Category: Nevin Manimala

Dermatol Ther (Heidelb). 2026 Jan 19. doi: 10.1007/s13555-025-01647-0. Online ahead of print.

ABSTRACT

INTRODUCTION: Atopic dermatitis (AD) is a complex disease with clinical heterogeneity. Nemolizumab is a novel interleukin (IL)-31 receptor alpha inhibitor that has demonstrated efficacy in managing moderate-to-severe AD. However, there are no head-to-head trials that compare nemolizumab with other anti-IL-4/13 monoclonal antibodies (mAbs). To support clinical decision-making, the comparative efficacy and safety of nemolizumab versus other advanced systemic therapies, in combination with topical treatments, were estimated using network meta-analyses (NMAs).

METHODS: Randomized controlled trials (RCTs) investigating advanced systemic therapies for moderate-to-severe AD in adolescents (12-17 years) and adults (≥ 18 years) were identified through a systematic literature review (searches conducted 31 March 2025, CRD42023492392). The trial results were analyzed in fixed- and random-effects Bayesian NMA models. Outcomes included ≥ 75% improvement in the Eczema Area Severity Index (EASI-75), an Investigator’s Global Assessment (IGA) score of 0 or 1 (IGA success), treatment-emergent adverse events, and discontinuations due to adverse events. Analyses for all endpoints were conducted at week 16. This publication presents a targeted comparison of licensed anti-IL mAbs.

RESULTS: Twenty-two RCTs were included in the NMA. When measuring response through EASI-75 and IGA success, no statistically significant differences were observed between nemolizumab and all other anti-IL mAbs in CsA-experienced adults or CsA-naïve adolescents. In CsA-naïve adults, only lebrikizumab demonstrated statistically superior efficacy against nemolizumab. Nemolizumab demonstrated a comparable safety profile with other available treatments.

CONCLUSIONS: The results of this study suggest that compared with other anti-IL mAb therapies for the treatment of moderate-to-severe AD, nemolizumab has similar efficacy in achieving EASI-75 and IGA success, and a comparable safety profile. This is in addition to nemolizumab’s well-demonstrated efficacy in improving itch. Nemolizumab may be particularly beneficial in clinical settings where patients and physicians are seeking to manage AD with a well-tolerated therapeutic.

PMID:41553701 | DOI:10.1007/s13555-025-01647-0

Environ Sci Pollut Res Int. 2026 Jan 19. doi: 10.1007/s11356-026-37394-8. Online ahead of print.

ABSTRACT

Climate change is a critical global challenge driven by rising greenhouse gas emissions, particularly carbon dioxide CO $_2^{}$ . Accurate forecasting of CO $_2^{}$ emissions is essential for developing effective mitigation strategies. This study focuses on modeling and forecasting CO $_2^{}$ emissions in Iraq based on data from 1937 to 2023, incorporating climatic variables such as temperature and precipitation as exogenous variables to enhance forecast accuracy using multiple models, including traditional time series ARIMAX, Feedforward Neural Networks (FNN), Recurrent Neural Networks (RNN), and hybrid FNN-RNN. ARIMAX requires the assumption of linearity, FNN alone can model complex nonlinear interactions for each observation, while the RNN capture temporal relationships in sequential data. The hybrid configuration combining FNN and RNN models provides a learning of both linear and nonlinear structures. Empirical results indicate that the hybrid FNN-RNN model outperforms other models using key evaluation metrics, including $R^2$ , MSE, RMSE, and MAE. The hybrid model shows that both training and validation losses decrease steadily and converge to very low values without overfitting. The close alignment of the two curves indicates good generalization, and the slight dip in validation loss suggests effective regularization. Additionally, the study forecasts a significant 9.18% rise in Iraq’s CO $_2^{}$ emissions over the 5 years from 2024 to 2028, and the forecast showed its highest recorded value in 2028. These findings may support policymakers in designing more accurate and proactive emission control strategies. While focused on climatic variables, the model offers a strong basis for future research to focus on socioeconomic factors such as GDP and population growth.

PMID:41553698 | DOI:10.1007/s11356-026-37394-8

J Autism Dev Disord. 2026 Jan 19. doi: 10.1007/s10803-025-07205-z. Online ahead of print.

ABSTRACT

PURPOSE: In low- and middle-income countries (LMICs), where the majority of children with developmental disorders live, access to early, specialized interventions is highly limited. While studies from high-income countries show that tailored early intervention can be effective in learning new skills, there remains a lack of evidence-based approaches specifically designed for the realities of LMICs.

METHODS: The study included 50 preschoolers, 25 of whom (mean age = 52.4 months) participated in an individualized developmental and behavioral program combined with parent education in addition to preschool attendance over a six-month period. The remaining 25 children (mean age = 50.5 months) attended only preschool. The intervention averaged 2.9 h per week (range: 2.1-4 h) and targeted age-appropriate developmental goals. Additionally, parents received an average of 0.6 h per week (range: 0.2-0.7 h) of education to support the generalization of skills to daily life.

RESULTS: Children who received the individualized developmental and behavioral intervention combined with parent education in addition to preschool made statistically significant progress across all developmental areas compared to those who attended only preschool.

CONCLUSION: These findings highlight the potential of locally adapted, evidence-based, low-intensity interventions, combined with parent education, to improve outcomes for children with developmental disorders, including autism, in LMICs.

PMID:41553659 | DOI:10.1007/s10803-025-07205-z

J Autism Dev Disord. 2026 Jan 19. doi: 10.1007/s10803-026-07221-7. Online ahead of print.

NO ABSTRACT

PMID:41553658 | DOI:10.1007/s10803-026-07221-7

J Robot Surg. 2026 Jan 19;20(1):188. doi: 10.1007/s11701-026-03141-x.

ABSTRACT

The Deep Pelvic Endometriosis Index (dPEI) is a preoperative MRI-based score initially validated to predict surgical outcomes in patients undergoing laparoscopic treatment for deep pelvic endometriosis (DPE). Its applicability in robotic-assisted laparoscopy (RAL) has not yet been established. This study aimed to evaluate whether the dPEI can predict surgical outcomes following RAL for DPE. From February 2019 to December 2024, a retrospective analysis from a prospective database including patients undergoing RAL for DPE at Tenon Hospital, Paris, was performed. Preoperative staging was based on MRI and the dPEI scoring system, which evaluates the involvement of different anatomical compartments by deep endometriosis. Patients were classified into three categories: mild endometriosis (dPEI ≤ 2), moderate endometriosis (dPEI 3-4), and severe endometriosis (dPEI ≥ 5). Surgical outcomes including operative time, hospital stay, postoperative complications using the Clavien-Dindo classification and voiding dysfunction were assessed. A hundred and seventy patients were included. Overall complication rate was 24.7%, including 7.7% Clavien-Dindo grade > II. De novo voiding dysfunction occurred in 10.6% of patients, lasting > 1 month in 4.1%. dPEI categories showed a positive correlation with longer operative time (Spearman’s ρ = 0.40, p < 0.001) and increased hospital stay (Spearman’s ρ = 0.43, p < 0.001) and were also significantly associated with higher rates of grade > II complications (OR = 13.1; 95% CI [1.54-111.3], p = 0.02) and high incidence of voiding dysfunction (OR = 5.9; 95% CI [1.48-23.5], p = 0.01). Involvement of lateral compartments was associated with high operative time, hospital stay, and de novo voiding dysfunction. Our results support the dPEI as a useful preoperative tool for predicting surgical outcomes after RAL for DPE. Its use can improve patient counseling, and shared decision-making, particularly in cases of severe disease (dPEI ≥ 5).

PMID:41553651 | DOI:10.1007/s11701-026-03141-x

J Behav Med. 2026 Jan 19. doi: 10.1007/s10865-025-00625-3. Online ahead of print.

ABSTRACT

Behavioral science and health psychology researchers often strive to investigate treatment effects using traditional statistical approaches, such as repeated measures ANOVA. However, these methods often fall short in addressing complexities like measurement error, intraindividual variability, and change processes over time. This study introduces the Two-Wave Latent Change Score Model (2W-LCSM; Henk & Castro-Schilo, 2016) as a robust alternative for modeling treatment-induced change and its long-term behavioral consequences. We demonstrate an illustrative example using data from individuals convicted of sexual crimes, incarcerated, and completing psychotherapy programs based on cognitive behavioral therapy. Our findings highlight the utility of 2W-LCSM in capturing both within-person change and its predictive relationship with recidivism. Results indicate a significant reduction in cognitive distortions post-treatment, with latent change scores emerging as a significant predictor of reduced sexual crime recidivism. These findings underscore the value of 2W-LCSM in behavioral medicine research, offering insights for tailoring interventions and advancing statistical methodologies in the field.

PMID:41553614 | DOI:10.1007/s10865-025-00625-3

J Robot Surg. 2026 Jan 19;20(1):194. doi: 10.1007/s11701-025-03120-8.

ABSTRACT

Urology has been a leading field in the adoption of robotic surgery, which offers technical advantages and low complication rates, including notably reduced intraoperative blood loss. In this study, we aimed to examine the relationship between formula-based estimated blood loss and visually estimated intraoperative blood loss in robotic urologic procedures. In this retrospective study, 111 robot-assisted urologic surgery were included. The agreement between the visually estimated intraoperative blood loss and the estimated values calculated using different formulas (Hb dilution method formula, Hb mass method, Gross Formula, López-Picado Formula). To determine how consistent each estimation was with the visually estimated intraoperative blood loss and with each other, Bland-Altman analysis, Concordance Correlation Coefficient (CCC) and Intraclass Correlation Coefficient (ICC) were applied. Intraoperative blood loss (visual estimation) indicated a mean blood loss of 220.72 ± 212.61 mL, whereas formula-based calculations consistently yielded higher estimates: López-Picado, 721.64 ± 532 mL; Hb mass method, 667.79 ± 429 mL; Gross formula, 726.97 ± 540 mL; and Hb dilution method, 737.99 ± 545 mL. The analyses revealed that all formulas differed statistically significantly from the visually estimated intraoperative blood loss. Evaluation of agreement and consistency demonstrated that the formulas showed poor agreement both with estimated blood loss and with one another. The strongest concordance was observed between López-Picado and Gross formula. There was a large discrepancy between visually estimated intraoperative blood loss and formula-based estimations. While formula-based methods show strong internal consistency, they differ substantially from the subjective estimates commonly used.

PMID:41553610 | DOI:10.1007/s11701-025-03120-8

Oral Radiol. 2026 Jan 19. doi: 10.1007/s11282-025-00894-3. Online ahead of print.

ABSTRACT

OBJECTIVES: In the course of a standard diagnostic procedure for temporomandibular joint disorder (TMD), there is often uncertainty regarding the necessity of magnetic resonance imaging (MRI) of the temporomandibular joint (TMJ). This study aims to clarify the relationship between clinical TMD symptoms and MRI findings using logistic regression models, to better define the role of MRI in diagnostics.

METHODS: In this retrospective study, the authors analysed a sample of 80 temporomandibular joints (TMJs). Forty patients with TMD symptoms were selected for the study, all of which had previously undergone examination in accordance with the diagnostic criteria for temporomandibular disorders (DC/TMD), as well as having undergone TMJ MRI. Descriptive statistics and regression analyses were used to explore any correlation between clinical symptoms and MRI findings.

RESULTS: MRI-based explanation of clinical symptoms revealed thirteen significant regression models with the following dependent variables: palpation pain at the lateral TMJ pole, TMJ crepitation, condylar hypermobility, uncorrected mandibular deviation, and palpation pain in the medial and lateral pterygoid muscles, as well as in the masseter and temporalis muscles. In contrast, the clinical symptom-based inference of MRI diagnoses yielded eleven significant models, with MRI findings as dependent variables: effusion, degenerative joint disease, anterior disc displacement without reduction, medial disc displacement, thickening at the insertion of the lateral pterygoid muscle, subluxation of the mandibular condyle, reduced glenoid fossa height, and abnormal disc morphology. Among all models, only anterior disc displacement without reduction with condylar hypermobility and with the pain in the masseter muscle demonstrated acceptable predictive accuracy. (AUC = 0.651, AUC = 0.637).

CONCLUSIONS: This study confirms that clinical examination alone may be insufficient for accurately diagnosing specific TMJ pathologies. Although some clinical signs show strong associations with MRI findings, only two regression models demonstrated acceptable predictive value.

PMID:41553600 | DOI:10.1007/s11282-025-00894-3

Drug Saf. 2026 Jan 19. doi: 10.1007/s40264-025-01645-3. Online ahead of print.

ABSTRACT

BACKGROUND: Previous evidence suggests a potential protective effect of warfarin against cancer, compared to non-users. However, it may be prone to immortal time bias and residual confounding.

OBJECTIVE: We aimed to examine the association between cancer and warfarin, compared with active comparator (direct oral anticoagulants).

METHODS: We conducted studies using population-based databases from England and Hong Kong to investigate the association between warfarin and hazard of cancer using a new-user active-comparator cohort design. People with atrial fibrillation aged ≥ 18 years who had first received anticoagulant treatment during 01/01/2011-31/12/2019 were involved.

RESULTS: No evidence supported the association between warfarin and hazard of overall cancer, compared with direct oral anticoagulants in both settings (England: hazard ratio [HR] = 1.03, 95% confidence interval [CI] 0.94-1.13; Hong Kong: HR = 0.89, 95% CI 0.79-1.01). A lower hazard of female breast (HR = 0.49, 95% CI 0.30-0.79), ovarian (HR = 0.07, 95% CI 0.01-0.58), and pancreatic (HR = 0.46, 95% CI 0.22-0.96) cancers and a higher hazard of kidney cancer (HR = 3.57, 95% CI 1.64-7.76) were found in Hong Kong, comparing warfarin with direct oral anticoagulants, but these were not replicated in England.

CONCLUSIONS: This study does not find a protective effect of warfarin against cancer versus direct oral anticoagulants. The risks of site-specific cancers including pancreatic, kidney, and sex-specific cancers between oral anticoagulants shown in the Hong Kong setting only may require further investigation in other independent datasets.

PMID:41553598 | DOI:10.1007/s40264-025-01645-3

Metabolomics. 2026 Jan 19;22(1):19. doi: 10.1007/s11306-025-02389-y.

ABSTRACT

INTRODUCTION: Tuberculosis (TB) and type 2 diabetes mellitus (T2DM) are highly prevalent diseases resulting in high mortality rates globally. Furthermore, T2DM increases susceptibility to TB and vice versa, worsening disease outcomes. This comorbidity is, however, not well described nor understood, despite its rising prevalence globally.

OBJECTIVES: This investigation aimed to better characterize the urinary metabolic profiles of patients with the TB and T2DM comorbidity in a South African cohort, to better understand its metabolic basis and associated clinical implications.

METHODS: Using untargeted GCxGC-TOFMS metabolomics, urine samples from 17 patients with TB and T2DM and 34 healthy controls were analyzed and statistically compared to identify significantly altered urinary metabolites.

RESULTS: TB-T2DM comorbid patients were characterized by altered metabolism of: (1) tryptophan and kynurenine (reduced kynurenic acid, anthranilic acid, picolinic acid) associated with changes to NAD⁺ synthesis and a redox imbalance, (2) nucleotides (reduced 3-aminoisobutyric acid, orotic acid, thymine, β-alanine, adenine, hypoxanthine), (3) tyrosine (reduced 3,4-dihydroxyphenylglycol, 4-hydroxy-3-methoxyphenylglycol, hydroxyphenylpyruvate), (4) lipids (reduced dec-2-enedioate, adipic acid, methylmalonic acid), (5) reduced concentrations of various glycine conjugates associated with glycine depletion, and (6) reduced urinary concentrations of various gut microbial metabolites indicative of microbial dysbiosis.

CONCLUSION: These results indicate several metabolic disruptions to amino acids, nucleotides, lipids, NAD⁺ homeostasis and the host microbiome, in TB-T2DM patients, mainly driven by inflammation and oxidative stress. Overall, the findings indicate synergistic amplification of metabolic stress, associated with immune suppression and TB-T2DM disease progression, and subsequently suggests how TB increases T2DM susceptibility and vice versa, as foundation for further investigations.

PMID:41553570 | DOI:10.1007/s11306-025-02389-y