Novel machine learning technique further clarifies unrelated donor selection to optimize transplantation outcomes.

We investigated the impact of donor characteristics on outcomes in allogeneic hematopoietic cell transplantation (HCT) recipients using a novel machine learning approach, the Nonparametric Failure Time Bayesian Additive Regression Trees (NFT BART). NFT BART models were trained on data from 10,016 patients who underwent a first HLA-A, B, C and DRB1 matched unrelated donor HCT between 2016 and 2019 reported to the CIBMTR, then validated on an independent cohort of 1,802 patients. The NFT BART models were adjusted based on recipient, disease and transplant variables. We defined a clinically meaningful impact on overall survival (OS) or event-free survival (EFS) (survival without relapse, graft failure, or moderate to severe chronic GVHD) as >1% difference in predicted outcome at 3 years. Characteristics with <1% impact (within a zone of indifference) were not considered to be clinically relevant. Donor CMV, parity, HLA-DQB1 and HLA-DPB1 T cell epitope matching fell within the zone of indifference. The only significant donor factor that associated with OS was age, where compared to 18-year-old donors, donors ≥31 years old were associated with lower OS. Both donor age (≤ 32 years old) and use of a male donor, regardless of recipient sex, improved EFS. We therefore recommend selecting the earliest available donor within the 18-30 age range for HCT to optimize OS. If several donors in the 18-30-year-old age range are available, a male donor may be chosen to optimize EFS.

Traveling Long Distances for Rectal Cancer Care: Institutional Outcomes and Patient Experiences.

INTRODUCTION: Mounting evidence supports traveling to high-volume centers for complex surgical procedures, such as a proctectomy, yet the burden of travel and outcomes of patients traveling long distances is not yet clear. Thus, we aimed to evaluate oncologic outcomes, quality of life, and travel burdens for patients treated for rectal cancer at a single tertiary-care institution. METHODS: A retrospective study of patients treated with proctectomy for locally advanced rectal cancer was performed comparing long and short travel distance (STD) cohorts. Primary outcome measures included overall mortality, disease recurrence, and quality of life. Secondary outcomes included out-of-pocket expenses. The cohorts were compared using Wilcoxon rank-sum and Chi-square tests for continuous and categorical variables, respectively. Kaplan-Meier plots were created to evaluate overall and disease-free survival. RESULTS: Among 102 patients, 51 (50%) were classified as long travel distance (LTD, mean 57.8 miles) and 51 (50%) were classified as STD (mean 12.8 miles). There was no statistical difference in 5-y mortality (4% LTD versus 4% STD, P = 1.000), disease recurrence (26% LTD versus 18% STD, P = 0.336), or quality of life (0.85 LTD versus 0.87 STD, P = 0.690). The LTD cohort did have significantly lower postresection compliance with surveillance (84% LTD versus 96% STD, P = 0.046). LTD cohort also had significantly more lodging ($77.1 LTD versus $0 STD, P = 0.025) and transportation expenses ($133.6 LTD versus $92.6 STD, P = 0.010). CONCLUSIONS: As the surgical management of rectal cancer becomes increasingly centralized, this study found patients who traveled long-distances received comparable care with outcomes similar to those who lived locally. Higher travel costs and lower compliance with surveillance were identified as barriers to care in the long-distance population, but a number of solutions can be implemented to address these issues.

Effects of Singing on Vascular Health in Older Adults with Coronary Artery Disease: A Randomized Trial.

Background: The impact of singing on cardiovascular health has not been extensively studied. The aim of this study is to investigate the effect of singing on cardiovascular biomarkers in an aging population with coronary artery disease. Methods: Participants had three study visits separated by 2-7 days, according to a randomized, single-blind, cross-over, controlled design: (1) a 30-minute period of coached singing from an in-person music therapist, (2) a 30-minute period of singing along to an instructional video and (3) a 30-minute rest (control). Primary outcomes included macrovascular endothelial function assessed by brachial artery flow-mediated dilation and microvascular function assessed by peripheral arterial tonometry (Framingham reactive hyperemia index; fRHI). Heart rate variability was a secondary outcome. Results: Sixty-five subjects (mean age 67.7± 0.8, 40% women) completed the study. Compared to control, there was an increase in fRHI for the singing video intervention (estimate 0.54, SE 0.25, p=0.005) but not for the coaching intervention (estimate 0.11, SE 0.18, p=0.570). There was no change in macrovascular function with either intervention. The low frequency/high frequency (LF/HF) ratio increased by 2.80 (SE 1.03, p=0.008), and the LnHF power decreased by -0.90 ms2 (SE 0.29, p=0.003) with the video (during to pre-change). When assessing post- to pre- change, the coaching intervention showed a significant change of -0.62 ms2 (SE 0.29, p=0.036) in LnHF power. Conclusions: Singing along to an instructional video for 30 minutes improved microvascular, but not macrovascular, endothelial function, in older patients with CAD. HRV changes with singing are similar to that of exercise. Clinical trial registration: ClinicalTrials.gov, identifier: NCT04121741.

Can We Actually Predict Long-Term Patient Satisfaction After Traumatic Brain Injury?

INTRODUCTION: The Traumatic Brain Injury - Patient Reported Outcome (TBI-PRO) model was previously derived to predict long-term patient satisfaction as assessed by the Quality of Life After Brain Injury (QOLIBRI) score. The aim of this study is to externally and prospectively validate the TBI-PRO model to predict long-term patient-reported outcomes and to derive a new model using a larger dataset of older adults with TBI. METHODS: Patients admitted to a Level I trauma center with TBI were prospectively followed for 1 y after injury. Outcomes predicted by the TBI-PRO model based on admission findings were compared to actual QOLIBRI scores reported by patients at 3,6, and 12 mo. When deriving a new model, Collaborative European NeuroTrauma Effectiveness Research in TBI and the Transforming Research and Clinical Knowledge in Traumatic Brain Injury databases were used to identify older adults (≥50 y) with TBI from 2014 to 2018. Bayesian additive regression trees were used to identify predictive admission covariates. The coefficient of determination was used to identify the fitness of the model. RESULTS: For prospective validation, a total of 140 patients were assessed at 3 mo, with follow-up from 69 patients at 6 mo and 13 patients at 12 mo postinjury. The area under receiver operating curve of the TBI-PRO model for predicting favorable outcomes at 3, 6, and 12 mo were 0.65, 0.57, and 0.62, respectively. When attempting to derive a novel predictive model, a total of 1521 patients (80%) was used in the derivation dataset while 384 (20%) were used in the validation dataset. A past medical history of heart conditions, initial hospital length of stay, admission systolic blood pressure, age, number of reactive pupils on admission, and the need for craniectomy were most predictive of long-term QOLIBRI-Overall Scale. The coefficient of determination for the validation model including only the most predictive variables were 0.28, 0.19, and 0.27 at 3, 6, and 12 mo, respectively. CONCLUSIONS: In the present study, the prospective validation of a previously derived TBI-PRO model failed to accurately predict a long-term patient reported outcome measures in TBI. Additionally, the derivation of a novel model in older adults using a larger database showed poor accuracy in predicting long-term health-related quality of life. This study demonstrates limitations to current targeted approaches in TBI care. This study provides a framework for future studies and more targeted datasets looking to assess long-term quality of life based upon early hospital variables and can serve as a starting point for future predictive analysis.

Reporting and analysis of sex in vascular surgery research.

OBJECTIVE: To examine sex in human vascular surgery research by quantifying the inclusion and analysis of sex-based data in high-impact vascular surgery journals. METHODS: A bibliographic review of original articles published in the European Journal of Vascular and Endovascular Surgery, Journal of Vascular Surgery, JVS: Venous and Lymphatic Disorders, Journal of Endovascular Therapy, and Annals of Vascular Surgery from January 1, 2018, to December 31, 2020, and from January 1, 2023, to December 31, 2023, was conducted. Abstracted data included sex-based data analysis, inclusion of sex as a variable in multivariable analysis, inclusion of sex as an independent variable, and a discussion of sex-based results. RESULTS: Of the 3762 articles that included human, animal, or cell subjects, 249 (6.6%) did not state sex. Of those 249 articles, 183 included human subjects, 55 included animal subjects, and 11 used cell lines as the subjects. These were removed from analysis as well as the remaining 68 articles with animal subjects. In addition, 23 researched a sex-specific pathology and were removed from analysis. Of the remaining 3422 articles included in our study, 42.3% analyzed sex, 46.9% included sex in multivariable analysis, 4.8% included sex as an independent variable, and 26.6% included a discussion of sex. There were no significant differences in all four sex variables between 2018, 2019, and 2020. Between 2018-2020 and 2023, there were significant increases in all four sex variables. Multicenter studies had significantly higher rates of independent analysis of sex over single-center studies (7.4% vs 3.3%, P < .001). There was no significant difference in independent analysis of sex between U.S.-based and non-U.S.-based studies. Only 191 articles (5.6%) had 90% or greater matching of men and women in their study. CONCLUSIONS: Equitable inclusion and analysis of sex is rare in vascular surgery research. Less than 5% of articles included an independent analysis of data by sex, and few studies included males and females equally. Clinical research is the basis for evidence-based medicine; therefore, it is important to strive for equitable inclusion, analysis, and reporting of data to foster generalizability of clinical research to men and women.

Optimal Donor Selection Across Multiple Outcomes For Hematopoietic Stem Cell Transplantation By Bayesian Nonparametric Machine Learning.

Allogeneic hematopoietic cell transplantation (HCT) is one of the only curative treatment options for patients suffering from life-threatening hematologic malignancies; yet, the possible adverse complications can be serious even fatal. Matching between donor and recipient for 4 of the HLA genes is widely accepted and supported by the literature. However, among 8/8 allele matched unrelated donors, there is less agreement among centers and transplant physicians about how to prioritize donor characteristics like additional HLA loci (DPB1 and DQB1), donor sex/parity, CMV status, and age to optimize transplant outcomes. This leads to varying donor selection practice from patient to patient or via center protocols. Furthermore, different donor characteristics may impact different post transplant outcomes beyond mortality, including disease relapse, graft failure/rejection, and chronic graft-versus-host disease (components of event-free survival, EFS). We develop a general methodology to identify optimal treatment decisions by considering the trade-offs on multiple outcomes modeled using Bayesian nonparametric machine learning. We apply the proposed approach to the problem of donor selection to optimize overall survival and event-free survival, using a large outcomes registry of HCT recipients and their actual and potential donors from the Center for International Blood and Marrow Transplant Research (CIBMTR). Our approach leads to a donor selection strategy that favors the youngest male donor, except when there is a female donor that is substantially younger.

Prevalence, Predictors, and Outcomes of Type 2 NSTEMI in Hospitalized Patients With COVID-19.

BACKGROUND: Data on the incidence of type 2 non-ST-segment-elevation myocardial infarction (T2MI) in hospitalized patients with COVID-19 has been limited to single-center studies. Given that certain characteristics, such as obesity and type 2 diabetes, have been associated with higher mortality in COVID-19 infections, we aimed to define the incidence of T2MI in a national cohort and identify pre-hospital patient characteristics associated with T2MI in hospitalized patients with COVID-19. METHODS AND RESULTS: Using the national American Heart Association COVID-19 Cardiovascular Disease Quality Improvement Registry, we performed a retrospective 4:1 matched (age, sex, race, and body mass index) analysis of controls versus cases with T2MI. We performed (1) conditional multivariable logistic regression to identify predictive pre-hospital patient characteristics of T2MI for patients hospitalized with COVID-19 and (2) stratified proportional hazards regression to investigate the association of T2MI with morbidity and mortality. From January 2020 through May 2021, there were 709 (2.2%) out of 32 015 patients with T2MI. Five hundred seventy-nine cases with T2MI were matched to 2171 controls (mean age 70; 43% female). Known coronary artery disease, heart failure, chronic kidney disease, hypertension, payor source, and presenting heart rate were associated with higher odds of T2MI. Anti-hyperglycemic medication and anti-coagulation use before admission were associated with lower odds of T2MI. Those with T2MI had higher morbidity and mortality (hazard ratio, 1.40 [95% CI, 1.13-1.74]; P=0.002). CONCLUSIONS: In hospitalized patients with COVID-19, those with a T2MI compared with those without had higher morbidity and mortality. Outpatient anti-hyperglycemic and anti-coagulation use were the only pre-admission factors associated with reduced odds of T2MI.

Timing and co-occurrence of symptoms prior to a diagnosis of light chain (AL) amyloidosis.

It is well-established that most patients with systemic light chain (AL) amyloidosis have multi-organ involvement and are often diagnosed after a lag period of increasing symptoms. We leverage electronic health record (EHR) data from the TriNetX research network to describe the incidence, timing, and co-occurrence of precursor conditions of interests in a cohort of AL amyloidosis patients identified between October 2015-December 2020. Nineteen precursor diagnoses of interest representing features of AL amyloidosis were identified using ICD codes up to 36 months prior to AL amyloidosis diagnosis. Among 1,401 patients with at least 36 months of EHR data prior to AL amyloidosis diagnosis, 46% were females, 16% were non-Hispanic Black, and 6% were Hispanic. The median age was 71 (range, 21-91) years. The median number of precursor diagnoses was 5 with dyspnea and fatigue being the most prevalent. The time from the first occurrence of a precursor to AL diagnosis ranged from 3.2 to 21.4 months. Analyses of pairwise co-occurrence of specific diagnoses indicated a high association (Cole's coefficient >0.6) among the examined precursor diagnoses. These findings provide novel information about the timing and co-occurrence of key precursor conditions and could be used to develop algorithms for early identification of AL amyloidosis.

Scaling care coordination through digital engagement: stepped-wedge trial assessing readmissions.

OBJECTIVES: Transitions of care are pivotal, vulnerable times as patients are discharged from the hospital. Telephonic care coordination is standard care, but labor intensive. We implemented a patient postdischarge digital engagement (PDDE) program to scale coordination. We hypothesized that PDDE could reduce readmissions for low-risk patients and supplement care coordination for medium- and high-risk patients. STUDY DESIGN: Pragmatic, stepped-wedge cluster randomization trial with 5 implementation waves based upon primary care clinic region. METHODS: All inpatient hospital discharges between March 2020 and November 2020 were stratified by readmission risk. Low-risk patients were offered access to PDDE, and moderate-risk and high-risk patients were offered access to PDDE and care coordination. Readmission was defined as an unplanned inpatient admission within 30 days from discharge. An intention-to-treat primary analysis was conducted using mixed-effects logistic regression clustering for wave; a treatment-on-the-treated analysis was also conducted to assess the impact among program users. RESULTS: A total of 5490 patient discharges were examined (2735 control; 2755 intervention); 1949 patients were high risk, 2032 were medium risk, and 1509 were low risk. PDDE intervention did not significantly affect readmission among low-risk (95% CI, -0.23 to 0.90; P = .23), medium-risk (95% CI, -0.14 to 0.60; P = .21), and high-risk (95% CI, -0.32 to 0.64; P = .48) groups after adjustment for time and patient factors. In a treatment-on-the-treated analysis, among patients who activated the PDDE program, readmission was also similar among the low-, medium-, and high-risk cohorts. CONCLUSIONS: Our study expanded resource-limited care coordination by offering low-risk patients a service they were unable to receive previously while having no impact on readmission. PDDE efficiently provided additional touch points between patients and providers.

Timing and co-occurrence of symptoms prior to a diagnosis of light chain (AL) amyloidosis.

It is well-established that light chain (AL) amyloidosis patients have multi-organ involvement and are often diagnosed after a lag period of increasing symptoms. We leverage electronic health record (EHR) data from the TriNetX research network to describe the incidence, timing, and co-occurrence of precursor conditions of interests in a cohort of AL amyloidosis patients identified between October 2015-December 2020. Nineteen precursor diagnoses of interest representing features of AL amyloidosis were identified using ICD codes up to 36 months prior to AL amyloidosis diagnosis. Among 1,401 patients with at least 36 months of EHR data prior to AL amyloidosis diagnosis, 46% were females, 16% were non-Hispanic Black, and 6% were Hispanic. The median age was 71 (range, 21-91) years. The median number of precursor diagnoses was 5 with dyspnea and fatigue being the most prevalent. The time from the first occurrence of a precursor to AL diagnosis ranged from 3.2 to 21.4 months. Analyses of pairwise co-occurrence of specific diagnoses indicated a high association (Cole's coefficient > 0.6) among the examined precursor diagnoses. These findings provide novel information about the timing and co-occurrence of key precursor conditions and could be used to develop algorithms for early identification of AL amyloidosis.

The Variation of Withdrawal of Life Sustaining Therapy in Older Adults With Traumatic Brain Injury.

INTRODUCTION: The decision to withdraw life sustaining treatment (WDLST) in older adults with traumatic brain injury is subject to wide variability leading to nonbeneficial interventions and unnecessary use of hospital resources. We hypothesized that patient and hospital factors are associated with WDLST and WDLST timing. METHODS: All traumatic brain injury patients ≥65 with Glasgow coma scores (GCS) of 4-11 from 2018 to 2019 at level I and II centers were selected from the National Trauma Data Bank. Patients with head abbreviated injury scores 5-6 or death within 24 h were excluded. Bayesian additive regression tree analysis was performed to identify the cumulative incidence function (CIF) and the relative risks (RR) over time for withdrawal of care, discharge to hospice (DH), and death. Death alone (no WDLST or DH) served as the comparator group for all analyses. A subanalysis of the composite outcome WDLST/DH (defined as end-of-life-care), with death (no WDLST or DH) as a comparator cohort was performed. RESULTS: We included 2126 patients, of whom 1957 (57%) underwent WDLST, 402 (19%) died, and 469 (22%) were DH. 60% of patients were male, and the mean age was 80 y. The majority of patients were injured by fall (76%, n = 1644). Patients who were DH were more often female (51% DH versus 39% WDLST), had a past medical history of dementia (45% DH versus 18% WDLST), and had lower admission injury severity score (14 DH versus 18.6 WDLST) (P < 0.001). Compared to those who DH, those who underwent WDLST had a lower GCS (9.8 versus 8.4, P < 0.001). CIF of WDSLT and DH increased with age, stabilizing by day 3. At day 3, patients ≥90 y had an increased RR of DH compared to WDLST (RR 2.5 versus 1.4). As GCS increased, CIF and RR of WDLST decreased, while CIF and RR of DH increased (RR on day 3 for GCS 12: WDLST 0.42 versus DH 1.31).Patients at nonprofit institutions were more likely to undergo WDLST (RR 1.15) compared to DH (0.68). Compared to patients of White race, patients of Black race had a lower RR of WDLST at all timepoints. CONCLUSIONS: Patient and hospital factors influence the practice of end-of-life-care (WDLST, DH, and death), highlighting the need to better understand variability to target palliative care interventions and standardize care across populations and trauma centers.

Nonparametric failure time: Time-to-event machine learning with heteroskedastic Bayesian additive regression trees and low information omnibus Dirichlet process mixtures.

Many popular survival models rely on restrictive parametric, or semiparametric, assumptions that could provide erroneous predictions when the effects of covariates are complex. Modern advances in computational hardware have led to an increasing interest in flexible Bayesian nonparametric methods for time-to-event data such as Bayesian additive regression trees (BART). We propose a novel approach that we call nonparametric failure time (NFT) BART in order to increase the flexibility beyond accelerated failure time (AFT) and proportional hazard models. NFT BART has three key features: (1) a BART prior for the mean function of the event time logarithm; (2) a heteroskedastic BART prior to deduce a covariate-dependent variance function; and (3) a flexible nonparametric error distribution using Dirichlet process mixtures (DPM). Our proposed approach widens the scope of hazard shapes including nonproportional hazards, can be scaled up to large sample sizes, naturally provides estimates of uncertainty via the posterior and can be seamlessly employed for variable selection. We provide convenient, user-friendly, computer software that is freely available as a reference implementation. Simulations demonstrate that NFT BART maintains excellent performance for survival prediction especially when AFT assumptions are violated by heteroskedasticity. We illustrate the proposed approach on a study examining predictors for mortality risk in patients undergoing hematopoietic stem cell transplant (HSCT) for blood-borne cancer, where heteroskedasticity and nonproportional hazards are likely present.

Mandibular advancement reduces pharyngeal collapsibility by enlarging the airway rather than affecting velopharyngeal compliance.

Mandibular advancement devices (MADs) are frequently prescribed for obstructive sleep apnea (OSA) patients, but approximately one third of patients experience no therapeutic benefit. Understanding the mechanisms by which MADs prevent pharyngeal collapse may help optimize MAD therapy. This study quantified the relative contributions of changes in airspace cross-sectional area (CSA) versus changes in velopharyngeal compliance in determining MAD efficacy. Sixteen patients with moderate to severe OSA (mean apnea-hypopnea index of 32 ± 15 events/h) underwent measurements of the velopharyngeal closing pressure (PCLOSE ) during drug induced sedated endoscopy (DISE) via stepwise reductions in nasal mask pressure and recording of the intraluminal pressure with a catheter. Airspace CSA was estimated from video endoscopy. Pharyngeal compliance was defined as the slope of the area-pressure relationship of the velopharyngeal airspace. MAD therapy reduced PCLOSE from a median of 0.5 cmH2 O pre-advancement to a median of -2.6 cmH2 O post-advancement (p = 0.0009), increased the minimal CSA at the velopharynx by approximately 20 mm2 (p = 0.0067), but did not have a statistically significant effect on velopharyngeal compliance (p = 0.23). PCLOSE had a strong correlation with CSA but did not correlate with velopharyngeal compliance. Our results suggest that MADs reduce velopharyngeal collapsibility by increasing airway size as opposed to affecting velopharyngeal compliance. This contradicts the speculation of previous literature that the effectiveness of MADs is partially due to a reduction in velopharyngeal compliance resulting from stretching of the soft palate. These findings suggest that quantification of velopharyngeal CSA pre- and post-MAD advancement has potential as a biomarker to predict the success of MAD therapy.

Patient similarity and other artificial intelligence machine learning algorithms in clinical decision aid for shared decision-making in the Prevention of Cardiovascular Toxicity (PACT): a feasibility trial design.

BACKGROUND: The many improvements in cancer therapies have led to an increased number of survivors, which comes with a greater risk of consequent/subsequent cardiovascular disease. Identifying effective management strategies that can mitigate this risk of cardiovascular complications is vital. Therefore, developing computer-driven and personalized clinical decision aid interventions that can provide early detection of patients at risk, stratify that risk, and recommend specific cardio-oncology management guidelines and expert consensus recommendations is critically important. OBJECTIVES: To assess the feasibility, acceptability, and utility of the use of an artificial intelligence (AI)-powered clinical decision aid tool in shared decision making between the cancer survivor patient and the cardiologist regarding prevention of cardiovascular disease. DESIGN: This is a single-center, double-arm, open-label, randomized interventional feasibility study. Our cardio-oncology cohort of > 4000 individuals from our Clinical Research Data Warehouse will be queried to identify at least 200 adult cancer survivors who meet the eligibility criteria. Study participants will be randomized into either the Clinical Decision Aid Group (where patients will use the clinical decision aid in addition to current practice) or the Control Group (current practice). The primary endpoint of this study is to assess for each patient encounter whether cardiovascular medications and imaging pursued were consistent with current medical society recommendations. Additionally, the perceptions of using the clinical decision tool will be evaluated based on patient and physician feedback through surveys and focus groups. This trial will determine whether a clinical decision aid tool improves cancer survivors' medication use and imaging surveillance recommendations aligned with current medical guidelines. TRIAL REGISTRATION: ClinicalTrials.Gov Identifier: NCT05377320.

Anatomical determinants of upper airway collapsibility in obstructive sleep apnea: A systematic review and meta-analysis.

Upper airway (UA) collapsibility is one of the key factors that determine the severity of obstructive sleep apnea (OSA). Interventions for OSA are aimed at reducing UA collapsibility, but selecting the optimal alternative intervention for patients who fail CPAP is challenging because currently no validated method predicts how anatomical changes affect UA collapsibility. The gold standard objective measure of UA collapsibility is the pharyngeal critical pressure (Pcrit). A systematic literature review and meta-analysis were performed to identify the anatomical factors with the strongest correlation with Pcrit. A search using the PRISMA methodology was performed on PubMed for English language scientific papers that correlated Pcrit to anatomic variables and OSA severity as measured by the apnea-hypopnea index (AHI). A total of 29 papers that matched eligibility criteria were included in the quantitative synthesis. The meta-analysis suggested that AHI has only a moderate correlation with Pcrit (estimated Pearson correlation coefficient r = 0.46). The meta-analysis identified four key anatomical variables associated with UA collapsibility, namely hyoid position (r = 0.53), tongue volume (r = 0.51), pharyngeal length (r = 0.50), and waist circumference (r = 0.49). In the future, biomechanical models that quantify the relative importance of these anatomical factors in determining UA collapsibility may help identify the optimal intervention for each patient. Many anatomical and structural factors such as airspace cross-sectional areas, epiglottic collapse, and palatal prolapse have inadequate data and require further research.

Impact of Reintervention During Stage 1 Palliation Hospitalization: A National, Multicenter Study.

BACKGROUND: Stage 1 palliation (S1P) for hypoplastic left heart syndrome remains associated with high morbidity and mortality. Previous studies on burden of reinterventions did not include patients who remain hospitalized before stage 2 palliation (S2P). This study described the rate of reintervention during S1P hospitalization and sought to determine the impact of reintervention on outcomes. METHODS: All participants enrolled in phase II of the National Pediatric Cardiology Quality Improvement Collaborative after S1P were included in this study. The primary outcome was the rate of reintervention during hospitalization after S1P and before hospital discharge or S2P. Reintervention was defined as 1 or more unplanned interventional cardiac catheterizations or surgical reoperations. RESULTS: Between March 1, 2016 and October 1, 2019, 1367 participants underwent S1P and 339 (24.8%) had a reintervention; most commonly to address the source of pulmonary blood flow. Gestational age, weight at S1P, atrioventricular septal defect, heterotaxy, preoperative pulmonary artery bands, hybrid S1P, and an additional bypass run or early extracorporeal membrane oxygenation were significantly associated with reintervention. Participants in the reintervention group experienced higher rates of nearly all postoperative complications, were less likely to be discharged before S2P (57.1% vs 86%; P < .001), and more likely to experience in-hospital mortality (17% vs 5%; P < .001). CONCLUSIONS: Unplanned reintervention during hospitalization after S1P palliation occurred in 25% of participants in a large, registry-based national cohort. Participants who underwent reintervention were more likely to remain as inpatient and were less likely to survive to S2P. Reintervention was associated with a multitude of postoperative complications that affect survival and long-term outcome.

Team principles for successful interdisciplinary research teams.

Interdisciplinary research teams can be extremely beneficial when addressing difficult clinical problems. The incorporation of conceptual and methodological strategies from a variety of research disciplines and health professions yields transformative results. In this setting, the long-term goal of team science is to improve patient care, with emphasis on population health outcomes. However, team principles necessary for effective research teams are rarely taught in health professional schools. To form successful interdisciplinary research teams in cardio-oncology and beyond, guiding principles and organizational recommendations are necessary. Cardiovascular disease results in annual direct costs of $220 billion (about $680 per person in the US) and is the leading cause of death for cancer survivors, including adult survivors of childhood cancers. Optimizing cardio-oncology research in interdisciplinary research teams has the potential to aid in the investigation of strategies for saving hundreds of thousands of lives each year in the United States and mitigating the annual cost of cardiovascular disease. Despite published reports on experiences developing research teams across organizations, specialties and settings, there is no single journal article that compiles principles for cardiology or cardio-oncology research teams. In this review, recurring threads linked to working as a team, as well as optimal methods, advantages, and problems that arise when managing teams are described in the context of career development and research. The worth and hurdles of a team approach, based on practical lessons learned from establishing our multidisciplinary research team and information gleaned from relevant specialties in the development of a successful team are presented.

Novel Pediatric Height Outlier Detection Methodology for Electronic Health Records via Machine Learning With Monotonic Bayesian Additive Regression Trees.

OBJECTIVE: To create a new methodology that has a single simple rule to identify height outliers in the electronic health records (EHR) of children. METHODS: We constructed 2 independent cohorts of children 2 to 8 years old to train and validate a model predicting heights from age, gender, race and weight with monotonic Bayesian additive regression trees. The training cohort consisted of 1376 children where outliers were unknown. The testing cohort consisted of 318 patients that were manually reviewed retrospectively to identify height outliers. RESULTS: The amount of variation explained in height values by our model, R2 , was 82.2% and 75.3% in the training and testing cohorts, respectively. The discriminatory ability to assess height outliers in the testing cohort as assessed by the area under the receiver operating characteristic curve was excellent, 0.841. Based on a relatively aggressive cutoff of 0.075, the outlier sensitivity is 0.713, the specificity 0.793; the positive predictive value 0.615 and the negative predictive value is 0.856. CONCLUSIONS: We have developed a new reliable, largely automated, outlier detection method which is applicable to the identification of height outliers in the pediatric EHR. This methodology can be applied to assess the veracity of height measurements ensuring reliable indices of body proportionality such as body mass index.

Environmental health literacy for Anishinaabe (Great Lakes Native American) fish consumers: A randomized control trial.

BACKGROUND: Fish consumption comprises an important part of what the Anishinaabe (Great Lakes Native Americans) call "minobimaadiziiwin" which translates roughly to "living in a good way". Industrial activity leading to the accumulation of persistent contaminants in fish disrupts minobimaadiziiwin. Our team of academic and Anishinaabe scientists co-developed a fish consumption advisory for the Anishinaabe using software that can be accessed via mobile phones and/or the internet. OBJECTIVES: The software, Gigiigoo'inaan ("our fish") is designed to improve environmental health literacy using culturally congruent messaging and aesthetics. We tested the following hypotheses: 1) the Gigiigoo'inaan would encourage consumption of fish high in Polyunsaturated Omega-3 fatty acids (PFUA-3) whilst minimizing contaminant intake (methylmercury (MeHg) and Polychorinated Biphenyls (PCBs)); and 2) intervention participants will be more likely than controls to achieve a favorable n-3 PUFA/MeHg consumption ratios. METHODS: We conducted a randomized controlled trial with prospective self-reported fish consumption using automated email surveys. One-month pre and one month post, control and intervention outcome variables were calculated per participant as µg/kg/day of MeHg, µg/kg/day of PCB, g of fish, and mg/day of EPA+DHA. These were modeled using an analysis of covariance (ANCOVA) with a-priori covariates: age, sex, and tribal affiliation. RESULTS: Most participants in both trial arms reported eating relatively elevated amounts of fish yet remained within advisory guidelines for contaminants. EPA+DHA:MeHg ratios were also favorable in most participants. Advisory limits for contaminants were exceeded by relatively few participants in the study. DISCUSSION: Gigiigoo'inaan was previously reported to increase confidence, the current user feedback confirms this. Most participants ate fish but did not exceed the advisory limits, which demonstrates Environmental Health Literacy progress in the region despite a lack of observed behavior change during the trial. A small number of participants exceeded contaminant intake guidelines which matches the pilot work for this study.