Nevin Manimala

Cureus. 2025 Jun 30;17(6):e87027. doi: 10.7759/cureus.87027. eCollection 2025 Jun.

ABSTRACT

Background Dengue has emerged as the most common arboviral infection in India and worldwide. Dengue presents with a varied clinical spectrum in different age groups. The changing epidemiology and presentation are a challenge for early diagnosis and management. This prospective observational study aimed to determine the epidemiological profile of hospitalized dengue-positive children aged 0-14 years and correlate their clinical and hematological profiles. Methodology One hundred and five children with laboratory-confirmed dengue were enrolled in this study over a six-month study period. They were categorized into severe and non-severe dengue according to the World Health Organization (WHO) classification. Detailed clinical examination and laboratory investigations, including complete blood count, liver enzymes, coagulation profile, and imaging (chest X-ray and abdominal ultrasound), were performed. Data were analyzed using descriptive statistics, chi-square test, and logistic regression analysis. Results Out of the total 105 cases, 90 children (85.7%) had non-severe dengue and only 15 (14.3%) had severe dengue. The mean age of children was 92.02 months, with a male predominance (72, 68.6%). The most commonly identified symptoms were fever (105, 100%), vomiting (47, 44.76%), and abdominal pain (46, 43.81%). It was found that although thrombocytopenia was seen in 79 children (75.2%), it was not significantly associated with the severity of the disease (P = 0.2364). The study found a high recovery rate (101, 96.3%) with a mortality of 3 patients (2.8%) in severe cases. Elevated serum glutamate pyruvate transaminase (SGPT) levels (P = 0.0025), pleural effusion on chest X-ray (P = 0.000452), abdominal pain (P = 0.0041), and a positive tourniquet test (P < 0.0001) were found to be significantly associated with severe dengue. Non-structural protein 1 (NS1) antigen and immunoglobulin M (IgM) antibodies were both found to be positive more frequently in severe cases compared to non-severe cases (P = 0.0361). Conclusions This study observed a high rate of recovery and low mortality, owing to the timely management. A possible shift in the seasonal distribution of dengue was observed, with many cases occurring in the winter season. While thrombocytopenia was prevalent, it was not found to be significantly associated with disease severity or bleeding. On the other hand, elevated liver enzymes, pleural effusion, abdominal pain, and a positive tourniquet test were found to be more strongly associated with severe dengue. They may serve as valuable early clinical indicators for the severity of the disease.

PMID:40741554 | PMC:PMC12309428 | DOI:10.7759/cureus.87027

Front Bioeng Biotechnol. 2025 Jul 16;13:1636011. doi: 10.3389/fbioe.2025.1636011. eCollection 2025.

ABSTRACT

BACKGROUND: Electrocardiogram (ECG) signals contain cardiopulmonary information that can facilitate sleep apnea detection. Traditional methods rely on extracting numerous ECG features, which is labor-intensive and computationally cumbersome.

METHODS: To reduce feature complexity and enhance detection accuracy, we propose a spectral feature-based approach using single-lead ECG signals. First, the ECG signal is preprocessed via ensemble empirical mode decomposition combined with independent component analysis (EEMD-ICA) to identify the most representative intrinsic mode function (IMF) based on the maximum instantaneous frequency in the frequency domain. Next, Hilbert transform-based time-frequency analysis is applied to derive the component’s 2D time-frequency spectrum. Finally, three spectral features-maximum instantaneous frequency (f_emax), instantaneous frequency amplitude (V), and marginal spectrum energy (S)-are quantitatively compared between normal and sleep apnea populations using an independent-sample t-test. These features are classified via a random forest machine learning model.

RESULTS: The f_emax and IMF7 components of the reconstructed signal exhibited statistically significant differences (p < 0.001) between normal and sleep apnea subjects. The random forest classifier achieved optimal performance, with 92.9% accuracy, 86.6% specificity, and 100% sensitivity.

CONCLUSION: This study demonstrates that spectral features derived from single-lead ECG signals, combined with EEMD-ICA and time-frequency analysis, offer an efficient and accurate method for sleep apnea detection.

PMID:40741538 | PMC:PMC12307459 | DOI:10.3389/fbioe.2025.1636011

Infect Drug Resist. 2025 Jul 25;18:3677-3687. doi: 10.2147/IDR.S529528. eCollection 2025.

ABSTRACT

PURPOSE: To evaluate the impact of secondary bloodstream infections (BSI) on healthcare quality indicators in patients with cerebral infarction, and to develop a validated predictive model.

METHODS: This study conducted a retrospective analysis of 7,698 distinct patients with cerebral infarction (2023) from a tertiary hospital in Guangzhou. Patients were categorized into two groups: BSI-negative (n=7,573) and BSI-positive (n=125). Healthcare quality indicators were compared using Mann-Whitney U-test. A predictive model was created using Least Absolute Shrinkage and Selection Operator (LASSO) regression, based on a 7:3 training-validation split. The model’s performance was validated through the area under the Receiver Operating Characteristic curve (AUC), calibration curves, and decision curve analysis (DCA).

RESULTS: Patients with BSI had significantly prolonged hospital stays (median of 17 days versus 11 days, p<0.001), higher costs (median of 34,859 yuan compared to 16,921 yuan, p<0.001), and increased adverse outcomes (34.4% versus 1.6%, p<0.001). The LASSO analysis identified four predictors: The following variables were found to have a statistically significant relationship to the occurrence of the primary complication: peripherally inserted central venous catheters (PICC) (odds ratio [OR] = 2.791, 95% confidence interval [CI] =1.514-5.148), use of ventilators(VA) (OR = 2.771, 95% CI=1.410-5.443), Indwelling urinary catheters(CAU) (OR = 1.800, 95% CI= 0.990-3.276), and hypoalbuminemia (OR = 3.643, 95% CI=2.195-6.046).The nomogram demonstrated an AUC of 0.789 in the training set and 0.778 in the test set, indicating a satisfactory model fit across data sets. Good model fit based on Hosmer-Lemeshowp-values(Hosmer-LemeshowP=0.338/0.170).DCA indicated a net clinical benefit at risk thresholds of 0-15%.

CONCLUSION: Secondary BSI in patients with cerebral infarction can seriously affect the quality of medical care.The developed nomogram functions as a pragmatic instrument for the preliminary identification of patients at high risk. It facilitates the implementation of targeted interventions, thereby reducing the incidence of BSI and enhancing patient outcomes.

PMID:40741529 | PMC:PMC12307543 | DOI:10.2147/IDR.S529528

MethodsX. 2025 Jul 16;15:103507. doi: 10.1016/j.mex.2025.103507. eCollection 2025 Dec.

ABSTRACT

Pretimed signalized intersections significantly contribute to traffic congestion, especially under the heterogeneous traffic conditions commonly observed in emerging economies such as Indonesia. Accurate estimation of the base saturation flow rate (BSFR) is essential for reliable capacity assessment, which influences effective intersection design and operation. However, the current BSFR estimation methods outlined in the Indonesian Highway Capacity Guidelines (IHCG, 2023) rely on outdated linear models derived from the Indonesian Highway Capacity Manual (IHCM, 1997), which are inadequate for addressing contemporary heterogeneous traffic complexities. This study introduces a Bayesian Markov Chain Monte Carlo (MCMC) model employing Gibbs sampling to improve BSFR estimation accuracy. The Bayesian MCMC model achieved a Root Mean Square Error Approximation (RMSEA) of 8.638 % compared to the existing IHCG method, which produced an RMSEA of up to 51.428 %, enabling a more precise intersection capacity design. Additionally, the developed model reduced the BSFR overestimation associated with the IHCG method by approximately 42.79 %, highlighting the potential of Bayesian MCMC methods to effectively address heterogeneous traffic challenges, enhance traffic management strategies, and optimize intersection operations. The Bayesian approach provides a probabilistic framework for quantifying uncertainty, allows for the incorporation of prior knowledge to enhance parameter estimation flexibility, and effectively mitigates model overfitting. The developed model demonstrates robust statistical validity, characterized by a mean beta parameter value of 403.30, standard deviation of 8.66, and Monte Carlo Standard Error (MCSE) of 0.0008, confirming high reliability and predictive precision. The proposed BSFR model exhibited superior performance in fitting empirical data, as evidenced by an RMSE of 240.403 PCU/g/h/We and RMSEA of 8.638 %, indicating an excellent model fit within acceptable thresholds (<10 %).

PMID:40741528 | PMC:PMC12309580 | DOI:10.1016/j.mex.2025.103507

J Diabetes Metab Disord. 2025 Jul 28;24(2):177. doi: 10.1007/s40200-025-01658-w. eCollection 2025 Dec.

ABSTRACT

INTRODUCTION: The current study aimed to investigate the possible association of TCF7L2 well-acknowledged SNPs including rs7903146, rs11196205, and rs12255372 with obesity occurrence among northern Iranians with Type 2 Diabetes Mellitus (T2DM).

MATERIALS AND METHODS: DNA extraction from whole blood of all subjects was done by salting-out technique. A total of 483 T2DM patients (307 T2DM individuals without Obesity and 176 T2DM individuals with Obesity) were genotyped through TaqMan assay technology. Statistical analyses were computed by ASSOTEST, Haploview (ver. 4.2), SPSS (ver. 27), and Python (ver. 3.13).

RESULTS: Clinical characteristics assessments between the study groups showed that there was significant association for the gender type of T2DM individuals for being obese (P < 0.001, males were at higher risk). Importantly, the genetic association analysis uncovered that rs7903146 was associated with the susceptibility of Obesity among T2DM people (P = 0.021, OR = 0.60[0.38-0.93]) in a recessive model of inheritance. Genotype-Phenotype association analysis indicated no significant associations. Finally, using Python programming and based on libraries including Pandas, NumPy, SciPy, and statsmodels, 6 haplotypes with frequency higher than 0.05 found. One significant haplotype including TT-GG-GT (P = 0.03) found, however, following p-value adjustment, it was not significant.

CONCLUSION: In conclusion, this study indicated various significant results highlighting on the association of rs7903146 with susceptibility to obesity among northern Iranians with T2DM. Importantly, this study showed that females are more at risk of getting obesity than males.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40200-025-01658-w.

PMID:40741526 | PMC:PMC12304359 | DOI:10.1007/s40200-025-01658-w

J Hand Surg Glob Online. 2025 Jul 22;7(5):100795. doi: 10.1016/j.jhsg.2025.100795. eCollection 2025 Sep.

ABSTRACT

PURPOSE: The purpose of this study was to examine the 6-year progression of modified Eaton staging, pain scores, and hand strength in patients with early carpometacarpal osteoarthritis (OA) and healthy controls, illustrating the differences between OA groups and controls. Osteoarthritis patients were stratified into stable and progressing groups using three-dimensional computed tomography imaging to identify clinical and radiographic markers differentiating progressing OA from stable disease and healthy controls.

METHODS: Data were collected from 86 early carpometacarpal OA patients, classified as stable or progressing OA based on trapezial osteophyte volume (progression defined as >150 mm³ at any visit or a growth rate >14.6 mm³/y), and from 22 healthy controls. Osteoarthritis patients were assessed at baseline and at 1.5-year intervals up to 6 years, whereas controls were evaluated at baseline and year 6. We analyzed modified Eaton stage, patient-rated wrist/hand evaluation, Australian/Canadian OA hand index pain and function scores, and key pinch and grip strengths across groups over 6 years. Tukey honestly significant difference tests evaluated intergroup differences, and fixed effects models assessed the effects of time and OA progression on outcomes, with statistical significance set at P < .05.

RESULTS: Progressing OA demonstrated an increase in modified Eaton score, with clear progression by year 6. Patient-rated wrist/hand evaluation and Australian/Canadian OA hand index pain scores were elevated in both stable and progressing OA groups at baseline and year 6 compared with controls (P < .05), although minimal differences existed between stable and progressing OA. Functional scores were similarly higher in OA groups, whereas key pinch and grip strength showed little trend over time, with minor differences between stable and progressing OA.

CONCLUSIONS: Marked radiographic differences in modified Eaton score distinguish progressing from stable OA, indicating that structural progression is a key marker of disease advancement. Minimal differences in pain, functional scores, and hand strength between OA groups suggest that radiographic changes are more distinct indicators of OA progression than subjective or objective functional measures. These findings emphasize radiographic monitoring as the major parameter for OA progression.

TYPE OF STUDY/LEVEL OF EVIDENCE: Prognostic III.

PMID:40741515 | PMC:PMC12308023 | DOI:10.1016/j.jhsg.2025.100795

One Health. 2025 Jul 19;21:101149. doi: 10.1016/j.onehlt.2025.101149. eCollection 2025 Dec.

ABSTRACT

In some rural areas of Madagascar, bushpigs (Potamochoerus larvatus) are reported to be attracted to human disturbed habitats and share the same environment with domestic animals, including pigs (Sus scrofa). Such cohabitation can facilitate the transmission of pathogens between bushpigs and other domestic animals. To assess bushpig-domestic animal interactions and their implications for pathogen transmission, 26 camera-traps were deployed for three months around 10 villages in two separate regions of western Madagascar. The camera-traps were positioned at animal attraction sites: trophic resources, resting areas, and water points, and captured 17,804 images. No direct interactions (simultaneous presence) between bushpigs and domestic species were observed after analysis of 2678 trap nights. However, 44 indirect interactions (non-simultaneous presence) were recorded. The median critical time window (CTW), calculated as the time interval between the consecutive presence of bushpigs and some domestic species, was 646 min [34-1412 min]) for pigs, 672 min for cats [range 44-886 min], and 690 min for cattle [range 584-765 min]. Such CTW estimates are shorter than the average survival rate of several infectious pathogens potentially present in the environment, including African swine fever virus, Mycobacterium bovis, and Toxoplasma gondii. Factors such as proximity to water sources and protected areas statistically increased the chances of these interactions. Our research provided novel information on the level of interaction between bushpigs and other domestic animals in anthropized rural areas and which can be used to design and implement strategies to mitigate the risk of pathogen spread at the wildlife/livestock/human interface.

PMID:40741511 | PMC:PMC12309490 | DOI:10.1016/j.onehlt.2025.101149

J Food Sci Technol. 2025 Sep;62(9):1764-1771. doi: 10.1007/s13197-024-06145-3. Epub 2024 Nov 28.

ABSTRACT

Artisanal Minas cheese (AMC) is a traditional Brazilian cheese that combines particular production techniques and maturation conditions resulting in cheeses with unique sensory properties. The objective was to use multivariate statistical to determine a quality index based on the correlation of sensory and instrumental analyses of AMC. 25 samples were obtained from a cheese contest, which were sensorially evaluated by judges. Composition, lipid oxidation, fatty acid and volatile compound profiles were analyzed. The data were analyzed using principal component analysis (PCA) and canonical correlation analysis (CCA). PCA helped identify the key variables that distinguished different types of cheeses based on their qualities. CCA showed that hardness and lipid oxidation are indicators of the sensorial quality of cheeses, parameters that classified the cheeses in the competition, with the best evaluated having higher levels of these attributes.

PMID:40741508 | PMC:PMC12304404 | DOI:10.1007/s13197-024-06145-3

J Food Sci Technol. 2025 Sep;62(9):1728-1741. doi: 10.1007/s13197-024-06141-7. Epub 2024 Nov 25.

ABSTRACT

Guava ranks among top five economically important crops of India. However, it records highest postharvest loss and needs to be processed for higher shelf life and utility. This study entails evaluation and process standardisation for development of guava crisps through atmospheric frying. Three maturity stages based on firmness affected the composition of guava and thereby the quality of crisps. ANOVA, PCA and correlation analysis indicated significant effect of fruit maturity (starch, pectin, solids, sugars, ascorbic acid) and process parameters. 84% variation in data could be explained by the first four PCs together. Colour, browning, fracturability and crispness of crisps were significantly affected by fruit maturity, freezing pre-treatment, and calcium impregnation. Freezing pre-treatment enhanced the texture, decreased toughness and gave superior crisps with crunchy mouthfeel. More than 15-fold increase in the calcium content of crisps (524.76 mg/ 100 g) was realised on calcium infusion. Highest ascorbic acid retention (56.7%) and overall acceptability of crisps (7.5) were recorded for crisps from ripe stage of guava fruits given freezing and calcium infusion pre-treatments. The shelf life of guava crisps was 90 days with free fatty acids value < 2%. Thus, nutrient rich guava fruit could be a good candidate for conversion to shelf stable and attractive snacks.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13197-024-06141-7.

PMID:40741503 | PMC:PMC12304378 | DOI:10.1007/s13197-024-06141-7

Tob Induc Dis. 2025 Jul 30;23. doi: 10.18332/tid/207800. eCollection 2025.

ABSTRACT

INTRODUCTION: The rapid increase in e-cigarette use, especially among youth, raises significant health concerns. Understanding their impact on high-risk populations, such as those with cardiovascular disease, is crucial for improving patient outcomes and reducing healthcare utilization. The aim of this study is to assess the impact of e-cigarette use on hospital length of stay (LOS) in patients with cardiovascular disease.

METHODS: This cross-sectional survey was conducted at the University of Ottawa Heart Institute (November 2019-May 2020) among consecutive cardiology inpatients. Eligible participants were those admitted to the cardiac unit, fluent in French or English, and without cognitive or hearing impairments. The primary outcome is length of hospital stay. Data analysis included descriptive statistics and adjusted linear regression to explore e-cigarette use and hospital stay length, with significance set at p<0.05.

RESULTS: Of 1616 cardiac patients, 1089 (73.0%) completed the survey. E-cigarette ever users were 10.4% (4.9% former, 5.5% current). Mean LOS was 11.03 days, longer for ever-users (13.1 days) than never-users (10.8 days). Ever users had a significantly longer LOS by 2.45 days (p=0.040), and current users by 3.24 days (p=0.039).

CONCLUSIONS: E-cigarette use is associated with longer hospital stays among cardiac patients, even after adjusting for confounders. This underscores the potential harmful effects of vaping on cardiac recovery. Further research is needed to explore these associations and their implications for healthcare utilization.

PMID:40741484 | PMC:PMC12309841 | DOI:10.18332/tid/207800