Background: Congenital heart disease (CHD) is a cardiac condition present from birth, contributing to ~28 % of all birth defects, and causing higher fetal and neonatal mortality worldwide. Complete blood count (CBC) is a routine diagnostic tool in clinical settings and has been suggested to be predictive of cardiovascular diseases and other metabolic disorders. This study investigates the correlation between CBC indices and CHD.

Methods: We analyzed pre-operative CBC data from 238 CHD patients and 50 healthy controls. Statistical analyses, including the Student’s t-test, chi-square test, and multivariate logistic regression, were employed to identify significant deviations and correlations.

Results: Our findings revealed that ~ 79% (11 out of 14) of CBC parameters differed significantly from those of healthy controls. Notably, lymphocytosis and a reduced platelet-to-lymphocyte ratio (PLR) were observed consistently across all CHD cases (p = 0.000). Cyanotic patients exhibited erythrocytosis and higher hemoglobin levels despite their tendency towards anemia (p = 0.000). Multivariate regression analysis demonstrated robust correlations: hematocrit was strongly associated with both hemoglobin (r = 0.92) and SpO₂ (r = -0.76), while red blood cell (RBC) counts correlated closely with hematocrit (r = 0.88), hemoglobin (r = 0.83), and SpO₂ (r = -0.78). Elevated pulse rates, platelet counts, and lymphocyte levels, coupled with lower body mass index (BMI), mean corpuscular volume (MCV), hemoglobin, and mean corpuscular hemoglobin (MCH), could facilitate early CHD diagnosis (p < 0.05). Additionally, reduced mean corpuscular hemoglobin concentration (MCHC) levels were linked to shorter ventilation times (p = 0.0004).

Conclusion: Our study underlines the significant associations between CBC indices and CHD in a North Indian cohort, highlighting the potential of CBC parameters for the early diagnosis and management of CHD. Our findings suggest that specific CBC alterations are closely linked to the severity and type of CHD, offering valuable insights for improving patient care and outcomes.

Abstract

Introduction

The integration of Artificial Intelligence (AI) into telemedicine represents a transformative advancement in the delivery of remote healthcare services. In rural communities of Nepal, geographical difficulties have deprived many adequate health facilities. To address this problem, this paper explores the synergistic potential of AI to enhance telemedicine by improving diagnostic accuracy, personalizing patient care, and optimizing healthcare resource management.

Methods:

The proposed framework incorporates machine learning techniques in telemedicine. The survey was conducted in a remote village and data were collected from 250 people. Data consist of different parameters, such as age, alcohol consumption, coughing, chest pain, and shortness of breath. The paper compares and examines machine learning algorithms, such as Naive Bayes, Support Vector, and Random Forest, to predict lung cancer disease. The result is evaluated using accuracy and k-fold cross-validation.

Results:

The result shows that Random Forest exhibits higher accuracy (95.4%) and Naive Bayes exhibits lower accuracy (76.2%). The finding shows that people in their 50s, 60s, or 70s who consume more alcohol have the highest chances of having lung cancer.

Conclusions: By providing a comparison among different machine learning techniques, this paper aims to inform healthcare professionals, policymakers, and technologists about the critical role of AI in shaping the future of telemedicine and to offer actionable insights for effectively integrating these machine learning technologies. With this, the people of remote villages will benefit and the diagnosis will be simplified. However, there are limitations to data privacy and misinformation. In the future, new techniques such as deep learning neural networks and big data techniques can be integrated into telemedicine with image processing capabilities to enhance the role of AI in telemedicine.

Keywords: artificial intelligence(AI); telemedicine; remote healthcare; health data integration; health records; rural community

Inflammatory bowel disease (IBD) treatment remains challenging due to the unpredictable therapeutic responses observed in patients with Crohn’s disease and ulcerative colitis. In this analysis, we explore a review of combining single-cell RNA sequencing (scRNA-seq) and microbial metabolomics to identify biomarkers predictive of therapeutic response. scRNA-seq allows for detailed gene expression analysis of immune cells, such as T cells and macrophages, within intestinal biopsies, providing insights into cellular drivers of inflammation and potential treatment outcomes. Concurrently, microbial metabolomics analyzes gut-derived metabolites like short-chain fatty acids (SCFAs) and bile acids, which influence immune modulation and therapeutic efficacy. This integrated approach offers a highly specific, dual-layered method for predicting patient responses to therapies such as TNF inhibitors and IL-23 blockers. The combination of these cutting-edge technologies allows for an unprecedented level of precision in predicting patient-specific treatment responses. Future research should focus on longitudinal studies to track these biomarkers before and after therapy initiation, validating their utility in large, multi-center trials with the potential to personalize IBD treatment and shift clinical practice towards precision medicine. This approach could dramatically shift the paradigm toward precision medicine in IBD, reducing treatment failures and improving patient outcomes by tailoring therapies to individual molecular and microbial profiles.

Tuberculosis (TB) continues to be a significant worldwide infectious disease, causing substantial illness and fatalities. Prompt and precise diagnosis is essential for efficient treatment and management. Distinguishing between active tuberculosis (ATB) and latent tuberculosis (LTBI) is extremely difficult yet necessary for specific forms of treatment. The objective of this study is to discover and confirm diagnostic biomarkers that can differentiate between ATB and LTBI, thereby improving the accuracy of diagnosis and enhancing patient care. We employed high-throughput transcriptome and proteomic methods to examine samples from patients with active tuberculosis, latent tuberculosis infection, and healthy individuals. The techniques of RNA sequencing (RNA-Seq) and differential expression gene analysis were utilized to explore and characterize the patterns of gene expression. The investigation of differential expression was conducted utilizing Bioconductor packages in R (DESeq2). Our investigation has found a group of biomarkers that have unique expression profiles for active tuberculosis and latent tuberculosis infection. The expression levels of important genes such as IFNG, TNF, and IL6 were markedly increased in patients with active tuberculosis compared to those with latent tuberculosis infection and the control groups. This indicates the presence of an active inflammatory response that is characteristic of active tuberculosis disease. In contrast, biomarkers such as TCF7 and IL10 were discovered to be increased in patients with latent tuberculosis infection, indicating a connection with immune regulation and the continued presence of the virus in a dormant state. This study identifies potential biomarkers that can accurately distinguish between active and latent tuberculosis, thereby aiding in the development of more accurate diagnostic and treatment strategies for tuberculosis.

Introduction: Myeloid-derived suppressor cells (MDSCs) are immature HLA‑DR^low/‑CD11b⁺CD33⁺ myeloid cells, which are elevated in various human disease states that involve abnormal haemopoiesis and act mainly through suppressing T-cell responses. They are divided into two subpopulations, the CD15⁺ (granulocytic) and the CD14⁺ (monocytic) cells. We have previously shown that the number and functionality of MDSCs in chronic idiopathic neutropenia (CIN) are altered, contributing to a possible primary bone marrow (BM) defect and to the pathogenesis of the condition. Moreover, MDSCs are proposed in a few studies to take part in ageing, in concordance with the novel theory of inflammageing. Thus, we further suggest that, in healthy individuals, their numbers increase with age through impaired myelopoiesis.

Methods: MDSC subsets were quantitated by flow cytometry in the peripheral blood mononuclear cells (PBMCs) of 70 healthy individuals (21-73 years old), using the combination of CD33PC7/CD15PC5/HLA-DRECD/CD14PE/CD11bFITC monoclonal antibodies and the Kaluza® analysis software. Statistical analysis was performed using the Spearman’s rank correlation coefficient and the GraphPad® software. The suppression of T-cell proliferation by MDSCs was estimated in five selected cases by comparing carboxy-fluorescein succinimidyl ester (CFSE) staining of the anti-CD3/anti-CD28-activated T-cells between PBMCs and CD33-depleted PBMCs after 3 days of culture.

Results: PMN-MDSCs (1.75% of PBMCs ± 2.55, mean±standard deviation) showed a statistically significant positive correlation with age (r=0.24, p=0.04), while neither M-MDSCs (3.97% of PBMCs ± 2.96) nor the total population of MDSCs (PMN-MDSCs plus M-MDSCs) (6.40% of PBMCs ± 2.17) showed a statistically significant correlation with age. MDSCs displayed the capacity to suppress T-cell proliferation, as was indicated by the T-cell generations in culture experiments in the presence or absence of MDSCs, irrespective of the age of the individual.

Conclusions: In conclusion, in our study population, PMN-MDSCs increase in older individuals, contributing to the process of ageing, while they retain their immunosuppressive capacity.

Introduction

Interdigital Pilonidal Sinus (IPNS), or barber’s disease, is a rare occupational condition where sharp clipped hair penetrates the webspace between fingers, causing a foreign body reaction. This study aimed to investigate the prevalence of IPNS among hair professionals in Bahrain and assess the role of hygiene practices in its prevention.

Materials and Methods

A cross-sectional study was conducted across the five governorates of Bahrain, involving 479 participants (253 male and 226 female) from 384 hair salons and barbershops selected through convenience sampling. Demographic data, including age, gender, hand dominance, work experience, type of work (barber or hairdresser), hygiene habits, and medical comorbidities, were collected via an interview-administered questionnaire.

Results

No cases of IPNS were identified among the participants. However, two male participants reported having Pilonidal Sinus (PNS) in the sacrococcygeal region. The majority of participants were aged between 26 and 45 (72.7%), with 52.8% reporting over 5 years of professional experience. Most participants were right-handed (89.1%). Only 1.9% of participants had diabetes, a known risk factor for IPNS. Regarding hygiene practices, 85.6% reported frequent handwashing, 69.5% used sanitizers, and 39.2% consistently used gloves.

Discussion

The absence of IPNS in our study, conducted during the COVID-19 pandemic, may be attributed to heightened hygiene practices, including frequent handwashing. Comparisons with regions where hygiene protocols vary or with other time periods, such as pre-pandemic, may yield different results. The low prevalence of diabetes in our population may have also contributed to the absence of IPNS.

Conclusion

Although no IPNS cases were found, this study highlights the importance of hygiene in preventing occupational diseases. Further longitudinal studies are recommended in order to explore IPNS risk factors and its potential association with hairdressing.

Introduction: Acute lymphoblastic leukemia (ALL) is the most common childhood malignancy. The cure rates for ALL are remarkably high (90%). This has been achieved due to chemotherapy protocols based on high doses of drugs. Unfortunately, this is associated with adverse effects of therapy in almost 75% of patients. Therefore, biomarkers that could indicate a higher risk of adverse effects are being searched for so that they can be prevented. miRNAs have recently been explored as such potential markers.

Material and Methods: A systematic review of scientific articles available in the PubMed, WOS, Medline and Google Scholar databases was conducted using the following keywords: “miRNA”, “chemotherapy toxicity”, “acute lymphoblastic leukemia”. Only full-text articles from 2014-2024 about children were included. We analyzed 21 studies.

Results: miRNAs are a good potential diagnostic, prognostic and predictive marker in ALL. Moreover, overexpression of miR-29b (AUC=0.75) and miR-499 (AUC=0.82) is useful in identifying patients at high risk of cardiomyopathy after anthracycline treatment and as an early marker of myocardial damage. Furthermore, some miRNAs have been associated with hepatotoxicity (miR-1208; OR=1.15), oral mucositis (miR-4268, OR=1.31; miR-1206; OR=3.6), hematotoxicity (miR-1206, OR=2.3; miR-323b, OR=0.36) and gastrotoxicity (miR-323b, OR=0.23; miR-4751, OR=12.38; miR-3117, OR=0.24) caused by methotrexate administration. Reduced expression of miR-24 (OR=0.43) also correlates with the toxicity of this drug at higher doses. In addition, changes in the expression and/or specific single-nucleotide polymorphisms of the target genes of miR-202 (OR=2.88), miR-4481 (OR=2.56), miR-3117, (OR=0.18) and miR-6067 (OR=0.58) correlate with vincristine neurotoxicity. Moreover, overexpression of miR-155 (rho=0.7) and reduced expression of miR-146a (rho=-0.67) are associated with gastrotoxicity after myeloablative conditioning before allogeneic hematopoietic stem cell transplantation.

Conclusions: The determination of changes in expression levels and/or single-nucleotide polymorphisms of target genes for specific miRNAs is a good potential tool for identifying patients at risk of developing complications during chemotherapy.

Abstract: Background: Abdominal tuberculosis comprises all forms of tuberculosis that involve the gastrointestinal tract. Controversies exist regarding the surgical approach and timing and type of intervention for complicated forms of abdominal tuberculosis. The aim of this systematic review is to define the rate of surgical treatment, the type of surgical procedures performed and the role of minimally invasive surgery in the management of abdominal tuberculosis. Methods: The literature in MEDLINE, Scopus and Google Scholar and forward and backward citations for studies published between database inception and July 2022 were searched without language restrictions. All prospective and retrospective studies were included. The electronic database search yielded 2440 records. Additionally, eight records were identified through snowball searching. Following duplicate removal (45 duplicates found), 2403 records were screened for titles and abstracts. After screening for titles and abstracts and the exclusion criteria, 38 reports were included in this systematic review, including 27 retrospective studies and 11 prospective studies. The data extracted included the general and demographic characteristics of the studies, the diagnostic methods used, clinical presentation, site of involvement and details on surgical treatment. Results: In total, 2870 patients with a diagnosis of abdominal tuberculosis were included, and 1803 (63%) underwent a surgical procedure. The majority of patients underwent an open surgical procedure (95%). The most commonly performed procedures were adhesiolysis (21%) and small-bowel resection with primary anastomosis (21%). Conclusions: The results of this review suggest that whenever surgery is required, there is a tendency to perform open surgical procedures in patients with complicated abdominal tuberculosis, both in emergency and elective settings, despite advances in minimally invasive surgery. The study protocol was registered on PROSPERO (CRD42022354322).

Rationale:

There is no high-level-of-evidence data to support the general notion that a fat-free diet is beneficial to patients with gallstone disease. Herein, we assess the feasibility and safety of a randomized study to assess the effect of recommending a fat-free diet versus a balanced-WHO diet on the quality of life (QoL) in symptomatic patients with gallstones (RADIGAL-1) and in patients undergoing cholecystectomy for gallstone disease (RADIGAL-2).

Methods:

This is a multicenter, randomized, single-blind, parallel-arm, non-inferiority trial. Patients presenting with biliary colic or acute cholecystitis or undergoing cholecystectomy for gallstones are randomly assigned to recommending either a fat-free or a balanced WHO diet. A follow-up at 3 months will appraise patient adherence and outcomes. A validated quality-of-life questionnaire (GIQLI) will be administered both at baseline and during follow-up. A total of 136 patients will be recruited for RADIGAL-1 and 106 for RADIGAL-2 according to sample size calculation based on the mean clinically important difference of GIQLI scores.

Results:

The rate of recruitment in the participating centers is eight patients per month for RADIGAL-1 and twenty for RADIGAL-2. In RADIGAL-1, full compliance was recorded in 87.8% of the patients. Additionally, 2.4% of the patients followed the diet for more than 50% of the follow-up time, while 4.8% followed it for less than 50% of the time. In RADIGAL-2, full compliance was recorded in 88.3% of the patients. Moreover, 8.3% of the patients followed the diet for more than 50% of the follow-up time, and 3.3% followed it for less than 50% of the time. Drop-off rates are 2.4% for RADIGAL-1 and 1.7% for RADIGAL-2. No adverse events such as hospital admissions or biliary colic have occurred in excess in the control groups.

Conclusion:

These data support the safety and the feasibility of the RADIGAL trial (NCT06405906).

The integration of Artificial Intelligence (AI) into Optical Coherence Tomography (OCT) technology represents a novel frontier in the early diagnosis and treatment of gastrointestinal (GI) cancers, particularly esophageal and colorectal cancers. OCT, a high-resolution imaging modality that provides cross-sectional views of tissue microstructure, has shown promise in identifying dysplastic and early cancerous changes in the GI tract. When combined with AI-driven algorithms, OCT enables real-time automated analysis of tissue patterns, increasing diagnostic accuracy and reducing the likelihood of missed lesions. This AI-assisted technology is particularly effective in distinguishing between benign and malignant tissues, which can be challenging using traditional imaging techniques alone. As AI models continue to evolve, their ability to recognize subtle histopathological features can potentially reduce reliance on biopsies, speeding up the diagnostic process and facilitating immediate therapeutic interventions, such as endoscopic mucosal resection (EMR). However, future research is needed to further refine these AI algorithms and ensure their applicability across diverse patient populations. Additionally, cost-effective strategies must be developed to make this technology more accessible in routine clinical settings. The fusion of AI with OCT holds immense potential to revolutionize the management of early GI cancers, offering a pathway to more personalized and minimally invasive treatment options.