Search Results (1,794)

Saudi Arabia is expanding its domestic coffee sector under Vision 2030, yet coffee farming remains vulnerable to leaf diseases and pest damage. Image-based artificial intelligence studies conducted under Saudi field conditions remain limited, particularly in relation to assessing image-based visible disease severity. This study designs a hierarchical deep learning framework for screening coffee leaf diseases using field-collected images of Saudi coffee leaves. Three tasks were addressed: binary health status classification, four-class disease or pest damage identification, and binary visible severity classification. A dataset of 550 RGB images was collected from Al-Dayer Governorate, Jazan, under natural field conditions. ResNet50, DenseNet121, and EfficientNet-B0 were evaluated via transfer learning in two phases: a Saudi-only phase and an integrated phase that combined Saudi data with selected JMuBEN and JMuBEN2 samples. In the Saudi-only phase, ResNet50 achieved 96.47% accuracy for binary classification, while DenseNet121 achieved 68.66% and 78.12% for disease and visible severity classification, respectively. In the integrated phase, performance improved to 99.74%, 97.76%, and 97.37%. These integrated-phase results are interpreted as evidence that dataset expansion and increased visual diversity can improve model performance, rather than as definitive estimates of field deployment performance. The results show that binary classification is feasible under limited local data, whereas fine-grained disease classification is more constrained by dataset size and class imbalance. Grad-CAM visualizations were used to support qualitative interpretability and should not be interpreted as biological validation of disease localization. The framework is positioned as a decision-support screening approach that requires further expert-validated, multi-farm, and multi-season evaluation before deployment. Full article

Advanced diffusion MRI techniques, particularly intravoxel incoherent motion (IVIM) and diffusion tensor imaging (DTI), have emerged as promising functional imaging tools for improving cervical cancer assessment beyond conventional anatomical MRI. This narrative review summarizes current evidence on the clinical utility of these diffusion-based techniques for tumor characterization, local staging, parametrial invasion, lymph node evaluation, treatment response monitoring, and emerging radiomics applications. Across studies, diffusion-related parameters, especially the apparent diffusion coefficient (ADC) and pure molecular diffusion coefficient (D), tend to be lower in malignant cervical tissues and correlate with increased cellularity, higher tumor grade, and more aggressive disease features. IVIM metrics appear especially useful for differentiating cervical cancer from normal tissue, predicting pelvic lymph node involvement, and detecting early treatment response to chemoradiotherapy or neoadjuvant chemotherapy before substantial morphological regression occurs. In contrast, DTI remains less extensively investigated; however, preliminary findings suggest potential value for evaluating parametrial invasion, stromal disruption, tumor grade, and lymph node metastasis, particularly when integrated with IVIM-derived indices. Although diffusion-derived radiomics may further support risk stratification and treatment-response prediction, the evidence base remains limited by small cohorts, single-center designs, methodological heterogeneity, and insufficient external validation. Overall, IVIM and DTI provide valuable non-invasive insight into cervical cancer biology, but standardized acquisition protocols, reproducible thresholds, and multicenter validation are needed before routine clinical implementation. Full article

This study examined Saudi adolescents’ digital use, experiences of cyberbullying, and willingness to seek help when facing online risks. Furthermore, the study examined how perceived online safety, preferred reporting sources, exposure to online safety education, and demographic characteristics are associated with resistance to help-seeking. A cross-sectional online survey was completed by 302 adolescents aged 11–17 years across Saudi Arabia. Descriptive statistics, one-way ANOVAs, and hierarchical multiple regression were used to explore patterns and predictors of resistance to help-seeking. Descriptively, the results showed near-universal smartphone access, high daily screen time, and that a substantial minority had experienced recent cyberbullying, including repeated victimization. Although most participants reported feeling safe online, many expressed uncertainty and endorsed self-reliant or avoidant responses, with over half agreeing they would “just ignore” cyberbullying. Parents were the most frequently identified reporting source, yet around one-fifth of adolescents said that they would not seek help from anyone. Regression analyses indicated that female gender, higher socioeconomic status, feeling less safe online, and receiving online safety education from multiple sources were associated with lower resistance to help-seeking, whereas greater cyberbullying exposure predicted higher resistance. Overall, the results highlight the need for multi-source, culturally grounded online safety education and strengthened reporting pathways across families, schools, and digital platforms to support Saudi adolescents who experience cyberbullying and related online harms. Full article

Arboviral diseases are emerging as important public health threats in Saudi Arabia, driven by rapid urbanization, climate variability, the expansion of Aedes aegypti populations, international travel, and large-scale religious mass gatherings. Dengue virus remains the most established arboviral infection in the Kingdom, particularly in the southwestern regions such as Jazan and the western urban centers of Makkah and Jeddah, where ecological and climatic conditions are conducive to sustained vector survival and transmission. This review synthesizes current evidence on the epidemiology, vector ecology, climatic determinants, diagnostics, and prevention strategies of arboviral diseases in Saudi Arabia. Particular attention is paid to the impacts of rising temperatures, changes in rainfall patterns, urban heat island effects, population mobility, and cross-border movement on vector expansion and disease emergence. The review also identifies gaps in surveillance, diagnostics, insecticide resistance monitoring, and integrated vector management programs. Emerging preparedness strategies include climate-informed early warning systems, Geographic Information System-based risk mapping, multiplex molecular diagnostics, genomic surveillance, and community-based vector control. The review emphasizes the importance of implementing a One Health approach that combines data on humans, the environment, entomology, and climate. Currently, sustained endemic transmission of chikungunya and Zika viruses has not been conclusively demonstrated in Saudi Arabia, but increased environmental suitability and connectivity with other areas highlight the need for proactive surveillance and preparedness. Full article

Background: Therapeutic resistance following cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) plus endocrine therapy (ET) represents a key unmet need in hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR+/HER2−) metastatic breast cancer (mBC). Treatment paradigms have advanced from non-targeted options, such as fulvestrant monotherapy or everolimus-based combinations, to precision medicine strategies, including inhibitors of the PI3K/AKT pathway, oral selective estrogen receptor degraders (SERDs), and novel ER-modulating agents, often guided by biomarkers and molecular surveillance. Methods: This narrative review synthesizes evidence from randomized clinical trials, real-world studies, and biomarker-driven analyses published from 2010 to 2026, with emphasis on next-generation sequencing (NGS)-guided genomic profiling, targeted pathway therapies, and circulating tumor DNA (ctDNA)-based proactive interventions in the post-CDK4/6i setting. This review was conducted and reported in accordance with the SANRA recommendations for narrative reviews. Results: Early second-line standards, including fulvestrant and alpelisib for PIK3CA-mutated tumors, established the basis for biomarker-guided treatment in hormone receptor–positive, HER2-negative metastatic breast cancer. With the widespread use of CDK4/6 inhibitors in the first-line setting, the optimal post-progression strategy has shifted toward molecularly selected combination approaches rather than single-agent endocrine therapy, as endocrine monotherapy has shown limited efficacy in acquired resistance. Multiple randomized studies have demonstrated that adding targeted agents to endocrine therapy improves progression-free survival compared with hormonal therapy alone, supporting combination regimens as the preferred strategy after CDK4/6 inhibitor progression, except in carefully selected patients with low disease burden, indolent biology, or frailty where tolerability is a major concern. Precision-based trials have further refined this approach. Elacestrant improved progression-free survival in ESR1-mutated disease in the EMERALD trial, capivasertib plus fulvestrant demonstrated significant benefit in tumors harboring AKT/PIK3CA/PTEN pathway alterations in CAPItello-291, and inavolisib plus palbociclib and fulvestrant achieved both progression-free and overall survival improvement in PIK3CA-mutated patients with early relapse in INAVO120. Real-world analyses further support the effectiveness of these biomarker-directed strategies across diverse clinical subgroups. Comprehensive genomic profiling has identified multiple resistance mechanisms, including ESR1 mutations, PI3K/AKT/mTOR pathway activation, RB1 loss, and FGFR alterations, which may co-occur and reduce sensitivity to endocrine monotherapy. While ESR1 and PI3K pathway alterations now guide approved therapies, FGFR alterations remain investigational targets, with ongoing trials evaluating selective FGFR inhibitors. Proactive switching approaches evaluated in SERENA-6 and PADA-1 demonstrate that serial circulating tumor DNA (ctDNA) monitoring can detect emergent ESR1 mutations before radiographic progression, providing a clinically actionable lead time for early therapeutic modification and extending endocrine-based disease control by approximately 5 to 7 months. Conclusions: Post-CDK4/6i management increasingly relies on NGS-guided precision approaches, integrating pathway-specific therapies and ctDNA surveillance to tailor sequencing based on resistance profiles, prior ET response, and tumor heterogeneity. Future investigations into novel ER degraders and multi-targeted combinations hold potential to further optimize algorithms, extend non-chemotherapy options, and enhance survival in HR+/HER2− mBC. Full article

Purpose: Variation in knee MRI diagnostic yield is often interpreted as reflecting imaging effectiveness. However, in real-world healthcare systems, diagnostic yield may instead be driven by referral behavior and patient selection. Understanding this distinction is essential for evaluating imaging utilization, healthcare efficiency, and potential overuse of advanced imaging. This study examines whether differences in MRI yield reflect imaging pathways or underlying referral patterns in routine clinical practice. Materials and Methods: This retrospective cohort study included consecutive patients undergoing knee MRI between January 2020 and December 2024. Patients with red flag indications were excluded to focus on discretionary imaging. The primary outcome was clinically relevant MRI findings based on final report impressions. The primary exposure was prior X-ray before MRI. Multivariable logistic regression was used for adjusted analysis, including age, sex, trauma status, mechanical symptoms, and symptom duration. Results: Among 486 patients, 59.5% had prior X-ray. Clinically relevant MRI findings were less frequent among patients with prior X-ray (40.1%) than among those without (49.7%), corresponding to an absolute difference of 9.6%. After adjustment for sex and clinical covariates, prior X-ray showed lower odds of clinically relevant findings, although this association was attenuated and no longer statistically significant (aOR 0.74, 95% CI 0.50–1.10; p = 0.138). Male sex was independently associated with higher odds of clinically relevant MRI findings (aOR 2.48, 95% CI 1.61–3.83; p < 0.001). Formal interaction testing did not demonstrate significant effect modification by trauma status (p = 0.317). These findings suggest that variation in MRI yield may reflect differences in referral pathways, patient selection, and healthcare utilization patterns. Conclusions: MRI yield in routine practice may be influenced by differences in clinical context and referral-related patient selection. Further studies are needed to better understand the contribution of imaging pathways to observed variation in diagnostic yield. Full article

Large language models (LLMs) have been widely adopted in educational settings, particularly among university students. However, the behavioral mechanisms through which these systems influence academic outcomes remain insufficiently understood. This study develops and empirically tests a framework explaining how the technological attributes of LLMs—perceived usefulness, ease of use, system reliability, accessibility, and interface design—affect student motivation and personalization, which foster anthropomorphic perception and enhance self-efficacy and academic performance. Data were collected from university students in Saudi Arabia using a structured survey and analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that technological attributes positively influence motivation and personalization, which strengthen anthropomorphism and subsequently improve self-efficacy and academic performance. The results provide practical insights into the effective application of LLMs in higher education and highlight the role of generative AI in supporting sustainable educational practices. Full article

Background/Objectives: Systematic assessment of orthodontic treatment needs is essential for prioritizing care in public health programs. The Dental Aesthetic Index (DAI) provides a composite severity score; however, understanding which individual occlusal traits drive severe treatment needs has a practical screening value. This study aimed to determine which occlusal features, categorized using established clinical thresholds, independently associated with severe orthodontic treatment need. Methods: Pretreatment records of 292 patients (141 men, 151 women; aged 13–42 years) were analyzed. The outcome was severe treatment need (DAI ≥ 31). Ten DAI components were categorized using IOTN-DHC severity cutpoints; Angle and skeletal classifications were also assessed. Candidate predictors (p < 0.20) were entered into multivariate logistic regression with backward elimination. Discrimination was assessed by ROC analysis; internal validation used bootstrap resampling and cross-validation. Results: Of the 292 patients, 141 (48.3%) had severe treatment needs. Six occlusal features were independently associated with severe treatment need (all p < 0.001): overjet severity (adjusted odds ratio [OR] = 412.4; 95% confidence interval [CI]: 82.1–2072.1), missing anterior teeth (OR = 29.3; 95% CI: 8.6–99.5), open bite severity (OR = 13.4; 95% CI: 4.6–39.5), diastema (OR = 7.4; 95% CI: 2.4–22.5), molar cusp relationship (OR = 4.7; 95% CI: 2.3–9.5), and anterior spacing (OR = 2.9; 95% CI: 1.5–5.4). The area under the ROC curve was 0.971 (optimism-corrected: 0.968), and 90.8% of the patients were correctly classified by the final model (sensitivity, 89.4%; specificity, 92.1%). Angle classification, skeletal classification, sex, age, and crowding were not included in the final model. Conclusions: Six clinically categorized occlusal features assessed by visual inspection were independently associated with severe orthodontic treatment need in this explanatory analysis, with overjet severity as the dominant determinant. Categorical severity grades based on established clinical thresholds retained strong discriminative information (optimism-corrected AUC = 0.968), suggesting that simplified assessments may be sufficient for the initial screening. Dental and skeletal classifications did not provide an independent predictive value beyond that of occlusal features. External validation is needed before clinical implementation. Full article

The inverse problem under consideration concerns a one-dimensional parabolic equation whose thermal diffusivity takes the quadratic-in-space form $a_s\left(\tau \right){\kappa }^2+b_s\left(\tau \right)\kappa +c_s\left(\tau \right)$. The unknowns are three time-dependent coefficients $a_s\left(\tau \right),b_s\left(\tau \right),c_s\left(\tau \right)$ together with the temperature field $T(\kappa ,\tau )$. The direct problem supplies initial data, Neumann boundary conditions, and three over-determination conditions: two boundary temperatures and the spatial integral of T. We prove two theorems. The first theorem establishes the local-in-time existence of a solution under explicit regularity and sign conditions on the given data $\xi ,{\nu }_k,{\delta }_{\ell },\theta$ and compatibility at $\tau =0$. The second theorem guarantees the uniqueness of this solution. Despite uniqueness, the inverse reconstruction remains ill-posed: small perturbations in the over-specified data can cause large deviations in the recovered coefficients. For the forward model, we implement two numerical schemes: (i) a Crank–Nicolson finite difference methodology (CN-FDM) on a uniform grid and (ii) a semi-discretized Crank–Nicolson approach combined with Bell spectral collocation in space (CN–Bell). The inverse step minimizes a Tikhonov-regularized least-squares functional using MATLAB’s (R2026a) lsqnonlin. Two numerical examples (smooth and non-smooth), tested with both exact synthetic data and artificially added noise, demonstrate stable and accurate coefficient reconstructions. The framework applies directly to heat conduction and porous media flow where diffusivity varies quadratically in space. Full article

Background: Hepatitis B virus (HBV) infection poses a persistent global public health challenge, with substantial associated morbidity, mortality, and healthcare utilization. Although Saudi Arabia has maintained a national HBV vaccination program for decades, population-level data on hepatitis B infection knowledge, attitudes, and practices (KAP) remain scarce and regionally limited. This study aimed to comprehensively assess KAP toward hepatitis B infection prevention among the general adult population across all regions of Saudi Arabia and to identify independent sociodemographic predictors of each domain to inform targeted healthcare interventions. Methods: This nationwide cross-sectional study used a convenience sampling approach and a validated, self-administered questionnaire disseminated via online social media platforms across all regions of Saudi Arabia between August 2024 and February 2025. KAP was assessed using an instrument adapted from Haq et al. (Cronbach’s α = 0.70). Good knowledge was defined as a score ≥11/20 (≥55%), positive attitude as ≥5/7 (≥71.4%), and good practice as ≥6/8 (≥75%). Multivariable linear regression was used to identify independent predictors, adjusting for sociodemographic covariates. Results: A total of 1278 participants were included (mean age 30.3 ± 12.4 years; 60.9% female). Overall, 54.2% demonstrated good knowledge, 68.5% demonstrated positive attitudes, and only 16.2% exhibited good preventive practices. Screening (14.6%) and vaccination uptake (26.5%) were markedly low. Educational program participation was the strongest modifiable predictor across all three domains: knowledge (β = +1.89, 95% CI: 1.20–2.58, p < 0.001), attitude (β = +0.47, 95% CI: 0.25–0.69, p < 0.001), and practice (β = +1.43, 95% CI: 1.09–1.77, p < 0.001). Healthcare sector employment was independently associated with higher KAP scores across all domains. Income demonstrated a positive dose–response relationship with knowledge and practice outcomes. Polygyny was associated with lower scores across all three domains. Conclusions: Despite moderate knowledge and generally favorable attitudes, preventive practices remain critically deficient, revealing a persistent knowledge–practice gap. Integrated, behavior-oriented interventions targeting modifiable determinants, particularly health education, income disparities, and stigma, are urgently needed to support progress toward national and global HBV elimination targets. Full article

Agricultural waste materials can serve as functional constituents in cement-based composites through three pathways: (i) organic bio-aggregates that lower density and alter thermal behavior, (ii) lignocellulosic fibers that control cracking and improve post-cracking resistance, and (iii) agro-ash supplementary cementitious materials (SCMs) that densify pore structure and reduce permeability when ash quality and curing are controlled. This review draws on 98 papers, with coconut shell aggregate and coir/coconut fibers as the core focus; agro-ash SCMs (notably palm oil fuel ash, POFA, and rice husk ash, RHA) enter where they clarify mechanisms or inform hybrid design. Rather than cataloging compressive-strength data, the synthesis is organized around controllable process inputs (feedstock conditioning, mix design, curing) and the interface-governed mechanisms that determine performance: interfacial transition zone (ITZ) character and pore connectivity. In coconut shell systems, density reductions come at a cost: elastic modulus drops and moisture sensitivity rises unless shell conditioning, particle packing, and matrix refinement are managed. In fiber systems, gains in toughness and residual capacity are bounded by mixing workability and by the long-term stability of the fiber–matrix bond under alkaline and wet–dry exposure. A mix must first meet strength, serviceability, and transport requirements before its embodied impact is compared with conventional alternatives. The contribution is to reframe these systems around controllable processing and interface mechanisms instead of tabulated strength values; preparation, treatment, and characterization data are consolidated into bounded design windows, an explicit core versus supporting evidence convention is applied, and sustainability is judged under functional equivalency rather than per-volume carbon. Full article

Background: Adopting a healthy lifestyle through a balanced diet and regular physical activity is essential for chronic disease prevention, but healthcare workers face occupational constraints that may limit such behaviors. This study assessed perceived capability for healthy diet and physical activity among healthcare workers in the Jazan region of Saudi Arabia using the Capability Assessment for Diet and Activity (CADA) instrument and examined associated factors. Methods: A cross-sectional analytical study was conducted in 2026 in governmental healthcare facilities in the Jazan Health Cluster. A structured electronic questionnaire collected sociodemographic, occupational, and health-related data alongside the 34-item CADA. Total, Diet and Physical Activity CADA scores (1–5) were analyzed using descriptive statistics and multivariable ordinary least squares regression adjusted for sex, education, profession, and workplace; standardized coefficients and Cohen’s f² were reported. Results: A total of 601 healthcare workers participated. Internal consistency was good (Cronbach’s α = 0.84 for the full scale). Mean Total CADA was 3.28 ± 0.80 (scale midpoint 3.0); perceived Diet capability (3.45 ± 0.85) was higher than perceived Physical Activity capability (3.11 ± 0.85). Female sex was independently associated with lower Physical Activity CADA (β = −0.16; 95% CI −0.32 to −0.01; p = 0.042). Bachelor’s and board/doctoral qualifications were associated with higher Total CADA (β = 0.20; 95% CI 0.02 to 0.38; p = 0.026 and β = 0.33; 95% CI 0.07 to 0.58; p = 0.013, respectively). Compared with hospital-based participants, those in primary healthcare centers had lower Total (β = −0.19; 95% CI −0.32 to −0.05; p = 0.007), Diet (β = −0.17; 95% CI −0.31 to −0.02; p = 0.024) and Physical Activity (β = −0.21; 95% CI −0.35 to −0.06; p = 0.006) CADA scores. Effect sizes were small (|β*| ≤ 0.16; R² = 0.076–0.082; Cohen’s f² = 0.08–0.09). Conclusions: As CADA captures perceived capability, these findings reflect self-perception rather than objectively measured behavior; longitudinal studies combining CADA with validated behavioral instruments are warranted to clarify whether perceived capability translates into actual dietary and physical-activity behaviors in healthcare workers, and to evaluate whether workplace-based interventions targeting time pressure and access to supportive environments improve both perceived capability and measured behavior. Full article

Background/Objectives: Arsenic (ARS) exposure is a major cause of kidney injury, driven by oxidative stress, inflammation, fibrosis, and apoptosis. This study evaluated the renoprotective effects of morin (MOR) and morin-loaded PLGA nanoparticles (MOR–PGNPs) against ARS-induced nephrotoxicity in rats. Methods: Sixty male Sprague Dawley rats were randomly allocated into six groups (n = 10 per group). The control group received corn oil. The MOR group received MOR (100 mg/kg), and the MOR–PGNPs group received the same dose of MOR encapsulated in PLGA nanoparticles. ARS was administered at 10 mg/kg for 14 days. Co-treated groups received ARS together with either MOR or MOR–PGNPs, with a 28 min interval between administrations. Renal function markers (serum urea, creatinine, uric acid, renal KIM-1), oxidative stress and antioxidant parameters (Nrf2/HO-1, CAT, SOD, GPx, ROS, MDA), inflammatory mediators (TLR4/NF-κB, TNF-α, IL-6, IL-1β), fibrotic markers (TGF-β1, fibronectin), and apoptotic proteins (caspase-3, caspase-8, Bax, Bcl-2) were assessed, alongside histopathological and ultrastructural evaluations. Results: ARS exposure significantly impaired renal function, increased KIM-1, suppressed Nrf2/HO-1 signaling, reduced antioxidant enzyme activities, and elevated ROS and MDA levels. It also activated TLR4/NF-κB signaling, upregulated pro-inflammatory cytokines and fibrotic markers, and increased pro-apoptotic proteins while downregulating Bcl-2. MOR co-treatment partially ameliorated these alterations. MOR–PGNPs produced potentially enhanced protection, restoring kidney function markers, enhancing antioxidant defenses, and markedly attenuating inflammation, fibrosis, and apoptosis. Histopathological and ultrastructural analyses confirmed preservation of glomerular and tubular architecture, mitochondrial integrity, and minimal cytoplasmic vacuolization in the MOR–PGNPs group. Conclusions: MOR–PGNPs at 100 mg/kg effectively mitigated ARS-induced renal damage through antioxidant, anti-inflammatory, antifibrotic, and anti-apoptotic mechanisms, supporting PLGA-based morin nanoparticles as a promising and safe renoprotective strategy. Full article

Phenformin, a representative of the biguanides class was previously used for treatment of type 2 diabetes and discontinued due to a risk of causing lactic acidosis, has shown promising anticancer activity in numerous studies. Since many types of cancer arise and proliferate due to dysregulation in apoptotic or autophagic pathways, this study aimed to assess the underlying anticancer effects of phenformin in terms of these two processes. We initially set out to examine the antiproliferative effects of phenformin on multiple cancer cell lines including breast, pancreatic, cervical cancers, hepatocellular carcinoma and malignant melanoma. Subsequently, the expression of apoptosis and autophagy related proteins was measured in the cervical cancer cell lines found to be the most susceptible to antiproliferative effects of phenformin. Additionally, the ability of phenformin to potentiate the antitumor effect of resveratrol and vistusertib was assessed. Phenformin increased the expression of pro-apoptotic factor, Bax, and lowered the level of anti-apoptotic protein, Bcl-2. Hence, it was proposed that phenformin promotes antiproliferative activity by inducing apoptosis. Our findings demonstrate that phenformin decreases the proliferation of various cancer cell lines in a dose-dependent manner and may have an ability to increase the autophagic flux in cervical cancer cells. Our findings demonstrate that phenformin decreases the proliferation of various cancer cell lines in a dose-dependent manner potentially by inducing apoptosis. Full article

Background/Objectives: Patients undergoing metabolic and bariatric surgery (MBS) are at risk of micronutrient deficiencies and gut dysbiosis. Probiotics (such as Lactobacillus, Bifidobacterium) have been proposed as adjunct therapy to optimize postoperative outcomes. This review aimed to evaluate the effect of postoperative probiotic supplementation on anthropometric, metabolic, inflammatory, and micronutrient outcomes in MBS patients. Methods: Nine electronic databases were systematically searched, including PubMed, Web of Science, Cochrane Library, Google Scholar, Popline, Global Health Library, Virtual Health Library, New York Academy of Medicine, and OpenGrey, from inception through October 2024. Only randomized controlled trials (RCTs) were included. The Cochrane Collaboration risk-off-bias tool was used for quality assessment. Meta-analyses were performed using Comprehensive Meta-Analysis software version 2. Fixed-effects or random-effects models based on heterogeneity (I² threshold: 50%) were applied. Mean differences (MD) and 95% confidence intervals (CI) were calculated for all continuous variables. Results: Thirteen RCTs encompassing 666 patients (probiotics group: n = 344; control group: n = 322) were included. Incomplete outcome data represented the most prevalent high-risk domain (23%). Probiotic supplementation was associated with significantly improved serum vitamin D (MD: 25.32 nmol/L, 95% CI: 6.96–43.67, p = 0.007) and vitamin B12 levels (MD: 39.36 pg/mL, 95% CI: 1.88–76.84, p = 0.04). No statistically significant differences were observed in anthropometric outcomes (%EWL, BMI, weight, or waist circumference), lipid profile, glycemic indices, or inflammatory markers (TNF-α, IL-6, CRP). Conclusions: Postoperative probiotic supplementation may significantly improve vitamin D and B12 levels in patients undergoing MBS, suggesting a supportive role in mitigating micronutrient deficiencies. However, these findings should be interpreted with caution due to substantial heterogeneity across studies. Probiotics did not significantly affect weight loss, metabolic parameters, or inflammatory markers. Clinicians may consider probiotics as an adjunct strategy to support micronutrient status in at-risk postoperative patients. Large-scale, strain-specific trials incorporating standardized dietary control and microbiome profiling are warranted. Full article