
MKMalik Khattab
Malik Khattab
MKMostafa Khalifa A. Khalifa
Mostafa Khalifa A. Khalifa
Gut colonization by multidrug-resistant organisms (MDROs) is an important reservoir for subsequent infection and transmission. Fecal microbiota transplanta

20 February 2026 in SSRN Electronic Journal
Verified
Preprint
Open access
MAMohammed Ali Qasem Al-Soufi
Mohammed Ali Qasem Al-Soufi
AHAbdulmajeed Khalid Hassan
Abdulmajeed Khalid Hassan
SHSohaib Hadi
Sohaib Hadi
BABelal Issa Abufara
Belal Issa Abufara
MAMohammed Saleh Al-Maghriby
Mohammed Saleh Al-Maghriby
MSMohamed Sakr
Mohamed Sakr
Background: The COVID-19 pandemic accelerated adoption of telemedicine and digital decision systems, including artificial intelligence (AI), in primary care. However, quantitative evidence on the clinical effectiveness of AI-integrated telemedicine across outcome domains remains fragmented. We conducted a systematic review and meta-analysis to evaluate the effectiveness of AI-supported telemedicine and hybrid care models in primary care settings after the onset of the pandemic.Methods: We performed a systematic review and meta-analysis in accordance with PRISMA 2020 guidance. PubMed and Scopus were searched for studies published from March 2020 onward evaluating AI-supported telemedicine interventions in primary care or closely related front-line care settings. Two reviewers independently screened studies and extracted data. Risk of bias was assessed using RoB 2. Random-effects meta-analysis was applied using harmonized effect measures. Heterogeneity was quantified using I² and Tau². Prespecified subgroup analyses and meta-regression were conducted to explore variability. Publication bias was evaluated using Egger’s test and Trim-and-Fill methods.Findings: Of 146 eligible studies, 82 provided extractable quantitative effect estimates. The pooled standardized effect suggested an overall positive association between AI-integrated telemedicine and primary care outcomes (10·31, 95% CI 4·86–15·77), although between-study heterogeneity was very high (I²≈100%). Subgroup analyses showed larger effects in broader clinical outcome domains and more modest effects in mental health, infectious disease, and clinical control outcomes. Meta-regression did not identify study year, specialty, or design as significant moderators. Egger’s test indicated possible small-study effects, whereas Trim-and- Fill adjustment did not materially change pooled estimates.Interpretation: AI-supported telemedicine interventions are associated with improved outcomes across multiple primary care domains, although effect magnitude varies by context and outcome type. Very high heterogeneity limits interpretation of a single pooled estimate and supports outcome-specific interpretation. Further standardized and domain-focused studies are needed to refine effectiveness estimates and guide implementation.

23 September 2026 in BMC Neurology
Verified
Journal Article
Open access
PDF file
MKMostafa Khalifa A. Khalifa
Mostafa Khalifa A. Khalifa
DHDiaaeldin Hassanein
Diaaeldin Hassanein
AAAbd Alrahman I. Alsabbagh
Abd Alrahman I. Alsabbagh
AGAhmed Samir Gamil
Ahmed Samir Gamil
DADarin Emad Abdelhaleem
Darin Emad Abdelhaleem
MKMustafa H. Khazali
Mustafa H. Khazali
Background: Psychosocial stress has been recognized as a potential risk factor for stroke; however, the strength and consistency of its association with first-ever stroke remain uncertain. This systematic review and meta-analysis aimed to determine the overall association between psychosocial stress and the risk of first stroke in a stroke-free population. Methods: We conducted a systematic review and meta-analysis in accordance with the PRISMA and MOOSE guidelines. PubMed, Scopus, Web of Science, and Ovid were searched from inception to 1 January 2026 for cohort or case–control studies. Eligible studies enrolled participants without a prior history of stroke and reported adjusted risk estimates with 95% confidence intervals. Psychosocial stressors were categorized into psychological, vocational, interpersonal, and behavioral domains. Stroke outcomes included ischemic stroke, hemorrhagic stroke, subarachnoid hemorrhage, transient ischemic attack, and unspecified stroke. Results: Eighty-four studies were included (72 prospective cohort and 12 case–control), comprising 4,128,167 participants. In cohort studies, psychological stress was associated with a higher risk of first-ever stroke (hazard ratio [HR] 1.27, 95% confidence interval 1.19–1.36). Vocational stressors were also associated with increased stroke risk (HR 1.32, 95% CI 1.23–1.43). Interpersonal stressors showed a smaller but statistically significant association (HR 1.11, 95% CI 1.03–1.20). Behavioral stress-related traits showed the largest effect estimate (HR 1.51, 95% CI 1.05–2.15), although this finding should be interpreted cautiously because it was based on only three cohort studies. In sex-stratified analyses, the association was significant among men (HR 1.19, 95% CI 1.07–1.32) but not among women (HR 0.86, 95% CI 0.58–1.28); however, the subgroup interaction was not statistically significant and should be interpreted as inconclusive rather than evidence of a definite sex-specific difference. Conclusion: Psychosocial stress is associated with an increased risk of first-ever stroke, particularly psychological and vocational stressors, supporting psychosocial factors as potentially modifiable components of stroke prevention.