Nevin Manimala

BMC Med Inform Decis Mak. 2025 Jun 3;25(1):204. doi: 10.1186/s12911-025-03034-3.

ABSTRACT

BACKGROUND: Fatigue is a prevalent and debilitating symptom of non-communicable diseases (NCDs); however, its biological basis are not well-defined. This exploratory study aimed to identify key biological drivers of fatigue by integrating metabolomic, microbiome, and genetic data from blood and saliva samples using a multi-omics approach.

METHODS: Metabolomic, microbiome, and single nucleotide polymorphisim analyses were conducted on saliva and blood samples from 52 patients with NCDs. Fatigue dimensions were assessed using the Multidimensional Fatigue Inventory and correlated with biological markers. LightGBM, a gradient boosting algorithm, was used for fatigue prediction, and model performance was evaluated using the F1-score, accuracy, and receiver operating characteristic area under the curve using leave-one-out cross-validation. Statistical analyses included correlation tests and multiple comparison adjustments (p < 0.05; false discovery rate <0.05). This study was approved by the Yokohama City University Hospital Ethics Committee (F230100022).

RESULTS: Plasmalogen synthesis was significantly associated with physical fatigue in both blood and saliva samples. Additionally, homocysteine degradation and catecholamine biosynthesis in the blood were significantly associated with mental fatigue (Holm p < 0.05). Microbial imbalances, including reduced levels of Firmicutes negativicutes and Patescibacteria saccharimonadia, correlated with general and physical fatigue (r = – 0.379, p = 0.006). Genetic variants in genes, such as GPR180, NOTCH3, SVIL, HSD17B11, and PLXNA1, were linked to various fatigue dimensions (r range: -0.539-0.517, p < 0.05). Machine learning models based on blood and salivary biomarkers achieved an F1-score of approximately 0.7 in predicting fatigue dimensions.

CONCLUSION: This study provides preliminary insights into the potential involvement of alterations in lipid metabolism, catecholamine biosynthesis disruptions, microbial imbalances, and specific genetic variants in fatigue in patients with NCDs. These findings lay the groundwork for personalized interventions, although further validation and model refinement across diverse populations are needed to enhance the prediction performance and clinical applicability.

PMID:40462080 | DOI:10.1186/s12911-025-03034-3

BMC Pulm Med. 2025 Jun 3;25(1):279. doi: 10.1186/s12890-025-03747-1.

ABSTRACT

BACKGROUND: This study aimed to evaluate the diagnostic efficacy of nanopore sequencing for Mycobacterium tuberculosis (MTB) drug resistance in respiratory specimens from pulmonary tuberculosis (PTB) patients. It compared it to the Xpert MTB/RIF and fluorescent polymerase chain reaction (PCR) melting curve to explore the validity and feasibility of detecting MTB drug resistance in respiratory specimens.

METHODS: This study retrospectively analyzed 52 respiratory specimens. The proportional method applied the phenotypic drug susceptibility test (pDST) to respiratory specimens. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), consistency statistic (kappa) with phenotypic drug susceptibility testing (pDST), and the area under the curve (AUC) from the receiver operating characteristic (ROC) curve were calculated for nanopore sequencing, Xpert MTB/RIF, and fluorescent PCR melting curve. These calculations used the pDST results as the reference standard.

RESULTS: Among the resistance mutation genes detected by nanopore sequencing, rpoB, and katG were the most frequent, followed by embB, rpsL, gyrA, inhA, ahpC, gyrB, gid, and rrs. In bronchoalveolar lavage fluid (BALF) specimens, nanopore sequencing showed high sensitivity (100.00%,90.32%,82.35%,82.35%,100.00%,76.92%), specificity (70.00%,81.82%,88.00%,96.00%93.75%,93.10%0.100.00%), and AUC values (0.85,0.86,0.85, 0.89,0.97,0.85) for rifampicin (RIF), isoniazid (INH), ethambutol (EMB), streptomycin (SM), levofloxacin (LFX), moxifloxacin (MFX). Nanopore sequencing exhibited good detection efficacy (kappa value ≥ 0.70) and perfect diagnostic resistance value (AUC value ≥ 0.85). For RIF, nanopore sequencing showed Kappa values of 0.01 and 0.38 and AUC values of 0.02 and 0.18 higher than the Xpert MTB/RIF and fluorescent PCR melting curve, respectively; for INH, nanopore sequencing had a higher Kappa value of 0.65 and a higher AUC value of 0.32 than the fluorescent PCR melting curve. Nanopore sequencing provided superior overall performance.

CONCLUSION: Nanopore sequencing has significant technical advantages and clinical application potential in detecting MTB drug resistance. Its rapid and highly accurate detection capabilities support early diagnosis and personalized treatment of drug-resistant MTB. As the technology continues to mature and the cost is further reduced, it is expected that nanopore sequencing technology will play a more important role in MTB resistance detection.

PMID:40462071 | DOI:10.1186/s12890-025-03747-1

BMC Health Serv Res. 2025 Jun 3;25(1):794. doi: 10.1186/s12913-025-12704-x.

ABSTRACT

BACKGROUND: Recognising the diverse healthcare needs of the population, there is a growing emphasis on tailoring hospital discharge processes to address the unique challenges faced by individuals who are homeless, aiming to enhance the efficiency and effectiveness of post-hospitalisation care for this vulnerable demographic. This study aimed to evaluate the costs and consequences of specialist hospital discharge and intermediate care (support after discharge) services for people who are homeless in England.

METHODS: We estimated the comparative costs and consequences of different types of specialist care provided by 17 homeless hospital discharge and intermediate care services. We compared ‘clinically-led’ (multidisciplinary) services with those that were ‘housing-led’ (uniprofessional). A retrospective observational study was conducted to estimate effectiveness and costs for two’intervention groups'(clinically-led and housing-led) and a previously published RCT for’standard care’. Use of resources data for specialist care was sourced through linkage with Hospital Episode Statistics. The measure of effectiveness was the number of bed days avoided (in terms of hospital stays for all readmissions in the follow-up period) per homeless user. Additional secondary analysis of three services looked at quality-adjusted life years (QALYs) and service delivery costs. The perspective adopted was NHS in England.

RESULTS: Data from the comparative analysis showed that specialist homeless hospital discharge (HHD) care is likely to be cost-effective compared with standard care. Patients accessing specialist care use fewer bed days per year (including both planned and unplanned readmissions). Patients using specialist care have more planned readmissions to hospital and, overall, use more NHS resources than those who use standard care. We interpret this as a positive outcome indicating that specialist care is likely to work more effectively than standard care to improve access to healthcare for this marginalised group. Specialist care remained cost-effective over a range of sensitivity analyses. Secondary analyses of three specific schemes found better QALY outcomes, but results are not generalisable to all 17 schemes.

CONCLUSION: Specialist HHD services are likely to be cost-effective for the NHS compared with standard care, although further research is needed to access patient level data for both costs and outcomes to conduct a rigorous statistical analysis between groups and address possible underlying biases due to data coming from non-randomised study design.

PMID:40462065 | DOI:10.1186/s12913-025-12704-x

BMC Oral Health. 2025 Jun 3;25(1):896. doi: 10.1186/s12903-025-06194-w.

ABSTRACT

OBJECTIVE: The aim of this study was to evaluate the adequacy of responses provided by experts and artificial intelligence-based chatbots (ChatGPT-4.0 and Microsoft Copilot) to frequently asked orthodontic questions, utilizing scores assigned by patients and orthodontists.

METHODS: Fifteen questions were randomly selected from the FAQ section of the American Association of Orthodontists (AAO) website, addressing common concerns related to orthodontic treatments, patient care, and post-treatment guidelines. Expert responses, along with those from ChatGPT-4.0 and Microsoft Copilot, were presented in a survey format via Google Forms. Fifty-two orthodontists and 102 patients rated the three responses for each question on a scale from 1 (least adequate) to 10 (most adequate). The findings were analyzed comparatively within and between groups.

RESULTS: Expert responses consistently received the highest scores from both patients and orthodontists, particularly in critical areas such as Questions 1, 2, 4, 9, and 11, where they significantly outperformed chatbots (P < 0.05). Patients generally rated expert responses higher than those of chatbots, underscoring the reliability of clinical expertise. However, ChatGPT-4.0 showed competitive performance in some questions, achieving its highest score in Question 14 (8.16 ± 1.24), but scored significantly lower than experts in several key areas (P < 0.05). Microsoft Copilot generally received the lowest scores, although it demonstrated statistically comparable performance to other groups in certain questions, such as Questions 3 and 12 (P > 0.05).

CONCLUSIONS: Overall, the scores for ChatGPT-4.0 and Microsoft Copilot were deemed acceptable (6.0 and above). However, both patients and orthodontists generally rated the expert responses as more adequate. This suggests that current current chatbots does not yet match the theoretical adequacy of expert opinions.

PMID:40462054 | DOI:10.1186/s12903-025-06194-w

BMC Oral Health. 2025 Jun 3;25(1):889. doi: 10.1186/s12903-025-06143-7.

ABSTRACT

BACKGROUND: The prevalence of dentin hypersensitivity (DH) differed significantly among previous reports, which may confuse clinicians and public health practitioners. This study aimed to identify which survey methods contributed to the difference in reported DH prevalence.

METHODS: A systematic search was performed in Medline, Embase, ProQuest, CNKI, and ClinicalTrial.gov databases up to November 2022. Two authors extracted the basic characteristics and survey methods independently. A random-effect meta-analysis was performed to estimate the effects of survey methods on estimated DH prevalence. The Newcastle-Ottawa Scale (NOS) was employed to appraise the methodological quality of the studies included in the analysis.

RESULTS: Thirty-nine studies were included. The average estimate of DH prevalence was 32% (95% CIs: 27 – 37%). The statistical heterogeneity was very high among studies (I² = 99.7%, P < 0.001), especially in the field of survey methods. Variables were observed in sampling approaches, study settings, and inclusion criteria. Besides, clinical examination protocols and reporting of inter-examiner reliability remained inconsistent. Meta-regression analysis showed that the DH prevalence might be underestimated when the clinical examinations were conducted only for participants with positive subjective symptoms (P = 0.001). The included studies scored 5.74 ± 1.7 on the NOS, indicating relatively low methodological quality. The lower study quality was primarily attributed to insufficient elaboration on representativeness of the exposed cohort, comparability of cohorts on the basis of the design or analysis controlled for confounders, and follow-up procedures.

CONCLUSION: The included studies demonstrated substantial heterogeneity in survey methods. Conducting clinical examinations for all participants enhanced detection rates. The reliability of our pooled prevalence estimates was substantially compromised due to the studies’ low methodological quality and high heterogeneity. It is recommended to propose the instructive detailed guideline to standardize the design and improve the quality of studies.

PMID:40462051 | DOI:10.1186/s12903-025-06143-7

J Psychiatr Res. 2025 May 24;188:243-251. doi: 10.1016/j.jpsychires.2025.05.057. Online ahead of print.

ABSTRACT

Existing evidence suggested a potential link between mental health problems in children and adolescents and an increased odds of developing gaming disorder (GD). However, the relationship between emotional and behavioral problems (EBP) and GD remains unknown. This cross-sectional study, involving a sample size of 201,906 students aged 6-18 years from Guangzhou city, aims to investigate this association. The assessment of GD was performed using the Gaming Disorder Test, while EBP was evaluated via parent-reported Strength and Difficulty Questionnaire. Statistical analyses, including multiple logistic regression, subgroup analyses, and sensitivity analyses, were employed to examine the association between EBP and GD. The prevalence rate of GD was 11.4 %, with higher rates observed among adolescents and boys. After adjusting for covariates, children and adolescents with border or abnormal levels of total difficulties, internalizing problems, externalizing problems, emotional symptoms, conduct problems, hyperactivity/inattention problems, and pro-social behaviors exhibited a significantly increased odds of developing GD. This study suggests that Chinese children and adolescents with EBP may be more vulnerable to developing GD. Further longitudinal researches are needed to better understand this association.

PMID:40460467 | DOI:10.1016/j.jpsychires.2025.05.057

Int J Pediatr Otorhinolaryngol. 2025 May 29;195:112404. doi: 10.1016/j.ijporl.2025.112404. Online ahead of print.

ABSTRACT

OBJECTIVES: Peripheral vestibular disease primarily involves the part of the inner ear that controls balance and may affect the physical and psychological well-being of children. Peripheral vestibular disease can be challenging to assess in children due to the difficulty of patients with verbalization of symptoms, variety of clinical presentations, and the involvement of other organ systems of balance. This cross-sectional study aimed to identify clinical factors that are associated with vertigo and migraine in pediatric patients.

METHODS: The clinical records of 292 children seen at the specialty clinic for an assessment of dizziness were reviewed for demographic variables, medical history, imaging, and audiovestibular symptoms and tests. Standard statistical testing was performed.

RESULTS: Logistic regression analysis showed that having abnormal MRI findings (odds ratio [OR] = 0.74; p = 0.001), a previous referral diagnosis of “nystagmus” (OR = 0.58; p = 0.04), attention deficit hypersensitivity or autism spectrum disorder (OR = 0.70; p = 0.007), and migraine (OR = 0.71; p = 0.0004) were associated with a less likely diagnosis of peripheral vertigo. On the other hand, cardiovascular conditions (OR = 2.64; p = 0.02) were associated with migraine in patients with vertigo.

CONCLUSION: Our findings suggest that thorough evaluation for neurologic and cardiovascular disorders is important in order to improve diagnosis and management of vertigo and dizziness in children.

PMID:40460462 | DOI:10.1016/j.ijporl.2025.112404

JMIR Diabetes. 2025 Jun 3;10:e70380. doi: 10.2196/70380.

ABSTRACT

BACKGROUND: Adherence to type 1 diabetes mellitus (T1DM) treatment regimens decreases during adolescence. While comorbid depression and health insurance disparities are individually known to potentiate this risk, technological devices for T1DM appear to be protective.

OBJECTIVE: We examined whether technology use impacted the association between depression and poorer health outcomes in T1DM. Given established insurance-based disparities based on technology access, we also studied whether the protective effects of T1DM technology differed among publicly and privately insured youth.

METHODS: Data were prospectively collected from pediatric patients with T1DM across 3 California medical centers. We used linear and negative binomial regression analyses to examine whether technology use was related to diabetes outcomes and whether this differed based on depression status (technology-by-depression interaction) and health insurance type (technology-by-insurance interaction).

RESULTS: Across 1573 patients aged 12 to 25 years (mean age 15.9, SD 2.9 years; n=1050, 66.4%, non-Hispanic White; n=745, 47.0% female), those with a depression diagnosis had higher hemoglobin A1c (HbA1c; mean 9.1%, SD 2.1% vs 10.1%, SD 2.2%) and more frequent diabetic ketoacidosis (DKA) events per year (mean 0.10, SD 0.36 vs 0.24, SD 0.66) than those without (P=.003). Patients using both a continuous glucose monitor (CGM) and pump had lower HbA1c levels and fewer DKA events per year (mean HbA1c 8.2%, SE 0.1%; mean DKA events per year 0.05, SE 0.01) than those using one device (mean HbA1c 9.0%, SE 0.1%; mean DKA events 0.08, SE 0.1%) or none (mean HbA1c 10.0%, SE 0.1%; mean DKA events 0.19, SE 0.1%; P<.001). While youth with public insurance had significantly higher HbA1c levels than those with commercial insurance (mean 9.3%, SD 2.1% vs 9.0%, SD 2.0%, P<.001), those using a CGM had no reliable decrease in HbA1c compared to their commercially insured peers (P=.35).

CONCLUSIONS: Technology use in pediatric T1DM appears protective for both youth with a history of depression and those who are publicly insured. These data underscore the importance of universal access to technology to mitigate disparities based on comorbid mental health issues and differential access to care.

PMID:40460446 | DOI:10.2196/70380

JMIR Serious Games. 2025 Jun 3;13:e67250. doi: 10.2196/67250.

ABSTRACT

BACKGROUND: Age-related physiological changes in older adults involve a rapid decline in motor exercise ability; some older adults may also experience difficulties in maintaining focus, memory loss, and a decline in reaction time, which consequently impair their ability to perform dual tasks. Motor-cognitive training (MCT) refers to a blend of motor activity and cognitive training that occurs simultaneously and can assist older adults in enhancing their physical function, cognitive abilities, and dual-task performance. In recent years, the use of technology for delivering MCT has become increasingly popular in research. This has been achieved through various technologies that simplify MCT for older adults.

OBJECTIVE: This study aimed to systematically examine the feasibility and effectiveness studies on technology-assisted MCT among older adults.

METHODS: This rapid review was conducted following the updated PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 standards, and the Synthesis Without Meta-analysis (SWiM) in systematic reviews reporting guideline. Four databases were searched, including CINAHL, Embase, PubMed, and Scopus, from January 2013 to March 2025. Search strategies were constructed based on three main topics: (1) older adults, (2) MCT, and (3) technology. Inclusion criteria followed the population, intervention, comparator, outcome, and study design framework as follows: older adults (population); technology-assisted MCT (intervention); standard treatment control, active control, partial intervention control, placebo control, and dose-response control (comparator); various measures of physical, cognitive, and dual-task performance (outcome); and randomized controlled trials (RCTs) and pilot RCTs (study design). The Cochrane Risk of Bias Tool was applied for quality appraisal of the included studies. The feasibility of the included studies was assessed using completion rates and attrition rates. Descriptive statistics were used to describe the demographic and clinical characteristics of the groups, while narrative methods were used to categorize and synthesize their effectiveness.

RESULTS: In total, 20 studies were included, comprising 16 RCTs and 4 pilot RCTs, most of which were conducted within a 6-week period. Each session typically lasted between 10 and 30 minutes and was held 2 to 3 times per week. Feasibility analysis showed that technology-assisted MCT was generally feasible. While the workload was high, the perceived usability was also high, with a considerable amount of positive feedback and very few reported adverse events. The types of MCT varied in terms of components, duration, and frequency. The majority of studies (18/20, 90%) demonstrated statistically significant improvements in physical, cognitive, and dual-task performance because of technology-assisted MCT.

CONCLUSIONS: The feasibility of technology-assisted MCT among older adults was high regardless of the perceived high workload, and most studies showed statistical effectiveness in improving physical, cognitive, and dual-task performance.

TRIAL REGISTRATION: Open Science Foundation (OSF) Registries 10.17605/OSF.IO/5SRCQ; https://osf.io/5srcq.

PMID:40460432 | DOI:10.2196/67250

J Med Internet Res. 2025 Jun 3;27:e71169. doi: 10.2196/71169.

ABSTRACT

BACKGROUND: Parkinson disease (PD) presents motor and nonmotor challenges that significantly affect quality of life. Telemedicine has emerged as a promising approach to deliver interventions, including exercise performed through remote equipment (e-Exercise), cognitive behavioral training sessions conducted remotely (e-Cognitive), and consultations conducted through remote devices (e-Visits), yet their comparative effectiveness remains unclear.

OBJECTIVE: This paper aimed to evaluate the effectiveness of telemedicine interventions on motor and nonmotor outcomes in PD and compare the efficacy of e-Exercise, e-Cognitive, and e-Visits.

METHODS: A systematic review and network meta-analysis were conducted by searching PubMed, MEDLINE, Embase, Cochrane CENTRAL, and Web of Science through November 2024. Randomized controlled trials comparing telemedicine interventions with usual care were included. Outcomes assessed included total motor symptoms, quality of life, cognitive function, depressive and anxiety symptoms, fear of falling, 6-minute walk test, walking velocity, balance ability, and timed up and go. Two investigators independently performed study selection, data extraction, and risk-of-bias assessment using the Cochrane risk of bias 2 tool. Data synthesis included (1) pairwise meta-analyses using random-effects models to calculate standardized mean differences (SMDs) and mean differences; and (2) Bayesian network meta-analysis integrating direct and indirect comparisons to rank intervention efficacy, with transitivity and inconsistency evaluated. Evidence quality was graded using GRADE (Grading of Recommendations, Assessment, Development and Evaluation), incorporating risk of bias, heterogeneity (I²>50% indicating substantial heterogeneity), precision, and publication bias (Egger test). Statistical heterogeneity was quantified by τ² and I².

RESULTS: A total of 23 studies involving 1330 participants were included. Pairwise meta-analyses demonstrated that telemedicine significantly improved total motor symptoms (SMD=-0.61, 95% CI -1.19 to -0.4), cognitive function (SMD=0.58, 95% CI 0.15-1.01), depressive symptoms (SMD=-0.46, 95% CI -0.88 to -0.04), anxiety symptoms (SMD=-0.57, 95% CI -1.10 to -0.03), fear of falling (SMD=-0.48, 95% CI -0.77 to -0.19), and 6-minute walk test performance (mean difference=18.98, 95% CI 16.06-21.90 meters). The network meta-analysis revealed that e-Exercise was most effective for improving total motor symptoms (SMD=-1.01, 95% credible interval [CrI] -1.96 to -0.05) and 6-minute walk test performance. e-Cognitive was most effective for enhancing quality of life (SMD=0.39, 95% CrI 0.06-0.73) and cognitive function (SMD=1.02, 95% CrI 0.38-1.66), and reducing depressive (SMD=-1.28, 95% CrI -1.61 to -0.96) and anxiety symptoms (SMD=-1.07, 95% CrI -1.40 to -0.75). e-Visits had a limited impact across outcomes. Evidence quality was moderate or high for motor symptoms, quality of life, and depression, but low or very low for other outcomes.

CONCLUSIONS: Telemedicine is effective for improving motor and nonmotor outcomes in PD. e-Exercise is optimal for motor function and physical performance, while e-Cognitive is most effective for psychological and cognitive challenges. These findings highlight the importance of tailoring telemedicine programs to address specific therapeutic needs in PD management.

TRIAL REGISTRATION: PROSPERO CRD42024628687; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024628687.

PMID:40460428 | DOI:10.2196/71169