Nevin Manimala

JMIR Res Protoc. 2026 May 25;15:e87020. doi: 10.2196/87020.

ABSTRACT

BACKGROUND: Postoperative delirium (POD) is a frequent and serious complication in older surgical patients, characterized by acute cognitive dysfunction and fluctuating levels of consciousness. POD is associated with prolonged hospitalization, long-term cognitive decline, reduced quality of life, and increased mortality. Despite its clinical relevance, the underlying pathophysiological mechanisms remain poorly understood, and reliable biomarkers for early prediction and prevention are lacking.

OBJECTIVE: The CONFUSED study aims to identify molecular and clinical predictors of POD by integrating clinical data with proteomic, transcriptomic, and epigenetic analyses. The primary objective is to develop predictive models for POD using multimodal data. Secondary objectives include the identification of delirium-associated genes, proteins, and epigenetic signatures, as well as the exploration of patient subgroups at increased risk for POD.

METHODS: CONFUSED is a prospective observational cohort study conducted at a German university hospital. Adult patients undergoing major surgery under general anesthesia will be enrolled until 100 cases of POD have been observed, which is expected to require a total sample size of approximately 200 to 300 patients. Blood samples are collected at 4 predefined time points: before premedication, immediately after surgery, and on postoperative days 2 and 5. Samples undergo comprehensive proteomic profiling, transcriptomic analysis using RNA microarrays, DNA methylation analysis, and genotyping of selected polymorphisms. Clinical data, including demographics, comorbidities, perioperative variables, medications, and delirium assessments using the Confusion Assessment Method (CAM) and CAM for the intensive care unit, are systematically recorded. Statistical analyses include univariate and multivariate methods, as well as machine learning approaches such as random forests and support vector machines, to identify relevant biomarkers and develop predictive models. The study protocol follows STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) and TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) guidelines and was approved by the responsible ethics committees.

RESULTS: The study was registered in the German Clinical Trials Register (DRKS00033854) on March 18, 2024. Recruitment started in January 2024 and is ongoing at the time of manuscript submission. As of now, 135 patients have been enrolled. Sample collection and laboratory analyses are ongoing. Data analysis began in January 2026, with first results anticipated in July 2026. Final data lock is anticipated after the completion of recruitment.

CONCLUSIONS: By integrating multimodal molecular data with clinical parameters and applying advanced machine learning techniques, the CONFUSED study aims to improve the prediction and understanding of POD. The results are expected to support the development of personalized preventive strategies and contribute to improved perioperative care for patients at risk of POD.

PMID:42184339 | DOI:10.2196/87020

JMIR Nurs. 2026 May 25;9:e84436. doi: 10.2196/84436.

ABSTRACT

BACKGROUND: The growing aging population and staff shortages are placing pressure on Dutch nursing homes (NHs). These challenges have led to an increased interest in digital health technologies. Among these are wearable devices that allow for remote continuous monitoring of vital signs. An example is the Healthdot (smartQare), a wearable electronic device that continuously monitors heart rate, respiratory rate, and physical activity. In the context of acute respiratory infections (ARIs) in NHs, where initial symptoms can go unnoticed, continuous monitoring may aid in early recognition, timely intervention, and reduce staff workloads. However, little is known about how health care professionals perceive the use of continuous vital signs monitoring devices, such as the Healthdot, for this cause in NHs.

OBJECTIVE: This study aims to explore the perspectives of healthcare professionals on the use of the Healthdot for early detection and monitoring of ARIs in NHs, to inform potential future implementation.

METHODS: Semistructured interviews were conducted with 20 physicians, nurses, and certified nursing assistants from 4 NHs and 1 acute geriatric community hospital located in a NH. Interview transcripts were thematically analyzed to identify themes regarding their perspectives on the use of the Healthdot for monitoring ARIs in this setting.

RESULTS: Five main themes were identified that related to the appropriate use of the Healthdot for NH clients and health care professionals: alignment of Healthdot use and NH clients’ treatment policies, balancing safety and freedom, impact of the Healthdot on work processes, supporting rather than replacing care, and possible use during pandemics and in the future. Additionally, several preconditions for the use of the Healthdot were identified, including its usability, a support base among care staff, adequate training and guidance, communication with NH clients and their relatives, and a clear policy regarding its use.

CONCLUSIONS: Given the complexity of care in NHs, where clinical care is typically balanced against quality of life and a homelike environment, physicians generally expressed reserved attitudes toward the Healthdot, highlighting the need to consider multiple factors in its implementation. Care staff were generally positive about the device. Nevertheless, tailored assessment for each individual NH client remains essential, balancing treatment goals, safety, autonomy, and person-centered care. Additionally, clear communication and alignment between health care professionals in this setting are crucial, specifically regarding their expectations of the Healthdot’s role in care processes. This study offers practical guidance that may inform future implementation efforts of continuous vital sign monitoring devices in NHs.

PMID:42184338 | DOI:10.2196/84436

JMIR Dermatol. 2026 May 25;9:e93639. doi: 10.2196/93639.

ABSTRACT

BACKGROUND: Climate and weather factors of temperature and humidity are widely reported to be associated with xerosis (dry skin), a common inflammatory skin condition and frequent driver of pruritus (itchy skin) and reduced quality of life. Growing evidence supports links between environmental conditions and skin barrier function, with extreme climates associated with increased atopic dermatitis-related clinical visits. Mechanistically, temperature and humidity affect the stratum corneum, the skin’s primary permeability barrier, with low humidity and high temperature increasing transepidermal water loss and promoting cutaneous inflammation.

OBJECTIVE: This study examines the relationship between climate, namely temperature and humidity, and the general public’s experience in dry skin and moisturizing products, throughout the United States. This study sought to address gaps in traditional epidemiologic approaches by linking climate conditions with population-level online search behavior related to dry skin and moisturizer use across the United States.

METHODS: Publicly available climate data were obtained from the National Oceanic and Atmospheric Administration (NOAA), including average temperature and dew point by state over a recent nine-year period (2016-2025). Dew point served as a proxy for ambient humidity. Google Trends was used to assess relative search interest for five dry skin- and moisturizer-related terms by state during the same period. Search interest was normalized per million residents, and associations between climate variables and search interest were evaluated using linear regression analyses. Statistical analyses were conducted using R.

RESULTS: Lower average temperatures and lower dew points were associated with higher dry skin-related search interest, while warmer, more humid states showed lower interest. Both temperature and dew point demonstrated significant negative associations with Google search interest. This work was not funded and data collection was performed using publicly available, free databases.

CONCLUSIONS: Population-level search behavior related to xerosis reflects national patterns of climate-associated dermatologic burden.

PMID:42184334 | DOI:10.2196/93639

Ann Plast Surg. 2026 May 25. doi: 10.1097/SAP.0000000000004775. Online ahead of print.

ABSTRACT

BACKGROUND: The pathophysiology of keloid formation remains poorly understood, and treatment typically involves multimodal approaches. Previous studies suggest that keloids on the earlobes, head, and neck may be more responsive to radiation than those on other anatomic sites due to putative differences in skin tension and biomechanical properties. However, limited comparative data exist to substantiate these anatomic distinctions in clinical outcomes.

AIM: To compare recurrence rates, treatment outcomes, and radiation-related side effects between auricular and nonauricular keloids following surgical excision with adjuvant radiation therapy or surgical excision alone.

METHODS: This retrospective cohort study analysed 168 cases with keloids (60 auricular and 108 nonauricular) treated by a single surgeon between January 2020 and May 2024. Of these, 122 patients underwent surgical excision followed by adjuvant radiation therapy, while 46 patients received surgical excision only. Intralesional 5-Fluorouracil and Kenalog was injected across both groups during surgical excision. Demographic and clinical data, including age, sex, race, BMI, keloid site and size, and treatment modality, were collected. Patients were followed up post-treatment to assess recurrence, radiation-related side effects, and treatment response patterns.

RESULTS: Auricular keloids were more common in younger patients and significantly smaller in size (median 12 vs. 19.5 mm for nonauricular, P<0.001). The majority of patients received 2100 cGy of radiation. Among those receiving surgery plus radiation, 17.07% of auricular and 16.22% of nonauricular keloids recurred (P=0.91). In the surgery-only group, recurrence was 47.37% and 44.12%, respectively (P=0.82). Notably, radiation-related side effects were significantly more frequent in nonauricular sites (37%) compared with auricular (20%) (P=0.022). Age, sex, race, BMI, and radiation dose did not independently predict recurrence in the final model.

CONCLUSION: Anatomic site did not significantly influence keloid recurrence rates, challenging previous assumptions about site-specific treatment responses, while adjuvant radiotherapy significantly reduced recurrence irrespective of site. Radiation-related side effects were more common in nonauricular locations. Age, sex, race and BMI did not emerge as statistically significant demographic predictors of recurrence in this study. These findings support the routine inclusion of radiotherapy in keloid management and suggest that demographic and treatment factors may outweigh anatomic considerations in predicting outcomes.

PMID:42184131 | DOI:10.1097/SAP.0000000000004775

Arch Clin Neuropsychol. 2026 May 6;41(4):acag039. doi: 10.1093/arclin/acag039.

ABSTRACT

OBJECTIVE: Confrontational naming is an important part of many neuropsychological evaluations. Yet, data on the feasibility and psychometric properties of telephone-based confrontational verbal naming tests (VNTs) are quite limited. The current study conducted a preliminary, exploratory examination of the psychometrics and correlates of an abbreviated version of the 50-item VNT administered via telephone.

METHOD: Participants were 220 healthy adults, including 110 younger adults (ages 18-35) and 110 middle-aged to older adults (ages 50-85). Participants completed a 15-item version of the VNT as part of a broader telephone-based cognitive battery.

RESULTS: Confirmatory factor analysis suggested support for a 12-item model of the VNT (VNT-T12) with acceptable fit. VNT-T12 scores were negatively skewed and demonstrated good internal consistency. A quantile regression predicting VNT-T12 from domain-level cognitive variables showed that executive functions (e.g., verbal fluency) and fund of verbal knowledge were significantly and positively associated with VNT-T12 scores at most percentile ranges. The VNT-T12 scores were also significantly associated with race/ethnicity and English as a second language at higher quantiles of performance. Demographically-adjusted coefficients and an associated calculator are provided as a normative resource.

CONCLUSIONS: Findings provide mixed and preliminary support for the feasibility, psychometrics, and validity of a 12-item VNT administered via telephone. Future research on the psychometrics and validity of the VNT-T12 is warranted in samples with lower levels of education and in clinical populations.

PMID:42184122 | DOI:10.1093/arclin/acag039

Brief Bioinform. 2026 May 4;27(3):bbag243. doi: 10.1093/bib/bbag243.

ABSTRACT

Understanding protein functions in biological processes is pivotal for disease elucidation and drug discovery. Despite notable progress, existing approaches primarily focus on function transfer under in-distribution (ID) settings, where training and test proteins exhibit high sequence similarity. As a result, their performance often degrades when applied to novel, diverse, and low-homology protein sequences, posing a major challenge for out-of-distribution (OOD) generalization encountered in practice. Towards this end, we develop ProteinScore, a graph transformer approach tailored to improve protein function prediction in OOD settings. ProteinScore integrates a label-invariant variational subgraph generator with self-supervised contrastive learning, thereby identifying meaning substructures within proteins. By highlighting informative features while filtering out redundant ones, ProteinScore improves generalization to diverse and low-homology sequences. Experiments on datasets with both experimentally resolved and AlphaFold2-predicted structures demonstrate that ProteinScore consistently outperforms strong baselines and provides biologically meaningful interpretability through accurately identifying binding sites. In addition, ProteinScore generalizes effectively to two additional downstream tasks, drug-target interaction classification and subcellular localization prediction, achieving superior predictive performance and reliable interpretability.

PMID:42184116 | DOI:10.1093/bib/bbag243

Brief Bioinform. 2026 May 4;27(3):bbag251. doi: 10.1093/bib/bbag251.

ABSTRACT

N 6-methyladenosine (m6A), the most prevalent internal RNA modification, is an emerging key regulator of gene expression in the central nervous system, and its dysregulation is connected to psychiatric disorders. However, disentangling the causal links between specific m6A sites and diseases phenotypes remain challenging. This review presents a comprehensive survey of practical bioinformatics strategies to address it. Our review outlines four analytical themes: (i) the reliable calibration of false-positive signals, (ii) causal inference via statistical genetics, (iii) the acquisition of cell-type-specific functional insights, and (iv) the application of machine learning to predict clinical biomarkers. We validate these analytical strategies through a case study in major depressive disorder, specifically by intersecting m6A effects with psychiatric genetic risk. By streamlining these workflows, we provide a roadmap for formulating testable hypotheses regarding epitranscriptome-targeted therapeutic interventions in psychiatric disorders.

PMID:42184108 | DOI:10.1093/bib/bbag251

Brief Bioinform. 2026 May 4;27(3):bbag249. doi: 10.1093/bib/bbag249.

ABSTRACT

The Coronavirus Disease 2019 (COVID-19) pandemic has highlighted the significance of reliable molecular biomarkers in clinical use. Despite the popularity of traditional statistical approaches, the high dimensionality of transcriptomic data presents challenges for these conventional methods. While artificial intelligence (AI) algorithms have emerged as highly advantageous for handling these complex datasets, there is a lack of evaluation of these approaches in COVID-19 transcriptomic studies. This review aims to provide an evaluation of these studies employed for transcriptomic biomarker discovery in COVID-19 using AI, assessing their study designs, methodologies, and outcomes. Based on a comprehensive search for literature across five databases including Web of Science Core Collection, Scopus, PubMed/MEDLINE, IEEE Xplore Digital Library, and LitCovid from December 2019 to March 2025, this review selected 63 studies for a narrative synthesis of four key sections: (i) The Landscape of AI-Driven COVID-19 Transcriptomics, (ii) Limitations of Studies, (iii) A Proposed AI-Driven Transcriptomics Framework, and (iv) Clinical Translation Challenges, Opportunities, and Future Directions. Our analysis revealed limitations in data quality, sample size, and heterogeneity, as well as methodologies regarding validation and interpretability. Thus, we proposed an evidence-informed workflow that addresses these current limitations in study design, while acknowledging real-world constraints. We further discuss the emerging potential of agentic AI systems as a promising solution to current limitations. By bridging methodological gaps with translation considerations, this review can enhance pandemic response strategies for future emerging infectious diseases. Key Points Applications observed in reviewed studies mainly included applications in diagnosis and severity stratification of COVID-19 patients. The limitations of current studies included small sample sizes, the reliance on public datasets lacking detailed metadata, batch effects and data heterogeneity reducing model robustness, the lack of external validation, risks of data leakage and circular validation leading to inflated performance metrics, and challenges in model interpretability. An evidence-informed AI-driven framework is proposed, acknowledging real-world constraints including small pandemic cohort sizes, domain shift from viral evolution, and resource-limited settings, with emerging agentic AI systems offering potential solutions.

PMID:42184107 | DOI:10.1093/bib/bbag249

Crit Care Explor. 2026 May 25;8(6):e1418. doi: 10.1097/CCE.0000000000001418. eCollection 2026 Jun 1.

ABSTRACT

IMPORTANCE: Pediatric cerebral venous sinus thrombosis (CVST) is being increasingly recognized and can pose substantial risks of morbidity and mortality. Data on the epidemiology, management, and outcomes of CVST in the PICU remain limited.

OBJECTIVES: To describe the clinical characteristics, management, and outcomes of critically ill children with CVST during their admission to the PICU.

DESIGN, SETTING, AND PARTICIPANTS: We conducted a retrospective observational cohort study in a quaternary PICU in Toronto, Canada, between 2018 and 2023. Patients 18 years old and younger with acute primary CVST (CVST being the primary indication for ICU admission) and secondary CVST (diagnosis during an admission for an alternative diagnosis) were included in this study.

MAIN OUTCOMES AND MEASURES: The primary outcome was in-hospital mortality. Descriptive statistics were used to describe characteristics and outcomes.

RESULTS: Thirty patients were admitted with a diagnosis of CVST: 19 (63%) primary, 11 (37%) secondary. Fourteen (47%) had an associated cerebral infarct, and nine (30%) had an associated intracranial hemorrhage. The most common condition associated with secondary CVST was a brain disease requiring neurosurgical intervention (5/11). Five (17%) children with CVST died in this study, of which four had a primary CVST. Children residing in neighborhoods with increased marginalization were disproportionally represented in this cohort.

CONCLUSIONS AND RELEVANCE: Primary CVST is more common than secondary and is associated with significant mortality. The disproportionate impact on marginalized children emphasizes the need for heightened awareness and determination of factors associated with this finding.

PMID:42184099 | DOI:10.1097/CCE.0000000000001418

J Gastrointest Cancer. 2026 May 25;57(1):124. doi: 10.1007/s12029-026-01492-0.

ABSTRACT

PURPOSE: Adjuvant radiation (AR) remains a controversial treatment modality for pancreatic ductal adenocarcinoma (PDAC). This study aimed to evaluate the findings of the RTOG 0848 trial assessing the benefits of adjuvant radiation in node-negative disease utilizing a national database.

METHODS: Utilizing the National Cancer Database, all patients diagnosed with non-metastatic PDAC, who underwent pancreatectomy, were included (2004-2019). The trend of adjuvant radiation utilization was evaluated. Overall survival in a cohort of patients mimicking the RTOG 0848 protocol was examined as were clinicodemographic and pathologic predictors of adjuvant radiation.

RESULTS: Overall rates of adjuvant radiation decreased from 45 to 12%, while neoadjuvant radiation rates simultaneously increased from 4 to 12%. Positive margins and nodal disease were the strongest predictors of adjuvant radiation receipt (OR 1.7[ 95% CI: 1.6-1.7] p < 0.001 and OR: 1.1 [95% CI: 1.1-1.2] p < 0.001; respectively). Both high-risk pathologic groups experienced a decline in the use of adjuvant radiation over time, even after exclusion of patients who received neoadjuvant radiation. After application of the RTOG 0848 criteria, improved overall survival was observed in patients with node-negative and positive margins (adjuvant radiation: 28.6 [95% CI: 25.4-31.8] vs 23.0 [95% CI: 19.4-26.7] months; p = 0.005). In the margin positive cohort, adjuvant radiation was significantly associated with reduced mortality (HR: 0.791 [95% CI: 0.7-0.9]; p < 0.001).

CONCLUSION: Evaluation of RTOG 0848 in the setting of real-world data indicates a role for adjuvant radiation for patients with margin-positive, node-negative pancreatic cancer. This highlights the essential role of multidisciplinary discussions regarding patients with PDAC care.

PMID:42184090 | DOI:10.1007/s12029-026-01492-0