Category: Nevin Manimala

Clin Interv Aging. 2025 Aug 22;20:1305-1313. doi: 10.2147/CIA.S527660. eCollection 2025.

ABSTRACT

BACKGROUND: Enhanced Recovery After Surgery (ERAS) has been extensively applied across numerous surgical specialties. However, there remains a paucity of research regarding the implementation of ERAS in advanced age patients (≥75 years) who undergo InterTAN nail surgery for intertrochanteric femoral fractures (ITF). This study aimed to assess if our ERAS protocol improves satisfaction and clinical outcomes in such patients.

METHODS: This was a retrospective cohort study included advanced age patients who underwent InterTAN nail surgery. The ERAS group included patients who underwent surgery between January 2022 and December 2024, while the non – ERAS group consisted of those who had the same surgery between January 2019 and December 2023. Demographics, comorbidities, surgical details, ERAS compliance, outcomes, complications, and length of stay (LOS) were evaluated.

RESULTS: A total of 144 patients were included in the ERAS group and 135 in the non – ERAS group. Analysis of demographic data showed no statistically significant intergroup differences. ERAS compliance was 100%. There were no significant differences between the ERAS and non – ERAS groups in terms of operative side, anesthesia type, operating time, intraoperative blood loss, and postoperative Visual Analogue Scale scores. Moreover, 30 – day follow – up revealed no significant differences in readmission rates and mortality between the two groups. However, the LOS was significantly shorter in the ERAS group (5.68±2.34 days vs 6.54±2.04 days in the non – ERAS group; p = 0.03). The overall complication rate was also significantly lower in the ERAS group (10/144 vs 23/135; P < 0.01).

CONCLUSION: In this cohort of advanced age patients with ITF managed via our ERAS program, it was evidenced that this program is safe and can effectively reduce the LOS and the incidence of complications.

PMID:40874207 | PMC:PMC12380002 | DOI:10.2147/CIA.S527660

Open Forum Infect Dis. 2025 Aug 15;12(8):ofaf496. doi: 10.1093/ofid/ofaf496. eCollection 2025 Aug.

ABSTRACT

BACKGROUND: Amid the opioid epidemic in the United States, hepatitis C virus (HCV) infections are rising, with one-third of individuals with infection unaware due to the asymptomatic nature. This study aimed to develop and validate a machine learning (ML)-based algorithm to screen individuals at high risk of HCV infection.

METHODS: We conducted prognostic modeling using the 2016-2023 OneFlorida+ database of all-payer electronic health records. The study included individuals aged ≥18 years who were tested for HCV antibodies, RNA, or genotype. We identified 275 features of HCV, including sociodemographic and clinical characteristics, during a 6-month period before the test result date. Four ML algorithms-elastic net (EN), random forest (RF), gradient boosting machine (GBM), and deep neural network (DNN)-were developed and validated to predict HCV infection. We stratified patients into deciles based on predicted risk.

RESULTS: Among 445 624 individuals, 11 823 (2.65%) tested positive for HCV. Training (75%) and validation (25%) samples had similar characteristics (mean, standard deviation age, 45 [16] years; 62.86% female; 54.43% White). The GBM model (C statistic, 0.916 [95% confidence interval = .911-.921]) outperformed the EN (0.885 [.879-.891]), RF (0.854 [.847-.861]), and DNN (0.908 [.903-.913]) models (P < .0001). Using the Youden index, GBM achieved 79.39% sensitivity and 89.08% specificity, identifying 1 positive HCV case per 6 tests. Among patients with HCV, 75.63% and 90.25% were captured in the top first and first to third risk deciles, respectively.

CONCLUSIONS: ML algorithms effectively predicted and stratified HCV infection risk, offering a promising targeted screening tool for clinical settings.

PMID:40874186 | PMC:PMC12378832 | DOI:10.1093/ofid/ofaf496

Open Forum Infect Dis. 2025 Aug 18;12(8):ofaf499. doi: 10.1093/ofid/ofaf499. eCollection 2025 Aug.

ABSTRACT

Among patients with blastomycosis (n = 281), coccidioidomycosis (n = 1920), and histoplasmosis (n = 2180), 62% experienced diagnostic delays (mean 29 days). Patients who experienced delays incurred average excess healthcare costs of up to $15 648 (95% confidence interval: $8600-$22 695) compared with those without a delay. Earlier diagnosis may help reduce excess costs.

PMID:40874182 | PMC:PMC12378736 | DOI:10.1093/ofid/ofaf499

J Neuroophthalmol. 2025 Aug 28. doi: 10.1097/WNO.0000000000002393. Online ahead of print.

ABSTRACT

BACKGROUND: Multimodal artificial intelligence (AI) models have recently expanded into video analysis. In ophthalmology, one exploratory application is the automated detection of extraocular movement (EOM) disorders. This proof-of-concept study evaluated the feasibility of using Gemini 2.0 to recognize EOM abnormalities, identify the affected eye, and recognize specific movement limitations from publicly available, real-world clinical videos.

METHODS: We retrospectively collected 114 YouTube videos of EOM disorders, including cranial nerve (CN) palsies, internuclear ophthalmoplegia (INO), supranuclear disorders, nystagmus, and ocular myasthenia gravis (MG), alongside 15 control videos demonstrating normal EOMs. Videos were trimmed to include only the pertinent clinical examinations, and audio was removed to avoid diagnostic cues. Using a standardized zero-shot prompt, Gemini 2.0 analyzed each video via the Google AI Studio platform. Gemini 2.0 was evaluated based on its ability to provide the correct diagnosis, identify the affected eye, and recognize the specific movement limitation (if any). Descriptive statistics, Spearman correlations, and comparative analyses were used to assess performance.

RESULTS: Gemini 2.0 correctly identified the primary diagnosis in 43 of 114 videos, yielding an overall diagnostic accuracy of 37.7%. Diagnostic performance varied by condition, with the highest accuracies observed in third nerve palsy (81.1%), INO (80.0%), sixth nerve palsy (66.7%), and ocular MG (20.0%), whereas normal EOMs were correctly classified in 93.3% of cases. In misclassified cases, the correct diagnosis appeared in the differential diagnosis in 15.5% of instances. Laterality was correctly identified in 26.5% of eligible cases overall, 73.1% among correctly diagnosed cases vs. 9.6% in misclassified ones. Similarly, movement limitations were accurately identified in 30.3% of eligible cases overall, with a marked increase to 88.5% accuracy in correctly diagnosed cases compared to 9.6% in misclassified cases. Longer videos moderately correlated with longer processing time (ρ = 0.55, P < 0.001). Significant correlations were observed between correct diagnosis and correct laterality identification (ρ = 0.45, P < 0.001), correct diagnosis and correct movement limitation identification (ρ = 0.61, P < 0.001), and laterality and movement limitation (ρ = 0.51, P < 0.001). Processing time averaged 11.0 seconds and correlated with video length (ρ = 0.55, P < 0.001).

CONCLUSIONS: This proof-of-concept study demonstrates the feasibility of using Gemini 2.0 for automated recognition of EOM abnormalities in clinical videos. Although performance was stronger in overt cases, overall diagnostic accuracy remains limited. Substantial validation on standardized, clinician-annotated datasets is needed before clinical application.

PMID:40867040 | DOI:10.1097/WNO.0000000000002393

Crit Care. 2025 Aug 27;29(1):387. doi: 10.1186/s13054-025-05612-3.

ABSTRACT

BACKGROUND: As global populations age, the number of nonagenarians admitted to intensive care units (ICUs) is rising. Frailty, a multidimensional syndrome marked by diminished physiological reserves, has been associated with adverse outcomes in older ICU patients. However, evidence remains limited regarding its prognostic significance in nonagenarians, who represent a unique and rapidly growing subset of critically ill patients. This study aimed to evaluate the impact of frailty on in-hospital mortality and length of stay among nonagenarian ICU patients in Australia and New Zealand.

METHODS: We conducted a retrospective cohort study using data from the ANZICS Adult Patient Database, including nonagenarians admitted to 211 ICUs between 2017 and 2023 with documented Clinical Frailty Scale (CFS) scores. Patients were classified as frail (CFS ≥ 5) or non-frail (CFS < 5). Propensity score matching (1:1) was applied to adjust for confounders including age, sex, illness severity, admission type, and comorbidities. Outcomes included ICU and hospital mortality, and ICU and hospital lengths of stay (LOS). Statistical analyses included multivariable Cox regression, log-transformed logistic regression, and Fine Gray competing risks models.

RESULTS: Among 16,439 nonagenarians, 8220 patients were propensity matched. In the matched cohort, frailty was independently associated with increased hospital mortality (adjusted HR 1.352, 95% CI 1.192-1.534, p < 0.001) and ICU mortality (adjusted HR 1.242, 95% CI 1.044-1.440, p = 0.017). Each one-point increase in CFS score was associated with a 9% increase in the odds ratio of ICU mortality (OR 1.09, 95% CI 1.01-1.18, p = 0.026) and a 19% increase in the odds ratio of hospital mortality (OR 1.19, 95% CI 1.10-1.28, p < 0.001). Frailty was not associated with ICU LOS after adjustment (p = 0.739) but predicted prolonged hospital LOS (adjusted β = 1.051, 95% CI 1.033-1.070, p < 0.001).

CONCLUSIONS: Frailty is a strong, independent predictor of hospital mortality and prolonged hospitalization in critically ill nonagenarians, even after adjusting for illness severity and comorbidities. These findings support the incorporation of frailty assessment into early risk stratification and clinical decision-making in ICU settings, to facilitate goal-concordant care and optimize resource allocation for the very elderly.

PMID:40867013 | DOI:10.1186/s13054-025-05612-3

Nutr Metab (Lond). 2025 Aug 27;22(1):102. doi: 10.1186/s12986-025-00999-w.

ABSTRACT

BACKGROUND: The association of sugar sweetened beverages (SSBs) and coronary artery disease (CAD) has not been well-established in Asians, where SSBs are the leading ultra-processed food product.

OBJECTIVE: We aim to examine the association between SSBs and premature CAD (PCAD) in Iranian adults.

DESIGN: Case-control.

PARTICIPANTS: A multi-centric study of Iranians including 2006 PCAD and 1131 healthy individuals as control group.

MAIN OUTCOME MEASURES: Dietary intakes were assessed using a validated food frequency questionnaire (FFQ). SSBs consist of artificial juice and sugar -sweetened drinks. The PCAD was determined based on the results of angiography and the occlusion percent of vessels.

STATISTICAL ANALYSIS: The odds of PCAD across the quartiles of SSBs were assessed by binary logistic regression.

RESULTS: The mean (SD) age of participants and SSB consumption was 51.5 years and 46.9 g/d, respectively. In the fully-adjusted model, compared with participants in the first quartile, those in the fourth quartile had higher risk of PCAD (OR = 1.50, 95% CI: 1.12, 2.00; P trend = 0.044). Consistently, SSB consumption was directly associated with the severity of PCAD. The higher SSB consumption, the greater risk for the severe PCAD (OR Q4 vs. Q1 = 1.34, 95% CI: 1.06, 1.68; P < 0.001).

CONCLUSION: This study demonstrated that higher consumption of SSB might be associated with higher risk of PCAD. However, more prospective cohort studies are necessary to confirm this association.

PMID:40867011 | DOI:10.1186/s12986-025-00999-w

BMC Psychol. 2025 Aug 27;13(1):971. doi: 10.1186/s40359-025-03350-3.

ABSTRACT

BACKGROUND: Physical activity has numerous physical and psychological benefits for university students. The present study aims to analyze the influence of physical activity intensity on the variables of physical pain and hyper mental activity.

METHOD: A comparative, descriptive and exploratory design was used in this study. The sample comprises 1900 physical therapy undergraduate students, who were recruited from several universities in the south of Spain using convenience sampling. The International Physical Activity Questionnaire-Short Form, Chronic Pain Assessment Questionnaire and Mental Hyperactivity Questionnaire were used. A structural equation model has been developed. The proposed model analyzes the relationship between physical activity, bodily pain and hyper mental activity.

RESULTS: The model shows satisfactory fit across the different indices (Chi² = 2.853; Df = 5; IFI = 0.948, CFI = 0.903; NFI = 0.900; RMSEA = 0.069). Statistically significant differences were observed in the effect of physical activity intensity on hyper mental activity (p < 0.05). There are also significant differences of hyper mental activity on bodily pain between groups (p < 0.05). A relationship of hyper mental activity on bodily pain was observed for participants performing light-intensity physical activity (β = 0.642). Regarding the effect of physical activity on physical pain, no statistically significant differences between groups were found (p > 0.05). A positive effect between both variables was observed for moderate intensity (β = 0.006).

CONCLUSIONS: Physical activity has a very weak effect on mental hyperactivity, regardless of its intensity. On the other hand, mental hyperactivity significantly influences body pain. No significant effect was found between physical activity and body pain. In terms of applicability, strategies should be designed that integrate physical activity and emotional regulation strategies to prevent pain and reduce mental hyperactivity.

PMID:40867003 | DOI:10.1186/s40359-025-03350-3

Diabetol Metab Syndr. 2025 Aug 27;17(1):359. doi: 10.1186/s13098-025-01929-9.

ABSTRACT

BACKGROUND: The gut-retina axis, an emerging area of research, has uncovered the bidirectional link between the intestines and retina, offering new insights into ophthalmic disease management. Diabetic retinopathy (DR), a common diabetes complication with a digestive-related connection, lacks large-sample retrospective studies on the impact of gut microbiota-related diets. The association between the Dietary Index for Gut Microbiota (DI-GM) and DR requires further investigation.

METHODS: 1,285 diabetic patients from the National Health and Nutrition Examination Survey (NHANES) spanning the years 2009 to 2018 were analyzed. DI-GM, based on 14 foods or nutrients intake, served as the exposure variable. Associations were assessed via Spearman correlation, weighted logistic regression, restricted cubic spline (RCS) analysis, and subgroup analyses.

RESULTS: Spearman analysis revealed predominantly inverse correlations among DI-GM components. After adjusting for confounders, each 1-point increase in DI-GM was associated with a 12% lower DR risk (OR = 0.88, 95% CI 0.78-0.99, P = 0.039). The Q4 DI-GM exhibited a 67% reduced DR risk compared to Q1 (OR = 0.33, 95%CI 0.12-0.88, P = 0.028). RCS analysis identified a nonlinear dose-response relationship (P-nonlinearity < 0.01), with rapid risk reduction at DI-GM < 4 and diminishing returns thereafter. Subgroup analyses indicated that most subgroup associations showed no statistically significant differences (interaction P > 0.05), except for participants with long-standing diabetes, without hypertension and BMI < 25 (OR = 0.55, 95%CI: 0.33-0.93, P = 0.03).

CONCLUSIONS: Higher DI-GM scores are linked to lower DR risk, supporting dietary optimization (e.g., increased whole grains/vegetables, reduced processed meat) as a potential strategy for DR prevention through gut microbiota modulation. These findings advance gut-retina axis theory and provide actionable dietary guidelines for diabetes complications.

PMID:40867002 | DOI:10.1186/s13098-025-01929-9

Mol Neurodegener. 2025 Aug 27;20(1):93. doi: 10.1186/s13024-025-00882-5.

NO ABSTRACT

PMID:40866991 | DOI:10.1186/s13024-025-00882-5

Nutr Metab (Lond). 2025 Aug 27;22(1):101. doi: 10.1186/s12986-025-01000-4.

ABSTRACT

BACKGROUND: The coexistence of sarcopenia and obesity has been established as a pivotal factor driving the pathological progression of metabolic dysfunction-associated steatotic liver disease (MASLD). This study systematically evaluates the prevalence and risk of MASLD in patients with sarcopenic obesity (SO).

METHOD: A comprehensive literature search was conducted in PubMed, Cochrane Library, EMBASE, Web of Science and SCOPUS up to March 2025. All studies investigating the association between SO and MASLD were included in this meta-analysis. Two independent reviewers performed screening and data extraction. ORs and 95% CIs were calculated using random effect models. Subgroup analysis was used to identify the sources of heterogeneity. Heterogeneity was assessed using Cochran’s Q test and quantified via the I² statistic. Quality assessment and publication bias (by Funnel plots and Egger’s test) evaluation were also performed.

RESULTS: Thirteen studies involving 35,373 SO patients (from six countries) were included after screening. Odds ratios (ORs) of the included studies were combined by random effect model. The pooled results revealed that 63.4% of SO patients had MASLD. Compared to non-SO individuals, SO was significantly associated with an increased risk of MASLD (OR = 4.45, 95% confidence interval (CI): 2.57-7.72, P < 0.001). Females exhibited a higher MASLD risk than males (OR = 4.22, 95% CI: 2.10-8.50 vs. OR = 7.56, 95% CI: 2.39-23.92). Substantial heterogeneity was observed across pooled results and subgroups. Additionally, SO patients had a 2.34-fold higher risk of MASLD-related fibrosis than non-SO individuals (OR = 2.34, 95% CI: 1.78-3.08, P < 0.001).

CONCLUSION: SO may be closely associated with a high prevalence of MASLD and accelerated fibrosis progression. These findings highlight SO as a potential high-risk population for MASLD, underscoring the need for targeted screening and intervention strategies. However, more high-quality research with unified definitions and different races is needed.

PMID:40866987 | DOI:10.1186/s12986-025-01000-4