Longitudinal clinical decision support for assessing decisions over time: State-of-the-art and future directions.

Objective: Patients and clinicians rarely experience healthcare decisions as snapshots in time, but clinical decision support (CDS) systems often represent decisions as snapshots. This scoping review systematically maps challenges and facilitators to longitudinal CDS that are applied at two or more timepoints for the same decision made by the same patient or clinician. Methods: We searched Embase, PubMed, and Medline databases for articles describing development, validation, or implementation of patient- or clinician-facing longitudinal CDS. Validated quality assessment tools were used for article selection. Challenges and facilitators to longitudinal CDS are reported according to PRISMA-ScR guidelines. Results: Eight articles met inclusion criteria; each article described a unique CDS. None used entirely automated data entry, none used living guidelines for updating the evidence base or knowledge engine as new evidence emerged during the longitudinal study, and one included formal readiness for change assessments. Seven of eight CDS were implemented and evaluated prospectively. Challenges were primarily related to suboptimal study design (with unique challenges for each study) or user interface. Facilitators included use of randomized trial designs for prospective enrollment, increased CDS uptake during longitudinal exposure, and machine-learning applications that are tailored to the CDS use case. Conclusions: Despite the intuitive advantages of representing healthcare decisions longitudinally, peer-reviewed literature on longitudinal CDS is sparse. Existing reports suggest opportunities to incorporate longitudinal CDS frameworks, automated data entry, living guidelines, and user readiness assessments. Generating best practice guidelines for longitudinal CDS would require a greater depth and breadth of published work and expert opinion.

Transcriptomic Differences in Peripheral Monocyte Populations in Septic Patients Based on Outcome.

ABSTRACT: Post-sepsis early mortality is being replaced by survivors who experience either a rapid recovery and favorable hospital discharge or the development of chronic critical illness (CCI) with suboptimal outcomes. The underlying immunological response that determines these clinical trajectories remains poorly defined at the transcriptomic level. As classical and non-classical monocytes are key leukocytes in both the innate and adaptive immune systems, we sought to delineate the transcriptomic response of these cell types. Using single-cell RNA sequencing and pathway analyses, we identified gene expression patterns between these two groups that are consistent with differences in TNFα production based on clinical outcome. This may provide therapeutic targets for those at risk for CCI in order to improve their phenotype/endotype, morbidity, and long-term mortality.

The post-septic peripheral myeloid compartment reveals unexpected diversity in myeloid-derived suppressor cells.

Introduction: Sepsis engenders distinct host immunologic changes that include the expansion of myeloid-derived suppressor cells (MDSCs). These cells play a physiologic role in tempering acute inflammatory responses but can persist in patients who develop chronic critical illness. Methods: Cellular Indexing of Transcriptomes and Epitopes by Sequencing and transcriptomic analysis are used to describe MDSC subpopulations based on differential gene expression, RNA velocities, and biologic process clustering. Results: We identify a unique lineage and differentiation pathway for MDSCs after sepsis and describe a novel MDSC subpopulation. Additionally, we report that the heterogeneous response of the myeloid compartment of blood to sepsis is dependent on clinical outcome. Discussion: The origins and lineage of these MDSC subpopulations were previously assumed to be discrete and unidirectional; however, these cells exhibit a dynamic phenotype with considerable plasticity.

Wearable sensors in patient acuity assessment in critical care.

Acuity assessments are vital for timely interventions and fair resource allocation in critical care settings. Conventional acuity scoring systems heavily depend on subjective patient assessments, leaving room for implicit bias and errors. These assessments are often manual, time-consuming, intermittent, and challenging to interpret accurately, especially for healthcare providers. This risk of bias and error is likely most pronounced in time-constrained and high-stakes environments, such as critical care settings. Furthermore, such scores do not incorporate other information, such as patients' mobility level, which can indicate recovery or deterioration in the intensive care unit (ICU), especially at a granular level. We hypothesized that wearable sensor data could assist in assessing patient acuity granularly, especially in conjunction with clinical data from electronic health records (EHR). In this prospective study, we evaluated the impact of integrating mobility data collected from wrist-worn accelerometers with clinical data obtained from EHR for estimating acuity. Accelerometry data were collected from 87 patients wearing accelerometers on their wrists in an academic hospital setting. The data was evaluated using five deep neural network models: VGG, ResNet, MobileNet, SqueezeNet, and a custom Transformer network. These models outperformed a rule-based clinical score (Sequential Organ Failure Assessment, SOFA) used as a baseline when predicting acuity state (for ground truth we labeled as unstable patients if they needed life-supporting therapies, and as stable otherwise), particularly regarding the precision, sensitivity, and F1 score. The results demonstrate that integrating accelerometer data with demographics and clinical variables improves predictive performance compared to traditional scoring systems in healthcare. Deep learning models consistently outperformed the SOFA score baseline across various scenarios, showing notable enhancements in metrics such as the area under the receiver operating characteristic (ROC) Curve (AUC), precision, sensitivity, specificity, and F1 score. The most comprehensive scenario, leveraging accelerometer, demographics, and clinical data, achieved the highest AUC of 0.73, compared to 0.53 when using SOFA score as the baseline, with significant improvements in precision (0.80 vs. 0.23), specificity (0.79 vs. 0.73), and F1 score (0.77 vs. 0.66). This study demonstrates a novel approach beyond the simplistic differentiation between stable and unstable conditions. By incorporating mobility and comprehensive patient information, we distinguish between these states in critically ill patients and capture essential nuances in physiology and functional status. Unlike rudimentary definitions, such as equating low blood pressure with instability, our methodology delves deeper, offering a more holistic understanding and potentially valuable insights for acuity assessment.

Development and validation of a race-agnostic computable phenotype for kidney health in adult hospitalized patients.

Standard race adjustments for estimating glomerular filtration rate (GFR) and reference creatinine can yield a lower acute kidney injury (AKI) and chronic kidney disease (CKD) prevalence among African American patients than non-race adjusted estimates. We developed two race-agnostic computable phenotypes that assess kidney health among 139,152 subjects admitted to the University of Florida Health between 1/2012-8/2019 by removing the race modifier from the estimated GFR and estimated creatinine formula used by the race-adjusted algorithm (race-agnostic algorithm 1) and by utilizing 2021 CKD-EPI refit without race formula (race-agnostic algorithm 2) for calculations of the estimated GFR and estimated creatinine. We compared results using these algorithms to the race-adjusted algorithm in African American patients. Using clinical adjudication, we validated race-agnostic computable phenotypes developed for preadmission CKD and AKI presence on 300 cases. Race adjustment reclassified 2,113 (8%) to no CKD and 7,901 (29%) to a less severe CKD stage compared to race-agnostic algorithm 1 and reclassified 1,208 (5%) to no CKD and 4,606 (18%) to a less severe CKD stage compared to race-agnostic algorithm 2. Of 12,451 AKI encounters based on race-agnostic algorithm 1, race adjustment reclassified 591 to No AKI and 305 to a less severe AKI stage. Of 12,251 AKI encounters based on race-agnostic algorithm 2, race adjustment reclassified 382 to No AKI and 196 (1.6%) to a less severe AKI stage. The phenotyping algorithm based on refit without race formula performed well in identifying patients with CKD and AKI with a sensitivity of 100% (95% confidence interval [CI] 97%-100%) and 99% (95% CI 97%-100%) and a specificity of 88% (95% CI 82%-93%) and 98% (95% CI 93%-100%), respectively. Race-agnostic algorithms identified substantial proportions of additional patients with CKD and AKI compared to race-adjusted algorithm in African American patients. The phenotyping algorithm is promising in identifying patients with kidney disease and improving clinical decision-making.

Identifying acute illness phenotypes via deep temporal interpolation and clustering network on physiologic signatures.

Using clustering analysis for early vital signs, unique patient phenotypes with distinct pathophysiological signatures and clinical outcomes may be revealed and support early clinical decision-making. Phenotyping using early vital signs has proven challenging, as vital signs are typically sampled sporadically. We proposed a novel, deep temporal interpolation and clustering network to simultaneously extract latent representations from irregularly sampled vital signs and derive phenotypes. Four distinct clusters were identified. Phenotype A (18%) had the greatest prevalence of comorbid disease with increased prevalence of prolonged respiratory insufficiency, acute kidney injury, sepsis, and long-term (3-year) mortality. Phenotypes B (33%) and C (31%) had a diffuse pattern of mild organ dysfunction. Phenotype B's favorable short-term clinical outcomes were tempered by the second highest rate of long-term mortality. Phenotype C had favorable clinical outcomes. Phenotype D (17%) exhibited early and persistent hypotension, high incidence of early surgery, and substantial biomarker incidence of inflammation. Despite early and severe illness, phenotype D had the second lowest long-term mortality. After comparing the sequential organ failure assessment scores, the clustering results did not simply provide a recapitulation of previous acuity assessments. This tool may impact triage decisions and have significant implications for clinical decision-support under time constraints and uncertainty.

Gender differences in autonomy and performance assessments in a national cohort of vascular surgery trainees.

OBJECTIVE: Gender disparities in surgical training and assessment are described in the general surgery literature. Assessment disparities have not been explored in vascular surgery. We sought to investigate gender disparities in operative assessment in a national cohort of vascular surgery integrated residents (VIRs) and fellows (VSFs). METHODS: Operative performance and autonomy ratings from the Society for Improving Medical Professional Learning (SIMPL) application database were collected for all vascular surgery participating institutions from 2018 to 2023. Logistic generalized linear mixed models were conducted to examine the association of faculty and trainee gender on faculty and self-assessment of autonomy and performance. Data were adjusted for post-graduate year and case complexity. Random effects were included to account for clustering effects due to participant, program, and procedure. RESULTS: One hundred three trainees (n = 63 VIRs; n = 40 VSFs; 63.1% men) and 99 faculty (73.7% men) from 17 institutions (n = 12 VIR and n = 13 VSF programs) contributed 4951 total assessments (44.4% by faculty, 55.6% by trainees) across 235 unique procedures. Faculty and trainee gender were not associated with faculty ratings of performance (faculty gender: odds ratio [OR], 0.78; 95% confidence interval [CI], 0.27-2.29; trainee gender: OR, 1.80; 95% CI, 0.76-0.43) or autonomy (faculty gender: OR, 0.99; 95% CI, 0.41-2.39; trainee gender: OR, 1.23; 95% CI, 0.62-2.45) of trainees. All trainees self-assessed at lower performance and autonomy ratings as compared with faculty assessments. However, women trainees rated themselves significantly lower than men for both autonomy (OR, 0.57; 95% CI, 0.43-0.74) and performance (OR, 0.40; 95% CI, 0.30-0.54). CONCLUSIONS: Although gender was not associated with differences in faculty assessment of performance or autonomy among vascular surgery trainees, women trainees perceive themselves as performing with lower competency and less autonomy than their male colleagues. These findings suggest utility for exploring gender differences in real-time feedback delivered to and received by trainees and targeted interventions to align trainee self-perception with actual operative performance and autonomy to optimize surgical skill acquisition.

Intraoperative hypotension and postoperative acute kidney injury: A systematic review.

BACKGROUND: There is no consensus regarding safe intraoperative blood pressure thresholds that protect against postoperative acute kidney injury (AKI). This review aims to examine the existing literature to delineate safe intraoperative hypotension (IOH) parameters to prevent postoperative AKI. METHODS: PubMed, Cochrane Central, and Web of Science were systematically searched for articles published between 2015 and 2022 relating the effects of IOH on postoperative AKI. RESULTS: Our search yielded 19 articles. IOH risk thresholds ranged from <50 to <75 â€‹mmHg for mean arterial pressure (MAP) and from <70 to <100 â€‹mmHg for systolic blood pressure (SBP). MAP below 65 â€‹mmHg for over 5 â€‹min was the most cited threshold (N â€‹= â€‹13) consistently associated with increased postoperative AKI. Greater magnitude and duration of MAP and SBP below the thresholds were generally associated with a dose-dependent increase in postoperative AKI incidence. CONCLUSIONS: While a consistent definition for IOH remains elusive, the evidence suggests that MAP below 65 â€‹mmHg for over 5 â€‹min is strongly associated with postoperative AKI, with the risk increasing with the magnitude and duration of IOH.

Are we ready for "green surgery" to promote environmental sustainability in the operating room? Results from the WSES STAR investigation.

BACKGROUND: The importance of environmental sustainability is acknowledged in all sectors, including healthcare. To meet the United Nations Sustainable Development Goals 2030 Agenda, healthcare will need a paradigm shift toward more environmentally sustainable practices that will also impact clinical decision-making. The study investigates trauma and emergency surgeons' perception, acceptance, and employment of environmentally friendly habits. METHODS: An online survey based on the most recent literature regarding environmental sustainability in healthcare and surgery was created by a multidisciplinary committee and endorsed by the World Society of Emergency Surgery (WSES). The survey was advertised to the 917 WSES members through the society's website and Twitter/X profile. RESULTS: 450 surgeons from 55 countries participated in the survey. Results underline both a generally positive attitude toward environmental sustainability but also a lack of knowledge about several concepts and practices, especially concerning the potential contribution to patient care. DISCUSSION: The topic of environmental sustainability in healthcare and surgery is still in its infancy. There is a clear lack of salient guidance and knowledge, and there is a critical need for governments, institutions, health agencies, and scientific societies to promote, disseminate, and report environmentally friendly initiatives and their potential impacts while employing an interdisciplinary approach.

Operating Room Supply Cost and Value of Care after Implementing a Sustainable Quality Intervention.

BACKGROUND: Variability in operating room supply cost is a modifiable cause of suboptimal resource use and low value of care (outcomes vs cost). This study describes implementation of a quality improvement intervention to decrease operating room supply costs. STUDY DESIGN: An automated electronic health record data pipeline harmonized operating room supply cost data with patient and case characteristics and outcomes. For inpatient procedures, predicted mortality and length of stay were used to calculate observed-to-expected ratios and value of care using validated equations. For commonly performed (1 or more per week) procedures, the pipeline generated figures illustrating individual surgeon performance vs peers, costs for each surgeon performing each case type, and control charts identifying out-of-control cases and surgeons with more than 90th percentile costs, which were shared with surgeons and division chiefs alongside guidance for modifying case-specific supply instructions to operating room nurses and technicians. RESULTS: Preintervention control (1,064 cases for 7 months) and postintervention (307 cases for 2 months) cohorts had similar baseline characteristics across all 16 commonly performed procedures. Median costs per case were lower in the intervention cohort ($811 [$525 to $1,367] vs controls: $1,080 [$603 to $1,574], p < 0.001), as was the incidence of out-of-control cases (19 (6.2%) vs 110 (10.3%), p = 0.03). Duration of surgery, length of stay, discharge disposition, and 30-day mortality and readmission rates were similar between cohorts. Value of care was higher in the intervention cohort (1.1 [0.1 to 1.5] vs 1.0 [0.2 to 1.4], p = 0.04). Pipeline runtime was 16:07. CONCLUSIONS: An automated, sustainable quality improvement intervention was associated with decreased operating room supply costs and increased value of care.

Surgical leadership: Ensuring financial stability through growth.

Maintaining financial stability is important for leaders in surgery because it (1) allows consistent, fair (market value) reimbursement for employees, which conveys that they are valued; (2) enables strategic investment in new programs that may not generate direct financial gains but are required; and (3) builds trust with stakeholders outside the department while strengthening the department's position in negotiations. Key strategies that we have used to increase revenue (income) over the past 6 years have been hiring more faculty, advocating for greater operating room and staffing capacity, staffing surgeons at other institutions using affiliation agreements, attempting to shift grant-funded efforts to non-clinical (research) faculty to mitigate National Institutes of Health salary cap penalties, and increasing efforts to identify external funding for educational and administrative tasks performed by surgeons (eg, increasing contact hours with medical students to secure a greater proportion of state general revenue). Using these strategies, our total revenue has increased 66% over the past 6 years, whereas Academic Support Agreement funds from the College of Medicine concurrently have decreased by 75%. Key strategies that we have used for curtailing expenses have been increasing clinic workflow efficiency; shifting advance practice provider contractual expenses and trainee indirect costs to the hospital; focusing on driving down delayed accounts receivable over time; and using net collections to preferentially invest in research likely to receive future external funding, for which indirect costs return to the department. Despite using these strategies, the total expenses of our department have increased 74% over the past 6 years, driven primarily by the doubling of clinic costs and contractual expenses for advance practice providers. These losses could theoretically be offset by (1) increasing billing by advance practice providers who can also facilitate excellent continuity of surgical care while allowing residents and fellows to shift their effort from service toward education and (2) increasing clinic capacity to generate increasing operative volumes. A department's financial stability is affected by complex interactions among several stakeholders, including the College of Medicine, faculty group practices, and hospitals, with competing interests. Leaders in surgery must understand and manage major categories of revenue and expenses to create a financially stable environment in which they can fulfill their multi-prong missions.

Adverse outcomes and an immunosuppressed endotype in septic patients with reduced IFN-γ ELISpot.

BACKGROUNDSepsis remains a major clinical challenge for which successful treatment requires greater precision in identifying patients at increased risk of adverse outcomes requiring different therapeutic approaches. Predicting clinical outcomes and immunological endotyping of septic patients generally relies on using blood protein or mRNA biomarkers, or static cell phenotyping. Here, we sought to determine whether functional immune responsiveness would yield improved precision.METHODSAn ex vivo whole-blood enzyme-linked immunosorbent spot (ELISpot) assay for cellular production of interferon γ (IFN-γ) was evaluated in 107 septic and 68 nonseptic patients from 5 academic health centers using blood samples collected on days 1, 4, and 7 following ICU admission.RESULTSCompared with 46 healthy participants, unstimulated and stimulated whole-blood IFN-γ expression was either increased or unchanged, respectively, in septic and nonseptic ICU patients. However, in septic patients who did not survive 180 days, stimulated whole-blood IFN-γ expression was significantly reduced on ICU days 1, 4, and 7 (all P < 0.05), due to both significant reductions in total number of IFN-γ-producing cells and amount of IFN-γ produced per cell (all P < 0.05). Importantly, IFN-γ total expression on days 1 and 4 after admission could discriminate 180-day mortality better than absolute lymphocyte count (ALC), IL-6, and procalcitonin. Septic patients with low IFN-γ expression were older and had lower ALCs and higher soluble PD-L1 and IL-10 concentrations, consistent with an immunosuppressed endotype.CONCLUSIONSA whole-blood IFN-γ ELISpot assay can both identify septic patients at increased risk of late mortality and identify immunosuppressed septic patients.TRIAL REGISTRYN/A.FUNDINGThis prospective, observational, multicenter clinical study was directly supported by National Institute of General Medical Sciences grant R01 GM-139046, including a supplement (R01 GM-139046-03S1) from 2022 to 2024.

Machine learning-based prediction models for home discharge in patients with COVID-19: Development and evaluation using electronic health records.

OBJECTIVE: This study aimed to develop and validate predictive models using electronic health records (EHR) data to determine whether hospitalized COVID-19-positive patients would be admitted to alternative medical care or discharged home. METHODS: We conducted a retrospective cohort study using deidentified data from the University of Florida Health Integrated Data Repository. The study included 1,578 adult patients (≥18 years) who tested positive for COVID-19 while hospitalized, comprising 960 (60.8%) female patients with a mean (SD) age of 51.86 (18.49) years and 618 (39.2%) male patients with a mean (SD) age of 54.35 (18.48) years. Machine learning (ML) model training involved cross-validation to assess their performance in predicting patient disposition. RESULTS: We developed and validated six supervised ML-based prediction models (logistic regression, Gaussian Naïve Bayes, k-nearest neighbors, decision trees, random forest, and support vector machine classifier) to predict patient discharge status. The models were evaluated based on the area under the receiver operating characteristic curve (ROC-AUC), precision, accuracy, F1 score, and Brier score. The random forest classifier exhibited the highest performance, achieving an accuracy of 0.84 and an AUC of 0.72. Logistic regression (accuracy: 0.85, AUC: 0.71), k-nearest neighbor (accuracy: 0.84, AUC: 0.63), decision tree (accuracy: 0.84, AUC: 0.61), Gaussian Naïve Bayes (accuracy: 0.84, AUC: 0.66), and support vector machine classifier (accuracy: 0.84, AUC: 0.67) also demonstrated valuable predictive capabilities. SIGNIFICANCE: This study's findings are crucial for efficiently allocating healthcare resources during pandemics like COVID-19. By harnessing ML techniques and EHR data, we can create predictive tools to identify patients at greater risk of severe symptoms based on their medical histories. The models developed here serve as a foundation for expanding the toolkit available to healthcare professionals and organizations. Additionally, explainable ML methods, such as Shapley Additive Explanations, aid in uncovering underlying data features that inform healthcare decision-making processes.

Adverse Long-Term Outcomes and an Immune Suppressed Endotype in Sepsis Patients with Reduced Interferon-γELISpot: A Multicenter, Prospective Observational Study.

BACKGROUND: Sepsis remains a major clinical challenge for which successful treatment requires greater precision in identifying patients at increased risk of adverse outcomes requiring different therapeutic approaches. Predicting clinical outcomes and immunological endotyping of septic patients has generally relied on using blood protein or mRNA biomarkers, or static cell phenotyping. Here, we sought to determine whether functional immune responsiveness would yield improved precision. METHODS: An ex vivo whole blood enzyme-linked immunosorbent (ELISpot) assay for cellular production of interferon-γ (IFN-γ) was evaluated in 107 septic and 68 non-septic patients from five academic health centers using blood samples collected on days 1, 4 and 7 following ICU admission. RESULTS: Compared with 46 healthy subjects, unstimulated and stimulated whole blood IFNγ expression were either increased or unchanged, respectively, in septic and nonseptic ICU patients. However, in septic patients who did not survive 180 days, stimulated whole blood IFNγ expression was significantly reduced on ICU days 1, 4 and 7 (all p<0.05), due to both significant reductions in total number of IFNγ producing cells and amount of IFNγ produced per cell (all p<0.05). Importantly, IFNγ total expression on day 1 and 4 after admission could discriminate 180-day mortality better than absolute lymphocyte count (ALC), IL-6 and procalcitonin. Septic patients with low IFNγ expression were older and had lower ALC and higher sPD-L1 and IL-10 concentrations, consistent with an immune suppressed endotype. CONCLUSIONS: A whole blood IFNγ ELISpot assay can both identify septic patients at increased risk of late mortality, and identify immune-suppressed, sepsis patients.

Resident Operative Autonomy and Attending Verbal Feedback Differ by Resident and Attending Gender.

Objectives: This study tests the null hypotheses that overall sentiment and gendered words in verbal feedback and resident operative autonomy relative to performance are similar for female and male residents. Background: Female and male surgical residents may experience training differently, affecting the quality of learning and graduated autonomy. Methods: A longitudinal, observational study using a Society for Improving Medical Professional Learning collaborative dataset describing resident and attending evaluations of resident operative performance and autonomy and recordings of verbal feedback from attendings from surgical procedures performed at 54 US general surgery residency training programs from 2016 to 2021. Overall sentiment, adjectives, and gendered words in verbal feedback were quantified by natural language processing. Resident operative autonomy and performance, as evaluated by attendings, were reported on 5-point ordinal scales. Performance-adjusted autonomy was calculated as autonomy minus performance. Results: The final dataset included objective assessments and dictated feedback for 2683 surgical procedures. Sentiment scores were higher for female residents (95 [interquartile range (IQR), 4-100] vs 86 [IQR 2-100]; P < 0.001). Gendered words were present in a greater proportion of dictations for female residents (29% vs 25%; P = 0.04) due to male attendings disproportionately using male-associated words in feedback for female residents (28% vs 23%; P = 0.01). Overall, attendings reported that male residents received greater performance-adjusted autonomy compared with female residents (P < 0.001). Conclusions: Sentiment and gendered words in verbal feedback and performance-adjusted operative autonomy differed for female and male general surgery residents. These findings suggest a need to ensure that trainees are given appropriate and equitable operative autonomy and feedback.