Nevin Manimala

BMC Nephrol. 2025 Aug 13;26(1):457. doi: 10.1186/s12882-025-04393-9.

ABSTRACT

BACKGROUND: To assess satisfaction and perspectives of adult hemodialysis (HD) patients on different vascular access (VA) types (AVF, AVG, CVC) by synthesizing quantitative studies using validated questionnaires, focusing on overall satisfaction, physical symptoms, social functioning, and complications.

METHODS: We systematically searched Medline, Web of Science, and Scopus for studies assessing adult HD patients’ perspectives on VA using structured questionnaires. Risk of bias was assessed using the Newcastle-Ottawa Scale. Meta-analysis was performed using a random-effects model across three pairwise comparisons: AVF vs. CVC, AVF vs. AVG, and CVC vs. AVG.

RESULTS: Of 1,253 records, 11 studies (n = 2910) met inclusion criteria. AVF patients had higher overall satisfaction compared to those with CVCs (MD: 7.06%, 95% CI: 2.98-11.14). Compared to AVG, AVF patients had higher overall satisfaction, though not statistically significant (MD: 5.12%, 95% CI: – 0.42 to 10.66; p = 0.069). Dissatisfaction with physical symptoms was significantly higher in AVF patients than in those with CVCs (MD: 8.76%, 95% CI: 4.19 to 13.34). Compared to CVC, AVF patients reported significantly lower dissatisfaction in both social functioning (MD: – 9.48%, 95% CI: – 15.98 to – 2.98) and dialysis-related complications (MD: – 10.08%, 95% CI: -12.66 to -7.50).

CONCLUSIONS: AVFs are associated with higher overall patient satisfaction compared to other VA types. While AVF patients experience more physical discomfort, this is outweighed by significantly greater satisfaction in areas such as social functioning and dialysis-related complications. These findings emphasize the importance of considering patient-reported outcomes when evaluating VA options in HD care.

CLINICAL TRIAL NUMBER: Not applicable.

PMID:40804373 | DOI:10.1186/s12882-025-04393-9

BMC Infect Dis. 2025 Aug 13;25(1):1012. doi: 10.1186/s12879-025-11430-3.

ABSTRACT

BACKGROUND: Tuberculosis (TB) is a top infectious disease killer worldwide. The susceptibility to infectious diseases, including tuberculosis, has been linked to several cytokine gene polymorphisms.

METHOD: A case-control study was conducted at Abu Anja Chest Hospital, Omdurman, Khartoum state, using PCR-RFLP in 200 Sudanese patients with pulmonary tuberculosis and 200 healthy controls between February 2018 and February 2021. Data analysis was done using the IBM SPSS software package version 20.0. (Armonk, NY: IBM Corp).

RESULT: The mutant and heterozygous genotypes of IL-12+16974 A/C polymorphism were associated with an almost four-fold [P-value <0.001 OR= 3.703(2.243- 6.115), 95% CI] increased risk of TB in the Sudanese population. No statistically significant differences were found in the genotype and allele frequencies of the IFN-γ+874T/A gene between patients and controls.

CONCLUSION: These findings suggest, for the first time in Sudan, the significant risk of TB in people carrying the mutant and heterozygous genotypes of IL-12+16974 A/C genes.

PMID:40804362 | DOI:10.1186/s12879-025-11430-3

BMC Neurol. 2025 Aug 13;25(1):340. doi: 10.1186/s12883-025-04361-8.

ABSTRACT

BACKGROUND: Stroke is a sudden focal neurological deficit caused by vascular damage to the central nervous system. Globally, stroke is a leading cause of death and disability, with a particularly significant burden in low- and middle-income countries. In Iran, the incidence of acute stroke is increasing, and the age of onset is lower compared to developed countries. This study examines factors causing pre-hospital delays in acute stroke patients at Shahid Rajaei Hospital, Tonekabon, North of Iran (2022-2023). Timely intervention is critical for improving outcomes, as delays significantly affect treatment effectiveness. This study aims to identify the primary causes of pre-hospital delays in acute stroke patients and provide actionable insights to enhance timely intervention strategies, ultimately improving patient outcomes.

METHODS: A retrospective descriptive-analytical study was conducted on 150 acute stroke patients using census sampling. Data included demographics, symptoms, and time intervals from onset to hospital arrival. Analysis was performed with SPSS using chi-square, T-tests, and ANOVA.

RESULTS: Of the 150 patients, 81.3% arrived over 4.5 hours after symptom onset, missing the thrombolytic treatment window. Statistical analysis revealed significant associations between some demographic and clinical factors: shorter distances to the hospital and faster arrival (p = 0.037), presence of a witness (p = 0.041), and stroke onset during the daytime (p = 0.002) were linked to reduced delays. Marital status also influenced arrival times significantly (p = 0.007). Other delay factors included unawareness of stroke symptoms (46%), being alone (14.7%), and symptoms occurring during sleep (8.6%).

CONCLUSIONS: The study highlights the need for public education on stroke symptoms and improved emergency systems to reduce delays. Addressing these gaps can enhance patient outcomes, especially in areas with limited awareness and resources.

PMID:40804361 | DOI:10.1186/s12883-025-04361-8

Sci Rep. 2025 Aug 13;15(1):29629. doi: 10.1038/s41598-025-14804-4.

ABSTRACT

Extreme events in turbulent flows are rare, fast excursions from typical behavior that can significantly impact systems performance and reliability. Predicting such events is challenging due to their intermittent nature and rare occurrence, which limits the effectiveness of data-intensive methods. This paper, therefore, introduces a novel data-driven approach for on-the-fly early-stage prediction of extreme events in time signals. The method identifies the most energetic time-only POD mode of an ensemble of time segments leading to extreme events in a signal. High similarity between incoming signals and the computed mode serves as an indicator of an approaching extreme event. A support vector machine is employed to classify the signals as preceding an extreme event or not. This approach is fully data-driven and requires minimal training data, making it particularly suitable for significantly rare events. The method is applied to predict extreme dissipation events in a wall-bounded shear flow at different Reynolds numbers and wall distances, demonstrating robust performance across a range of intermittency levels. Even with limited training data, leading to an imperfect representation of the extreme event statistics, the method provides predictions at lead times that match and usually exceed the timeframe for which the Hankel-DMD method remains accurate. This opens up the possibility of using the conditional POD method to flag incoming extreme events so that potentially unreliable forecasts from signal prediction methods, such as Hankel-DMD, can be discarded or their forecasting horizon shortened.

PMID:40804352 | DOI:10.1038/s41598-025-14804-4

Sci Rep. 2025 Aug 13;15(1):29657. doi: 10.1038/s41598-025-14688-4.

ABSTRACT

Norovirus is a highly contagious virus and the leading cause of acute gastroenteritis worldwide. The World Health Organization (WHO) estimates that approximately 685 million cases of norovirus infection occur each year, with around 200 million affecting children under the age of five. The impact of this virus is substantial, contributing to roughly 200,000 deaths annually-about 50,000 of which are among young children-mostly in low-income countries. In addition to the human toll, norovirus imposes a significant economic burden, with global costs reaching approximately $60 billion each year due to healthcare expenses and lost productivity. In this paper, we present a fractional-order mathematical analysis of the norovirus epidemic model, focusing on its transmission dynamics, incorporating memory effects. The total population, denoted as N(t), is categorized into four compartments: susceptible, exposed, infected, and recovered. We analytically derive the equilibrium points and the basic reproduction number of the model. Furthermore, we discuss the properties of positivity, boundedness, uniqueness, and existence to ensure the model’s validity. The non-linear model is linearized around its equilibrium points, and local stability is analyzed using the eigenvalues of the Jacobian matrix. In addition, global stability is examined using the Lyapunov function and LaSalle’s invariance principle. To validate the theoretical findings, a numerical scheme based on the GL-Non-Standard Finite Difference (NSFD) method is developed, which serves to verify the theoretical analysis of the norovirus epidemic model.

PMID:40804347 | DOI:10.1038/s41598-025-14688-4

Nat Med. 2025 Aug 13. doi: 10.1038/s41591-025-03880-8. Online ahead of print.

ABSTRACT

Paranoia is a distressing and prevalent symptom in schizophrenia spectrum disorders. Virtual reality-based cognitive behavioral therapy for paranoia (VR-CBTp) has been proposed to augment behavioral interventions by providing controlled and safe virtual environments in which social situations inducing paranoid anxiety can be manipulated, allowing for new therapeutical possibilities such as gradual exposure and repetition. This assessor-masked, randomized parallel group superiority trial investigated the efficacy of VR-CBTp compared to standard CBTp. Participants were randomized to receive ten sessions of VR-CBTp or CBTp, both on top of treatment as usual. Intention-to-treat analyses included 254 participants (VR-CBTp: n = 126, CBTp: n = 128). Outcomes were assessed at baseline, treatment cessation and follow-up (6 months after treatment cessation). The primary outcome was Ideas of Persecution subscale from the Green Paranoid Thoughts Scale, measured at treatment cessation. There was not a statistically significant between-group difference on the primary outcome at endpoint (effect estimate: 2% in favor of VR-CBTp; 95% confidence interval: -11% to +17%; Cohen’s d = 0.04; P = 0.77, based on exponentiated log-transformed data). No deaths or violent incidents involving law enforcement occurred during the study. In conclusion, VR-CBTp was not superior to CBTp in reducing schizophrenia-spectrum-disorders-related paranoia. ClinicalTrials.gov registration: NCT04902066 .

PMID:40804323 | DOI:10.1038/s41591-025-03880-8

Sci Rep. 2025 Aug 13;15(1):29632. doi: 10.1038/s41598-025-14701-w.

ABSTRACT

Oxidative stress, an imbalance between reactive oxygen species and antioxidants, contributes to chronic diseases. Almonds, rich in vitamin E, polyphenols, and monounsaturated fats, exhibit antioxidant potential, though their overall effects on oxidative biomarkers are unclear. This systematic review and meta-analysis evaluate almond supplementation’s impact on these biomarkers in adults. Following PRISMA guidelines, PubMed, Scopus, and Web of Science were searched up to January 2025. Randomised controlled trials (RCTs) and crossover trials assessing biomarkers of antioxidant and oxidation status (e.g., malondialdehyde [MDA], superoxide dismutase [SOD], glutathione peroxidase [GPx], 8-hydroxy-2′-deoxyguanosine [8-OHdG], uric acid [UA]) were included. Risk of bias was evaluated using the Cochrane Tool, and random-effects models calculated weighted mean differences (WMDs) with 95% confidence intervals (CIs). Eight studies (5 RCTs, 3 crossover trials; n = 424) were included. Almond doses of > 60 g/day significantly reduced MDA (WMD = -0.46, p = 0.002), 8-OHdG (WMD = -5.83, p < 0.001), and UA (WMD = -0.64, p = 0.009), while increasing SOD (WMD = 2.02, p = 0.008). No effect was found for GPx (p = 0.270). High heterogeneity (I² = 92-96%) indicated variability in study design, dosage, and population. Almond supplementation (> 60 g/day) significantly improves oxidation status by reducing MDA, 8-OHdG, and UA while enhancing SOD activity. These findings support almonds as a functional food for oxidation management. However, high heterogeneity underscores the need for standardized trials to confirm optimal dosage, duration, and conditions. Trial registration: Prospero-CRD42025646264.

PMID:40804320 | DOI:10.1038/s41598-025-14701-w

Sci Rep. 2025 Aug 13;15(1):29758. doi: 10.1038/s41598-025-15070-0.

ABSTRACT

Nicotine pouches are becoming increasingly popular. However, there’s still a lack of comprehensive data on how widespread nicotine pouch use and its side effects in Saudi Arabia. This study aims to investigate the prevalence and associated side effects of the use of nicotine pouches among smokers and the public in Saudi Arabia. This study also investigated their utilization in smoking cessation. This study used an online cross-sectional questionnaire-based design. The study population included individuals over the age of 18 living in Saudi Arabia. The questionnaire was distributed through social media platforms. Statistical analysis was conducted using SPSS software. Descriptive statistics were used to generate means and percentages. Regression analysis was performed to predict factors associated with the use of nicotine pouches for the purpose of smoking cessation. A total of 657 participants were included in the analysis. Regarding age distribution, the majority were aged between 18 and 30 years. Most participants were male (422; 64.2%). Regarding the prevalence of nicotine pouches use, (21.2%) had tried the pouches before. Among those who had used nicotine pouches, 57 participants (41.0%) reported success in quitting smoking, while 53 participants (38.1%) experienced only a little success, and 29 participants (20.9%) were unsuccessful. The most common adverse effect was nausea (88, 13.4%), followed by fatigue (44, 6.7%) and headache (43, 6.5%). Participants who smoked 4-6 cigarettes per day, 7-9 cigarettes per day, or more than 10 cigarettes per day had higher odds of nicotine pouch use (OR = 3.70,95% CI = 1.14-11.96, p = 0.02), (OR = 6.74,95% CI = 1.71-26.5, p = 0.006) and (OR = 2.59,95% CI = 1.07-6.26, p = 0.03). This study showed a promising result of the use of nicotine pouches and success in quitting smoking in Saudi Arabia population. Most of the side effects reported in the study were mild. However, future studies with larger sample size and analytical design are needed.

PMID:40804318 | DOI:10.1038/s41598-025-15070-0

Sci Rep. 2025 Aug 13;15(1):29645. doi: 10.1038/s41598-025-12296-w.

ABSTRACT

Tracking the development of disability conditions presents significant challenges due to uncertainty, imprecision, and dynamic health progression patterns. Traditional multi-criteria decision-making (MCDM) techniques often struggle with such complex and fuzzy medical data. To address this gap, we propose a novel classification framework based on Tamir’s complex fuzzy Aczel-Alsina weighted aggregated sum product assessment (WASPAS) approach. This hybrid model incorporates complex fuzzy logic to handle multidimensional uncertainty and utilizes the Aczel-Alsina function for flexible aggregation. We apply this method to evaluate and classify AI-powered predictive models used for monitoring disability progression. The proposed framework not only improves classification accuracy but also enhances decision support in healthcare planning. A case study validates the robustness, sensitivity, and effectiveness of the proposed method in real-world disability tracking scenarios.

PMID:40804312 | DOI:10.1038/s41598-025-12296-w

Eur J Nucl Med Mol Imaging. 2025 Aug 14. doi: 10.1007/s00259-025-07511-9. Online ahead of print.

ABSTRACT

PURPOSE: To investigate the feasibility of ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) radiomics in preoperative prediction of visceral pleural invasion (VPI) status in invasive adenocarcinoma (IAC) with a maximum diameter ≤ 3 cm.

MATERIALS AND METHODS: A total of 590 IAC patients with a maximum diameter ≤ 3 cm were enrolled and divided into training set (n = 364), validations set 1 (n = 156) and validation set 2 (n = 70). A conventional model was built based on clinical and PET/CT imaging features by logistic regression. Radiomics features extracted from CT and PET images were screened using interclass correlation coefficients, Pearson correlation analysis and the least absolute shrinkage and selection operator. These selected features were used to calculate the CT and PET rad-scores. Finally, a combined model was constructed using multivariate logistic regression.

RESULTS: Tumor type [odds ratio (OR): 3.258, P = 0.012], distance between tumor and pleura (OR: 0.464, P = 0.001), and maximum standardized uptake value (SUVmax) (OR: 1.109, P = 0.002) were used to construct the conventional model. Ten CT radiomics features and six PET radiomics features were used to establish the CT and PET rad-score models. The area under the curve (AUC) value of the combined model (0.824) was higher than conventional model (0.734), CT rad-score model (0.790) and PET rad-score model (0.748) in the training set, and the differences were statistically significant as tested by Delong test (P < 0.05). In the validation set 1 and validation set 2, the combined model exhibited the highest AUC values (0.835 and 0.787), and the difference between the combined model and PET rad-score model (validation set 1: 0.835 vs. 0.747, P = 0.028; validation set 2: 0.787 vs. 0.657, P = 0.043) and CT rad-score model (validation set 2: 0.787 vs. 0.694, P = 0.025) was statistically significant.

CONCLUSION: The combined model based on PET/CT radiomics is an effective and non-invasive tool for preoperative predicting VPI status in IAC patients.

PMID:40804299 | DOI:10.1007/s00259-025-07511-9