Physiological Measurement

Coronary flow waveforms have a distinct diastolic-dominant shape with periods of low or retrograde flow during systole. While the general waveform shape has been attributed to complex interactions between cardiac and vascular mechanics, there is limited research into the variability in coronary flow waveforms and what this variability may reveal about cardiac function. This work presents a shape analysis of left anterior descending artery (LAD) flow waveforms using Fourier transforms and Singular Value Decomposition (SVD) performed on baseline data collected from 32 pigs. Pigs included in the study reflect two breeds (Ossabaw and Yorkshire) and three different experimental conditions (lean-control, lean-paced, and obese-paced). Fourier transforms were used to decompose the waveforms into 15 harmonics for each pig. An SVD analysis is then used to extract temporal patterns of the waveforms. Correlations between pig-specific coefficients for the SVD modes and clinical metrics were used to investigate physiological explanations of LAD waveform variability. Temporal LAD flow patterns of the second SVD mode are significantly correlated with heart rate. The third SVD mode significantly correlates with mean blood pressure and maximum hyperemic flow. Furthermore, the fourth SVD mode is weakly correlated with left-ventricular end diastolic pressure and endocardial-epicardial flow ratios. This work demonstrates that LAD flow waveforms can be broken down into temporal patterns that correlate with physiological features. Furthermore, this shape-analysis method allows for waveform reconstruction and simplifies visualization of the temporal patterns identified using SVD, an advantage over existing methods that focus on characterizing flow waveforms by points of interest.

Background Limited heart rate rise contributes to reduced exercise tolerance for people who have heart failure with reduced ejection fraction (HFrEF), yet rate-adaptive pacing does not improve functional capacity due to an attenuated force-frequency relationship (FFR). How the FFR relates to total peripheral resistance and sympathetic tone in HFrEF is unknown. Methods In a prospective, observational study, participants with HFrEF and controls underwent an incremental pacing protocol, during which heart rate was increased from 50 to 140 beats per minute. At each heart rate increment LV contractility was measured by echocardiography to determine the FFR, as well as continuous beat-to-beat measurement of systolic and diastolic blood pressures with a plethysmography device to determine cardiac output, total peripheral resistance and blood pressure variability (BPV). A microneurography study was then conducted to measure muscle sympathetic nerve activity (MSNA) during incremental pacing. Results A total of 157 participants with HFrEF and 55 controls (mean age 71.1{+/-}1.4 years, 172 (81.1%) male) underwent the pacing protocol. We observed single units in seven of 11 participants who participated in the microneurography study. In both groups, LV contractility and cardiac output increased until the peak of the FFR, after which these declined. We observed a reduction in total peripheral resistance, blood pressure variability, MSNA frequency and incidence coinciding with the peak of the FFR, beyond which these increased. Whilst these relationships were present in both groups, they were more evident in participants with HFrEF. Conclusions For people with HFrEF there is a bidirectional relationship between heart rate and sympathetic activation, with a nadir of sympathetic tone occurring at the peak of the FFR. Both excessively low and high heart rates are accompanied by greater sympathetic activation. Taken together, these data suggest that optimal heart rate targets for HFrEF are likely to be individual.

Cerebral hemodynamics are difficult to monitor continuously outside the laboratory. Optical head-worn wearables have been proposed for tracking cerebral blood-flow signals, but they require comparison with an established cerebrovascular reference before they can be interpreted. We evaluated a temple-worn optical wearable, Temple, that outputs a proprietary, dimensionless Brain Flow index, intended as a proxy for relative changes in cerebral hemodynamics, against transcranial Doppler (TCD) ultrasound, which measures blood-flow velocity in the middle cerebral artery (MCAv). Twenty-three healthy adults completed two physiological challenges that elicit distinct and acute cerebral hemodynamic responses: a cycle-ergometer exercise protocol and a stand-to-supine postural transition protocol. Twenty participants were analyzed per protocol. The Brain Flow index tracked MCAv in both protocols, with significant within-subject temporal correlations (median Pearson r = 0.795 and 0.799 for exercise and postural transition; p < 0.001) and directionally concordant, statistically significant transition responses for both increases and decreases in flow. Bland-Altman analysis of the normalized transition responses showed small mean biases between the two devices, consistent with similar relative response shapes. Because both signals were standardized within session before this comparison, it addresses the shape of the relative change rather than agreement in absolute units. The Brain Flow index reproduced the direction and time course of MCAv under both perturbations, including the postural transition, where heart rate moved in the opposite direction. Further studies using complementary modalities and additional cerebrovascular reactivity challenges are required to establish clinical use cases and cerebral specificity of the Brain Flow index.

Background. Whether predictors of intraoperative hypotension (IOH) add information beyond the mean arterial pressure (MAP) already displayed on the monitor is contested: selection bias in common evaluation designs inflates apparent performance, and the field has called for comparisons against simple MAP-based references under bias-resistant protocols. Existing predictors also depend on proprietary waveform analysis or pulse-contour monitors, restricting both deployment and external validation. Methods. Using 807 non-cardiac surgery patients from the open VitalDB database, we derived an additive gradient boosting model (one split per tree: a learned shape function per variable, no interactions) from three variables computable from an arterial line alone: current MAP, its drift from the patient's own 20-minute baseline, and the growth of its rolling variance (critical slowing down). Evaluation used patient-level 5-fold cross-validation under a strict protocol - exclusion of the 65-75 mmHg grey zone and of all samples already hypotensive at prediction time - with MAP alone (same learner class) as comparator. The frozen model was then validated, without any refitting, on an independent cohort from another continent (MOVER, University of California Irvine) following a pre-registered plan sealed before external data access. Results. In development the pressure-only model reached AUROC 0.907 vs. 0.884 for MAP alone (Delta AUROC +0.023, 95% CI +0.017 to +0.029) at 5 min, with +0.031 and +0.032 at 10 and 15 min, and good calibration (Brier skill +0.418 vs. prevalence). In external validation on 3,069 patients (442,194 samples, 1-minute charting, event prevalence 5.8%), the advantage not only transferred but was larger than in development: AUROC 0.696 vs. 0.638, Delta AUROC +0.058 (95% CI +0.051 to +0.064), meeting both pre-registered gates. Discrimination transferred; calibration did not (external Brier skill -0.014), requiring local recalibration. In the unrestricted scenario, where samples already at threshold are retained, the advantage collapsed (+0.007), reproducing the selection effect this paper documents. A secondary model adding pulse-contour cardiac output and stroke volume variation improved development discrimination further (Delta AUROC +0.035) but could be externally validated in only 39 patients, because those signals are rarely recorded. Conclusions. The dynamics of arterial pressure itself - drift from a patient-specific baseline and variance growth - carry predictive information beyond its current value, in a fully interpretable additive model that requires only an arterial line, no waveform access and no proprietary hardware. The advantage is confirmed in a pre-registered frozen-model external validation of over three thousand patients, and is largest at coarse recording cadence, where instantaneous pressure is least informative.

Background and Objectives: Preterm infants are commonly transfused, yet direct cardiorespiratory effects of red blood cell (RBC) transfusions remain poorly understood. We explored the feasibility of using multicentre electronic health data (EHD) to study such cardiorespiratory responses. Methods: Highly granular routine EHD were collected from preterm infants born <32 weeks gestational age at three European centres. Heart rate, oxygen saturation, and respiratory rate were evaluated 12 hours before and after the RBC transfusion. Results: A total of 321 transfusions in 164 infants were analysed. Overall, there was no significant change in the rate of bradycardia and apnoea following transfusion. Cardiorespiratory parameters varied substantially between infants; e.g. 20% of transfusions were associated with an unexpected, significant increase in heart rate. Respiratory rate and oxygen saturation exhibited similarly heterogenous patterns following transfusion. In sub-group analysis, the proportion of transfusions with increased heart rate was significantly higher within the first two weeks than later (32% vs 13%, p=0.0019). Conclusions: Multicentre EHD extraction allows to identify otherwise masked short-term effects of RBC transfusions on cardiorespiratory parameters, possibly indicating cardiac or pulmonary overload. Such effects may vary with adaptation to anaemia. Analysing EHD may ultimately enable personalized transfusion practice.

Background: Unstructured biomedical data, such as echocardiography reports, are rich in information but time consuming to analyze at scale. Rule-based, regular expression-driven terminology mapping can only extract individual variables while large language models (LLMs) offer scalable and clinically meaningful interpretations of heterogeneous disease processes. Right ventricular dysfunction (RVD) is an example of a multifactorial disease state in which key structural and physiologic features are captured both narratively and in structured fields, making it an ideal test case for evaluating whether LLMs can recover complex phenotypes that rules based methods routinely miss. Purpose: To compare an LLM-based extraction method to a conventional rules-based schema for identifying and phenotyping echocardiographic features associated with RVD in a large TTE dataset. Methods: MIMIC-III NOTE2NUM echocardiography reports (n = 45,794) were analyzed using GPT-4o-based LLM extraction deployed within a secure health system enclave and were benchmarked against echocardiographic measurements defined in the MIMIC-III dictionary schema. In MIMIC-III, PH was recorded qualitatively (mild/moderate/severe) based on tricuspid regurgitant (TR) jet velocity and then re-coded as present vs. absent. LLM based extraction defined RVD as (1) RV structural abnormality (>= 1 of hypertrophy, dilation, or wall hypo-/akinesis) or (2) RV pressure/volume overload (>= 2 of the following: estimated right atrial pressure > 8 mmHg, TR jet velocity > 2.8 m/s, fractional area change < 35%, tricuspid annular planar systolic excursion < 17 mm, S' < 9.5 cm/s, or E/e' > 14), with PH defined as estimated pulmonary artery systolic pressure > 35 mmHg or qualitative documentation of PH. Results: LLM extraction identified PH in 15,394 (33.6%), RV pressure/volume overload in 14,449 (31.6%), and RV structural abnormalities in 11,955 (26.1%). Co-occurrence was common: overload + structural changes in 9,380 (20.5%), overload + PH in 9,756 (21.3%), structural changes + PH in 6,183 (13.5%), and all three in 5,620 (12.3%). Using the MIMIC-III dictionary schema, PH prevalence was similar (15,371; 33.6%), but RV overload fields were captured less often (pressure overload 1,357 [3.0%], volume overload 1,128 [2.5%], pressure + volume overload 1,093 [2.4%]; any overload field 3,578 [7.8%]), and RV pressure/volume overload with PH was identified in only 731 (1.6%). Conclusions: LLM-based extraction outperforms rules-based schemas for identifying complex disease states not defined by any single variable. By synthesizing multifactorial signals, LLMs can phenotype RVD with higher fidelity and support population-level assessment. Further validation using multimodality imaging, invasive hemodynamics, and clinical outcome data is needed.

Despite its strong link to neuropsychiatric conditions, frustration remains critically understudied in humans and animals alike. Therefore, there is an urgent need to develop tools to understand and therapeutically target frustration-related functions. Interestingly, humans and rats respond similarly during frustrative nonreward by increasing barpress durations. We previously validated barpress duration in rat operant tasks as a reliable measure of frustration-related behavior; however, it is wellknown that in addition to duration of responding, emotional states such as frustration alter other aspects of responding such as force of pressing. One-dimensional, static measures such as maximum force could miss rich information contained within operant data. Thus, the objective of this study is to apply machine learning (ML) to force/time profiles to discriminate frustration-related barpresses from non-frustration-related barpresses. Results showed an AUROC for FR1 (i.e., non-frustrated) vs. extinction (frustrated condition) for individual barpresses of 0.65 that improved to 0.84 with a chunk size of 10. The model generalized well to progressive ratio responding, a different kind of frustration procedure. We conclude that force/time profiling does provide utility beyond one dimensional measures of duration or force separately, meaning that we can indeed infer the internal state of frustration from behavior using ML techniques. Importantly, this project will also serve as proof-of-concept for applying ML to predict other internal states from barpress data.

Artificial intelligence applied to routine electrocardiograms (ECGs) has largely focused on detecting existing disease or predicting individual cardiovascular outcomes. Whether ECGs can support prediction of multiple future diseases across organ systems remains unclear. We developed ECG-RISK, a multitask survival model for 67 incident three-character ICD-10 endpoints using ECG waveforms, demographic characteristics and routinely collected laboratory data from 86,673 MIMIC-IV patients. Discrimination was highest for heart, brain, kidney and lung endpoints, with organ-level C-indices ranging from 0.796 to 0.825, whereas liver and pancreatic endpoints showed lower discrimination. The ECG-only model achieved strong discrimination across most endpoints, whereas the incremental improvement gained by incorporating ECG and laboratory inputs beyond demographic information varied substantially across endpoints. Across the nine exploratory aggregated outcomes, Kaplan Meier curves showed clear separation among model-score tertiles. Discrimination was highest for dementia (C-index, 0.891) and heart failure (C-index, 0.857). These findings support the feasibility of ECG-based longitudinal risk prediction across multiple diseases. External validation and competing-risk analyses are required to assess generalisability and clinical utility.

Perioperative safety checklists standardize critical actions, but reliable completion depends on the surrounding work system and team behavior. We conducted a prospective observational analytic study from April to May 2026 in the central surgical unit of a high-volume public teaching referral hospital in Indonesia to examine whether patient safety culture and teamwork were associated with directly observed perioperative safety compliance and whether teamwork mediated the culture-compliance relationship. Patient safety culture was measured with the Hospital Survey on Patient Safety Culture 2.0, teamwork with a 35-item TeamSTEPPS Teamwork Perceptions Questionnaire research adaptation, and compliance by direct role-based observation using a 45-item checklist derived from the AORN Comprehensive Surgical Checklist. Eighty of 92 recruited professionals contributed 240 person-operation observations across 50 operations. Overall compliance was 74.75%, with sign-out lowest at 70.68%. Patient safety culture was associated with teamwork ({beta} = 0.590; 95% CI 0.510-0.770) and directly with compliance ({beta} = 0.407; 95% CI 0.187-0.712). The teamwork-compliance coefficient was positive ({beta} = 0.285; p = 0.046), but the prespecified percentile 95% CI included zero (-0.045 to 0.517). The indirect effect through teamwork was not supported ({beta} = 0.168; p = 0.079). These findings support a system-level interpretation of perioperative safety and identify learning-oriented responses to error, situation monitoring, and sign-out fidelity as measurable targets for future improvement efforts.

Conventional sleep electroencephalography (EEG) measures often rely on predefined bands, thresholds, and averages that incompletely capture transient oscillatory dynamics across an entire night. Here, we introduce the Dynamic Oscillation (DYNAM-O) Toolbox, an open-source, cross-platform (MATLAB, Python, and Rust) software package for data-driven characterization of individualized neural dynamics in sleep EEG. DYNAM-O identifies transient oscillations as time-frequency peaks on multitaper spectrograms using a novel multi-resolution procedure, computes intrinsic and sleep-state-dependent extrinsic features for each event, and represents the overnight distributions of tens of thousands of TF-peaks as feature histograms spanning oscillation frequency, slow oscillation power, and slow oscillation phase. This distributional representation preserves continuous brain-state variation that could be obscured by averaging within conventional sleep stages. The toolbox further provides Gaussian and spline basis-based dimensionality reduction, visualization, and whole-histogram statistical testing tools to support both exploratory and hypothesis-driven analyses. To demonstrate its use for group-level inference, we analyzed overnight C3-channel EEG from 133 adults (71 females, 72 males; ages 20-35 years) in the Cleveland Family Study. Whole-histogram and parameterized-mode analyses reproduced the established higher center frequency of fast-spindle activity in females and additionally revealed greater low-alpha transient oscillatory activity in females, a pattern outside the conventional sleep spindle range. By completing the analysis cycle from TF-peak extraction to statistical inference, DYNAM-O provides an accessible and interpretable framework for studying individualized sleep physiology and identifying subtle, reproducible electrophysiological patterns.

Background & Aims: Fatigue is a central symptom of chronic liver disease (CLD), substantially impacting health-related quality of life (HRQoL). This study aimed to further understand CLD symptomatology, including fatigue, and its impact on HRQoL from a patient perspective. Methods: Abbott Global Assessment of Patients unmet needs (aGAP) was a multinational, cross-sectional survey in adults with compensated CLD in China, India and Mexico, conducted between July and November 2024. Adult participants who self-reported that they had physician-diagnosed CLD and were experiencing fatigue completed a quantitative survey to assess symptom burden and included three HRQoL patient-reported outcome (PRO) questionnaires (Patient-Reported Outcomes Measurement Information System [PROMIS]-29+2, Work Productivity and Activity Impairment - Specific Health Problem version 2.0 [WPAI: SHP], Multidimensional Fatigue Inventory [MFI]). Results: Overall, 505 participants (China: 200; Mexico: 105; India: 200) completed the study. Participants reported that their CLD-related fatigue sometimes, often or always affected their self-esteem/confidence (45.1%) and ability to maintain or acquire new employment (38.6%). Most participants reported moderate (51.3%) or serious (26.9%) fatigue, with 33.5% experiencing fatigue every day or almost every day. Many participants felt their social life was negatively impacted by their fatigue (47.3%) and that there were related financial difficulties (53.9%). Use of validated PRO tools demonstrated severe fatigue (MFI: overall mean [SD] 13.9 [3.4] general fatigue and 13.4 [3.6] physical fatigue) as well as substantial levels of work and activity impairment (WPAI: SHP overall mean [SD] 53.0 [26.4]) and high levels of anxiety, pain interference, depression and sleep interference (PROMIS T-scores [&ge;]54). Conclusions: Fatigue has a substantial impact on HRQoL among adults with CLD across several countries, highlighting a global unmet need for targeted interventions to effectively identify and manage the condition.

Background: The condition of a patient with acute stroke often changes within hours of ICU admission. Prognostic work here targets fixed endpoints predicted from admission data, and trajectory phenotyping assigns one label per patient. We used longitudinal ICU data to identify interpretable dynamic clinical states, characterize transitions between them, and relate the current state to later events. Methods: Retrospective cohort study of 6368 adults with acute stroke in MIMIC IV v3.1. The first 72 h were divided into twelve 6-hour windows, and a hidden Markov model was fitted to 21 neurological, physiological and organ support variables. State number was chosen against criteria fixed before fitting: statistical fit, restart stability, state occupancy and clinical interpretability. Generalized estimating equations related the current state to new mechanical ventilation and vasopressor use within 12 h, and to ICU death within 72 h. Eleven sensitivity analyses assessed the robustness of the state solution. Results: Four states were selected: neurologically preserved-low support, neurological impairment low support, impairment renal dysfunction and impairment-respiratory support (63.3%, 7.8%, 11.8% and 17.1% of windows). Within 72 h, 40.3% of patients changed state at least once, and transitions ran in both directions rather than along a single severity gradient. States were identified without outcome data, yet ICU mortality by last state ranged from 2.9% to 43.9%. Adjusted for age, sex, subtype and Charlson index, the current state remained associated with organ-support escalation and death. State prevalence differed by at most 1.1 percentage points between training and test sets, and 10 of 11 sensitivity analyses gave a stable four-state solution (ARI 0.754 0.955). Conclusions: The early ICU course of acute stroke can be represented as movement among a small number of clinically interpretable states. The representation was reproducible in a held out set and across admission eras, but requires validation in an independent database before any clinical use.

Purpose: Otoacoustic emissions (OAEs) are used to assess outer hair cell (OHC) function. Clinical interpretation of OAE responses, however, is often limited to a present/absent binary since both physiological factors and measurement variability affect the measured OAE amplitude. Prior work showed elevated OAE responses in sedated compared to awake chinchillas, pointing to the potential influence of the medial olivocochlear (MOC) efferents on amplitudes, but this finding is inconsistent across species and OAE type. Here, we aimed to further investigate the effect of anesthesia on distortion- and reflection-type emissions in chinchillas using swept stimuli and more reliable calibration methods. Methods: Swept distortion-product (DP) and stimulus-frequency (SF) OAEs were measured in chinchillas with and without ketamine/xylazine sedation. Stimuli were presented using in-ear forward pressure level calibrations. DPOAE and SFOAE amplitudes and estimated Qerb from SFOAE group delays were compared across the two conditions. Results: We found that low-frequency DPOAE amplitudes were elevated when animals were sedated. The difference in SFOAE amplitudes was more variable across animals but appeared mildly reduced in sedated animals. Qerb estimates were slightly higher in sedated animals at some frequencies. The effect of sedation was not different across sexes. Conclusion: Taken together, these findings suggest that sedation impacts OAE measurements in chinchillas. MOC modulation could account for the present findings and differences across species. For diagnostic precision, OAE responses should be considered in the context of not only intrinsic OHC function but also extrinsic physiological processes that can modulate OHCs.

Background: Percutaneous mechanical circulatory support (pMCS) is increasingly used in critically ill patients, yet its value in relation to cost and outcomes remains unclear. We evaluated national variation in utilization, outcomes, and cost, and introduced a value of care framework integrating risk-adjusted outcomes and expenditures. Methods: We performed a retrospective cohort study using the National Inpatient Sample to identify non-elective hospitalizations of critically ill patients undergoing intra-aortic balloon pump (IABP) or percutaneous left ventricular assist device (pLVAD) placement using ICD-10 codes. Multivariable logistic regression and generalized linear models were used to estimate expected outcomes and costs. Observed-to-expected (O/E) ratios were calculated, and a value index was derived to compare procedural strategies. Results: A total of 57,910 weighted hospitalizations were included (IABP 78%, pLVAD 22%). In-hospital mortality exceeded 30% across regions. Significant regional variation was observed, with the West demonstrating the highest costs and the Midwest the lowest (p<0.001). Mean hospital charges were higher for pLVAD compared with IABP ($403,731 vs $320,769). Both strategies achieved outcomes better than expected after risk adjustment (O/E 0.92); however, costs were higher than expected for both, with greater relative cost inflation observed for IABP (O/E 1.41) and higher absolute costs for pLVAD. In value-of-care analysis, IABP was associated with lower cost and comparable outcomes, while pLVAD demonstrated higher cost without proportional outcome improvement. Conclusion: Substantial variation exists in the cost, outcomes, and value of pMCS strategies. While both IABP and pLVAD achieve favorable risk-adjusted outcomes, pLVAD is associated with higher costs without commensurate clinical benefit.

Introduction Postoperative analgesic management after minimally invasive cardiac surgery (MICS) should facilitate early recovery while providing adequate pain control. However, direct evidence comparing postoperative remifentanil- and fentanyl-based analgesic strategies after MICS remains limited. We compared these strategies and explored their associations with postoperative recovery, postoperative nausea and vomiting (PONV), and pain management. Methods This retrospective single-center observational cohort study included patients who underwent MICS via a right mini-thoracotomy between January 2023 and June 2026. Patients were categorized according to postoperative remifentanil- or fentanyl-based analgesia in the intensive care unit. Outcomes included time to extubation, PONV, postoperative pain assessed using the numerical rating scale (NRS), additional analgesic use, and intensive care unit length of stay. Multivariable logistic regression examined the association between postoperative opioid strategy and PONV, adjusting for age, sex, and smoking history. Results PONV occurred less frequently in the remifentanil group than in the fentanyl group (20.6% vs 45.0%, P = 0.004), and this association remained significant after adjustment (adjusted odds ratio, 0.23; 95% confidence interval, 0.10-0.56; P = 0.001). Time to extubation was shorter with remifentanil (median, 179 [interquartile range, 134-240.5] vs 247 [190.2-276.5] min; P < 0.001). In contrast, NRS pain scores on postoperative day 0 were higher with remifentanil (3 [1-6] vs 1 [0-2]; P < 0.001), and additional analgesics were used more frequently (80.6% vs 33.3%; P < 0.001). Pain scores on postoperative day 1 did not differ significantly between groups. Conclusion Postoperative remifentanil-based analgesia after MICS was associated with less PONV and earlier extubation but also with greater early postoperative pain and more frequent additional analgesic use than fentanyl-based analgesia. Appropriate transition to longer-acting analgesics with multimodal analgesia may help preserve the potential benefits of remifentanil while maintaining adequate postoperative pain control.

Background: Multiple sclerosis (MS) is a chronic, immune-mediated disease of the central nervous system marked by demyelination and neurodegeneration. Beyond physical symptoms, MS is often linked to clinically relevant sleep disturbances. The variability and unpredictability of symptoms and disease progression can also fuel fear of relapse (FoR), undermining well-being and potentially increasing morbidity through inflammatory processes. Understanding biopsychosocial risk factors, including childhood maltreatment (CM) and sleep, in relation to FoR remains an important gap in MS management and research. Methods: Data from N = 48 participants were collected via an online survey. We used the Pittsburgh Sleep Quality Index (PSQI), the Fear-of-Relapse Scale (FoR), and the Childhood Trauma Questionnaire (CTQ) to assess the variables of interest. In addition, time points of exposure to different CM subtypes were assessed. Linear regression analyses were conducted to examine associations within the proposed negative triad. Results: A significant negative association between overall sleep quality and FoR was observed. In the total cohort, the interaction between CM and sleep was not a significant predictor of FoR. However, exploratory analysis revealed a significant interaction between CM and sleep among male participants, whereas the same interaction was not significant among female participants. Conclusion: A history of CM and impaired sleep quality introduce new stressors in managing one's own illness that have received little attention to date. However, the present study found that these factors were at least partly influential on the FoR. The results underscore the translational need for additional support services to enhance prevention and personalized care.

Purpose: Lung cancer screening (LCS) with low-dose computed tomography (LDCT) reduces lung cancer mortality, yet screening participation remains low. We evaluated whether a brief informational video nudge delivered immediately before a scheduled clinical encounter increased LCS ordering and baseline LCS completion. Patients and Methods: We conducted a randomized feasibility trial within Kaiser Permanente Colorado from March through October 2025. LCS-eligible patients with an upcoming primary care or pulmonology appointment were assigned to intervention or usual care based on birth month. Intervention patients were split into two group, a group who received the LCS informational video nudge via text message within 24 hours of an eligible appointment; and second group who received the text plus a QR code video link during appointment rooming. Outcomes included LCS orders, baseline LCS-LDCT completion, and video engagement. Multivariable logistic regression was used to evaluate factors associated with LCS ordering. Results: Among 1,093 patients, 549 were assigned to intervention and 544 to usual care. Intervention patients were more likely to receive an LCS order within 1 day of their appointment (22.6% vs 16.4%; p=.010) and any time during follow-up (32.6% vs 24.1%; p=.002). Baseline LCS-LDCT completion was 51% higher in the intervention group, although the difference was not statistically significant (8.6% vs 5.7%; p=.078). Among the intervention group, 93 individuals (17%) viewed the video, generating 114 total views, and viewers watched an average of 79% of the video. Most views (82.5%) occurred through text-message delivery rather than QR codes. Conclusion: A brief, low-burden LCS informational video delivered immediately before a clinical encounter and integrated into existing workflows significantly increased LCS ordering and was associated with higher screening completion. Timely, scalable digital nudges may provide an effective strategy for improving LCS participation. Based on the observed effectiveness, feasibility, and efficiency of the intervention, KPCO incorporated the behavioral nudge into standard clinical care in February 2026.

Three-dimensional (3D) mural cell morphology is heterogeneous and coupled to vessel geometry, however, measurements from two-dimensional (2D) maximum intensity projections (MIP) obscure overlapping processes and cell-vessel contacts. Accordingly, we developed Mural-VISTA, a semi-automated Python workflow for mural cell-vessel interaction and single-cell topo-morphology analysis of reconstructed surface meshes. This workflow integrates mesh pretreatment, interactive centerline extraction, hierarchical segmentation of cell soma, main axis and secondary processes (branches), and extraction of 36 multiscale (cell process segment level, process level, and whole cell level) topo-morphological and vessel-referenced metrics. Mural-VISTA identified morphological changes in pericytes and vascular smooth muscle cells (vSMCs) with altered RhoA activity. Constitutive active RhoA (RhoA CA) over-expression reduced branch complexity and increased process alignment in both cell types, while increased whole-cell and branch solidity only in vSMCs. Dominant negative RhoA (RhoA DN) over-expression increased branch abundance and reduced branch solidity in pericytes but not vSMCs, suggesting cell-type specific effect of reduced RhoA activity. In conclusion, Mural-VISTA enables quantitative 3D profiling of mural cell architecture and its spatial relationship with the vessel.

Purpose: In clinical trials, treatment efficacy is commonly assessed by comparing control and treatment groups. However, in large samples, even small and clinically trivial differences may achieve statistical significance. Accordingly, the Minimal Clinically Important Difference (MCID) is used as a threshold to determine whether statistically-significant effects are also clinically meaningful to patients. The objective of this study was to estimate the MCID for the Childhood Autism Rating Scale Second-Edition (CARS2) using the Patient Impression of Change (PIC) as an external anchor. Methods: Single-item PICs are not well suited to characterizing improvement in a multifaceted disorder such as ASD. Accordingly, the 77-item Autism Treatment Evaluation Checklist (ATEC) was used as a multi-item PIC. CARS2 and ATEC were administered concurrently to 62 children with ASD, aged 1.8-7.9 years, with assessments conducted six months apart. Results: The correlation between changes in CARS2 and ATEC total scores was 0.41-0.44 (p<0.0001), supporting the use of ATEC as an anchor measure. Two anchor-based methods yielded MCIDs of 2.39-2.82 CARS2 points. Two distribution-based methods produced MCIDs of 1.33-3.32. Conclusions: Taken together, these approaches suggest that a between-group difference of 2.6 CARS2 points (the midpoint of the anchor-based estimates) may serve as the MCID in children with ASD.

Background: Reliable melanoma classification requires models that capture both local dermoscopic morphology and broader contextual patterns while maintaining auditable, leakageaware internal validation. Objectives: To develop and internally validate an EfficientNetB0-Swin Transformer Tiny ensemble for classifying histopathologically verified dermoscopic images as benign melanocytic lesions or malignant melanoma. Methods: This retrospective diagnostic model-development and internal validation study screened 552,869 ISIC Archive records; filtering and dermatologist review yielded 1,199 uniquepatient and unique lesion images (578 benign and 621 malignant). Images were the predictors and histopathology was the reference. ImageNet pretrained EfficientNetB0 and Swin-T features were fused. Patient independent five fold validation used weighted sampling, mixup, label smoothing, AdamW, early stopping, and five view test time augmentation. Results: Mean accuracy was 0.89325 {+/-} 0.03179, mean receiver operating characteristic area under the curve (ROC-AUC) was 0.96348 {+/-} 0.01695, and mean support weighted F1-score was 0.89300 {+/-} 0.03220. The fold level 95% confidence intervals were 0.8538-0.9327 for accuracy and 0.9424-0.9845 for ROC-AUC. Pooled counts were 526 true negatives, 52 false positives, 76 false negatives, and 545 true positives, yielding 87.76% sensitivity and 91.00% specificity. Qualitative Grad-CAM review showed peripheral artifact activation in two false positives and lesion centered activation in two correctly classified cases; these observations were not systematically scored. Limitations: The validation folds were also used for early stopping and checkpoint selection. Device stratified analysis, systematic interpretability scoring, calibration, and independent external validation were unavailable. Conclusions: The ensemble showed high internal discrimination and is intended only as a clinician facing adjunct. The error audit workflow enables targeted retrospective review, but external validation is required before clinical use or generalizability claims.