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Impact of Physical Environment of Pediatric Inpatient Wards on Children: A Systematic Literature Review.

ObjectiveThe study aimed to examine empirical studies published between 2003 and 2025 to identify elements of physical environments influencing health outcomes and experiences of children and families.BackgroundIn the past 40 years, research has shown that the physical environment influences the health and well-being of patients in the healthcare environment. However, similar research in the context of "pediatric inpatient wards" remains underexplored.MethodsPubMed, Embase, Scopus, and Web of Science were used to identify relevant articles. All extracted articles underwent a three-step screening process using PRISMA. A total of 30 eligible articles were used for the analysis. The protocol is registered at PROSPERO (CRD42023408997).ResultsKey findings reveal positive and negative impacts of identified elements. Positive-effect elements include play spaces, space for parents, natural light, connections with nature, and so on, which promote comfort, healing, and emotional resilience. Conversely, negative-effect elements, such as noise, artificial lighting, uncomfortable temperature, and so on, contribute to stress and disrupted sleep. Mixed effects were observed for elements like art and television, which underscore the complexity of designing environments that address the diverse needs of different age groups and genders.ConclusionsThe review findings highlight significant knowledge gaps. The study also tries to bridge existing gaps between research and practice by systematically identifying environmental elements, offering actionable insights to architects, designers, healthcare providers, and policymakers. Future research must adopt rigorous, culturally inclusive approaches to advance the field of pediatric healthcare design and ensure equitable care across diverse sociocultural contexts.

Humans

Construction of precision clinical-proteomics risk model based on machine learning for predicting heart failure in type II diabetes mellitus.

BACKGROUND AND AIMS: Heart failure (HF) is a severe complication in type 2 diabetes mellitus (T2DM), but current risk stratification scores have limited predictive accuracy. We aimed to develop novel prediction tools integrating clinical variables with proteomics to improve risk stratification of hospitalization for HF in T2DM. METHODS AND RESULTS: In this study, we included 2111 UK Biobank participants with T2DM but no prior HF, and profiled 2920 proteins to predict 10-year incident HF hospitalization. Participants were randomly divided into training (70%), tuning (10%), and validation (20%) sets.Three prediction models were developed: a Clinical model based on demographic characteristics, comorbidities, medication use, and laboratory indices; a Protein model based on 40 proteins selected by the Light Gradient Boosting Machine (LGBM); and the Clinical OMics and Protein ASSessment for Heart Failure (COMPASS-HF) model, which integrated both clinical variables and the LGBM-selected proteins. Models were evaluated for area under the curve (AUC), sensitivity, and specificity. During follow-up, 168 participants (7.96%) developed incident HF. The COMPASS-HF model showed better discrimination than the Clinical model, with an AUC of 0.897 (95% CI: 0.850-0.945) versus 0.790 (95% CI: 0.723-0.856). It also demonstrated higher sensitivity (0.882; 95% CI: 0.725-0.967) and consistent performance in subgroups. COMPASS-HF effectively stratified risk of hospitalization for HF, with cumulative incidence rates of 31.9% in the high-risk group and 1.2% in the low-risk group. CONCLUSIONS: By combining clinical and proteomic variables, we developed a high-performance HF prediction model for T2DM, enabling precise risk stratification and informing early intervention strategies.

Humans

Development and validation of a comprehensive prognostic model for 28-day ICU mortality in non-traumatic subarachnoid hemorrhage: an analysis based on the MIMIC-IV database.

BACKGROUND: Due to the complex pathophysiology of non-traumatic subarachnoid hemorrhage (SAH), accurate risk prediction remains a challenge. Our aim is to develop and validate a comprehensive prognostic model that integrates demographic characteristics, vital signs, laboratory parameters, and more, to provide clinical decision-making support in real-world practice. METHODS: We conducted a retrospective cohort study of 785 Non-traumatic subarachnoid hemorrhage patients. The cohort was randomly divided into a training set (n = 549) and a validation set (n = 236). Feature selection was performed using LASSO regression, followed by backward stepwise Cox regression for optimization. A nomogram was constructed based on independent predictive factors, and model performance was assessed using discrimination, calibration, and decision curve analysis. To prevent immortal-time bias, all predictors were anchored to a fixed early (first-24-hour) measurement window, treatment variables were modelled as binary indicators rather than cumulative exposures, and a five-model sensitivity analysis with baseline-severity adjustment was performed. RESULTS: The development of our model followed a systematic approach: first, 15 potential predictive factors were selected via LASSO regression, which were then refined to 12 independent predictors using backward stepwise Cox regression. The final predictive factors included: Ventilation, AHT, Nimodipine 60 mg, Age, SAPS.II, Input amount, Calcium total, Platelet count, White blood cells, Anion gap, pH, and Chloride. The integrated model demonstrated excellent predictive ability for 7-day, 14-day, and 21-day mortality in both the training set (AUC: 0.972, 0.934, 0.898) and the validation set (AUC: 0.968, 0.948, 0.911). Calibration curves and decision curve analysis confirmed the model's reliability and clinical utility across different time points. We constructed a nomogram for individualized risk prediction. Univariate Kaplan-Meier survival analysis demonstrated significant stratification of survival outcomes by each predictor, while restricted cubic spline analysis revealed non-linear relationships between continuous variables and mortality risk. Random survival forest analysis identified the top three predictive factors (Nimodipine 60 mg, Ventilation, AHT) and compared them with our full 12-variable model, confirming superior performance of the integrated model at all time points. At the 28-day primary endpoint, the model achieved a time-dependent AUC of 0.898 (training) and 0.904 (validation); after restricting predictors to the early baseline window, the leakage-controlled model retained good discrimination (validation C-index 0.803). CONCLUSIONS: Our ICU 28-day mortality prognosis model demonstrated robust performance in predicting ICU 28-day mortality in non-traumatic subarachnoid hemorrhage. The model, through the nomogram, provides individualized risk assessment, aiding clinical decision-making and patient stratification.

Humans

Teaching Engagement and Caregiving Help in the Intensive Care Unit (TEACH-ICU) Scale: Content Validity.

BACKGROUND: Having family members provide care to their loved ones in the intensive care unit (ICU) is a beneficial yet seldom implemented approach. For family members to perform caregiving, nurses must be willing to teach, and such willingness is a developing area of research. OBJECTIVES: To adapt an instrument validated in family members, the Family Willingness for Caregiving Scale, to address nurses' willingness to teach family members caregiving skills. METHODS: Purposive and snowball sampling were used to recruit 10 expert ICU nurses through the American Association of Critical-Care Nurses' research website and social media platforms. The researchers conducted cognitive interviews with the nurses to address the instrument's content validity. RESULTS: The scale was refined based on the participants' feedback. Items were deleted, added, and revised. Furthermore, scale instructions were adjusted to emphasize the willingness to teach families of patients receiving mechanical ventilation. Qualitative themes emerged related to barriers to family engagement, including time constraints, patient acuity, and nurse and family characteristics. CONCLUSIONS: Content validity of the scale was assessed, with future research aimed at pilot testing and evaluating construct validity before using the scale as a research instrument. Practical implications include using the scale as an evaluation tool to determine nurses' willingness to teach family members about caregiving. After evaluation, various strategies could be incorporated to enhance family engagement in adult ICUs.

Humans

Frequent readmissions after hospitalization for alcohol withdrawal: a systematic review and meta-analysis.

BACKGROUND: Alcohol use disorder and alcohol withdrawal syndrome impose substantial clinical and economic burdens, with repeated hospitalizations being common. We aimed to systematically review readmission rates following inpatient detoxification, assess variation across study designs and hospital settings, and identify key risk and protective factors. METHODS: We performed a literature search in Embase and Pubmed on 10/04/2026 focusing on studies assessing in hospital alcohol detoxification. Exclusion criteria included studies on substance use other than alcohol and outpatient or residential treatment. Main outcome was rehospitalization, and meta-analysis was performed to estimate pooled readmission proportions. Secondary outcomes were risk factors and protective factors influencing the rate of rehospitalization. RESULTS: Twenty-five studies were included. The pooled proportion of readmissions following alcohol detoxification was estimated at 17% (95% CI: 14%-21%; 13 studies, n = 287,896) within 1 month, increasing to 44% (95% CI: 36%-52%; 8 studies, n = 2,877) at 1 year. Substantial between-study heterogeneity was observed. Subgroup analyses found no significant differences by hospital setting or time period. Findings for study aim and study design were mixed and based on limited data A small number of studies suggested associations with housing stability, employment, and treatment engagement. CONCLUSIONS: This meta-analysis suggests that approximately one in six patients are readmitted within 1 month and nearly half within 1 year after inpatient alcohol detoxification. However, readmission rates varied considerably across settings and populations. Future research should evaluate targeted interventions to reduce readmissions among high-risk patient groups.

Humans

A Critical Assessment of Evidence-Based Design's Knowledge Base and Inspiration: A Systematic Review.

PurposeThis study examines Evidence-Based Design (EBD) as an epistemological framework for guiding design research and practice, with a particular focus on its reliance on Evidence-Based Medicine (EBM) as a source of methodological inspiration.BackgroundOver the past two decades, EBD has been promoted as a way to strengthen design processes through the systematic use of scientific evidence. Its relationship to EBM, however, remains conceptually ambiguous: EBD draws legitimacy from EBM's hierarchical conception of "best evidence" while at the same time acknowledging the specificities of design practice, which do not easily fit such a model.MethodologyA systematic review was conducted on 31 publications in the design research literature that explicitly address the tension surrounding EBD's conception of "best evidence." The criticisms raised were coded and analyzed by main topics and subtopics.ResultsThe review highlights several reasons why EBM's hierarchical view of "best evidence" is an unsuitable epistemological foundation for EBD. It imposes scientifically inappropriate and practically ineffective methodological standards, devalues important sources of design knowledge, and fails to address central epistemic challenges intrinsic to design processes.ConclusionsBy bringing together critical yet fragmented insights from the literature, this study argues for the development of an updated epistemological framework for EBD. Constructing this framework will require sustained interdisciplinary dialogue between design research and philosophy of science.

Humans

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning

Effects of hospital planning reforms on access, costs, efficiency, and quality of care in OECD countries: Systematic review and meta-analysis.

BACKGROUND: Many OECD countries have implemented hospital planning reforms to rising healthcare costs, demographic changes, and concerns about access, efficiency, and quality of care. Despite broad implementation, evidence on effectiveness remains fragmented and country-specific. OBJECTIVE: To synthesize evidence on the effects of hospital planning reforms aross four outcome domains: access, costs, efficiency, and quality of care. METHODS: We conducted a systematic review following Cochrane methodology, searching PubMed and Web of Science (January 2000 - September 2025). Studies were categorized into four intervention types - centralization, minimum volume requirements (MVR), performance-based targets, and governance and ownership restructuring. Risk of bias was assessed using Joanna Briggs Institute checklist for quasi-experimental designs. Where data permitted, random-effects meta-analyses pooled standardized mean differences (SMD) for access and efficiency and risk differences (RD) for quality outcomes. RESULTS: 26 studies from 12 countries were included. Centralization increased patient travel distances and reduced length of stay (SMD -0.09, 95% CI -0.17 to -0.01) and complications (RD -14.52 pp, -25.95 to -3.09), and, jointly with performance-based targets, 30-day readmissions (RD -0.43 pp, -0.65 to -0.22). Mortality effects varied by timepoint and intervention: short-term endpoints were largely non-significant, whereas 90-day mortality was reduced under centralization (RD -0.80 pp, -1.25 to -0.35) and 60-day mortality under MVR (RD -2.00 pp, -2.82 to -1.18). Survival was non-significant throughout. No study examined costs. CONCLUSION: The absence of cost evidence is a critical gap. Substantial heterogeneity reflects variation in reform design and context, underscoring the need to interpret findings by intervention and country conditions.

Humans

Construction of an infectious clone of Spodoptera frugiperda densovirus and its biological characteristics.

Densoviruses are highly pathogenic to their insect hosts and have great potential for biocontrol. Spodoptera frugiperda densovirus (SfDV) was isolated from diseased larvae of Spodoptera frugiperda, while its biological functions remain unclear. Herein, we successfully constructed an infectious clone of SfDV. The S. frugiperda larvae transfected with the infectious clone exhibited anorexia, stunted growth, and reduced activity. Histopathological analysis further showed that the epidermis, fat body and trachea were infected instead of muscle and midgut tissues. Transmission electron microscopy (TEM) revealed that numerous virions of about 22 nm were distributed within both the nucleoplasm and cytoplasm of epidermal cells. Moreover, many virions were also found contained within vesicles in the cytoplasm. The replication kinetics of the rescued SfDV (rSfDV) was similar to that of the parental SfDV. The median lethal dose (LD50) and median lethal time (LT50) values of rSfDV were 6.63 × 107 viral genome copies (vgc), 5.23 d, respectively, which were also comparable to those of the parental SfDV. Taken together, the infectious clone of SfDV provides an important tool for further exploring the genome function, pathogenesis, and interactions with its hosts.

Animals

[Analysis of a Chinese pedigree affected with Townes-Brocks syndrome due to a novel variant of SALL1 gene and a literature review].

OBJECTIVE: To analyze a novel exonic variant of the SALL1 gene and its impact on the binding site of SALL protein. METHODS: Clinical data of three children diagnosed with Townes-Brocks syndrome and their family members who had presented at the First Affiliated Hospital of Shandong First Medical University in April 2022 were retrospectively collected. The pathogenic variant was identified through whole-genome sequencing (WGS) and validated by Sanger sequencing. Protein structural prediction was performed using AlphaFold and PyMOL software to construct three-dimensional models of the wild-type and mutant proteins. Additionally, previously reported cases were systematically reviewed. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: 2023-386). RESULTS: The proband was one of triplet sisters born at 34+4 gestational weeks. All three cases had presented with anal atresia and rectovaginal fistula, and case 3 also had toe malformation of left foot. WGS revealed a novel heterozygous c.757C>T (p.Gln253*) variant in the SALL1 gene, which was predicted to be pathogenic. Sanger sequencing confirmed co-segregation of the variant with the disease within the family. Protein structural modeling demonstrated that the variant has introduced a premature stop codon at position 253, resulting in a truncated protein. CONCLUSION: Above finding has enriched the mutation spectrum of the SALL1 gene in association with Townes-Brocks syndrome, which also represented a rare case of anal atresia in triplets, and provided a basis for molecular diagnosis, genetic counseling, and further research.

Humans

Construction of circRNA-miRNA-mRNA regulatory networks in the intestine of turbot (Scophthalmus maximus) following Vibrio anguillarum infection.

Circular RNAs (circRNAs) play pivotal roles in post-transcriptional regulation by acting as molecular sponges for microRNAs (miRNAs) within the competitive endogenous RNA (ceRNA) network. However, the regulatory mechanisms in teleost immune responses remain poorly understood. In this study, circRNA-miRNA-mRNA networks were investigated in turbot (Scophthalmus maximus) following Vibrio anguillarum infection to elucidate host-pathogen interactions. Through high-throughput sequencing of intestinal tissues, a total of 50 differentially expressed circRNAs (DE-circRNAs) (18 at 2 hpi, 16 at 12 hpi, 16 at 48 hpi), 212 DE-miRNAs (11 at 2 hpi, 70 at 12 hpi, 15 at 48 hpi), and 1774 DE-mRNAs were identified. Functional enrichment analyses (GO/KEGG) revealed significant associations with immune pathways, including the MAPK signaling pathway and gap junction. An integrated circRNA-miRNA-mRNA regulatory network was constructed, highlighting key interactions including novel_circ_0002573/DE-miR-27a-3p/FGB and novel_circ_0002423/novel_347/GNE, which may regulate inflammatory and antibacterial responses. The expression patterns of selected circRNAs, miRNAs and mRNAs were validated using qRT-PCR, confirming the reliability of the sequencing results. Importantly, fibrinogen beta chain (FGB) and CXCR4/CXCL12 signaling were identified as critical immune modulators. These findings provide insights of the ceRNA regulatory networks involved in teleost intestinal immunity and provide potential molecular targets for selective breeding of disease resistance in this species.

Animals

Behind the Curtain of Care. Nurses' Experiences Providing Care to Consumers With Alcohol and Other Drug Issues: A Qualitative Scoping Review.

AIM: To scope and synthesise qualitative literature relating to nurses' experiences of providing care to consumers with alcohol and other drug issues and explore how meaning is constructed in practice. DESIGN: Scoping review. METHODS: A scoping review was conducted following Arksey and O'Malley's framework. Findings were analysed using thematic analysis. DATA SOURCES: Systematic searches were conducted between September and November 2025 across Medline, Emcare, CINAHL and Google Scholar, using controlled vocabulary and keywords relevant to nurses' experiences of providing care to consumers with alcohol and other drug issues. RESULTS: Twenty-four studies from 12 countries were included. Seven themes were identified: emotional aspects of care, education, training and skills in practice, the spectrum of stigma, ethical issues in professional practice, navigating pain management, limited support, and how meaning is constructed in practice. CONCLUSION: Nurses' experiences of providing care to consumers with alcohol and other drug issues are shaped by multiple intersecting factors influencing care delivery and professional practice. Further research is needed to examine how workplace culture, language and interpersonal interactions influence healthcare experiences, and inform education, service development and support needs. REPORTING METHOD: Reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

alcohol and other drugs

Exploring Immersive Virtual Reality as an Approach to Improve School Participation-Related Constructs in Children With ADHD.

BACKGROUND: School participation is frequency and involvement from person-environment transactions, not diagnosis, per the International Classification of Functioning, Disability and Health (ICF) and the family of participation-related constructs (fPRC). In this framework, the environmental and child determinants of school participation (e.g., school routines and peer/teacher context; self-regulation, activity competence and preferences) interact bidirectionally to shape everyday participation. However, many interventions still target isolated impairments, overlooking coordinated changes in capacities and context. Grounded in this contemporary view, this study aimed to investigate the impact of an immersive virtual reality (IVR) intervention on school participation-related constructs in children with ADHD. METHODS: The study included 92 children aged between 7 and 12&#x2009;years diagnosed with ADHD. Participants were randomly assigned into intervention (n&#x2009;=&#x2009;46) and control (n&#x2009;=&#x2009;46) groups. Both groups completed the School Participation Questionnaire (SPQ) and Bruininks-Oseretsky Test of Motor Proficiency Test 2 Brief Form (BOT2-BF) assessment prior to the intervention. The intervention group received an IVR intervention program twice a week for 8 weeks. During this period, the control group did not receive additional therapy. At the end of the 8 weeks, the SPQ was readministered to both groups. RESULTS: Baseline characteristics showed no significant differences in SPQ and BOT2-BF results between groups, confirming homogeneity prior to intervention. Following the intervention, the study group demonstrated significant improvements across all domains of the SPQ (doing, being, symptoms and environment), with large effect sizes for SPQ total score (d&#x2009;=&#x2009;0.978) and subdomains (d&#x2009;=&#x2009;0.452-0.910). In contrast, the control group showed no improvements and even declines in subdomains. Post-intervention, between-group comparisons revealed significant differences favouring the study group across all domains (p&#x2009;<&#x2009;0.001), with large effect sizes (d&#x2009;=&#x2009;0.878-1.165). CONCLUSIONS: Findings suggest that the IVR program was associated with improvements in teacher-rated environmental and child determinants of school participation (SPQ domains) in children with ADHD.

Humans

CanDo (Canadian Donor Milk) randomised controlled trial: pasteurised human donor milk supplementation in the well-baby unit - protocol.

INTRODUCTION: Mother's milk is the gold standard for feeding newborns. Despite lactation support while in hospital, supplementation rates remain high in Canadian well-baby units at 35-50%. When supplementation is needed, the choice between formula milk and pasteurised human donor milk (donor milk) remains uncertain with a lack of clinical trials to inform this practice. This study aims to compare the effect of supplementing mother's milk with donor milk versus formula in infants at higher risk for supplementation (infants of diabetic mothers, infants born small for gestational age or with a birth weight less than 2.5&#x2009;kg and late preterm infants born between 350/7 and 366/7 weeks gestation). METHODS AND ANALYSIS: This is an ongoing, open-label, single-centre, randomised controlled trial conducted at Mount Sinai Hospital, Toronto, Canada. A total of 112 infants (56 per group) will be randomised to receive donor milk or infant formula as a supplement to mother's milk during their initial hospital stay, when supplementation is deemed necessary by the family and/or healthcare team. The primary outcome is exclusive human milk feeding at 4 months of age. Secondary outcomes include any or exclusive human milk feeding at 1, 2 and 3 months; infant growth and health indicators and breastfeeding self-efficacy. Exploratory outcomes encompass infant temperament; parental mental health (assessed using the State-Trait Anxiety Inventory and Edinburgh Postnatal Depression Scale); milk cortisol concentrations; and informal milk sharing comparing donor milk and formula supplementation. Follow-up includes monthly telephone assessments and a virtual or in-person visit at 4 months post partum. Data will be analysed using intention-to-treat principles. ETHICS AND DISSEMINATION: The CanDo trial has received ethics approval from the Mount Sinai Hospital Research Ethics Board and the University of Toronto. Results will be disseminated through peer-reviewed journals, conference presentations and stakeholder engagement with hospital and public health decision-makers. Findings will address a critical evidence gap regarding the use of donor milk supplementation in well-baby units and may inform future clinical practice and policy in newborn feeding. TRIAL REGISTRATION NUMBER: NCT06315127.

Humans

A modified stomal construction technique to reduce incidence of stomal stenosis in continent catheterizable channels.

BACKGROUND: Antegrade continence enema (ACE) and catheterizable bladder channel (Mitrofanoff) procedures are routinely performed in pediatric urology patients diagnosed with a neurogenic bladder and bowel. Stomal stenosis is a common surgical complication of these procedures, occurring in approximately 10-30% of stomas. Our frustration with this complication prompted us to modify our suturing technique during stomal construction to attempt to decrease the incidence of stomal stenosis. METHODS: We compared the rates of stomal stenosis between patients with neurogenic bladder who underwent the creation of an ACE or Mitrofanoff channel using the historical techniques (prior to April 2018) versus the current technique (from April 2018 to December 2020). Our current technique for stoma creation consists of suturing full thickness bowel to only the dermal layer of the skin using interrupted 5-0 polydioxanone interrupted sutures with the knots buried. Statistics were performed using Fisher's exact t-test, with p-values <0.05 considered significant. RESULTS: There were no significant differences in demographics between patients in the 2 cohorts. Stomal stenosis occurred in 25 of 98 stomas (25.5%) after undergoing either an ACE or Mitrofanoff procedure using the historical techniques, with a median patient follow-up of 122.6 months for ACE cohort and 165.8 for Mitrofanoff cohort. The incidence of stomal stenosis was significantly decreased in the current technique, with one of the 31 stomas (3.2%) experiencing stenosis (p = 0.022), with a median follow-up of 78.4 months for ACE cohort, and 66.5 months for Mitrofanoff cohort. These follow-up durations exceed the upper limits of time-to-stenosis in the historical stomas. Stomas in the current cohort have a minimum follow-up of 4.5 years and a maximum follow-up of 7 years. CONCLUSIONS: Our current suturing technique has significantly reduced the incidence of stomal stenosis in our patients. The technique is straightforward and flexible and can be applied to any stoma placed in any position. Only one of the patients with stomas created with the current suturing technique have developed stomal stenosis, with follow-up exceeding the median time to development of stenosis of our historical cohort.

Humans

Machine learning-based prediction of unplanned readmission and construction of an online calculator for elderly patients with mild ischemic stroke.

OBJECTIVE: To screen for independent risk factors for unplanned readmission in elderly patients with mild ischemic stroke, and to construct and validate an online risk prediction calculator based on an interpretable machine learning model, thereby providing a promising practical tool for accurate clinical assessment of 30&#x2011;day all&#x2011;cause unplanned readmission risk in this population. METHODS: A prospective cohort study was conducted, including 1050 patients aged&#xa0;&#x2265;&#xa0;60&#xa0;years with mild ischemic stroke admitted between August 2023 and September 2024. Participants were randomly divided into a training set (840 cases) and a test set (210 cases) at a ratio of 8:2. Risk factors were screened by univariate analysis and multivariable Logistic regression. Four machine learning models, namely LightGBM, XGBoost, Random Forest, and K&#x2011;Nearest Neighbors (KNN), were developed and their performance was evaluated using AUC, accuracy, sensitivity, and specificity as metrics. The SHAP framework was used for interpretability analysis, and an online calculator was subsequently developed based on the optimal model. RESULTS: Univariate analysis showed significant differences (P&#xa0;<&#xa0;0.05) in 13 factors including age, smoking, AIP, TyG index, HALP score, etc. Multivariable Logistic regression identified age (OR&#xa0;=&#xa0;9.752), smoking (OR&#xa0;=&#xa0;5.171), AIP (OR&#xa0;=&#xa0;6.691), TyG index (OR&#xa0;=&#xa0;4.393), HALP score (OR&#xa0;=&#xa0;2.831), and&#xa0;&#x2265;&#xa0;2 comorbidities (OR&#xa0;=&#xa0;3.664) as independent risk factors. All four machine learning models demonstrated good predictive performance. Based on a comprehensive evaluation of multiple metrics and computational efficiency, the LightGBM model exhibited the best predictive performance (AUC&#xa0;=&#xa0;0.884, accuracy&#xa0;=&#xa0;0.829, sensitivity&#xa0;=&#xa0;0.812, specificity&#xa0;=&#xa0;0.875). SHAP analysis showed that age, AIP, TyG index, smoking, and HALP score were key predictors. An online calculator developed based on this model enables individualized risk predictions. CONCLUSION: Key risk factors associated with 30&#x2011;day unplanned readmission in elderly patients with mild ischemic stroke were identified. The LightGBM model demonstrated high predictive accuracy, and together with the interpretability analysis and online calculator, offers a practical tool to support clinical risk assessment. However, this tool requires future external validation.

Humans

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon

Symptom Burden After Dialysis Initiation and Its Association With Hospitalization.

RATIONALE & OBJECTIVE: Symptom burden is distressing for patients living with kidney failure, but there is limited information about the combination of symptoms and individual symptoms that most strongly predict health care use in this group. We classified and summarized patients' symptom burden levels and changes over time and estimated associations with hospitalizations among patients receiving incident hemodialysis. STUDY DESIGN: Longitudinal, observational. SETTING & PARTICIPANTS: Individuals initiating dialysis in the United States. EXPOSURE: Kidney Disease Quality of Life-36 (KDQOL-36) measure. OUTCOME: First hospitalization after dialysis initiation. ANALYTICAL APPROACH: Latent transition analysis was used to identify symptom burden classes using the KDQOL-36. Cox regression models were used to assess whether individual KDQOL-36 symptoms and symptom burden groups were associated with hospitalization risk after dialysis initiation, independent of demographics and comorbid conditions. RESULTS: 1,818 participants were Black (29%), were aged >65 years (59%), were women (42%), had diabetes (49%), and had hypertension (74%). Latent transition analysis identified the following 3 symptom burden groups: (1) low (low severity of all symptoms and kidney disease impacts), (2) moderate (high physical health impact and overall burden of kidney disease), and (3) high (high levels of all symptoms and kidney disease impact). After adjusting for patient characteristics, all KDQOL-36 scales except the Effects of Kidney Disease scale were associated with a higher hazard of hospitalization. Using the symptom burden groups, a high symptom burden was associated with a 20% increase in the hazard of hospitalization. A 1-category worsening in pain interference and in fatigue was associated with a 12% and an 8% increased hazard of hospitalization, respectively. LIMITATIONS: Findings may not generalize outside the United States. CONCLUSIONS: Pain interference and fatigue, as well as an overall symptom burden, are useful prognostic indicators in patients receiving in-center hemodialysis. Symptom burden should remain a treatment target in hemodialysis.

Hemodialysis