Diagnostics

12 pages, 1969 KB

Open AccessArticle

Preoperative Glucose–Albumin Ratio and Its Association with Postoperative Outcomes in Critically Ill Adult Burn Patients: A Retrospective Cohort Study of 1119 Patients

by Jihion Yu, Young-Kug Kim, Hee Yeong Kim, Yu-Gyeong Kong, Yongsoo Lee and Young Joo Seo

Diagnostics 2026, 16(15), 2441; https://doi.org/10.3390/diagnostics16152441 (registering DOI) - 2 Aug 2026

Abstract

Background/Objectives: Severe burn injury is associated with high postoperative morbidity and mortality due to profound metabolic and nutritional stress. The blood glucose-to-serum albumin ratio (GAR) may reflect both metabolic derangement and nutritional status, but its prognostic significance in burn intensive care unit (ICU) [...] Read more.

Background/Objectives: Severe burn injury is associated with high postoperative morbidity and mortality due to profound metabolic and nutritional stress. The blood glucose-to-serum albumin ratio (GAR) may reflect both metabolic derangement and nutritional status, but its prognostic significance in burn intensive care unit (ICU) patients remains unclear. This study evaluated the association between preoperative GAR and postoperative outcomes in adult burn ICU patients undergoing surgery. Methods: We retrospectively analyzed adult burn ICU patients who underwent surgery between 2014 and 2024. GAR was calculated using blood glucose and serum albumin levels measured within one day before surgery. The primary outcome was 90-day postoperative mortality. Secondary outcomes included 90-day hospital-free days and ICU-free days. Multivariable Cox regression and restricted cubic spline analyses were performed to assess the relationship between GAR and mortality risk. Receiver operating characteristic curve analysis was used to evaluate the discriminatory performance of GAR and determine the optimal cutoff value. Results: Among 1119 patients, the 90-day mortality rate was 25.6%. Higher preoperative GAR was independently associated with increased 90-day mortality in multivariable Cox regression analysis. Restricted cubic spline analysis demonstrated a significant overall association, with progressively increasing mortality risk at higher GAR levels. Receiver operating characteristic curve analysis showed moderate discriminatory performance (area under the curve = 0.789), and the optimal cutoff value based on the highest Youden index was 62.5. Patients with GAR ≥ 62.5 had significantly lower 90-day survival rates and fewer 90-day hospital-free days and ICU-free days than those with lower GAR values (all p < 0.001). Conclusions: Higher preoperative GAR was significantly associated with adverse postoperative outcomes, including increased 90-day mortality and fewer hospital-free and ICU-free days in adult burn ICU patients. Full article

(This article belongs to the Special Issue Clinical Diagnostics and Management in the ICU)

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11 pages, 4446 KB

Open AccessArticle

A New Era in Early Postoperative OCT: Swept-Source Versus Spectral-Domain in Gas-Filled Eyes

by Federico Giannuzzi, Mattia Cusato, Umberto De Vico, Diletta Paganelli, Lorenzo Hu, Giuseppe Liuzzi, Kevin Forgione, Paolo Lando, Arianna Pignatelli, Miriana Capodiferro, Valentina Cestrone, Ludovica Paris, Maria Cristina Savastano and Stanislao Rizzo

Diagnostics 2026, 16(15), 2440; https://doi.org/10.3390/diagnostics16152440 (registering DOI) - 2 Aug 2026

Abstract

Objectives: This study aims to compare the imaging performance of spectral-domain optical coherence tomography (SD-OCT) and swept-source OCT (SS-OCT) in the early postoperative assessment of patients undergoing vitreoretinal surgery with intraocular gas or air tamponade. Methods: Seventeen eyes of 17 patients [...] Read more.

Objectives: This study aims to compare the imaging performance of spectral-domain optical coherence tomography (SD-OCT) and swept-source OCT (SS-OCT) in the early postoperative assessment of patients undergoing vitreoretinal surgery with intraocular gas or air tamponade. Methods: Seventeen eyes of 17 patients who underwent pars plana vitrectomy with either sulfur hexafluoride (SF₆, 20%) or air tamponade were prospectively enrolled. All patients underwent OCT imaging on postoperative day 1 using both the SD-OCT system and the SS-OCT platform, without pharmacological mydriasis. Images were independently evaluated by two experienced ophthalmologists based on the ability to delineate four prespecified anatomical layers: inner retinal layers, ellipsoid zone (EZ), retinal pigment epithelium (RPE) and choroid. Images were classified as adequate quality if two or more of these structures were identifiable. Results: SS-OCT provided adequate-quality images in all 17 eyes (100%), with complete visualization of the inner retinal layers, EZ, RPE, and choroid in 15 eyes (88.2%). In contrast, SD-OCT yielded adequate-quality images in only three of 17 eyes (17.6%), demonstrating marked signal attenuation, interface artifacts, and inability to resolve deeper retinal structures in most cases. No difference in imaging performance was observed between SF₆ and air tamponade subgroups. Conclusions: SS-OCT demonstrates markedly superior imaging performance in gas-filled eyes on postoperative day 1 compared to SD-OCT, primarily attributable to its longer wavelength, reduced sensitivity roll-off, and superior penetration through optically challenging media. These findings suggest that SS-OCT may offer meaningful advantages for early postoperative monitoring following vitreoretinal surgery with tamponade; confirmation in larger prospective cohorts with clinical-outcome correlation is warranted before it can be recommended as the preferred modality. Full article

(This article belongs to the Special Issue Expanding Horizons: Optical Coherence Tomography in Cross-Specialty Diagnostic Practice)

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11 pages, 243 KB

Open AccessArticle

Clinical Significance of Vulvar Condyloma as a Marker of Concurrent High-Risk Cervical HPV Infection and Abnormal Cervical Cytology

by Eda Güner Özen, Süleyman Özen, Özgün Akbaş, Ahkam Göksel Kanmaz and Yaşam Kemal Akpak

Diagnostics 2026, 16(15), 2439; https://doi.org/10.3390/diagnostics16152439 (registering DOI) - 2 Aug 2026

Abstract

Background/Objectives: Human papillomavirus (HPV) infection is the principal etiological factor in cervical cancer and its precursor lesions. Although vulvar condyloma is typically associated with low-risk HPV types, high-risk HPV genotypes may coexist. This study evaluated the association between vulvar condyloma, cervical cytological abnormalities, [...] Read more.

Background/Objectives: Human papillomavirus (HPV) infection is the principal etiological factor in cervical cancer and its precursor lesions. Although vulvar condyloma is typically associated with low-risk HPV types, high-risk HPV genotypes may coexist. This study evaluated the association between vulvar condyloma, cervical cytological abnormalities, high-risk HPV positivity, and cervical histopathological outcomes. Methods: This retrospective observational study included 407 women evaluated at the Department of Obstetrics and Gynecology, Izmir City Hospital, between January 2025 and January 2026. Patients underwent cervical cytology, HPV testing, vulvar examination, and colposcopic biopsy when clinically indicated. Patients were categorized according to the presence or absence of histopathologically confirmed vulvar condyloma. Logistic regression analyses were performed to identify factors associated with vulvar condyloma. Results: Vulvar condyloma was identified in 180 patients (44.2%). Abnormal cervical cytology was recorded in 66/180 patients (36.7%) with vulvar condyloma and 41/227 patients (18.1%) without condyloma (p < 0.001). High-risk HPV positivity was observed in 104/180 (57.8%) and 86/227 (37.9%) patients, respectively (p < 0.001). In multivariate analysis, adjusted ORs were 2.30 for HPV16 positivity (95% CI 1.36–3.89, p = 0.002), 3.29 for HPV18 positivity (95% CI 1.40–7.73, p = 0.006), and 2.01 for abnormal cervical cytology (95% CI 1.24–3.25, p = 0.005). Recorded CIN2+ was 15/180 (8.3%) in the condyloma-positive group and 7/227 (3.1%) in the condyloma-negative group in the overall cohort; in the biopsy-restricted analysis, CIN2+ was 15/82 (18.3%) and 7/41 (17.1%), respectively. Conclusions: Vulvar condyloma was independently associated with abnormal cervical cytology and high-risk HPV infection, particularly HPV16/18 positivity. These robust associations suggest that vulvar condyloma may represent a clinically visible marker of concurrent cervical HPV-related disease. Careful cervical evaluation is warranted in women presenting with vulvar condyloma, whereas CIN2+ findings should be interpreted cautiously until confirmed in larger prospective cohorts with standardized histopathological verification. Full article

(This article belongs to the Section Pathology and Molecular Diagnostics)

14 pages, 1229 KB

Open AccessProtocol

Duplex Doppler Measurement of Renal Resistive Index in Non-Dialysis Chronic Kidney Disease Outpatients: A Proposed Standardized Protocol

by GianLuca Colussi, Lisa Giusto, Alessandra Rigamonti, Stefania Rondinella, Giulia Marta Viglione, Marco Fabio Cola, Piergiorgio Gaudenzi, Maurizio Tonizzo and Giulio Romano

Diagnostics 2026, 16(15), 2438; https://doi.org/10.3390/diagnostics16152438 (registering DOI) - 1 Aug 2026

Abstract

The renal resistive index (RRI) is a Doppler-derived parameter influenced by intrarenal hemodynamics, vascular compliance, pulsatile load, and systemic cardiovascular factors. In outpatient nephrology practice, RRI may provide adjunctive hemodynamic and prognostic information when interpreted together with kidney morphology, estimated glomerular filtration rate, [...] Read more.

The renal resistive index (RRI) is a Doppler-derived parameter influenced by intrarenal hemodynamics, vascular compliance, pulsatile load, and systemic cardiovascular factors. In outpatient nephrology practice, RRI may provide adjunctive hemodynamic and prognostic information when interpreted together with kidney morphology, estimated glomerular filtration rate, proteinuria, blood pressure, heart rate, rhythm, and cardiovascular context. This protocol aims to standardize duplex Doppler acquisition, calculation, interpretation, and reporting of RRI in outpatient adults with native-kidney chronic kidney disease (CKD). The protocol defines patient eligibility and preparation, same-visit clinical data collection, grayscale kidney assessment, color Doppler localization of intrarenal arteries, pulsed-wave Doppler settings, bilateral upper-, middle-, and lower-pole sampling, waveform validity criteria, RRI calculation rules, image archiving, and structured reporting. Technical pitfalls and hemodynamic confounders are incorporated into the workflow to support reproducibility and serial comparability. The expected output is a standardized RRI report including kidney-specific and bilateral mean RRI values when minimum validity criteria are met, the number and location of valid sampling sites, grayscale morphologic findings, same-visit hemodynamic context, relevant technical limitations, and interpretive caveats. The protocol is designed to reduce acquisition variability and improve the consistency of RRI documentation in outpatient CKD practice. RRI should not be interpreted as a stand-alone diagnostic test or direct surrogate of renal vascular resistance. A standardized acquisition and reporting protocol may improve reproducibility and allow RRI to be used more appropriately as an adjunctive hemodynamic and prognostic marker in adults with non-dialysis-dependent CKD. Full article

(This article belongs to the Special Issue Kidney Disease: Biomarkers, Diagnosis, and Prognosis—4th Edition)

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5 pages, 1204 KB

Open AccessInteresting Images

Head-to-Head ¹⁸F-rhPSMA-7.3 and ¹⁸F-PSMA-1007 PET/CT in Recurrent Prostate Cancer: Pulmonary and Nodal Uptake as a Diagnostic Challenge

by Yin-Shen Chen, Daniel Hueng-Yuan Shen, Ya-Ting Huang, Ming-Chan Lee and Hung-Pin Chan

Diagnostics 2026, 16(15), 2437; https://doi.org/10.3390/diagnostics16152437 (registering DOI) - 1 Aug 2026

Abstract

This report presents a within-patient comparison of ¹⁸F-rhPSMA-7.3 and ¹⁸F-PSMA-1007 PET/CT in a 71-year-old man with Gleason score 4 + 3 = 7, pT3bN1 metastatic castration-resistant prostate cancer after robot-assisted radical prostatectomy, multiple androgen-deprivation and androgen receptor-directed treatments, and radiotherapy for [...] Read more.

This report presents a within-patient comparison of ¹⁸F-rhPSMA-7.3 and ¹⁸F-PSMA-1007 PET/CT in a 71-year-old man with Gleason score 4 + 3 = 7, pT3bN1 metastatic castration-resistant prostate cancer after robot-assisted radical prostatectomy, multiple androgen-deprivation and androgen receptor-directed treatments, and radiotherapy for para-aortic nodal metastases. The scans showed concordant PSMA-avid cervical-to-mediastinal lymphadenopathy and an ill-defined right lower-lobe pulmonary lesion with a recorded SUVmax > 15, despite distinct physiologic biodistributions. Infection or inflammation remained a relevant differential diagnosis, and the patient declined biopsy. Antibiotics did not improve the CT findings. After enrollment in a clinical trial of systemic therapy, the last available pretreatment prostate-specific antigen (PSA) level of 42.4 ng/mL decreased to 3.1 ng/mL, with marked disease regression. The concordant dual-tracer findings, lack of response to antibiotics, and subsequent radiographic and biochemical response to systemic therapy favored nodal and pulmonary metastases from prostate cancer. However, without histopathologic confirmation, the diagnosis remains presumptive, highlighting the need to integrate PET biodistribution, semiquantitative uptake, anatomic imaging, and longitudinal clinical findings. Full article

(This article belongs to the Section Medical Imaging and Theranostics)

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24 pages, 3382 KB

Open AccessArticle

SpecAtt-Net: Time-Frequency-Based Image Representations of Slice-Level Radiomic Features for Explainable Lung Cancer Classification via Slice-Wise Activation Mapping

by Merve Ceyhan and Uğur Gürel

Diagnostics 2026, 16(15), 2436; https://doi.org/10.3390/diagnostics16152436 (registering DOI) - 1 Aug 2026

Abstract

Background: Extracting radiomic features from volumetric imaging data for lung cancer classification is limited by high dimensionality and the black-box nature of deep learning models. Traditional methods may overlook dependencies between slices, leading to the loss of sequential spatial information. Even when classification [...] Read more.

Background: Extracting radiomic features from volumetric imaging data for lung cancer classification is limited by high dimensionality and the black-box nature of deep learning models. Traditional methods may overlook dependencies between slices, leading to the loss of sequential spatial information. Even when classification is correct, the model’s explanatory power may remain insufficient. Objective: This study proposes SpecAtt-Net, which processes spectral representations of slice-level radiomic data from computed tomography (CT) scans of lung cancer patients. A slice-based explainability approach is also presented to identify the slice groups used in model decision-making. Methods: Slice-level radiomic data were preprocessed, and slice-position–frequency representations were generated using the Short-Time Fourier Transform (STFT). This enables the model to capture spectral textures and spatial transitions from 720 × 288 feature maps. SpecAtt-Net employs a dual-attention mechanism to focus on distinctive radiomic features. To address the lack of slice-level labels, Slice-Wise Activation Mapping (SWAM), a post hoc interpretability technique, was developed. SWAM converts two-dimensional (2D) activation maps into one-dimensional (1D) importance vectors and provides a weakly supervised indication of the slice groups most relevant to the model’s decision. Results: SpecAtt-Net achieved competitive performance in accuracy, precision, recall, and F1-score compared with the evaluated reference architectures. SWAM highlighted slice-sequence regions contributing strongly to model predictions, providing preliminary evidence for interpretability. Conclusion: SpecAtt-Net provides a compact and interpretable approach for lung cancer subtype classification using attention-based feature modeling. SWAM offers an exploratory visualization of decision-relevant sequence regions and may support future radiological interpretation and validation studies. Full article

(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)

25 pages, 1564 KB

Open AccessSystematic Review

Large Language Models in Adverse Drug Reaction Detection and Pharmacovigilance: A Systematic Review of Current Applications, Challenges, and Future Directions

by Tae You Kim, Won-Sik Oh and Dong-Hwa Jeong

Diagnostics 2026, 16(15), 2435; https://doi.org/10.3390/diagnostics16152435 (registering DOI) - 1 Aug 2026

Abstract

Background/Objectives: Pharmacovigilance workflows rely heavily on unstructured text across diverse sources. Here, we systematically reviewed how large language models (LLMs) are being explored as support tools for adverse drug reaction (ADR) detection, extraction, triage, and documentation, highlighting their potential for precision medicine and [...] Read more.

Background/Objectives: Pharmacovigilance workflows rely heavily on unstructured text across diverse sources. Here, we systematically reviewed how large language models (LLMs) are being explored as support tools for adverse drug reaction (ADR) detection, extraction, triage, and documentation, highlighting their potential for precision medicine and big data-enabled safety monitoring. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines, we systematically searched PubMed, Scopus, and Web of Science for studies published between January 2022 and March 2026. Ultimately, 83 empirical studies satisfied the inclusion criteria. A narrative synthesis was conducted to address methodological heterogeneity across these studies. Results: LLM applications were concentrated in constrained information-extraction and classification tasks, including signal evaluation, clinical-note extraction, social media surveillance, and literature screening. Quantitative performance varied substantially by system design: error-correction prompting yielded an F1-score of 0.921 for ADR named entity recognition, whereas retrieval-augmented generation improved data-retrieval accuracy from 8.3% to 78.3%. Most studies were retrospective, benchmark-based, or proof-of-concept evaluations. Across 581 paired pre-consensus domain judgements, observed inter-rater agreement was 90.4% and Cohen’s κ was 0.837 (95% CI 0.772–0.895). Hallucination, low specificity, prompt sensitivity, narrow datasets, and weak external validation remained common limitations. Conclusions: Current evidence supports supervised, task-specific applications of LLMs for extraction, triage, retrieval, and documentation rather than autonomous pharmacovigilance decision-making. Prospective evaluation, external validation, transparent reporting, and accountable human oversight are required before high-stakes clinical or regulatory deployment. Full article

(This article belongs to the Special Issue Diagnosis and Management of Adverse Drug Reactions in Precision Medicine and Big Data)

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13 pages, 251 KB

Open AccessArticle

Serological and Immunological Markers in Dengue Fever: A Retrospective ELISA-Based Pilot Study from Trinidad and Tobago

by Angel Justiz-Vaillant and Sachin Soodeen

Diagnostics 2026, 16(15), 2434; https://doi.org/10.3390/diagnostics16152434 (registering DOI) - 1 Aug 2026

Abstract

Background: Dengue fever remains a major mosquito-borne viral disease in tropical and subtropical regions and continues to represent an important public health challenge in the Caribbean. Despite endemic transmission in Trinidad and Tobago, limited laboratory-based studies have evaluated serological markers associated with [...] Read more.

Background: Dengue fever remains a major mosquito-borne viral disease in tropical and subtropical regions and continues to represent an important public health challenge in the Caribbean. Despite endemic transmission in Trinidad and Tobago, limited laboratory-based studies have evaluated serological markers associated with recent dengue infection. Objective: To evaluate serological and immunological markers associated with recent dengue virus infection through the detection of anti-dengue virus immunoglobulin M (IgM) antibodies in serum samples obtained from Trinidad and Tobago using an enzyme-linked immunosorbent assay (ELISA). Methods: Anti-dengue virus IgM antibodies were detected using a commercial enzyme-linked immunosorbent assay (ELISA). Results were classified as positive, borderline or negative according to manufacturer-recommended criteria. Descriptive statistical analysis was performed to determine seroprevalence in anonymized serum samples. Results: A total of 161 serum samples were analyzed. Twenty samples (12.4%) demonstrated positive anti-dengue IgM reactivity, while 29 samples (18.0%) showed borderline reactivity and 112 samples (69.6%) were negative. Under the conservative analytical approach, the estimated dengue IgM seroprevalence was 12.4% (20/161; 95% CI: 7.7–18.6%). Conclusions: The estimated seroprevalence of dengue IgM in this pilot study was highly dependent on the analytical treatment of borderline ELISA results. Conservative classification provided the most cautious and reproducible estimate of recent dengue infection, while liberal interpretation substantially increased the apparent disease burden. Early viral replication triggers inflammation that progresses to cytokine-driven vascular damage, while cross-reactive humoral responses and host factors ultimately shape dengue severity. Ultimately, understanding the drivers of IgM cross-reactivity is essential for accurate dengue surveillance, outbreak detection, and clinical decision-making. Full article

(This article belongs to the Section Pathology and Molecular Diagnostics)

14 pages, 2558 KB

Open AccessArticle

In Vivo Visualization and Quantification of Dermal Nevus Microvasculature Using Super-Resolution Ultrasound of Erythrocytes

by Rikke Baarts, Ali Salari, Alexander Cuculiza Henriksen, Nathalie Sarup Panduro, Emma Kanchana Ertner Bengtsson, Niels Kvorning Ternov, Caroline Clausen, Lisbet Rosenkrantz Hölmich, Lars Lönn, Charlotte Mehlin Sørensen, Jørgen Arendt Jensen and Michael Bachmann Nielsen

Diagnostics 2026, 16(15), 2433; https://doi.org/10.3390/diagnostics16152433 (registering DOI) - 1 Aug 2026

Abstract

Background/Objectives: Distinguishing melanoma from benign melanocytic nevi remains a central diagnostic challenge, and vascular features may provide additional information beyond surface morphology. Super-resolution ultrasound using the erythrocytes (SURE) is a contrast-free imaging technique that uses endogenous erythrocyte scattering signals to reconstruct microvascular [...] Read more.

Background/Objectives: Distinguishing melanoma from benign melanocytic nevi remains a central diagnostic challenge, and vascular features may provide additional information beyond surface morphology. Super-resolution ultrasound using the erythrocytes (SURE) is a contrast-free imaging technique that uses endogenous erythrocyte scattering signals to reconstruct microvascular architecture beyond the conventional diffraction limit. This study evaluated the feasibility of SURE for in vivo visualization and quantitative assessment of dermal microvasculature in clinically benign nevi. Methods: Eleven participants with 35 clinically benign dermal nevi were included. All lesions underwent clinical and dermoscopic assessment, conventional B-mode ultrasound, color and power Doppler imaging, and SURE imaging. Eight larger nevi were imaged in two imaging planes, resulting in 43 SURE acquisitions. SURE reconstructions were assessed qualitatively for microvascular morphology and quantitatively for vessel diameter and erythrocyte flow velocity in proximal, intermediate, and distal visible intralesional vessel segments. Results: Dermoscopic and conventional ultrasound images were acquired for all lesions. SURE reconstructions of sufficient quality for quantitative analysis were obtained for all included acquisitions, yielding 129 vessel diameter measurements and 129 corresponding velocity measurements. Conventional Doppler demonstrated absent or minimal detectable vascular signal in the majority of lesions, whereas SURE visualized branching structures consistent with dermal microvascular networks in all the lesions. The mean vessel diameter was 85.0 ± 20.2 µm, with measured diameters ranging from 48.1 to 173.0 µm. The median flow velocity was 1.80 [1.30–2.50] mm/s. No significant differences in vessel diameter or velocity were observed between proximal, intermediate, and distal intralesional segments. Conclusions: SURE enabled contrast-free in vivo visualization and quantitative assessment of low-velocity dermal microvasculature in clinically benign nevi. These findings support the feasibility of SURE for microvascular mapping of melanocytic lesions and provide a basis for future studies including malignant lesions, volumetric imaging, and histopathological validation. Full article

(This article belongs to the Special Issue Ultrasound Imaging: Current Status and Future Perspectives)

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18 pages, 4165 KB

Open AccessArticle

Lipofuscin: Wear Pigment or Alarm Signal for Cardiac AlloGraft Vasculopathy?

by Anca Otilia Farcas, Mihai Ciprian Stoica, Septimiu Voidazan, Carmen Corina Radu, Laszlo Hadadi, Liviu Gavrilovici, Horatiu Suciu and Anca Ileana Sin

Diagnostics 2026, 16(15), 2432; https://doi.org/10.3390/diagnostics16152432 (registering DOI) - 1 Aug 2026

Abstract

Background: CAV (cardiac allograft vasculopathy) is considered the leading cause of late post-transplant mortality and affects approximately 50% of transplant patients at 10 years post-transplant. Its etiopathogenetic mechanism is considered to be immune-mediated, but the identification of other non-immunological risk factors could [...] Read more.

Background: CAV (cardiac allograft vasculopathy) is considered the leading cause of late post-transplant mortality and affects approximately 50% of transplant patients at 10 years post-transplant. Its etiopathogenetic mechanism is considered to be immune-mediated, but the identification of other non-immunological risk factors could represent new therapeutic targets for this pathology. Lipofuscin is due to reactive oxygen species (ROS) and appears to have a determining role in CAV. The aim of this study is to investigate the association between the amount of lipofuscin identified on EMB (endomyocardial biopsy) from patients followed up after heart transplantation, and the presence of CAV detected by coronary angiography. Methods: This retrospective study includes 99 EMBs from 47 transplanted patients, who also had coronary angiography. The amount of lipofuscin, damage to intramyocardial small vessels, vasculitis, Quilty effect, and acute cellular and humoral rejection was evaluated microscopically. Results: 19 CAV cases (19.2%) were identified, of which 15 (68.18% of total CAV cases) were insignificant. Grade 3 lipofuscin affected equally the cases with insignificant and significant CAV, 3 cases (37.5%) from each group. Grade 2 lipofuscin was reported in 10 cases (58.8%) of insignificant CAV, respectively 1 case of significant CAV (5.9%), (p-value of 0.0001). Quantitative evaluation of lipofuscin on microscopic sections revealed 8 EMBs (8.1%) with grade 3 lipofuscin. Two cases (25.0%) with lipofuscin score 3 were associated with moderate ACR (acute cellular rejection), ISHLT 2R and 3 cases (37.5%) with lipofuscin score 3 were associated with mild ACR ISHLT 1R, the differences being statistically significant, (p = 0.0001). Lipofuscin grades 2 and 3 were associated with severe fibrosis in 6 cases (35.3%) and 2 cases (25.0%), respectively (p = 0.042). A statistically significant association between the degree of damage to the intramyocardial small vessels and the amount of intracytoplasmic lipofuscin was observed (p = 0.00014). Discussion: Our study revealed that lipofuscin was more frequently associated with CAV, fibrosis, and damaged small vessels. Oxidative stress influences lipofuscinogenesis and CAV, which leads to endothelial dysfunction and neointimal hyperplasia, which over time will produce progressive narrowing of the vascular lumen and dysfunction of the cardiac allograft. Of the total number of 19 cases with CAV, 17 (89.47%) presented a lipofuscin score of 2 or 3 concomitantly with CAV, (p = 0.0001). This could mean that lipofuscin is not a harmless degradation product. At the same time, the association of a large number of cases with lipofuscin score 2, 10 cases (58.8%) with insignificant CAV could lead to the idea of using lipofuscin as a potential biomarker in the early diagnosis of CAV. Conclusions: We evidenced a significant association between the amount of intracytoplasmic lipofuscin and CAV. Accordingly, lipofuscin might be involved in the pathogenesis of CAV. Further research is needed to clarify the exact mechanisms of this association. Full article

(This article belongs to the Special Issue Molecular Diagnostics in Cardiovascular Diseases: From Biomarkers to Individualized Medicine)

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22 pages, 673 KB

Open AccessArticle

Biomarker-Based Prediction of Treatment Outcomes in Pediatric Intussusception: A Retrospective Cohort Study

by Karla Pehar, Danijela Jurić, Kristina Jurković and Marko Bašković

Diagnostics 2026, 16(15), 2431; https://doi.org/10.3390/diagnostics16152431 (registering DOI) - 1 Aug 2026

Abstract

Background/Objectives: Intussusception is a common pediatric emergency characterized by bowel telescoping, often leading to ischemia, necrosis, and perforation if untreated. Early identification of prognostic biomarkers could improve management strategies. This study aimed to evaluate the association between admission biomarkers and treatment outcomes [...] Read more.

Background/Objectives: Intussusception is a common pediatric emergency characterized by bowel telescoping, often leading to ischemia, necrosis, and perforation if untreated. Early identification of prognostic biomarkers could improve management strategies. This study aimed to evaluate the association between admission biomarkers and treatment outcomes in children with intussusception, to identify potential predictors. Methods: A retrospective analysis was conducted on 141 pediatric patients diagnosed with intussusception over ten years. Patients were stratified into three groups based on treatment outcome: spontaneous resolution, hydrostatic reduction, or surgery. Data collected included demographic, clinical, radiological, and laboratory parameters. Results: Among the cohort, 34% experienced spontaneous resolution, 27.7% underwent hydrostatic reduction, and 38.3% required surgery. Biomarkers such as erythrocyte count, hemoglobin, hematocrit, and platelets differed significantly across groups. Multivariate analysis identified erythrocyte count, platelet count, and potassium as variables independently associated with surgical management. Lower erythrocyte counts, higher platelet counts, and lower potassium were associated with increased likelihood of surgical intervention. The erythrocyte count, platelet count, and serum potassium showed ROC AUCs of 0.64, 0.65, and 0.70, respectively. Conclusions: Admission erythrocyte count, platelet count, and serum potassium were independently associated with the need for surgery but each showed only modest standalone discrimination. They are therefore best regarded as candidate variables for multivariable or composite predictive models rather than as standalone, clinically actionable triage markers. Further prospective studies are warranted to validate their incremental value within such models. Full article

(This article belongs to the Special Issue Diagnosis and Prognosis of Abdominal Diseases)

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12 pages, 1840 KB

Open AccessArticle

An Interpretable Multi-Objective Machine Learning Framework for In Silico Prioritization of Anti-Staphylococcus aureus Antimicrobial Peptides

by Jianguo Xu, Donghua Yang, Qingyong Zheng, Tengfei Li, Yating Cui and Jinhui Tian

Diagnostics 2026, 16(15), 2430; https://doi.org/10.3390/diagnostics16152430 (registering DOI) - 1 Aug 2026

Abstract

Background: Staphylococcus aureus, including methicillin-resistant lineages, is a leading cause of device- and catheter-related infection, and rising resistance motivates the search for antimicrobial peptides (AMPs) with strong anti-staphylococcal activity and low host toxicity. Machine learning can prioritize candidate peptides. However, the [...] Read more.

Background: Staphylococcus aureus, including methicillin-resistant lineages, is a leading cause of device- and catheter-related infection, and rising resistance motivates the search for antimicrobial peptides (AMPs) with strong anti-staphylococcal activity and low host toxicity. Machine learning can prioritize candidate peptides. However, the literature-derived AMP datasets are prone to homology-driven optimism, and computational studies frequently overstate their translational reach. Methods: We curated 4007 deduplicated S. aureus-active AMP records and 582 binary-labeled hemolysis records. Each peptide was encoded with a transparent 538-dimensional physicochemical and compositional feature vector. Five classifiers and five regressors were evaluated for four endpoints (potency classification, log₁₀ MIC regression, hemolysis classification, normalized hemolytic index) under both conventional random 5-fold cross-validation and homology-aware cross-validation, in which sequences were clustered by 3-mer similarity and whole clusters were confined to single folds. Class imbalance was handled by class weighting. Model behavior was interpreted with SHAP and Fisher-exact k-mer enrichment, and candidates were ranked by a multi-objective score that combines the independently trained heads. Results: Under homology-aware validation, performance was lower than under random splitting, as expected. Potency classification reached an AUROC of about 0.71 (Random Forest), compared with 0.797 under random cross-validation. Hemolysis classification remained strong at AUROC 0.90 (95% CI 0.88 to 0.93), which indicates that its high accuracy is not a homology leakage artifact. MIC regression was modest (homology-aware R² 0.17, Spearman ρ 0.39) and is therefore treated only as a rank-ordering signal. SHAP and k-mer analyses recovered interpretable structure–activity relationships. Net positive charge and amphipathicity drove potency, whereas bulk hydrophobicity drove hemolysis. Applying the pipeline to a generated pool prioritized 20 candidates. Nearest-neighbor analysis shows that these are close optimized variants of known potent scaffolds, with a median identity of 95% to a known peptide, rather than novel sequences. Conclusions: We present an interpretable, honestly benchmarked multi-objective pipeline that optimizes known anti-S. aureus AMP scaffolds toward lower predicted hemolysis. The prioritized peptides are computational hypotheses for future synthesis and experimental testing. Their low predicted hemolysis reflects a selection criterion rather than validated safety, and cross-species selectivity was not assessed. Full article

(This article belongs to the Special Issue Artificial Intelligence in Epidemiological Diagnostics: Advances and Applications)

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19 pages, 6171 KB

Open AccessArticle

High-Dimensional Immune Profiling Reveals Innate-Adaptive Rebalancing and Subpopulation Trajectories in Pediatric Severe Mycoplasma pneumoniae Pneumonia

by Chen Shen, Deze Li, Xiaotong Wang, Yang Sun, Huiwen Zheng, Hao Chen, Xin Ni and Shunying Zhao

Diagnostics 2026, 16(15), 2429; https://doi.org/10.3390/diagnostics16152429 (registering DOI) - 31 Jul 2026

Abstract

Background: Severe Mycoplasma pneumoniae pneumonia (SMPP) presents with heterogeneous clinical complications and imaging manifestations, including pleural effusion (PE), bronchiolitis obliterans (BO), and distinct imaging/bronchoscopic phenotypes. The precise systemic immune subpopulation dynamics underlying these distinct phenotypes remain poorly defined. Methods: We conducted [...] Read more.

Background: Severe Mycoplasma pneumoniae pneumonia (SMPP) presents with heterogeneous clinical complications and imaging manifestations, including pleural effusion (PE), bronchiolitis obliterans (BO), and distinct imaging/bronchoscopic phenotypes. The precise systemic immune subpopulation dynamics underlying these distinct phenotypes remain poorly defined. Methods: We conducted flow cytometric profiling of peripheral blood mononuclear cells (PBMCs) from pediatric patients to compare mild MPP (MMPP-N) and severe MPP subtypes. SMPP patients were stratified into subgroups including those with BO (SMPP&BO, n = 3), PE (SMPP&PE), and three imaging/bronchoscopic phenotypes: Group A (SMPP-GA, mucous plugs), Group B (SMPP-GB, mucosal necrosis), and Group C (SMPP-GC, diffuse bronchiolitis). Composite immune indices and multi-marker discriminant analysis were constructed for secondary analysis. Results: Comprehensive high-dimensional profiling suggested that a fundamental innate-adaptive immune rebalancing may represent a key pathophysiological axis in severe disease. Patients with PE exhibited massive CD16⁻ monocyte expansion (Delta = 40.0%) coupled with CD8⁺ Teff collapse (Delta = −9.2%). Preliminary data also suggest BO may be marked by CD56⁻CD11C⁺ monocyte depletion (Delta = −23.1%, n = 3), warranting further validation. Imaging subgroup profiling revealed that SMPP-GC featured major B-cell maturation alterations (HLADR⁺CD45RA^high expansion and CD38⁺CD25^low depletion). Composite indices including the Adaptive Exhaustion Score suggested discriminatory power (AUC = 0.90 for PE vs. uncomplicated SMPP). The Innate-Adaptive Ratio increased progressively with severity (Spearman rho = +0.40, p = 0.0002). Conclusions: SMPP is not immunologically uniform. Innate-adaptive rebalancing underlies complication-specific phenotypes: inflammatory monocyte mobilization with adaptive exhaustion is strongly associated with PE, whereas B-cell maturation alterations characterize diffuse bronchiolitis. These findings identify potential biomarker candidates for patient stratification, though small-cohort observations require extensive validation in larger prospective studies. Full article

(This article belongs to the Special Issue Accurate Diagnosis and Management of Infectious and Respiratory Diseases)

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23 pages, 8380 KB

Open AccessArticle

PCA-Enhanced Deep Features for Alzheimer’s Disease Stage Classification with EFMM

by Marwa Mawfaq Mohamedsheet Al-Hatab, Ruaa H. Ali Al-Mallah, Maysaloon Abed Qasim, Mohammed Falah Mohammed, Taha H. Rassem and Abdulghani Ali Ahmed

Diagnostics 2026, 16(15), 2428; https://doi.org/10.3390/diagnostics16152428 - 31 Jul 2026

Abstract

Background/Objectives: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder necessitating accurate and timely diagnosis for effective clinical intervention. While deep learning methods have shown promise in AD classification, many rely on computationally intensive architectures and high-dimensional feature representations. This study introduces a [...] Read more.

Background/Objectives: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder necessitating accurate and timely diagnosis for effective clinical intervention. While deep learning methods have shown promise in AD classification, many rely on computationally intensive architectures and high-dimensional feature representations. This study introduces a lightweight hybrid framework combining deep feature extraction, dimensionality reduction, and adaptive classification for MRI-based Alzheimer’s disease stage classification. Methods: Utilizing MRI images from a publicly available Alzheimer’s disease dataset encompassing four clinical stages (Non-Demented, Very Mild Demented, Mild Demented, and Moderate Demented), deep features were extracted using a pre-trained SqueezeNet model as a fixed feature extractor, generating 1000-dimensional feature vectors. Due to the computational complexity and for the improvement of the model efficiency, the dimensionality reduction technique, Principal Component Analysis (PCA) was then applied. This resulted in an optimum representation of 100 principal components, retaining about 96% of the variance. Then, the performances of various machine learning classifiers such as k-Nearest Neighbors (kNN), Support Vector Machine (SVM), Decision Tree (DT), Neural Network (NN), Naïve Bayes (NB), Logistic Regression (LR) and Enhanced Fuzzy Min–Max Neural Network (EFMM) were tested. The accuracy, precision, recall, F1-score, area under the receiver operating characteristic curve (AUC), and confusion matrices were used to evaluate the performance. Stratified 5-fold cross validation was used to ensure the strength of our results. Results: The findings show that PCA has a significant improvement in classification accuracy for most of the models. In particular, the EFMM classifier outperformed the other classifiers, with an accuracy of 97.19% on the independent test set. After PCA, the AUC values for classes such as Mild Demented, Moderate Demented, Non-Demented and Very Mild Demented were obtained as 97.12%, 99.97%, 93.79% and 95.26% respectively. We further validated our proposed framework using stratified 5-fold cross validation which further corroborated the robustness of our proposed framework. The EFMM achieved a mean accuracy of 98.38% ± 0.36 and a mean macro-F1 score of 98.48% ± 0.43. Friedman statistical testing demonstrated that there were significant differences between the performance of the classifiers evaluated (p < 0.001), which further validated the performance of the EFMM. Conclusions: To sum up, the proposed SqueezeNet–PCA–EFMM is an effective and efficient method for Alzheimer’s disease stage classification under MRI images. The combination of SqueezeNet, PCA, and EFMM—led not only to high classification performance, but also to good cross validation results. Furthermore, this property of incremental learning is the intrinsic one of the EFMM and renders this framework interesting for its incorporation in the next-generation intelligent clinical decision supports in particular, as medical care evolves. Full article

(This article belongs to the Special Issue Artificial Intelligence in Alzheimer’s Disease Diagnosis—2nd Edition)

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25 pages, 4242 KB

Open AccessArticle

A Robust Dual-Stage Learning-Based Pipeline for Multiclass Segmentation of Multiple Sclerosis Lesions in MRI

by Reza Naghne, Mahdiyeh Rahmani, Ali Kazemi, Mostafa Abdolghaffar, Tina Anjomshoa, Niusha Ghadesi, Abolfazl Zamanirad, Asra Karami, Ebrahim Najafzadeh and Parastoo Farnia

Diagnostics 2026, 16(15), 2427; https://doi.org/10.3390/diagnostics16152427 - 31 Jul 2026

Abstract

Background: Accurate segmentation and classification of multiple sclerosis (MS) lesions are vital for a reliable diagnosis and disease monitoring. However, lesion heterogeneity in size, location, and intensity poses significant challenges to automated analysis. Methods: To address this, we developed a dual-stage [...] Read more.

Background: Accurate segmentation and classification of multiple sclerosis (MS) lesions are vital for a reliable diagnosis and disease monitoring. However, lesion heterogeneity in size, location, and intensity poses significant challenges to automated analysis. Methods: To address this, we developed a dual-stage pipeline integrating deep learning (DL) for precise spatial delineation and machine learning (ML) for robust classification of MS lesions. Two advanced DL models, nnU-Net and UNETR++, were optimized for lesion segmentation. Moreover, UNETR++ and several conventional ML methods were considered for the classification task, and Random Forest was found to be the best choice. Results: Experimental results indicate that nnU-Net outperformed UNETR++ for lesion segmentation across all cases, achieving a maximum improvement of 12.8%. During classification, Random Forest consistently outperformed advanced DL models, achieving at least 12% higher performance. Under practical conditions, an optimized hybrid pipeline that integrates nnU-Net for precise segmentation with Random Forests for robust classification delivers the best overall performance. Furthermore, qualitative analysis indicates that some apparent false positives may correspond to lesions missed during annotation, highlighting potential limitations in ground truth labeling. Conclusions: Overall, the proposed pipeline effectively leverages the complementary strengths of DL and ML, offering a promising, accurate framework for automated MS lesion analysis with potential clinical utility. Full article

(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)

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17 pages, 13655 KB

Open AccessArticle

Routine MRI Signal Intensity as a Surrogate of Subchondral Bone Healing: Validation Against Micro-CT and Histology in an Ovine Model

by Felix R. M. Koenig, Veronika Janacova, Markus Schreiner, Marlene Stuempflen, Vladimir Juras, Pavol Szomolanyi, Raoul Varga, Gregor Wollner, Janina M. Patsch, Giuseppe Filardo, Ali Guermazi and Siegfried Trattnig

Diagnostics 2026, 16(15), 2426; https://doi.org/10.3390/diagnostics16152426 - 31 Jul 2026

Abstract

Background/Objectives: To test whether routine T1-weighted spin-echo (T1-SE) and proton-density fast spin-echo (PD-FSE) MRI signal intensity (SI) can index bone regeneration after osteochondral scaffold implantation by correlating MRI metrics with micro-CT and histology. Methods: Twenty-eight sheep with bilateral trochlear defects were evaluated in [...] Read more.

Background/Objectives: To test whether routine T1-weighted spin-echo (T1-SE) and proton-density fast spin-echo (PD-FSE) MRI signal intensity (SI) can index bone regeneration after osteochondral scaffold implantation by correlating MRI metrics with micro-CT and histology. Methods: Twenty-eight sheep with bilateral trochlear defects were evaluated in separate cohorts at 30, 180, and 365 days (n = 7, 11, and 10, respectively). One knee received a tri-layered resorbable scaffold; the contralateral defect was left empty. MRI (T1-SE, PD-FSE) was read by two blinded musculoskeletal radiologists using 10-point Likert scales (T1: apparent mineralization; PD: SI normalization). Contrast-to-noise ratio (CNR) between repair-bone and reference bone was computed. MRI measures were correlated with micro-CT (new bone volume; trabecular bone volume) and histology (ICRS subchondral bone reconstruction; new bone; filling). Results: Likert ratings on both T1-SE and PD-FSE correlated with micro-CT new bone volume and trabecular bone volume and with histological measures of repair. PD-FSE CNR was inversely associated with micro-CT new bone volume and trabecular bone volume (both p < 0.001), indicating lower CNR with greater bone regeneration, whereas T1-SE CNR showed no significant associations. Inter-reader agreement was excellent (ICC 0.947 individual; 0.973 average), with good-to-excellent intra-reader reliability (0.920–0.963). Conclusions: Reader-based Likert assessment on both sequences and PD-FSE CNR provide complementary, non-invasive markers of subchondral bone regeneration, supporting MRI for radiation-free follow-up and endpoint selection in future translational studies. T1-SE CNR did not track incremental mineralization and should not be used as a stand-alone quantitative marker in early healing. Full article

(This article belongs to the Special Issue Advanced Imaging for Diagnosis and Management of Musculoskeletal Disorders)

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14 pages, 877 KB

Open AccessArticle

Quantifying User Satisfaction: Weighted Metric Approach for Evaluating Deep Learning-Based Thigh MRI Segmentations

by Falko Ensle, Ilker Özgür Koska, Nina Derron, Cagan Koska, Ulf Bach, Philipp Nikolaus Maintz, Marta Porta-Vilarό, Jonas Kroschke, Philipp Gerber and Roman Guggenberger

Diagnostics 2026, 16(15), 2425; https://doi.org/10.3390/diagnostics16152425 - 31 Jul 2026

Abstract

Background: The aim of this paper is to develop a clinically useful benchmark signature of deep learning (DL)-based MRI segmentations and objectively predict user satisfaction based on a weighted combination of multiple performance metrics. Methods: This post hoc analysis of a prospective study [...] Read more.

Background: The aim of this paper is to develop a clinically useful benchmark signature of deep learning (DL)-based MRI segmentations and objectively predict user satisfaction based on a weighted combination of multiple performance metrics. Methods: This post hoc analysis of a prospective study analyzed MRI data from 68 patients (29.4 ± 5.6 years; 45% female) acquired during a randomized clinical trial. Fat fraction maps of axial Dixon MRI were used to segment six classes of the thigh. Two radiologists qualitatively scored DL-based segmentations using a 5-point Likert scale. A hybrid deep learning model (MobileNetV2 and DINOv2) was developed to predict Likert scores directly from MRI slices and segmentation maps. Additionally, a weighted combination of quantitative metrics (Dice score, Hausdorff distance, Jaccard index) was determined to best correlate with the Likert scores. Statistical analyses included Cohen’s kappa, Spearman correlation, and regression model performance (MAE, RMSE, ROC_AUC). Results: Interreader agreement for Likert scores was near-perfect (κ = 0.82). The DINOv2 model achieved lower MAE (0.2343) and RMSE (0.1129) than MobileNetV2 (0.3488 and 0.431, respectively) in predicting Likert scores. The weighted metric combination model, using Lasso regression, predicted Likert = 5 with 84.1% accuracy, 100% recall, and ROC_AUC of 0.824. Individual metrics showed weak-to-moderate correlation with Likert scores, with Dice and Jaccard indices for extensor intramuscular fat exhibiting the highest correlation (r = 0.37 and r = 0.34, respectively). Conclusion: The proposed DL-based model accurately predicted radiologist-assigned Likert five scores, while the weighted metric combination model aligned closely with user satisfaction, offering a practical alternative to manual validation for clinical adoption of automated segmentation tools. Full article

(This article belongs to the Special Issue Innovations in Diagnostic Radiology: AI, Advanced Imaging and Precision Medicine)

17 pages, 952 KB

Open AccessReview

The Role of Sex Hormone Receptors in the Squamous Cell Carcinoma of the Uterine Ectocervix: A Review and Future Directions

by Mun-Kun Hong and Dah-Ching Ding

Diagnostics 2026, 16(15), 2424; https://doi.org/10.3390/diagnostics16152424 - 31 Jul 2026

Abstract

Cervical cancer (CxCa) remains a major global gynecological malignancy causally linked to high-risk human papillomavirus (HPV) infection. However, HPV alone is insufficient for carcinogenesis; sex hormones and their receptors serve as essential cofactors. This review aims to synthesize current knowledge on the role [...] Read more.

Cervical cancer (CxCa) remains a major global gynecological malignancy causally linked to high-risk human papillomavirus (HPV) infection. However, HPV alone is insufficient for carcinogenesis; sex hormones and their receptors serve as essential cofactors. This review aims to synthesize current knowledge on the role of cervical histoarchitecture and hormonal microenvironments in ectocervical squamous cell carcinoma (SCC), and to explore how receptor-mediated signals contribute to malignant transformation and metastatic spread. The review examines the expression patterns of estrogen receptor α (ERα) and progesterone receptor (PR) in the uterine cervix, which is a hormone-responsive tissue. It discusses how these receptors fluctuate throughout the menstrual cycle and evaluates evidence from HPV-transgenic mouse models and human tissue analyses. The findings converge on a compelling model: stromal ERα drives pro-carcinogenic paracrine signaling, epithelial PR suppresses neoplastic transformation, and stromal PRB confers antimetastatic protection. These insights highlight the complex interplay between hormonal signals and SCC development in the ectocervix. Future therapeutic exploitation of these mechanistic insights—including selective estrogen receptor modulators, selective progesterone receptor modulators, and PR status-guided chemoprevention—holds considerable promise. This review provides a coherent framework for translating laboratory findings into clinical diagnostics and targeted interventions. Full article

(This article belongs to the Special Issue Diagnostic Advances in Obstetrics and Gynecology, Breast Disease and Women’s Health)

18 pages, 2154 KB

Open AccessArticle

Integrative Clinical and Functional Characterization of the TCF7L2 rs7903146 Variant Reveals Regulatory Mechanisms Linking Genetic Susceptibility to Oxidative Stress in Type 2 Diabetes

by Ahmed M. Ahmed, Hakeemah H. Al-Nakhle, Amjad M. Yousuf, Hamza M. A. Eid, Abdel Rahim M. Muddathir, Awadh S. Alsubhi, Hashim M. Aljohani, Renad M. Alhamawi, Mustafa Y. Taher, Faisal Almalki, Kholoud Ashour and Yahya A. Almutawif

Diagnostics 2026, 16(15), 2423; https://doi.org/10.3390/diagnostics16152423 - 31 Jul 2026

Abstract

Background: The transcription factor 7-like 2 (TCF7L2) gene is one of the strongest genetic determinants of type 2 diabetes mellitus (T2DM), with the rs7903146 (C > T) polymorphism consistently associated with impaired insulin secretion and glucose dysregulation. This study investigated the [...] Read more.

Background: The transcription factor 7-like 2 (TCF7L2) gene is one of the strongest genetic determinants of type 2 diabetes mellitus (T2DM), with the rs7903146 (C > T) polymorphism consistently associated with impaired insulin secretion and glucose dysregulation. This study investigated the associations between the TCF7L2 rs7903146 polymorphism, glycemic control, oxidative stress biomarkers, and T2DM susceptibility, integrating bioinformatic analyses to explore the functional significance of this variant. Methods: This case–control study included 200 patients with T2DM, 100 prediabetic individuals, and 120 healthy controls. Genotyping of rs7903146 was performed using TaqMan SNP assays. Biochemical analyses included fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), lipid profile, and oxidative stress biomarkers, including superoxide dismutase (SOD), glutathione peroxidase (GPx), total antioxidant capacity (TAC), and malondialdehyde (MDA). Bioinformatic analyses included population frequency analysis, regulatory annotation, chromatin accessibility assessment, expression quantitative trait locus (eQTL) analysis, protein interaction network construction, and pathway enrichment analyses to investigate the functional consequences of rs7903146. Results: The T allele frequency was markedly higher in T2DM patients (33.5%) and prediabetic individuals (30%) than in controls (13.3%) (p < 0.001). T2DM susceptibility increased under allelic (OR = 3.27, 95% CI: 2.14–5.01), dominant (OR = 3.9, 95% CI: 2.37–6.42), and recessive (OR = 6.92, 95% CI: 1.59–30.07) models (p < 0.01). T2DM patients also showed significantly lower superoxide dismutase (SOD) and glutathione peroxidase (GPx) activities, lower total antioxidant capacity (TAC), and higher MDA levels (p < 0.001). T allele carriers had poorer glycemic control and greater oxidative stress. Bioinformatic analyses showed that rs7903146 resides within an active intronic regulatory region with chromatin accessibility, enhancer-associated histone marks, transcription factor occupancy, and candidate cis-regulatory elements. eQTL analyses showed tissue-specific effects on TCF7L2 expression, while network and pathway analyses highlighted WNT signaling, β-catenin transcriptional complexes, and metabolic regulation and oxidative stress pathways. Conclusions: The TCF7L2 rs7903146 polymorphism was significantly associated with T2DM susceptibility, impaired glycemic regulation, and altered oxidative stress biomarkers. Bioinformatic analyses provided predictive evidence suggesting that rs7903146 may have tissue-specific regulatory relevance and may be indirectly linked to metabolic and WNT/β-catenin signaling pathways. However, because of the observational case–control design, these findings do not establish causality, and the proposed regulatory mechanisms require experimental validation. Full article

(This article belongs to the Section Clinical Laboratory Medicine)

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