Value in Health

Background: Cost-effectiveness analyses (CEA) built on simulation models are usually delivered through project-specific scripts. Each new model, and often each new question, rebuilds the same scaffolding: parameter management, calibration, base-case analysis, sensitivity analysis and export. This is costly, and is where traceability between an estimate and the model version producing it is lost. We present THALASSA, a web application providing this infrastructure once, for any model satisfying a small programming contract. Methods: A simulation model is connected by one file implementing a fixed contract of R functions that determine its behaviour. THALASSA exposes the complete CEA workflow in a browser: a generated overview of the connected model, parameter editing, calibration, base-case comparison with the efficiency curve, and deterministic and probabilistic sensitivity analysis at a willingness-to-pay threshold, each with timestamped file export carrying the parameter values it was run with. Every session is bound to a repository version, so results carry their generating model version. Results: We demonstrate THALASSA on two public models of contrasting difficulty: a simple tutorial model and a generic cancer screening model with two competing natural-history pathways and a 21-dimensional calibration deliberately built to be more complex. Both ran on the same unmodified setup, implementing the same contract, with no code changes. Conclusions: Separating analysis infrastructure from model logic makes the CEA workflow reusable across projects and reproducible by construction. A modelling team can move from a versioned repository to audit-ready, exportable CEA outputs without writing analysis code. The integration effort does not grow with model size and one installation serves unrelated projects.

Abstract Background Estimates of the healthcare costs associated with influenza treatment are essential for cost-effectiveness analyses that inform preventative and treatment strategies such as vaccination and non-pharmaceutical interventions. Existing evidence varies across treatment settings, age groups, and countries and there is little data from low- and middle-income settings. Methods We conducted an umbrella review of systematic reviews and meta-analyses reporting direct admitted and non-admitted hospitalisation costs of seasonal influenza treatment in children, adults, and older people. We supplemented an evidence gap with a systematised review of studies reporting adult non-admitted treatment costs. Costs were extracted and adjusted to 2023 USD. We fitted a Bayesian mixed-effects model to estimate influenza treatment costs using national economic indicators, age group, and treatment setting as a priori predictors. We predicted admitted and non-admitted treatment costs for children, adults, and older people in 195 countries and territories. Results Seven reviews were included in the umbrella review, supplemented by 17 primary studies for adult non-admitted care. Extracted data points most frequently described admitted treatment costs and came from high-income countries. The best-fitting model used healthcare expenditure per capita to predict treatment costs, with country-level random effects. Estimated costs increased with healthcare expenditure per capita, were higher for admitted than non-admitted care, and were highest for adults and lowest for children. Conclusions This study provides novel estimates of influenza-associated healthcare costs across age groups and treatment settings by synthesising the available global evidence. By extrapolating to settings without data, our estimates can inform future economic evaluation studies of influenza interventions worldwide.

BackgroundEvaluating fairness in artificial intelligence (AI) is essential before clinical implementation to prevent unintended harm across diverse patient populations. This study assesses performance differences of an image-based surgical site infection (SSI) detection model across age, gender, geography, race, and skin color. MethodsModel development/validation study using retrospective, multicenter data across surgical subspecialties from adults who submitted an image of their incision via the electronic health record within 30 days of their procedure between 2019-2024. Area under receiver operating curve (AUROC) was compared by age (<55 vs. [&ge;]55 years old), gender (male vs. female), geography (Rochester, Minnesota vs. Jacksonville, Florida vs. Scottsdale, Arizona vs. regional Minnesota/Wisconsin areas), race (White/Caucasian vs. non-White/Caucasian), and skin color (Fitpatrick I-III vs. IV-VI and Monk A-E vs. F-J). ResultsTraining data contained 13,702 images from 4,274 patients between 2019-2022 (50.1% [&ge;]55 years old; 63.2% female; 91.6% White/Caucasian; 58.5% Rochester, 17.3% Florida, 10.5% Arizona; 96.3% light skin tone), of which 1,348 images (9.8%) had an SSI. No differences in SSI detection existed for age, gender, race, or skin color (AUROC 0.83-0.87, p>0.09), however geographical differences were significant: lowest AUROC 0.83 (95% CI 0.77-0.88) vs. highest AUROC 0.87 (95% CI 0.84-0.89, p=0.01). Temporal validation using 4,242 images from 1,353 patients between 2022-2023 showed intact fairness across subgroups ({Delta}AUROC [&le;]0.06) except geography ({Delta}AUROC [&le;]0.16). ConclusionsThe model behaved fairly across age, gender, race, and skin color, however geographical differences persisted. These findings have practical implications underscoring the importance of evaluating bias in clinical AI before deployment.

Introduction: Hospitals face increasing financial pressures. Hospital reimbursement is tied to the Case Mix Index (CMI). The CMI is a measure of complexity of care provided by the hospital and the total reimbursement is the CMI multiplied by a base pay factor, multiplied by the total number of discharges from the hospital. The few studies in the literature have involved logistically complex attempts to improve documentation. We sought to determine whether limited, structured chart review by surgeons can improve CMI in a multihospital system. Methods: We performed a prospective, observational study in a four-hospital academic medical system on all surgical patients from 10/2022 to 7/2026. Two clinically busy trauma surgeons performed limited structured chart reviews for select surgical patients. In the limited intervention period (1/2024-9/2024) this focused only on the trauma division. In the full intervention period (10/2024-7/2026) expanded to all surgical patients across the system. The main outcome was surgical case mix index (CMI). Results: A total of 35,695 patients were included (13,811 pre-intervention, 9,337 limited intervention, 12,547 full intervention). CMI increased significantly among surgical patients across the whole system (2.68 (95%CI 2.65-2.71) to 2.87 (95%CI 2.82-2.92) to 2.97 (95%CI 2.93-3.01), ANOVA p <0.001). Overall length of stay was unchanged among surgical patients across the whole system. The estimated increase in revenue per patient attributable to this intervention was $3,912 in surgical patients across the system. Conclusion: Having trauma surgeons review targeted surgical patients for high value documentation capture significantly enhanced the CMI and estimated revenue of surgical services across a multi-hospital integrated health system. Such documentation reviews may represent a practical method to improve hospital documentation and revenue.

Background: Robust evidence linking individual surgeon technical performance to patient outcomes in complex minimally invasive surgery remains scarce. Crowd-sourced video assessment offers a scalable alternative to expert review, but its clinical relevance in complex oncologic procedures such as robot-assisted minimally invasive esophagectomy (RAMIE) is unestablished. Methods: In this exploratory study, video recordings of 60 consecutive RAMIE procedures performed by 7 surgeons (2018-2023) were segmented into five representative surgical steps and rated by 93 blinded crowd-raters per segment using a modified GEARS instrument. Tertiles were used to compare top-performing operations and steps against the remaining two terciles for overall and step-specific performance, and associations with perioperative outcomes were analyzed. Results: Top-tercile overall performance was associated with significantly shorter operative time (abdominal, thoracic, and total) and less intraoperative blood loss (all p<0.05), without differences in postoperative outcomes. In exploratory step-specific analyses, top-tertile performance during infracarinal lymphadenectomy was associated with significantly fewer surgical complications (30.0% vs 60.0%; p=0.028), fewer severe surgical complications (25.0% vs 52.5%; p=0.043), and higher lymph node yield (22.8 vs 18.9; p=0.037), while the purse-string suture step showed the broadest operative-time benefit. These step-specific findings are hypothesis-generating and were not adjusted for multiple testing. Conclusion: Crowd-sourced video assessment enables scalable, step-specific evaluation of surgical performance in RAMIE associated with intraoperative blood loss and operative time. Exploratory analyses suggest that the relationship between technical performance and clinical outcomes might be step-specific, with infracarinal lymphadenectomy emerging as risky step linked to postoperative morbidity. These findings support further investigation of individualized performance assessment for quality improvement and risk stratification.

Background: Lean Healthcare has been adopted as an approach to reducing waste, enhancing process efficiency, and optimizing clinical and administrative workflows. However, empirical evaluations aimed at establishing a causal relationship between Lean Healthcare interventions and outcomes remain limited. This evidence gap is particularly pronounced in the context of large-scale implementations in low- and middle-income countries, where more efficient allocation could yield substantial improvements in population health. Methods: We conducted an impact evaluation study employing a staggered difference-in-differences approach to estimate the effects of the Lean Healthcare in Emergency Departments (ED) initiative in the Brazilian context. The intervention was implemented between January 2017 and December 2025 across 309 hospitals. We analyzed hospital-level indicators of the number of hospitalizations and the average length of stay (in days) among patients admitted through urgent or emergency pathways. Results: Our estimates suggest that the intervention was associated with an average increase of 38.6 admissions per hospital per month (p = 0.033), corresponding to approximately a 5.9% increase relative to the monthly admission volume. We also observed a reduction of 0.184 days in the average length of stay (p = 0.058), equivalent to an approximately 3.0% decrease in hospitalization time. These effects exhibited distinct temporal dynamics: the effect on the number of hospitalizations emerged gradually and increased with the duration of the intervention, whereas the reduction in length of stay became evident earlier. Conclusion: This study provides evidence of a causal effect of Lean Healthcare implementation in emergency departments on operational performance. The simultaneous increase in admissions and reduction in length of stay suggests improved bed productivity and effective capacity without expanding physical infrastructure. These findings support the use of flow-management methodologies as an effective strategy for mitigating emergency department overcrowding while increasing service capacity.

Background/Objectives: Older adults are at high risk of influenza-related severe disease and complications. HD-IIV, currently recommended for adults [&ge;]65 years, is egg-based and may be subject to egg-adapted mutations. An mRNA-based vaccine for influenza, mRNA-1010, has been approved by the Food and Drug Administration. Given the clinical benefits observed in mRNA-1010 clinical trials and potential to avoid egg-adapted mutations, this analysis explores the clinical impact of mRNA-1010 compared to HD-IIV in those [&ge;]65 years in the United States. Methods: This study used a decision-analytic model of influenza infection and downstream outcomes to project influenza burden with each vaccine over a one-year timeframe. Vaccine coverage, HD-IIV vaccine effectiveness (VE) and influenza epidemiology was estimated based upon Centers for Disease Control and Prevention data. The relative VE (rVE) for mRNA-1010 vs. HD-IIV was modelled based on data from the clinical trial and published literature on the impact of egg adaptation. Results: The base-case analysis suggests mRNA-1010 may prevent an additional 232,200 symptomatic influenza infections, 130,000 outpatient cases, 21,100 influenza-related hospitalizations, and 2,200 influenza-related deaths compared to HD-IIV. The number needed to vaccination to prevent one hospitalization was 514 or mRNA-1010 vs no vaccine and 404 for HD-IIV versus no vaccine, for an incremental NNV of 110. Scenario and deterministic sensitivity analyses results indicate that clinical outcomes prevented by mRNA-1010 are most sensitive to influenza incidence and VE. Conclusions: mRNA-1010 may improve protection against influenza in US adults aged [&ge;]65 years, leading to meaningful reductions in the clinical influenza-related disease burden in older adults.

PurposeTo describe the development of - and outcomes from - an institution-level initiative supporting access to innovative genetic medicines information and opportunities. MethodsWe developed and implemented a Genetic Medicines Patient Assessment Pathway for rare genetic conditions at a large public hospital, with multidisciplinary teams collaborating to evaluate a patients molecular and clinical amenability to experimental and/or to-be-developed genetic medicines (primarily nucleic acid therapeutics). A Genetic Medicines Consult Clinic operating in parallel offered no-cost specialized consultations and counseling to families regarding genetic medicines inquiries and Pathway outcomes. We retrospectively reviewed submissions, decisions, and outcomes over a >2-year period. ResultsA total of 63 submissions were reviewed in the Patient Assessment Pathway. Most submissions were classified as eligible or potentially eligible for at least one genetic medicines approach (42/63; 67%). Recommendations generated 87 discrete actions, such as outreach to potential collaborators (n = 28), offering participation in existing research studies (n = 23), or referral to the Consult Clinic (n = 19). Two patients have been approved for therapeutic program initiation or clinical trial enrolment. ConclusionFindings to date support feasibility and high uptake of a structured, multidisciplinary, medical genetics-led model for assessing patient-level opportunities for genetic medicines.

Background: While health system costs of COVID-19 are well documented, evidence on out-of-pocket costs to patients and families, including non-medical and time burden, is limited. This study aimed to estimate out-of-pocket medical, non-medical, and time burden of COVID-19 illness directly from patients and caregivers. Methods: Two cross-sectional surveys were fielded to national nonprobability samples of U.S. adults in Fall 2023: a personal burden survey (adult sample) and a caregiver burden survey (child sample). Surveys collected data on care setting, visit duration including travel and wait time, and medical and non-medical out-of-pocket costs. After applying quality-based exclusion criteria, 409 adult sample and 52 child sample responses were analyzed. Results: Over 87% of respondents were insured. Median out-of-pocket medical costs per visit were low, ranging from $5 (emergency department) to $10 (urgent care) in the adult sample, and from $0 (emergency department) to $75 (hospitalization) in the child sample. Median non-medical costs were $28 or less across care settings. Median time spent receiving care ranged from 90 minutes (primary care, child sample) to 300 minutes (emergency department, adult sample). Despite the relatively low reported out-of-pocket costs, COVID-related financial challenges were reported by 34% of the adult sample and 29% of the child sample, with the most common difficulty being paying non-medical bills (11% and 15%, respectively). Twelve percent in both groups reported problems paying COVID-19-related medical bills. Conclusions: In this post-pandemic non-probability sample, individual out-of-pocket costs for COVID-19 illness were relatively modest. However, time burden was substantial and one-third of respondents reported financial hardship. These estimates, including non-medical and time burden not captured in administrative data, can support more robust economic evaluations of COVID-19 prevention and treatment interventions.

Background/Aims This work aimed to estimate the annual tertiary healthcare and societal costs associated with paediatric congenital heart disease (CHD) in the United Kingdom using real-world data from a Level 1 cardiac surgical centre in the National Health Service (NHS). Methods A prevalence-based cost-of-illness analysis was conducted using patient-level inpatient and outpatient activity data from Evelina London Children's Hospital between 1 June 2023 and 31 May 2024. Costs were estimated from NHS and societal perspectives and extrapolated to national level using National Congenital Heart Disease Audit (NCHDA) procedural activity data. Healthcare costs included tertiary centre care costs. Societal costs included parental productivity losses and impacts on lifetime earnings for children. Deterministic sensitivity analysis explored parameter uncertainty. Results Approximately 9.6% of UK paediatric CHD procedures were undertaken at Evelina London Children's Hospital at a cost of {pound}15.0 million per annum, corresponding to a national estimate of {pound}156.4 million. Single-ventricle procedures accounted for 4.8% of inpatient activity but 19.4% of inpatient costs. Sensitivity analysis produced national healthcare cost estimates ranging from {pound}125.1 million to {pound}187.7 million. National productivity losses associated with parental absence from work were estimated at {pound}82.4 million annually. Individuals with CHD were estimated to experience a mean reduction in lifetime earnings of {pound}81,509. Conclusion Paediatric CHD imposes a substantial economic cost on the UK healthcare system and wider society. This study provides the first real-world national estimate of the economic impact of paediatric CHD in the UK and may inform future service planning, research investment, and innovation adoption strategies.

ObjectiveTo evaluate usability and workflow implications of Pheno+, an electronic health record- (EHR) embedded natural language processing tool that extracts patient phenotypes and maps them to Human Phenotype Ontology (HPO) terms. Materials and MethodsThis study performed a mixed-methods formative evaluation of Pheno+ in the context of rapid genome sequencing in the neonatal intensive care unit. Two rounds of think-aloud interviews and surveys were conducted with neonatologists, advanced practice providers, medical geneticists, genetic counselors, non-genetics pediatric subspecialists and laboratory molecular geneticists. Usability was assessed using the System Usability Scale (SUS). Structured data were analyzed descriptively. Qualitative data underwent hybrid deductive-inductive thematic analysis. ResultsTwenty-eight interviewees participated in two rounds of data collection. Users retained an average of 24.2 HPO terms from an average of 45.6 terms per patient. Mean time curating terms was 8:59 per patient. Final SUS score was 76 (above scale mean). Qualitative themes included: burden of curating terms; interpretation of phenotypes; adding information to phenotypes; role of genetics expertise; and tool uses beyond the original core use case for Pheno+. DiscussionPheno+ demonstrated positive usability but required curation effort to reduce erroneous terms. Participant responses indicate that effective use may depend on knowledge of HPO structure and laboratory workflows. Automated phenotyping seems likely to reduce net clinician workload, while also reshaping clinical responsibilities, expertise requirements, and communication in genetic testing. ConclusionTools like Pheno+ can support scalable genomic medicine. Design and implementation may benefit from addressing curation burden, phenotype contextualization, expertise requirements, and other workflow needs.

Abstract Background: In Pakistan approximately 7 million people were living with diabetes in 2014. To address the burden of diabetes, a randomized controlled trial was conducted to evaluate the effectiveness of a standardized care package in improving diabetes outcomes in health care settings of Punjab, Pakistan. A costing study was embedded within this RCT to estimate the cost-effectiveness of the standardized diabetes care package in improving diabetes outcomes. Methods: 166 patients were recruited for the costing study from 14 public health clusters in Sargodha district of Pakistan. Analyses was conducted using the societal perspective, broader societal perspective and sensitivity analyses to explore the uncertainty in analyses. Data was analysed for both 166 participants enrolled in costing study and for the 495 participants recruited in the cRCT, using multiple amputations. Results: Using the societal perspective, standardized diabetes care package was found to be cost-effective as compared to the standardized care and was cost saving as the costs in the intervention arm were lower than those in the control arm whereas greater effects were demonstrated in the intervention arm. As per the broader societal perspective and the healthcare perspective only, the standardized care package was not proven to be cost-effective. Keywords: Diabetes management, health services cost, out of pocket cost, cost-effectiveness.

We analyse the effect of waiting time for elective musculoskeletal treatment on labour market outcomes in England using hospital records for working-age adults who received treatment between April 2015 and March 2023 to Census, tax and benefit records. To address clinical prioritisation and unobserved severity, we leveraged provider-level waiting time as an instrument for individual waiting time and estimated two-stage least squares models adjusted for baseline labour market outcomes, demographic and socioeconomic characteristics, and provider, referral-time and procedure fixed effects. We find that longer waits reduce annual employee earnings, with effects persisting for up to five years. For an additional four weeks of waiting, the largest estimated annual losses range from {pound}301 for osteoarthritis to {pound}487 for other joint disorders. There was no evidence of effects on employment status or benefit receipt, suggesting that delays primarily operate through reduced productivity or hours worked among those who remain employed. Reducing waiting times may not only improve health outcomes but help patients maintain earnings and support economic

Polygenic risk scores (PRS) are rapidly developing, enabling estimates of genetic risk for developing psychiatric disorders. Psychiatric PRS are also increasingly entering consumer and clinical settings. Yet, little is known about how adults with psychiatric disorders perceive their potential use. Here, we conducted semi-structured interviews with 29 adults with psychiatric disorders to examine their perspectives on hypothetically receiving psychiatric PRS for themselves and their current or future children. Key themes emerged around perceived utility, motivations and deterrents to genetic testing, interpretation of PRS, and anticipated responses to results. In particular, participants expressed hope that PRS could support self-understanding, inform better psychiatric care, and enable earlier recognition of difficulties for their children. Participants however raised multiple concerns, including those of privacy, stigma, discrimination, eugenics, and the risk of self-fulling prophecies. Together, these findings offer critical empirical evidence to inform guidance on the responsible use of psychiatric PRS in clinical and consumer settings.

Background.Respect for autonomy is central to biomedical ethics but is rarely assessed with a structured, reproducible measure. This gap matters as patients, families, and clinicians increasingly use general-purpose language models for health-related questions. We developed the Autonomy Index (AIx) to characterize autonomous agency in clinical-ethics vignettes and compared ratings from trained human reviewers with ratings from current language models. Methods.We reviewed ten decisional-capacity instruments and classified them by target construct into consent capacity, decision capacity, and functional autonomy, identifying a region of autonomous agency (values, deliberation, and enactment) that existing instruments measure least well. The resulting thirteen-item instrument scores four domains: Values Awareness, Factual Understanding, Rational Deliberation, and Intentional Action, on a five-point ordinal scale with an explicit not-applicable option; the External Constraint Index and Support Provided Index are reported separately. Nine models scored 89 clinical vignettes. We selected 50 vignettes by model-score tier and inter-model disagreement, then obtained 173 ratings from 30 clinical and bioethics-informed reviewers and 3,431 valid scores from eight models in July 2026. The prespecified comparison summarized each source within vignette and estimated the paired human-minus-model difference; mixed-effects, domain, agreement, and variance-component analyses were secondary or exploratory. Human data were collected under Harvard Longwood Campus IRB protocol IRB26-0146. Results.Across the selected 50-vignette comparison set, human and model composites were strongly associated (Pearson r = 0.781, P = 2.3 x 10-{superscript 1}{superscript 1}; Spearman {rho} = 0.775). The human mean was 50.2 and the model mean was 39.2, a paired human-minus-model difference of 11.0 index points (95% CI, 6.3 to 15.8; P = 2.6 x 10-; d_z = 0.66). Human means exceeded model means on 36 of 50 vignettes. Bland-Altman limits of agreement were wide (-21.9 to 43.9), indicating substantial case-level variation. Mean differences were positive in all four domains: Factual Understanding, 13.7; Intentional Action, 12.3; Values Awareness, 10.4; and Rational Deliberation, 7.9 points; the joint domain-by-source test did not detect heterogeneity (Wald {chi}{superscript 2}[3] = 2.27, P = 0.52). Vignette content accounted for 80.9% of score variance, whereas source accounted for 0.7%. Models never selected not applicable; human reviewers did so for 22.5% of item responses. Among 19 vignettes with at least four human ratings, 9 had human-minus-model differences greater than 15 points and none had a difference below -15 points. Conclusions.In this deliberately selected 50-vignette set, trained reviewers assigned higher autonomy scores than the tested general-purpose language models on average, while the two sources ranked cases similarly. Wide limits of agreement and variation across well-rated vignettes preclude treating the mean difference as a prediction for an individual case. Because the comparison set was selected using prior model scores, reviewers were a convenience sample, and human ratings are a reference standard rather than ground truth, the findings should be interpreted as evidence of systematic divergence in this sample, not proof that models underestimate patient capacity. External validation in prospectively sampled cases with denser human rating is required before clinical use.

Background. Large language models (LLMs) are increasingly used to support systematic review and meta-analysis, but complex evidence flow, trial-family identification, study-level data extraction, and statistical execution remain vulnerable to omissions, untraceable data paths, and scientifically flawed steps. It remains unclear whether gains are driven by modular skills or by fixed orchestration, and whether these effects differ across base models. Methods. We conducted a controlled, multi-model benchmark in which six LLMs completed the same randomized controlled trial (RCT) meta-analysis task under three conditions: (A) no meta-analysis-specific skills; (B) autonomous access to modular meta-analysis skills; and (C) the same skills executed under a Quality-First fixed directed acyclic graph (DAG). Each model was run three times per condition (54 runs total). The primary outcome was the scientific performance score (SPS, 0-100), rated by two meta-analysis experts; one expert was masked to explicit model and condition labels during SPS scoring, and final scores were the arithmetic mean of the two raters. Inter-rater reliability was high (SPS ICC(A,2) = 0.991). Results. Mean SPS was 43.50 (condition A), 55.65 (B), and 54.44 (C). Relative to unassisted models, modular skills improved mean SPS by +12.15 points (unadjusted 95% CI 3.15-21.16; Holm-adjusted P = 0.033). The combined modular-skills-plus-fixed-DAG condition showed a positive but not statistically significant difference relative to unassisted models (C-A = +10.94; Holm-adjusted P = 0.073) and no incremental gain over skills alone (C-B = -1.21; Holm-adjusted P = 0.746). No condition-by-model interaction was detected (P = 0.801). Conclusions. In this benchmark task, access to modular skills improved mean scientific performance relative to unassisted execution; fixed orchestration of the same skills did not provide a detectable incremental benefit. The findings are task-specific and do not establish general effects for other meta-analysis settings, models, or orchestration designs. Keywords: Large language models; meta-analysis; Agent skills; Workflow orchestration; Evidence synthesis

Background. Comparing long-term outcomes of gastric cancer surgery between hospitals requires a common reference. Risk-adjusted benchmarks depend on the model and population used to build them and are difficult for another hospital to reproduce. TNM stage is a prognostic classification already recorded for every resected gastric cancer. We report unadjusted stage-specific overall survival from a consecutive cohort with complete follow-up as reference data and propose a minimal dataset for producing comparable figures elsewhere. Methods. The cohort comprised 690 consecutive eligible patients who underwent curative-intent D2 gastrectomy for stage I to III adenocarcinoma at Ruijin Hospital, Shanghai, in 2019. All operations were performed by eight experienced, high-volume consultant surgeons. Stage followed the AJCC 8th edition: pTNM after upfront surgery (n = 570) and ypTNM after neoadjuvant chemotherapy (n = 120). Overall survival was estimated by the Kaplan-Meier method without adjustment. Results. There were 199 deaths, 181 within five years. Every survivor was followed for at least 68.1 months. After upfront surgery, five-year overall survival was 95.0% (95% CI 91.4 to 97.1) for stage I, 83.8% (76.5 to 89.0) for stage II and 56.5% (49.2 to 63.1) for stage III, and was 95.0% in IA and 95.2% in IB, falling to 26.7% in IIIC. After neoadjuvant chemotherapy, five-year survival was 78.6%, 61.9% and 31.3% for ypStage I, II and III. Pooling pTNM and ypTNM lowered stage III five-year survival to 50.2%. The proposed minimal dataset has 16 items, 13 of them recorded during the admission for gastrectomy. Conclusions. These figures are intended as a reference for comparing hospitals rather than as a standard of care. We propose 16 items, most of them routinely recorded, from which another hospital can produce the same table and compare its results by stage.

The aim of this study was to develop a framework for assessing the incremental value of decisions on drug amount, timing, input structure, cessation and restart. The LOGOS (Longitudinal Optimization of Global Outcomes and Strategies) approach combines matched nested regimen classes, mechanism-specific benchmarks and evidence requirements in a single longitudinal comparison. Thus, the contribution of additional regimen freedom is assessed separately from improvements due to different resources, constraints or evaluation horizons. Nested feasible classes have nondecreasing objective suprema, whereas a strict gain requires a feasible witness above a valid bound for the smaller class. The approach is illustrated through analytical examples of periodic smoothing, matched desensitization, relaxed exposure allocation, finite-course loading and safety after cessation. In a normalized finite Emax model, integrated benefit increased from 0.629606 for three equal boluses to 0.672945 after optimization of amounts, 0.677043 for an amount-and-time candidate and 0.679553 for a globally certified loading-maintenance-coast solution. The adjacent observed gains were 6.88%, 0.61% and 0.37%, respectively, and all schedules satisfied the full-tail injury bound. In addition, a periodic factorial example separated response curvature from a joint recovery and repair process, including a null case and results dependent on feasibility constraints. The LOGOS framework allows assessment of whether additional regimen flexibility improves benefit, provides no added value or restores feasibility. These dimensionless examples support conditional mathematical and model-based conclusions; clinical superiority and safe restart in patients have not been established.

Background: Rapid genome sequencing (rGS) is a first-tier test in the neonatal intensive care unit (NICU). Implementation strategies to scale rGS for clinical care may change clinician roles. We analyzed the NICU rGS workflow to understand challenges rGS poses for clinical roles and responsibilities. Methods: The study took a qualitative approach to understanding the rGS workflow in Level III and Level IV NICUs. The five workflow phases studied included: i) identification of a patient with a suspected genetic disorder, ii) subspecialist consultation, iii) test selection and ordering, iv) return of results, and v) disclosure. Data were collected via job task journals, interviews, and workflow diagram construction with clinicians involved in rGS. Analysis included participant-guided workflow diagram refinement, qualitative thematic analysis, and identification of rGS workflow challenges. Results: We documented issues related to decision-making authority and scope of responsibility for clinicians, with the majority relating to complexities of subspecialist consultations. Issues included differences in: criteria for triggering consultations, expectations of consulted subspecialists' roles, test selection preferences, and responsibility for documenting clinical interpretations and disclosure. Conclusion: Subspecialist consultations in clinical rGS involved significant role ambiguity and communication challenges, requiring intentional implementation efforts to ensure clear clinical roles and responsibilities.

Background: Articulated laparoscopic instruments require a reliable mechanical connection between the handle and shaft to maintain the intended instrument configuration during surgical manipulation. The handle shaft locking interface should resist unintended relative displacement under external loading. However, the appropriateness of a specific slip resistance threshold must be evaluated in relation to the instrument design and intended conditions of use. Objective: To evaluate the mechanical performance associated with an 8 N slip resistance specification for the locked handle shaft interface of an articulated laparoscopic instrument using a controlled bench model. Methods: A bench based mechanical evaluation method was designed using the instrument under test, mechanical fixtures, a calibrated force measurement device, and displacement measurement equipment. After engagement of the handle shaft locking mechanism, external forces were applied to evaluate resistance to relative displacement. Testing included axial loading, loading in relevant transverse directions, and repeated locking unlocking cycles. The primary outcome was the force corresponding to the onset of relative slippage at the locked interface. Secondary outcomes included displacement under load, complete locking failure, and changes in mechanical performance after repeated operation. Acceptance criteria should be established before confirmatory testing. Results: All 30 instruments from three production batches met the 8 N axial requirement (30/30). The axial slip onset force was 12.40 N . Under a sustained load of 8 N for 60 s, mean relative displacement increased from 0.06 mm to 0.10 mm, and mean residual displacement was 0.02 mm. After 1,000 cycles, the axial slip-onset force was 12.00 N . Conclusions: This study provides a bench-testing framework for evaluating an 8 N slip resistance specification for the handle shaft locking interface of an articulated laparoscopic instrument. Whether this specification provides adequate mechanical stability can be determined only by comparing the measured performance with engineering acceptance criteria established in advance on the basis of the instrument's intended use and foreseeable loading conditions.