Medicine and Pharmacology

Abstract: Background/Objectives: Pressure ulcers remain a significant clinical problem in palliative care. Identifying risk factors can support early intervention and prevention strategies. This study aimed to calculate the prevalence of pressure ulcers among palliative care patients, evaluate associated risk factors, enhance patients’ quality of life and care, and contribute significantly to the literature. Methods: This retrospective, descriptive, and correlational study was conducted between April 1, 2018, and November 30, 2023. Among 1,942 patients hospitalized in the Palliative Care Unit of Tokat Gaziosmanpaşa University Hospital, the medical records of 279 patients with pressure ulcers were retrospectively reviewed. The collected data included patients’ demographic characteristics, pressure ulcer risk factors, and Braden Pressure Ulcer Risk Assessment Scale scores. Results: The incidence of pressure ulcers was found to be 14.36%. Of the patients with pressure ulcers, 217 (77.8%) had pressure ulcers at the time of admission to the unit, while 62 (22.2%) developed pressure ulcers during hospitalization. The evaluated risk factors (age, use of medical devices and invasive procedures, type of nutrition, urinary and fecal elimination status, comorbidity status, mobility status, level of consciousness, and primary diagnosis) were found to be significantly associated with pressure ulcer development. Conclusion: In line with the data and results obtained, our hypothesis— “As a patient’s immobility increases, risk factors increase; consequently, the Braden Pressure Ulcer Risk Assessment Scale score decreases, and the likelihood of pressure ulcer development increases”—was supported. It is believed that this study will contribute to and guide researchers, healthcare professionals, and administrators interested in the field of palliative care.

Abstract: Respiratory syncytial virus (RSV) is a leading cause of severe respiratory infections in infants and young children globally. The severity of RSV-associated diseases is often ascribed to a dysregulated immune response, characterized by increased secretion of proinflammatory proteins and ineffective T helper type 2 (Th2) cells activity. The host’s primary defense against RSV relies on a well-coordinated innate immune response initiated by resident airway epithelial cells, the first target of RSV infection. These cells respond to viral invasion by generating reactive oxygen species (ROS), activating the production of Type I and III interferons, and releasing proinflammatory cytokines and chemokines. Moderate levels of ROS act as key molecules that regulate antiviral signaling, enhancing the host’s ability to recognize and eliminate invading pathogens. However, severe RSV infection disrupts cellular homeostasis triggering excessive ROS production, while simultaneously weakening the host's antioxidant defenses. This redox imbalance subverts the activity of key cellular defensive mechanisms, ultimately increasing viral replication, and worsening RSV infection severity. Modulation of oxidative stress may offer an innovative approach in managing the progression and outcome of RSV infection.

Abstract: Background: Accurate preoperative localization of hyperfunctioning parathyroid glands is essential for minimally invasive surgery in primary hyperparathyroidism (PHPT). Although dual-phase 99mTc-MIBI planar scintigraphy is widely used, its diagnostic performance may be limited in small or ectopic lesions. Hybrid SPECT/CT imaging combines functional and anatomical information and may improve localization accuracy. The aim of this study is to evaluate the diagnostic contribution of SPECT/CT to dual-phase 99mTc-MIBI planar scintigraphy for preoperative localization in patients with PHPT. Methods: This retrospective study included 128 patients with biochemically confirmed PHPT who underwent dual-phase 99mTc-MIBI planar scintigraphy followed by delayed-phase SPECT/CT imaging before parathyroidectomy between January 2020 and May 2024. Imaging findings were compared with postoperative histopathological results. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated. The effects of lesion size, biochemical parameters, and ultrasonographic findings on imaging performance were also evaluated. Results: Histopathology confirmed parathyroid lesions in 122 of 128 patients (95.3%). The sensitivity, specificity, PPV, NPV, and accuracy of planar imaging were 57.4%, 66.7%, 97.2%, 7.1%, and 57.8%, respectively, whereas those of SPECT/CT were 92.6%, 66.7%, 98.3%, 30.8%, and 91.4%, respectively. SPECT/CT findings showed significant concordance with histopathology (p=0.001), while planar imaging did not (p=0.247). Among lesions smaller than 1 cm, sensitivities were 37.1% for planar imaging and 91.4% for SPECT/CT. SPECT/CT also provided superior anatomical localization, particularly in ectopic lesions and in patients with concomitant thyroid pathology. Conclusion: SPECT/CT demonstrated substantially higher diagnostic performance than dual-phase planar scintigraphy for preoperative localization in PHPT. Its incremental value was particularly evident in subcentimeter lesions, ectopic parathyroid adenomas, and patients with coexisting thyroid disease.

Abstract: The application of Large Language Models (LLMs) in the medical field signifies a revolutionary shift in medical informatics and patient care. LLMs trained on vast and specialized medical corpora bring precision and efficiency to medical diagnostics, treatment planning, and service delivery. This paper outlines the essential methodologies for preparing LLMs for deployment in healthcare as well as pre-training and fine-tuning processes. Innovative pre-training methods are introduced, such as the multimodal and Contrastive Language-Image Pre-training (CLIP)-based approaches that enhance the model's understanding across different data types. Besides, fine-tuning techniques such as Supervised Fine-Tuning (SFT), Instruction Fine-Tuning (IFT), and Parameter-Efficient Tuning (PET) are discussed, which can tailor the LLMs to specific medical tasks with relatively low resource requirements. Moreover, our paper delves into advanced prompting strategies, including zero/few-shot, Chain-of-Thought (CoT), and self-consistency prompting, which refine the model's capacity to handle complex medical queries, as well as Retrieval-Augmented Generation (RAG) and interactive web search technologies in improving the accuracy and reliability of model responses, which can enhance the applicability of LLMs in real-world medical practice. At last, our article depicts the applications of multimodal models in medicine and LLMs in medical texts and images. Our paper not only provides the common methods and applications of LLMs in medicine but also the future directions, ethics, and privacy in this rapidly advancing field.

Abstract: Severe metabolic acidosis is a frequent finding in the intensive care unit (ICU) and a critical marker of clinical severity and organ dysfunction, closely linked to acute kidney injury (AKI) due to shared physiological mechanisms and the loss of the kidney's ability to maintain acid-base homeostasis. Therefore, it represents the biochemical expression of heterogeneous pathophysiological mechanisms related to acid-base balance. These include tissue hypoperfusion, sepsis, mitochondrial dysfunction, accumulation of unmeasured anions, bicarbonate loss, and reduced renal excretion of the acid load. Its presence is associated with increased mortality, greater vasopressor and mechanical ventilation requirements, prolonged ICU stay, and a higher likelihood of renal replacement therapy (RRT). However, pH correction alone does not guarantee clinical improvement. Therefore, contemporary management prioritizes the etiology, severity of the acidemia, and hemodynamic status. In this context, sodium bicarbonate plays a limited and selective role, particularly in severe acidemia with advanced AKI or hyperkalemia, or as temporary supportive therapy while the underlying cause is corrected or extracorporeal support is arranged. Similarly, RRT should be reserved for refractory cases and should not be initiated based solely on isolated pH thresholds. This review analyzes the definition, epidemiology, clinical implications, pathophysiology, and therapeutic strategies for severe metabolic acidosis in critically ill patients, with emphasis on its interaction with AKI, the rational use of bicarbonate, and the timing of RRT initiation.

Abstract: Virtual surgery environments are increasingly used in surgical training, robotics, and reinforcement learning, yet their practical reproducibility remains insufficiently studied. Prior work focuses primarily on simulation capabilities and task performance, with limited attention to installation effort, dependency stability, and long-term usability. This paper presents a reproducibility audit of several open-source frameworks, including Surgical Gym, iMSTK, and SOFA, based on hands-on installation and execution attempts in up-to-date computing environments. The results reveal substantial heterogeneity in both architecture and reproducibility outcomes. Surgical Gym failed due to reliance on a deprecated Isaac Gym interface that is no longer supported in current Isaac Sim releases. iMSTK failed to build because of unresolved dependencies, and its archived status makes an upstream fix unlikely. SOFA installation was hindered by extensive system-level dependencies and distribution-specific package mismatches. Across all systems, failures were driven primarily by external dependency ecosystems rather than core simulation logic. These findings indicate that reproducibility in virtual surgery frameworks is strongly shaped by architectural design and dependency surfaces. The study highlights a gap between open-source availability and practical usability, underscoring the need for improved dependency management, environment specification, and reproducibility reporting in surgical simulation research.

Abstract: This comprehensive literature review delves into the multifaceted roles of RNA-binding motif protein 3 (RBM3) in cellular processes, disease pathogenesis, and therapeutic poten-tial. RBM3 has been implicated in shaping cell morphology, synaptic protection in neuro-degenerative conditions, and regulating gene expression through binding to specific RNA sequences. In cancer, RBM3 exhibits contrasting effects, influencing cell proliferation, tu-morigenic potential, and RNA splicing. Clinical studies suggest RBM3 as a predictive bi-omarker in chemotherapy response for muscle-invasive bladder cancer. Despite promising therapeutic implications in neuroprotection and cancer, challenges persist in under-standing the regulatory mechanisms and clinical behavior of RBM3. Further research is warranted to elucidate the molecular mechanisms underlying RBM3's diverse functions and its significance as a potential target for personalized medicine in cancer therapy. This review underscores the pivotal role of RBPs, particularly RBM3, in disease progression and highlights the need for continued investigation to harness their therapeutic potential effectively.

Abstract:

Antimicrobial resistance (AMR) and virulence have traditionally been viewed as competing traits in bacterial evolution due to fitness costs. However, Streptococcus pneumoniae has emerged as a paradigm of successful coevolution, with multidrug-resistant clones simultaneously maintaining or enhancing pathogenic potential. This review examines the molecular mechanisms, epidemiological patterns, and clinical consequences of the convergence between AMR and virulence in pneumococci. Resistance to β-lactams is driven by mosaic penicillin-binding proteins (pbp1a, pbp2b, pbp2x), while macrolide resistance is mediated primarily by erm(B) (MLS phenotype) and mef(A/E)–msr(D) efflux systems. These determinants are frequently co-localized on mobile genetic elements (e.g., Tn916 family) within successful clonal complexes such as CC271/320 and lineages including ST320 and GPSC10. Contrary to the classical fitness cost hypothesis, compensatory epistasis, capsular recombination, metabolic adaptations, and intra-serotype phenotypic variation enable certain clones to combine high-level resistance to β-lactams, macrolides, and tetracyclines with enhanced colonization, biofilm formation, immune evasion, and invasive capacity. Post-pneumococcal conjugate vaccine (PCV) surveillance reveals the persistence and expansion of these high-risk lineages, contributing to treatment-refractory invasive pneumococcal disease (IPD), increased morbidity, and mortality. Although PCVs have reduced vaccine-type resistant strains in some settings, serotype replacement and emerging metabolic genotypes continue to drive adaptation. This review highlights the need for integrated genomic surveillance, novel therapeutics (e.g., omadacycline, lefamulin, endolysins), monoclonal antibodies, and next-generation vaccines targeting both resistance and conserved virulence determinants. A multifaceted strategy combining antimicrobial stewardship, strengthened surveillance, and innovative interventions is essential to curb the evolving threat of resistant and virulent S. pneumoniae.

Abstract: Background: The popularization of generative artificial intelligence (GenAI) has brought both opportunities and challenges to medical education. Objective: To investigate medical students' usage status, usage intention of GenAI and its possible influencing factors. Methods: A questionnaire survey was conducted among 199 students from a medical university, and statistical analysis was performed using SPSSAU. Results: Tools such as DeepSeek and ChatGPT are widely used in medical students' learning and scientific research. High-frequency users (≥4 days per week) scored significantly higher than low-frequency users (<4 days per week) in 9 dimensions; gender showed significant differences in dimensions such as perceived ease of use (P<0.05), while major background differed only in some dimensions, and age showed no significant difference. Regression analysis revealed that external variables (P<0.001), perceived usefulness (P=0.001) and individual factors (P=0.009) had significant positive effects on behavioral intention, whereas effort expectancy (P=0.049) had a significant negative effect. Conclusion: GenAI has been deeply integrated into medical students' autonomous learning. External support, technical practicality and individual adaptability are key driving factors for usage intention, while effort expectancy constitutes a barrier. This study provides empirical evidence for the standardized application of GenAI in medical education.

Abstract: Radiomics has produced tens of thousands of publications yet almost no tools in routine clinical use, and the reasons are increasingly understood to be problems of reproducibility and clinical translation rather than of algorithms. This critical narrative review argues that the field systematically generates paper-grade evidence—findings sufficient to publish—far faster than decision-grade evidence—findings sufficient to change clinical practice. Drawing on meta-scientific research, we describe seven fragility mechanisms (publication bias, analytical flexibility, underpowering, HARKing [hypothesizing after the results are known], citation distortion, cognitive bias, and misaligned incentives) and show why radiomics is structurally exposed to all of them simultaneously: high-dimensional feature spaces, acquisition-dependent measurement instability, segmentation variability, retrospective single-centre data, small samples, and leakage-prone validation. We then summarise empirical evidence on the radiomics literature, which remains pervaded by suboptimal methodological quality, near-absent negative results, limited external validation, sparse calibration and clinical-utility assessment, low data and code sharing, and a measurable retraction signal. We interpret these patterns as the output of a self-reinforcing system rather than isolated errors, and argue that better algorithms alone cannot resolve them. Finally, we argue that closing this gap requires not better models but evidentiary discipline: the consistent, enforceable application of standards the field already has, and the calibration of published claims to the strength of the underlying evidence.

Abstract: Background/Objectives: Pelvic floor dysfunctions (PFD) have functional and psychosocial impact. Although pelvic floor rehabilitation is recommended as first-line care, effectiveness depends on access, communication, adherence support, and self-management. This study quantified patient–professional alignment and translated gaps into care-improvement recommendations using a Delphi-Dialogue Patients–Professionals (DDPP) framework. Methods: A two-phase observational study with Real-Time Delphi-based feasibility assessment was conducted within the Spanish Society of Physical Medicine and Rehabilitation (SERMEF). In Phase 1, parallel online surveys were completed by patients with PFD (n = 225) and rehabilitation professionals (n = 164). Shared items were rated on a six-point Likert scale. Concordance was explored using descriptive statistics and an operational divergence index combining mean differences and differences in agreement proportions. In Phase 2, ten recommendations were assessed for feasibility by 35 PM&R physicians and two Spanish Incontinence Association representatives. Results: Alignment was heterogeneous and domain-specific. The greatest divergences concerned digital competence, information timing, bladder/bowel diaries, and adherence. Divergence was bidirectional: professionals rated diaries and some group-based activities as more useful, whereas patients reported higher digital competence, timelier information, and better adherence. Strong alignment was observed for hybrid care models, written and video-based instructions, app-supported follow-up, and satisfaction. Feasibility ratings supported prioritization of adherence monitoring tools, pathway visibility, and digital monitoring applications; home exercise programs and educational materials emerged as consolidation targets. Conclusions: Patient–professional divergence appears to reflect context-dependent differences in perceived value rather than generalized disagreement. The DDPP framework offers a structured exploratory approach to translate experiential gaps into feasibility-informed service-improvement priorities.

Abstract: The outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has emerged as one of the most significant global health crises in recent history. Coronaviruses are a diverse group of RNA viruses classified into alpha, beta, gamma, and delta genera, with SARS-CoV-2 belonging to the beta-coronavirus family. The virus exhibits high transmissibility and causes a wide spectrum of clinical manifestations ranging from mild respiratory symptoms to severe complications such as acute respiratory distress syndrome, multi-organ failure, and death, particularly among elderly and immunocompromised individuals. Structurally, SARS-CoV-2 possesses a large single-stranded RNA genome encoding major structural proteins, including spike (S), envelope (E), membrane (M), and nucleocapsid (N) proteins, which play critical roles in host cell recognition and viral infection. Understanding the molecular mechanisms of virus–host interactions, especially protein–protein interactions (PPIs), is essential for uncovering viral pathogenesis and identifying potential therapeutic targets. Traditional experimental techniques for PPI detection, such as yeast two-hybrid and affinity purification methods, are often expensive, labor-intensive, and prone to inaccuracies. Consequently, computational approaches based on machine learning and deep learning have gained significant attention for efficient and scalable PPI prediction. These methods utilize diverse biological information, including protein sequences, structural features, genomic data, gene ontology annotations, and interaction networks, to model complex biological relationships. This survey provides a comprehensive review of computational approaches for PPI prediction, highlighting both machine learning- and deep learning-based techniques, along with their methodological advancements and performance evaluations. Furthermore, the survey discusses major biological databases and data sources commonly employed in PPI studies, offering insights into current challenges and future directions in computational PPI prediction research.

Abstract: Cancer metabolism research has long been shaped by a pathway-centric paradigm, in which individual biochemical routes—most prominently aerobic glycolysis (the Warburg effect)—are studied and targeted in relative isolation. Accumulating evidence from systems biology, multi-omics profiling, and computational oncology suggests, however, that this view is insufficient to explain the adaptive resilience that solid tumors routinely demonstrate against metabolic inhibitors. Here we propose a conceptual synthesis: the tumor dynamic metabolic interaction network (DMIN), a graph-theoretic framework in which metabolic enzymes and transporters constitute nodes, substrate fluxes define weighted edges, and the system's overall state is governed by topological properties such as betweenness centrality and eigenvector centrality. Within this framework, we elaborate the hypothesis of dynamic network collapse (DNC)—the notion that simultaneous perturbation of several high-centrality nodes may push the tumor metabolic network beyond a thermodynamic instability threshold, triggering irreversible functional disintegration that cannot be escaped through known compensatory rerouting. We review the three dominant metabolic axes of tumor survival—glucose (GLUT1/HK2/PKM2), glutamine (SLC1A5/GLS1), and lactate efflux (MCT1/MCT4)—and examine how each contributes to immunosuppression through metabolic competition with cytotoxic T lymphocytes and through the acidification of the tumor microenvironment. We further discuss genome-scale metabolic models, flux balance analysis, and graph neural network approaches that may render the DNC concept computationally actionable. The clinical implications of multi-node targeting are considered alongside the limitations of existing evidence and unresolved methodological challenges. Although the DNC hypothesis remains to be tested experimentally in relevant in vivo models, it provides a coherent rationale for the next generation of combination metabolic therapies and for patient-specific metabolic profiling as a decision tool.

Abstract: A 79-year-old man with prostate cancer underwent initial staging prior to prostatectomy with 99mTc-methylene diphosphonate (99mTc-MDP) bone scintigraphy. Anterior and pos-terior images showed focal uptake overlying the pubic symphysis. Lateral views showed that the activity was extraosseous. Follow-up CT urography showed a bladder hernia as cause of the abnormality on bone scan. Prostatectomy and inguinal hernia repair were performed as a combination case. Four years postoperatively, follow-up ⁶⁸Ga-PSMA-11 positron emission tomography/computed tomography (PET/CT) showed no recurrence. The CT component of the exam show an intermediate density focus at the right inguinal hernia repair site, corresponding to a polypropylene mesh plug, and a hyperattenuating Gore-Tex mesh repair of the left inguinal hernia. This case highlights the importance of lateral projections in resolving scintigraphic pitfalls and recognizing mesh-related im-aging appearances to prevent misinterpretation.

Abstract: We present AortaSeg-60, an open dataset of 60 real-world thoraco-abdominal CT-angiography scans of the aorta encompassing normal anatomy and pathological variations, designed for AI research, benchmarking, and educational purposes. The dataset is organized into six balanced categories: young normal, elderly normal, aortic aneurysms, aortic dissections, venous acquisition, and non-contrast acquisition, capturing realistic anatomical and pathological diversity. All scans are provided in NIfTI format with fully automated aortic segmentation masks generated using TotalSegmentator, without manual correction, enabling evaluation of typical algorithmic errors and testing of refinement strategies. Two radiologists performed a technical validation to ensure dataset curation and correct category assignment. AortaSeg-60 is publicly available on Zenodo under a CC0 license. By providing paired imaging and automated labels, the dataset facilitates reproducible research, algorithm development, and method comparison for vascular segmentation, while noting limitations of sample size, single-centre acquisition, and reliance on automated annotations.

Abstract: A metal recycling facility scrapyard fire that burned for four days continuously in February 2020 in rural Minnesota resulted in firefighters from around Minnesota to mobilize and aid. Combusted material included cars, refrigerators, metals, glass, foam, insulation. Urine, blood and serum specimens were collected one day later. Parameters collected included: CBC with differential, BMP, blood heavy metals, urine heavy metals, and serum heavy metals. This massive and prolonged industrial fire provided an opportunity for biomonitoring of hazardous, and unique, exposures acutely, in concordance with concerns raised by the employees at risk. Initial analysis of these results did not find evidence of acute concern regarding the biomonitoring results. However, some of these results may portend the potential for long-term consequences such as the development of occupational cancers, especially if there was recurrent exposure in prior or proceeding fires.

Abstract: The physiological acidity of the skin microenvironment constitutes a paramount component of passive innate defense against pathogenic colonization and subsequent dysbiosis. The objective of this review is to critically evaluate the sequelae of chronic epidermal barrier exposure to chemical exfoliants and to elucidate the impact of hydroxy acids on microbiota stability. An analysis of recent literature delineates fundamental discrepancies in their antimicrobial mechanisms, inflammatory modulation, and induction of stratum corneum desquamation. Conventional exfoliants, notably glycolic and salicylic acids, exhibit the capacity for passive diffusion into bacterial cells, where they undergo dissociation, precipitating destructive cytoplasmic acidification; furthermore, salicylic acid specifically downregulates crucial transcription factors. While these mechanisms facilitate the efficacious eradication of pathogenic organisms, they concurrently jeopardize commensal populations, which may paradoxically pave the way for secondary dysbiosis and opportunistic colonization. Next-generation acids, such as lactobionic acid, emerge as a highly promising, albeit insufficiently investigated, alternative. They exhibit the capacity to compromise bacterial cell walls and intercalate with microbial DNA. Future paradigms regarding the utilization of hydroxy acids in clinical dermatology must extend beyond traditional macroscopic endpoints to encompass the preservation of microbiome diversity and stability, thereby precluding chronic impairment of the associated protective barrier.

Abstract: During HIV infection, the immune system initiates an immune response to control the viremia. In this in vitro study, we investigated the immunomodulatory and anti-HIV potential of a traditional medicine formulation, Product Nkabinde (PN). A freeze-dried extract of PN was used to determine cytotoxicity in MT4 cells. Non-cytotoxic doses were used to evaluate the immunomodulatory and anti-HIV effects of PN using neutralization, prophylactic and treatment approaches. Post-treatment, cytokine quantification and p24 detection were performed. In the neutralization strategy, PN restored IL-1α (p = 0.0389) and IL-10 (p = 0.0443) to levels of uninfected cells. It also reduced HIV-induced elevations in IL-8 (p = 0.035), IP-10 (p = 0.0886), and MCP-1 (p = 0.0733) compared to HIV-infected cells. In the prophylactic approach, HIV infection upregulated IL-1α (p = 0.676), which was suppressed by PN. In the treatment strategy, PN reversed the elevated levels of IL-1α (p = 0.049). IL-10 was fully restored by PN to levels of uninfected cells. In all strategies, PN induced a significant and dose-dependent decrease in HIV replication. These findings demonstrate that PN exerts potent immunomodulatory effects all strategies used by reversing HIV-induced cytokine dysregulation, thereby inducing significant anti-HIV effects.

Abstract: Background/Objectives: The objective of the present study was to determine the association between blood cadmium (Cd) and lead (Pb) levels and survival of the patients with kidney cancer. In this prospective study, we analyzed 272 consecutive, unselected kidney cancer patients and assessed their 8-year survival in relation to Cd and Pb levels. Methods: Cd and Pb concentrations were measured using inductively coupled plasma mass spectrometry (ICP-MS). Patients were categorized into four groups according to the quartile distribution of Cd and Pb levels, ranked in ascending order. Multivariable models were adjusted for covariates including age at diagnosis, sex, smoking status, type of surgery, histopathological classification and blood levels of selenium, zinc, copper, iodine, cadmium and lead. Results: We observed no association between blood Cd and Pb levels and all-cause mortality in patients with kidney cancer. Conclusions: To our knowledge, this study is the first to investigate the relationship between blood levels of cadmium and lead and kidney cancer survival.

Abstract: Background: Although Diagnostic Reference Levels (DRLs) based on anatomical regions are widely used in Computed Tomography (CT) imaging, a clinical-indication-based approach provides a more accurate representation of daily practice and protocol variation. This study aimed to establish typical radiation doses for common CT clinical indications among adult patients at King Abdulaziz University Hospital (KAUH) in Saudi Arabia. Methods: This retrospective cross-sectional study included 298 adult patients who underwent CT examinations between 2020 and 2025 using two dual-source scanners operating in single- and dual-source modes. Demographic data, acquisition parameters, and radiation dose metrics, including volume CT dose index (CTDIvol) and the dose–length product (DLP) were extracted from scanner consoles. Six clinical indications were analyzed: brain trauma, sinusitis, chest metastases (chest Mets), interstitial lung disease (ILD), abdominopelvic metastases (AbdPel Mets), and hernia. Results: Typical median CTDIvol values in mGy were 36.4 for brain trauma, 3.4 for sinusitis, 4.9 for chest Mets, 5.6 for ILD, 7.2 for AbdPel Mets and hernia. Corresponding DLP values in mGy·cm were 654, 50, 173, 188, 344, and 369, respectively. Brain trauma demonstrated the highest radiation exposure, whereas sinusitis CT showed the lowest. Most values were comparable to or lower than international DRLs. Conclusions: This study provides the first comprehensive clinical-indication-based DRL data in Saudi Arabia beyond anatomical benchmarks, supporting ongoing dose optimization and future national DRL development.