Functional rhinoplasty can improve disease-specific quality of life (QoL) domains. However, less is understood about its association with global health-related QoL outcomes. The goal of this study is to evaluate the relationship between disease-specific and long-term global QoL outcomes following functional rhinoplasty. Prospective cohort study at a tertiary medical center of patients undergoing functional rhinoplasty for nasal airway obstruction. Fifty patients (58% female, 42% male), with a mean age of 38.5 (StD 14.7), were surveyed. Baseline and long term (> 6 months) follow up Euroqol-5D (EQ-5D) and Standard Cosmesis and Health Nasal Outcomes Survey (SCHNOS) questionnaires were collected. Mean baseline SCHNOS-Obstructive (SCHNOS-O) score improved from 77.5 (95% CI: 71.5-83.5) to 22.7 (95% CI: 14.4-31.1) at follow up. Mean SCHNOS-Cosmesis (SCHNOS-C) score improved from 44.9 (95% CI: 33.9-56.0) to 13.9 (95% CI: 8.9-21.1). A higher SCHNOS-O is a significant predictor for expressing pain/discomfort at follow up (p = 0.011). A higher SCHNOS-C is a significant predictor for expressing anxiety/depression at follow up (p = 0.019). There is no relationship between SCHNOS-O/SCHNOS-C and mobility, self-care, or activity. A greater improvement in SCHNOS-O is associated with less anxiety/depression (p = 0.03) and pain/discomfort (p = 0.02) at follow up. However, a greater improvement in SCHNOS-C is not significantly associated with anxiety/depression (p = 0.678) or pain/discomfort (p = 0.558) at follow up. Patients who expressed anxiety/depression at baseline are more likely to express anxiety/depression at follow up. Patients with long-term improvements in nasal obstruction, but not cosmesis, are less likely to report long-term anxiety/depression and pain/discomfort following functional rhinoplasty.
Cystic fibrosis (CF) results from mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene, causing multisystem disease and impaired quality of life. CFTR modulators have improved pulmonary and nutritional outcomes, yet potential metabolic effects such as dyslipidemia remain a concern, particularly in adults. Pediatric data are limited. This study evaluated the effects of CFTR modulators on lipid and lipoprotein profiles in children with CF. This retrospective study was conducted at a tertiary pediatric pulmonology center. Body mass index (BMI) Z-scores, lung function tests, and serum lipid profiles were compared between baseline and six months after initiation of CFTR modulator therapy. Twenty-six patients were included finally. The median age was 11 (5.9-15.6) years; 53.8% were female, and 80.8% received elexacaftor/tezacaftor/ivacaftor. After six-month therapy, significant improvements were observed in BMI (p = 0.047), FEV₁ (p = 0.005), and FVC Z-scores (p = 0.001). Although HDL, LDL, VLDL, triglycerides, and total cholesterol increased numerically, none reached statistical significance. No difference was found between BMI changes and lipid alterations. Over six months of continuous CFTR modulator therapy, we observed improvements in pulmonary and nutritional outcomes without evidence of clinically meaningful lipid deterioration. This study adds real-world pediatric data regarding lipid profile changes during CFTR modulator therapy. While these therapies significantly improve pulmonary and nutritional outcomes, we observed no evidence of lipid deterioration over six months of treatment. These findings contribute to the evolving understanding of the systemic effects of CFTR modulators in childhood and underscore the importance of ongoing cardiometabolic evaluation as survival improves.
The aim of this study was to evaluate the real-world efficacy and safety of intravitreal faricimab for macular edema (ME) secondary to retinal vein occlusion (RVO) across a multicenter cohort with up to 52 weeks of follow-up. Data from 17 centers across Türkiye were retrospectively analyzed between 22 November 2024 and 1 March 2026. Patients with branch RVO (BRVO) or central RVO (CRVO) complicated by ME who received at least one intravitreal faricimab injection and had complete ophthalmic and optical coherence tomography (OCT) data with a minimum 4-week follow-up were included. Demographics, diagnosis, prior treatments, best-corrected visual acuity (BCVA; decimal converted to logMAR), central macular thickness (CMT), intraocular pressure (IOP), injection number, follow-up duration, and ocular/systemic adverse events were recorded at baseline, day 7, monthly after each of the first three injections, and at the final visit. A total of 70 patients (37 BRVO [52.9%], 33 CRVO [47.1%]) were included, with a mean follow-up of 23.69 ± 8.54 weeks; 44 (62.8%) were treatment-naïve and 26 (37.2%) were switch patients. When comparing baseline and final visits, treatment-naïve patients showed a mean CMT reduction of 306.9 ± 231.3 µm (from 594.1 ± 206.9 µm at baseline to 287.2 ± 89.9 µm at final visit; p < 0.001), while switch patients demonstrated a mean CMT reduction of 290.6 ± 114.3 µm (from 562.1 ± 107.3 to 271.5 ± 90.7 µm; p < 0.001). The mean logMAR BCVA gain was 0.77 (p < 0.001) in naïve and 0.38 (p < 0.001) in switch patients. IOP remained stable throughout, and no serious ocular or systemic adverse events were recorded. Faricimab demonstrated rapid anatomical and functional improvements in the RVO cohort, evident as early as day 7 after the initial injection. These findings support faricimab as a potent and reliable therapeutic option across both RVO subtypes in routine clinical practice. Retinal vein occlusion (RVO) is a condition where one of the veins draining blood from the back of the eye becomes blocked, causing fluid to build up in the retina and leading to blurred or reduced vision, the second most common cause of vision loss from retinal blood vessel disease. Faricimab is a new medicine that works by blocking two proteins, vascular endothelial growth factor-A (VEGF-A) and angiopoietin-2, which cause fluid leakage and blood vessel instability in the eye. While faricimab has shown promising results in clinical trials, less is known about how it performs in everyday clinical practice. This study looked at real-world outcomes in 70 patients with RVO treated across 17 eye centers in Türkiye. Faricimab led to rapid and meaningful improvements in both vision and retinal swelling, detectable as early as 1 week after the first injection, in both patients who had never received eye injections before and those switching from other treatments. No serious side effects were recorded. These findings support faricimab as an effective and well-tolerated treatment for RVO in routine clinical practice, though longer follow-up studies are needed to confirm lasting benefits, and the safety of rare inflammatory events cannot be fully assessed in a cohort of this size.
Policy Points Chronic absence should be recognized as a public health indicator and early warning sign that systems are failing to meet the developmental, social, and health needs of students. Improving student attendance requires cross-sector policy action across education, health, and public health to address the structural and social determinants of chronic absence. A prevention-oriented public health approach is essential, focusing on root causes that schools cannot address alone such as poor health, housing instability, and unreliable transportation. Chronic absence, defined as missing more than 10% of time in school, has risen sharply in the United States following the COVID-19 pandemic and now affects more than one in four students. It reflects unmet health and social needs and is patterned by deep structural inequalities. Both short- and long-term consequences include adverse impacts on educational attainment, health, and social outcomes. Despite this, chronic absence remains largely framed and addressed as an education-sector problem, limiting the scope and effectiveness of current responses. This perspective synthesizes interdisciplinary evidence from education, public health, and child development literature, drawing on ecological and life course frameworks to reconceptualize chronic absence as a public health issue. We develop a conceptual model integrating multilevel determinants of attendance across individual, family, school, community, and structural domains, and identify implications for policy and cross-sector action. Viewing chronic absence through a public health lens reframes it from a purely educational outcome to a signal of unmet need and a multidimensional indicator of system performance. Attendance patterns reflect the interaction of health, social, and structural factors that lie largely outside of the control of schools. Current approaches often emphasize individual responsibility, while overlooking the broader conditions that shape attendance. Reframing chronic absence in this way underscores the need for coordinated cross-sector interventions that address underlying determinants. Positioning chronic absence as a public health priority enables a more coherent response. We propose three principles to guide action: (1) use school attendance data as a vital sign of student and system well-being; (2) develop strategic partnerships to align goals and drive progress; and (3) develop strengths-based policies and programs to prevent chronic absence. Without this shift, efforts to reduce chronic absence are likely to remain fragmented and insufficient to achieve equitable improvements in child health and educational outcomes.
Persistent pain after total hip arthroplasty (THA) is a common complication requiring extensive diagnostic effort and is often associated with potentially invasive and morbid treatment options. With THA volume expected to steadily increase there is a similarly growing need for creative and effective diagnostic and therapeutic options for these clinically challenging patients. Hip arthroscopy has emerged as a promising tool in the setting of persistent pain after THA with expanding indications and promising outcomes. The purpose of this article was to provide a review of the current state of literature regarding arthroscopic and endoscopic solutions for common causes of persistent pain after THA with a focus on patient selection, indications, surgical considerations, outcomes, and complications. The most common indication for hip arthroscopy after THA is iliopsoas tendinopathy, showing excellent outcomes with symptom resolution in greater than 90% of patients after arthroscopic iliopsoas release or lengthening. The second most common indication is diagnostic arthroscopy in the setting of otherwise negative extensive work-up, which has shown diagnostic value for occult implant loosening, capsular fibrosis, and metal hypersensitivity. Endoscopic decompression for the treatment of ischiofemoral impingement and sciatic nerve decompression has also shown consistent improvements in pain and function. In addition to these well described indications, future utilization of hip arthroscopy for loose body removal, capsular plication for instability, and management of prosthetic joint infection are potentially emerging indications. Hip arthroscopy after THA is a safe and effective tool for the management of common causes of persistent pain after THA with robust support for iliopsoas pathology and emerging evidence and outcomes for less common indications. Future research will both expand and narrow these indications as diagnostic criteria, patient selection, and surgical techniques are refined.
Many children with oral language difficulties also experience challenges with word reading, as evidenced in the high comorbidity rate between developmental language disorders and dyslexia. The current study investigated a sample of students (n = 357) with language and literacy difficulties classified into latent classes based on pre-intervention performance on word reading and listening comprehension measures. Specifically, this study sought to determine the extent to which latent classes responded to an evidence-based, narrative language program at immediate post-test and a five-month follow-up time point, and whether performance varied as a function of class membership. Findings revealed that students in all latent profiles showed statistically significant improvements in narrative language at post-test, a primary target of the intervention. However, intervention effects varied at a five-month follow-up time point, with students with the greatest listening comprehension and word reading difficulties showing the most notable gains. Instructional response also varied according to performance on a narrative writing measure. These findings suggest that assessing initial performance on key variables may be able to help educators predict student response and adapt intervention plans to more effectively meet individual needs.
To evaluate the efficacy of teprotumumab in a subset of thyroid eye disease (TED) patients with prolonged disease duration and high clinical activity score (CAS). This is a retrospective study of all TED patients who underwent eight infusions of teprotumumab and had a consistently documented CAS ≥ 4 for at least 2 years prior to teprotumumab initiation at a single institution. Primary outcome measures included proptosis response (difference in median pre- and post-treatment Hertel exophthalmometry), CAS response (difference in median pre- and post‑treatment CAS), and diplopia response (≥1 point improvement in Gorman diplopia score), comparing pre-treatment values to post-treatment measurements at the immediate follow-up visit using Mann-Whitney U testing. . Of 198 patients who initiated teprotumumab treatment from April 1 2020 to March 31 2024, 8 patients met inclusion criteria. The median TED duration, measured from the first clinic visit to the clinic visit closest to initiation of teprotumumab was 42.3 months; the average follow‑up interval was 32.7 months. The median pre-treatment Hertel measurement was 24.25 mm (IQR 4.88) compared to a post-treatment measurement of 21.81 mm (IQR 4.63) (p < 0.001) - a mean proptosis reduction of 2.44 mm (13.6%). The median pre-treatment CAS was 5 (IQR 1) compared to a post-treatment CAS of 1 (IQR 2.25) (p < 0.001). The median pre-treatment diplopia score was 1.5 (IQR 1.25) compared to a post-treatment score of 0.5 (IQR 1.0) (p = 0.04). This retrospective study suggests that teprotumumab can be an effective treatment for patients with thyroid eye disease who have prolonged disease duration and high clinical activity.
Accurate survival prediction in non-small cell lung cancer (NSCLC) requires integrating clinical, radiological, and histopathological data. Multimodal deep learning (MDL) can improve precision prognosis, but small cohorts and missing modalities limit its clinical applicability, as conventional approaches enforce complete-case filtering or imputation. We present a missing-aware multimodal survival framework that combines computed tomography (CT), whole-slide histopathology images (WSI), and structured clinical variables for overall survival modeling in unresectable stage II-III NSCLC. The framework uses foundation models (FMs) for modality-specific feature extraction and a missing-aware encoding strategy that enables intermediate multimodal fusion under naturally incomplete modality profiles. By design, the architecture processes all available data without dropping patients during training or inference. Intermediate fusion outperforms unimodal baselines and both early and late fusion strategies, with the trimodal configuration reaching a C-index of 74.42. Modality-importance analyses show that the fusion model adapts its reliance on each data stream according to representation informativeness, shaped by the alignment between FM pretraining objectives and the survival task. The learned risk scores produce clinically meaningful stratification of disease progression and metastatic risk, with statistically significant log-rank tests across all modality combinations, supporting the translational relevance of the proposed framework.
Faecal incontinence (FI) increases up to 50% with age in institutionalized older individuals, and treatment options have been scarcely studied for older people. Posterior tibial nerve stimulation (PTNS) is a minimally invasive second-line treatment available. This research aims to assess long-term clinical outcomes of PTNS using the Wexner score in community-dwelling patients aged > 65 years, and its impact on quality of life (QoL). A prospective cohort study with 61 patients (median age 71 years; 79% women) was conducted. PTNS was administered in three phases over 12 months, with follow-ups (FUs) at 3, 6, 12 and 36 months. Optimal responders (ORs) were defined as achieving a > 50% reduction in Wexner score compared with baseline. Partial responders that presented a 25-50% reduction in Wexner score were also considered as potential long-term ORs. At the end of treatment, 64% of patients were OR, with sustained improvement in 77% of them at 36 months. Wexner score significantly decreased throughout FUs, from median ten to four (p < 0.001). Faecal incontinence quality of life questionnaires (FIQLs) showed limited improvement in depression domain at 6- and 36-month FUs. Faecal urgency improved in a logistic regression analysis (p < 0.01). Multivariable logistic regression identified increasing age as independently associated with clinical response (p = 0.04). PTNS was associated with improvement in incontinence severity scores and faecal urgency in selected community-dwelling older adults, although reductions in FI episode frequency and quality of life measures were limited. These findings suggest that PTNS may have a selective role within individualized management strategies, particularly in urgency-predominant symptoms. NCT05016453, retrospectively registered in 2021.
Most genetic variants associated with complex heritability phenotypes lie in non-coding regions and are thought to influence disease risk by regulating gene expression. However, most transcriptome-wide association approaches primarily model local (cis) genetic effects, leaving much of gene regulation unexplained. Here, we show that incorporating distal (trans) regulatory effects improves the prediction of gene expression and the identification of disease-associated genes. Using RNA sequencing data from six human post-mortem brain regions, we developed INGENE and MODULE, two models capturing the combined influence of candidate trans-acting variants within gene coexpression networks. Integrating these models with conventional cis-based predictors improved gene expression imputation (maximum likelihood estimation, α = 0.05) for 18,744 genes across regions. Applying this framework to Psychiatric Genomics Consortium wave 3 genotypes identified 766 genes associated with schizophrenia (PFDR < 0.01), including 641 not previously reported by transcriptome-wide analyses. These findings highlight the contribution of distal regulatory mechanisms and gene network interactions to schizophrenia risk.
Extending the π-conjugated bridge in donor-π-acceptor dyes improves light harvesting but systematically erodes interfacial charge-transfer performance. Here, density functional theory (DFT) and time-dependent DFT (TD-DFT) were used to investigate triphenylamine-cyanoacrylic acid dyes with one to four thiophene bridge units (T1-T4) alongside a site-specific alkyl-chain engineering strategy on the tetra-thiophene scaffold. Bridge extension progressively red-shifts the absorption maximum from 445 nm (T1) to 508 nm (T4) but simultaneously delocalizes excited-state electron density over the π-bridge, reducing effective electron density at the acceptor-TiO₂ interface and weakening adsorption stability, dye regeneration thermodynamics, and injection efficiency. Site-specific alkyl substitution addresses this conflict: the alternating a, d-substitution pattern constructs a bilateral steric fence that suppresses face-to-face π-π stacking and relocates dye-electrolyte interactions away from the conjugated core, thereby suppressing charge recombination. Lorentzian fitting of projected density-of-states profiles confirms that all alkylated variants retain ultrafast electron injection and near-unity injection efficiency, demonstrating that the steric modification is electronically decoupled from the injection channel. These results establish site-specific alkyl-chain engineering as an effective strategy for mitigating the trade-off inherent to long-bridge dye design.
Distributed drive electric vehicles (DDEVs) show great potential in electric vehicle applications owing to their high transmission efficiency and precise driving control. Nevertheless, existing stability control methods suffer from insufficient proactivity and limited real-time regulation capability, making them unable to guarantee satisfactory longitudinal stability performance under complex operating conditions. To address this issue, this paper presents a vehicle state estimation and longitudinal stability control system for complex driving scenarios. A LiDAR-IMU fusion scheme is developed, which combines the adaptive unscented Kalman filter (AUKF) and time-series analysis (TSA) to improve state estimation accuracy. Furthermore, a multi-model model predictive control (MPC) framework is established to classify driving conditions and generate integrated control commands through weighted fusion, so as to achieve optimized longitudinal stability and smooth mode switching. The main novelty of this work lies in the integration of predictive state estimation and scenario-classified weighted-fusion multi-model MPC, which differs from conventional switching MPC and gain-scheduled MPC by avoiding abrupt mode switching and explicitly considering model differences under typical DDEV operating conditions. Both simulation and hardware-in-the-loop (HIL) results validate that the proposed system effectively enhances longitudinal stability and control performance under complex conditions. The root-mean-square error (RMSE) of yaw rate estimation is reduced to 0.111 deg/s, and the control accuracy is improved by 21.7% compared with the conventional MPC method. This work lays a solid theoretical basis for the application of distributed drive electric vehicles.
Patients with advanced hematological malignancies often have red blood cell (RBC) transfusion needs at the end of life (EOL) to improve debilitating anemia-related symptoms. Given that patients with hematologic malignancies and their caregivers find that transfusions improve energy and quality of life, access becomes a critical factor influencing hospice enrollment decisions, given variable access to transfusions in hospice settings. Additionally, because blood is a finite resource, this raises important questions about its availability in hospice care. This paper aims to explore the clinical, ethical, financial considerations surrounding RBC transfusions at the EOL for patients with hematological malignancies by drawing on literature in hematology, bioethics, and palliative care. One notable clinical consideration is that RBC transfusions improve anemia-related symptoms, such as fatigue, weakness, and dyspnea. At the same time, ethical considerations include the scarcity of blood. Moreover, some financial factors to consider include the cost of blood transfusions and reimbursement rates. These complex considerations impact hospice agencies' capabilities to provide RBC transfusions at EOL. As a result, patients often delay enrolling in hospice, resulting in more aggressive treatments at the EOL and poorer EOL outcomes. Having a better understanding of such considerations will help create protocols that balance justice for all patients while improving EOL care for patients with hematological malignancies.
Accurate kidney ultrasound segmentation is fundamental for clinical measurement and computer-aided diagnosis. However, domain shifts across devices and centers-manifested as differences in grayscale intensity, contrast, and speckle texture statistics-can substantially degrade model generalization, while acquiring new pixel-level annotations is costly. To address this, we propose a statistical spectral-similarity-guided ultrasound-to-ultrasound translation method to improve kidney segmentation performance without target-domain annotations. Motivated by frequency-domain analysis of renal ultrasound data, we observe that mid-to-low frequency components, which encode global organ structure, exhibit high consistency across domains, whereas mid-to-high frequency components, dominated by device-dependent speckle and texture statistics, vary substantially. Based on dataset-level frequency statistics, our method automatically identifies spectrally similar frequency bands shared by the source and target domains and derives structural guidance from them. This guidance is injected as a soft condition throughout a diffusion-based image generation process, enabling translation to target-device appearance while preserving anatomical structure. The translated images, paired with source-domain labels, are then used to train a segmentation network without requiring any target-domain annotations. Experiments on two public renal ultrasound datasets (OKUS and UNK) and an in-house multi-center dataset demonstrate superior structural preservation in image translation and consistently improved downstream segmentation performance, with particularly large reductions in boundary error. In the challenging OKUS to UNK adaptation scenario, our method boosts the mean Dice score by up to 20.52% (from 56.05% to 76.57%) and drastically reduces the 95% Hausdorff Distance (HD95) boundary error by 71.96 mm compared to the direct transfer baseline. Furthermore, consistent performance gains are achieved across the in-house multi-center dataset. These results indicate that the proposed spectral-similarity-based guidance effectively handles ultrasound domain shifts, substantially improving robustness and generalization for kidney segmentation under zero-shot and cross-center settings.
Breast density is a breast cancer risk factor. The accurate quantification of breast density requires reliable segmentation of dense tissue in mammograms, but it is a challenging task due to large variations in tissue appearance across hospitals and imaging devices. We propose MammoDenseSegNet, a new deep encoder-decoder convolutional neural network designed to enhance segmentation performance through two complementary modules: a) Adaptive dual attention module, which captures long-range spatial and channel interdependencies to provide focused attention on relevant dense tissue areas regardless of their location; and b) Multi kernel receptive field module, which enlarges the network's receptive field at the bottleneck layer to aggregate multi-scale contextual features. Additionally, a multi-scale dice loss with deep supervision guides learning across decoder levels to improve robustness. We evaluated MammoDenseSegNet on two public digital mammogram datasets (VinDR-Mammo and EMBED) and one private dataset, spanning a variety of breast densities and imaging artifacts in a total of 1499 images from 606 women. Statistical analysis was done using generalized linear models accounting for correlation among images from the same women and adjusting for potential confounders (proc genmod, proc mixed, SAS v.9.4, SAS Institute, Cary, NC). MammoDenseSegNet demonstrated consistently high performance across various conditions (with Recall ranging from 0.64 to 0.90 and Dice from 0.63 to 0.91) and significantly (p < 0.001) outperformed the publicly available state-of-the-art algorithm based on the VGG16 (with Recall from 0.04 to 0.91 and Dice from 0.06 to 0.82 across the same conditions). The improvement was largest for low-density tissue, where the baseline algorithm practically fails (with the mean Recall of 0.14 and Dice of 0.16) while MammoDenseSegNet remained clinically useful (with the mean Recall of 0.66 and Dice of 0.63).
The recycling of thermal power plant ash and other industrial wastes in ceramic wall products is a promising strategy for reducing natural clay consumption; however, the interaction between ash dosage, multi-waste composition, pressing time, firing temperature, and ceramic performance remains insufficiently clarified. This study evaluates ceramic wall products based on Ekibastuz thermal power plant ash, red brick waste, metallurgical slag, and glass waste, with emphasis on composition-processing-property relationships and microstructural mechanisms. Ceramic mixtures containing 0-30% thermal power plant ash and selected multi-waste combinations were pressure-molded at 15 MPa, pressed for 60-90 s, dried, and fired at 900-1100 °C. Compressive strength, water absorption, density, and microstructure were assessed to identify the optimal balance between waste incorporation and material performance. The highest performance was achieved by the mixture containing 20% thermal power plant ash, which reached 43.5 MPa compressive strength, 6.1% water absorption, and 2.30 g/cm³ density after firing at 1100 °C and pressing for 90 s. Increasing ash content to 30% reduced strength because of increased residual porosity and microstructural heterogeneity. Multi-waste mixtures containing red brick waste, metallurgical slag, and glass waste produced technically acceptable ceramics but did not exceed the optimized ash-only composition, showing that maximum waste replacement does not automatically provide maximum performance. The main innovation of the study is the identification of a controlled composition-processing-property window in which moderate ash incorporation improves densification and pore refinement, whereas excessive ash or multi-waste loading promotes heterogeneity. The findings demonstrate the engineering significance of optimized waste-derived ceramic systems for sustainable wall-product manufacturing.
This study describes the development and feasibility testing of a digital health guide (DHG) to streamline genetic education, reduce barriers, and promote informed genetic testing (GT) decisions among cancer survivors. This study reports on the DHG's development, usability testing, acceptability, feasibility, and preliminary efficacy in improving genetic counseling (GC) and GT access for cancer survivors. Guided by the Ottawa Decision Support Framework, the DHG prototype was developed following community engagement with cancer patients and at-risk relatives from diverse sociodemographically backgrounds. It was refined through user (content-focused) and usability (functionality-focused) testing. Pilot trial participants provided data through semi-structured interviews and usability assessments. Qualitative data were analyzed using the Framework Method. The preliminary impact of the DHG on GC and GT uptake, and informed decision-making, was assessed in a feasibility and accessibility trial. The Chatbot Usability Questionnaire score for the DHG was 70.3 (IQR = 12.5), indicating good acceptability. The DHG also facilitated GT uptake (73.3%) compared to enhanced usual care (EUC; 7.7%). Pretest GC was requested by 1 of 13 patients in the EUC arm, while no request (0 of 15 patients) was made in the DHG arm. Users' feedback led to clearer language, improved navigation, and stronger messaging regarding data security. DHG participants had lower decisional conflict (33.37 ± 21.09) and decision regret (17.5 ± 16.50) than those in the EUC arm (53.25 ± 22.66 and 37.08 ± 17.38, respectively). The digital intervention is feasible, acceptable, and a promising strategy for expanding GT access and promoting informed decision-making. Further testing in a definitive randomized controlled trial is warranted. Clinical trial registration. This study was preregistered at the NIH clinical trial registry ( https://clinicaltrials.gov/study/NCT06184867 ).
Community-acquired pneumonia (CAP) is a leading cause of hospitalization and often results in impaired health-related quality of life (HRQoL). The prognostic value of HRQoL at admission and its recovery trajectory after CAP remain unclear. We investigated associations between HRQoL at admission and adverse outcomes, including ICU admission, rehospitalization, and mortality, and described changes in HRQoL 180 days post-discharge. In this prospective cohort study, 552 patients hospitalized with CAP completed the EQ-5D-5L questionnaire at admission; 262 patients were reassessed 180 days post-discharge. Patients were categorized into tertiles based on the EQ-5D utility index and dimension-specific scores. Associations between HRQoL and outcomes were analyzed using logistic and Cox regression models. The mean EQ-5D utility index at admission was 0.609 ± 0.266. Severe impairments were most common in usual activities (42%) and mobility (30%) dimensions. Lower HRQoL at admission (lowest vs. highest tertile) was associated with an increased risk of rehospitalization at 30 days (aHR 1.92, 95% CI: 1.18-3.13), 90 days (aHR 2.01, 95% CI: 1.33-3.03), and 180 days (aHR 1.82, 95% CI: 1.27-2.59) and an increased risk of mortality at 90 days (aHR 1.91, 95% CI 1.01-3.63) and 180 days (aHR 1.84, 95% CI 1.05-3.20). Severe impairment in the mobility dimension was associated with increased risks of ICU admission, rehospitalization within 30, 90, and 180 days, and mortality within 90 and 180 days, while severe impairment in the self-care dimension was associated with increased risks of rehospitalization within 30, 90, and 180 days and mortality within 180 days. Among survivors who completed the follow-up, HRQoL improved modestly over 180 days (+ 0.109 ± 0.247). Low HRQoL at admission, particularly impairments in the mobility and self-care dimensions, was associated with adverse outcomes in patients with CAP. HRQoL is an independent prognostic marker that may support clinical risk stratification in patients with CAP. The observed improvement in HRQoL over time should be interpreted cautiously as it reflects survivors who completed follow-up.Trial registration: ClinicalTrials.gov (NCT03795662).
Same-day discharge (SDD) following bariatric surgery is becoming increasingly more common to reduce healthcare utilization. However, predictors of successful SDD vary across the literature. This study applied machine learning to identify predictors of SDD and evaluate the relative contributions of patient- and procedure-related factors. Patients undergoing sleeve gastrectomy and gastric bypass were identified from the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program database between 2020 and 2023. Patient, procedure and operative characteristics were analyzed. Synthetic Minority Oversampling Technique was applied given that SDD represented the minority of the cases. Machine learning models including Random Forest, Naïve Bayes, Neural Network, Extreme Gradient Boosting (XGBoost), and categorical boosting (CatBoost) were developed to predict SDD. Model performance was evaluated using the area under the receiver operating characteristic curve and compared with multivariable logistic regression. Feature importance was assessed using SHapley Additive exPlanations (SHAP). A total of 768,744 patients underwent bariatric surgery, of whom 66,809 (8.7%) underwent same-day discharge (SDD). SHAP analysis identified operative duration as the strongest predictor of SDD, while baseline patient comorbidities demonstrated comparatively smaller contributions to model predictions. Among machine learning models, CatBoost demonstrated the highest predictive performance (AUC 0.80), followed by XGBoost (AUC 0.79), whereas multivariable logistic regression had the lowest predictive performance (AUC 0.50). We developed a machine learning model that outperformed logistic regression in predicting same-day discharge following bariatric surgery. Operative duration emerged as the most important predictor of discharge status, suggesting that intraoperative events may play a greater role in determining discharge status than preoperative patient comorbidities.
Cryptococcosis is a severe invasive fungal infection with limited therapeutic options beyond fluconazole-based regimens. Isavuconazole, a broad-spectrum triazole antifungal, has emerged as a potential alternative, although clinical data supporting its use remain scarce. We aimed to evaluate the real-world effectiveness and safety of isavuconazole in patients with different forms of cryptococcosis. A retrospective observational study was conducted at a tertiary-care hospital, including patients with cryptococcosis who received isavuconazole at any treatment phase. Standard microbiological methods were used for pathogen identification and susceptibility testing. Demographic, clinical, and microbiological data were collected. Clinical and microbiological responses and tolerability were assessed at end of treatment or until death. Eight patients with cryptococcosis received isavuconazole, most of whom were immunocompromised. Clinical presentations included pulmonary and disseminated disease, with Cryptococcus neoformans as the predominant species. Isavuconazole was primarily used during the consolidation and maintenance phases, after induction therapy with amphotericin B and flucytosine for 2 weeks in most cases, and as salvage therapy in two patients. It was well tolerated during prolonged treatment (6-12 months). In the two patients with isavuconazole therapeutic drug monitoring, plasma total trough concentrations were within the therapeutic range (5 and 3.5 µg/mL, respectively), whereas cerebrospinal fluid total concentration levels were undetectable. A favorable clinical response was observed in four patients, while three remain on treatment with ongoing clinical improvement; one patient died early. Microbiological clearance was achieved in all culture-positive cases. Isavuconazole demonstrated clinical effectiveness in this cohort of patients across different presentations of cryptococcosis. Treatment was safe and well tolerated, supporting its role as an alternative antifungal option against Cryptococcus, particularly when fluconazole is limited by adverse effects or drug-drug interactions. However, data on central nervous system penetration were limited, and further studies are needed to better define its role in cryptococcal meningitis management.