Group physical therapy for knee osteoarthritis: protocol for a hybrid type III effectiveness-implementation trial.

BACKGROUND: Knee osteoarthritis (OA) is a leading cause of chronic pain and disability and one of the most common conditions treated in outpatient physical therapy (PT). Because of the high and growing prevalence of knee OA, there is a need for efficient approaches for delivering exercise-based PT to patients with knee OA. A prior randomized controlled trial (RCT) showed that a 6-session Group Physical Therapy Program for Knee OA (Group PT) yields equivalent or greater improvements in pain and functional outcomes compared with traditional individual PT, while requiring fewer clinician hours per patient to deliver. This manuscript describes the protocol for a hybrid type III effectiveness-implementation trial comparing two implementation packages to support delivery of Group PT. METHODS: In this 12-month embedded trial, a minimum of 16 Veterans Affairs Medical Centers (VAMCs) will be randomized to receive one of two implementation support packages for their Group PT programs: a standard, low-touch support based on Replicating Effective Programs (REP) versus enhanced REP (enREP), which adds tailored, high-touch support if sites do not meet Group PT adoption and sustainment benchmarks at 6 and 9 months following launch. Implementation outcomes, including penetration (primary), adoption, and fidelity, will be assessed at 6 and 12 months (primary assessment time point). Additional analyses will include patient-level effectiveness outcomes (pain, function, satisfaction) and staffing and labor costs. A robust qualitative evaluation of site implementation context and experience, as well as site-led adaptations to the Group PT program, will be conducted. DISCUSSION: To our knowledge, this study is the first to evaluate the impact of tailored, high-touch implementation support on implementation outcomes when compared to standardized, low-touch support for delivering a PT-based intervention. The Group PT program has strong potential to become a standard offering for PT, improving function and pain-related outcomes for patients with knee OA. Results will provide information regarding the effectiveness and value of this implementation approach and a deeper understanding of how healthcare systems can support wide-scale adoption of Group PT. TRIAL REGISTRATION: This study was registered on March 7, 2022 at ClinicalTrials.gov (identifier NCT05282927 ).

Design and analysis of outcomes following SARS-CoV-2 infection in veterans.

BACKGROUND: Understanding how SARS-CoV-2 infection impacts long-term patient outcomes requires identification of comparable persons with and without infection. We report the design and implementation of a matching strategy employed by the Department of Veterans Affairs' (VA) COVID-19 Observational Research Collaboratory (CORC) to develop comparable cohorts of SARS-CoV-2 infected and uninfected persons for the purpose of inferring potential causative long-term adverse effects of SARS-CoV-2 infection in the Veteran population. METHODS: In a retrospective cohort study, we identified VA health care system patients who were and were not infected with SARS-CoV-2 on a rolling monthly basis. We generated matched cohorts within each month utilizing a combination of exact and time-varying propensity score matching based on electronic health record (EHR)-derived covariates that can be confounders or risk factors across a range of outcomes. RESULTS: From an initial pool of 126,689,864 person-months of observation, we generated final matched cohorts of 208,536 Veterans infected between March 2020-April 2021 and 3,014,091 uninfected Veterans. Matched cohorts were well-balanced on all 39 covariates used in matching after excluding patients for: no VA health care utilization; implausible age, weight, or height; living outside of the 50 states or Washington, D.C.; prior SARS-CoV-2 diagnosis per Medicare claims; or lack of a suitable match. Most Veterans in the matched cohort were male (88.3%), non-Hispanic (87.1%), white (67.2%), and living in urban areas (71.5%), with a mean age of 60.6, BMI of 31.3, Gagne comorbidity score of 1.4 and a mean of 2.3 CDC high-risk conditions. The most common diagnoses were hypertension (61.4%), diabetes (34.3%), major depression (32.2%), coronary heart disease (28.5%), PTSD (25.5%), anxiety (22.5%), and chronic kidney disease (22.5%). CONCLUSION: This successful creation of matched SARS-CoV-2 infected and uninfected patient cohorts from the largest integrated health system in the United States will support cohort studies of outcomes derived from EHRs and sample selection for qualitative interviews and patient surveys. These studies will increase our understanding of the long-term outcomes of Veterans who were infected with SARS-CoV-2.

BMI Trends for Veterans Up to 10 Years After VA Enrollment Following Military Discharge.

BACKGROUND: Obesity (body mass index [BMI]≥30kg/m2) among US adults has tripled over the past 45 years, but it is unclear how this population-level weight change has occurred. OBJECTIVE: We sought to identify distinct long-term BMI trajectories and examined associations with demographic and clinical characteristics. DESIGN: The design was latent trajectory modeling over 10 years of a retrospective cohort. Subgroups were identified via latent class growth mixture models, separately by sex. Weighted multinomial logistic regressions identified factors associated with subgroup membership. PARTICIPANTS: Participants were a retrospective cohort of 292,331 males and 62,898 females enrolled in VA. MAIN MEASURES: The main outcome measure was 6-month average VA-measured BMI over the course of 10 years. Additional electronic health record measures on demographic, clinical, and services utilization characteristics were also used to characterize latent trajectories. KEY RESULTS: Four trajectories were identified for men and for women, corresponding to standard BMI categories "normal weight" (BMI <25), "overweight" (BMI 25-29.99), and "with obesity" (BMI ≥30): "normal weight" and increasing (males: 28.4%; females: 22.8%), "overweight" and increasing (36.4%; 35.6%), "with obesity" and increasing (33.6%; 40.0%), and "with obesity" and stable (males: 1.6%) or decreasing (females: 1.6%). Race, ethnicity, comorbidities, mental health diagnoses, and mental health service utilization discriminated among classes. CONCLUSIONS: BMI in the 10 years following VA enrollment increased modestly. VA should continue prioritizing weight management interventions to the large number of veterans with obesity upon VA enrollment, because the majority remain with obesity.

TEAM: A MULTIPLE TESTING ALGORITHM ON THE AGGREGATION TREE FOR FLOW CYTOMETRY ANALYSIS.

In immunology studies, flow cytometry is a commonly used multivariate single-cell assay. One key goal in flow cytometry analysis is to detect the immune cells responsive to certain stimuli. Statistically, this problem can be translated into comparing two protein expression probability density functions (pdfs) before and after the stimulus; the goal is to pinpoint the regions where these two pdfs differ. Further screening of these differential regions can be performed to identify enriched sets of responsive cells. In this paper, we model identifying differential density regions as a multiple testing problem. First, we partition the sample space into small bins. In each bin, we form a hypothesis to test the existence of differential pdfs. Second, we develop a novel multiple testing method, called TEAM (Testing on the Aggregation tree Method), to identify those bins that harbor differential pdfs while controlling the false discovery rate (FDR) under the desired level. TEAM embeds the testing procedure into an aggregation tree to test from fine- to coarse-resolution. The procedure achieves the statistical goal of pinpointing density differences to the smallest possible regions. TEAM is computationally efficient, capable of analyzing large flow cytometry data sets in much shorter time compared with competing methods. We applied TEAM and competing methods on a flow cytometry data set to identify T cells responsive to the cytomegalovirus (CMV)-pp65 antigen stimulation. With additional downstream screening, TEAM successfully identified enriched sets containing monofunctional, bifunctional, and polyfunctional T cells. Competing methods either did not finish in a reasonable time frame or provided less interpretable results. Numerical simulations and theoretical justifications demonstrate that TEAM has asymptotically valid, powerful, and robust performance. Overall, TEAM is a computationally efficient and statistically powerful algorithm that can yield meaningful biological insights in flow cytometry studies.

Comparison of 2-Year Outcomes of Extended Criteria Cardiac Transplantation Versus Destination Left Ventricular Assist Device Therapy Using Continuous Flow.

Alternatives have emerged for patients ineligible for cardiac transplantation under standard criteria. The purpose of our study was to compare outcomes in patients ineligible for cardiac transplantation under standard criteria, treated either with extended criteria cardiac transplantation (ECCT) or a continuous flow destination therapy left ventricular assist device (CF DT-LVAD). From 2005 to 2012, patients treated with either ECCT or CF DT-LVAD at our institution were retrospectively analyzed. In the overall unmatched cohort, we examined mortality and other outcomes, including index hospitalization length of stay, renal function, stroke, and readmission rates. After propensity score (PS) matching, outcomes were compared between ECCT and CF DT-LVAD recipients. Overall, 62 patients underwent ECCT, and 146 patients were treated with CF DT-LVAD. The 2-year mortality estimate for ECCT recipients was 27.3% (95% confidence interval 15.5% to 39.1%) and for CF DT-LVAD recipients was 11.2% (95% confidence interval 4.8% to 17.6%). After PS matching of 39 patients from each treatment group, there was no significant difference in overall survival after 2 years (p = 0.346). In both unmatched and PS-matched analyses, CF DT-LVAD patients compared with ECCT had a significantly higher estimated glomerular filtration rate at 1 year but also had significantly higher hospital readmission rates. Stroke also more commonly occurred after CF DT-LVAD compared with ECCT (17 vs 5, unmatched; and 2 vs 1, PS matched). However, there was no significant difference between PS-matched groups in 2-year stroke-free survival (p = 0.371). In conclusion, ECCT and CF DT-LVAD in select patients are comparable therapies with respect to 2-year survival.

Effects of left ventricular assist device support on biomarkers of cardiovascular stress, fibrosis, fluid homeostasis, inflammation, and renal injury.

OBJECTIVES: The purpose of this study was to examine changes in a broad panel of biomarkers following left ventricular assist device (LVAD) support in advanced heart failure (HF). BACKGROUND: LVAD therapy mechanically unloads the failing heart and may result in reversal of certain aspects of the end-stage HF phenotype. Changes in markers of myocardial stress, fibrosis, inflammation, fluid homeostasis, and renal injury in this setting are unknown. METHODS: Amino-terminal pro-B-type natriuretic peptide (NT-proBNP), galectin-3, ST2, copeptin, growth differentiation factor (GDF)-15, C-reactive protein (CRP), and neutrophil gelatinase associated lipocalin (NGAL) levels were measured in frozen plasma collected from 37 individuals prior to continuous flow LVAD implantation and a median of 136 (interquartile range: 94 to 180) days after implantation. RESULTS: The median age of patients was 68 years old. LVAD therapy was associated with significant decreases in NT-proBNP (3,093 to 2,090 pg/ml; p = 0.02), ST2 (67.5 to 45.2 ng/ml, p <0.01), galectin-3 (24.7 to 22.0 ng/ml; p = 0.04), GDF-15 (3,232 to 2,613 ng/l;p <0.001), hs-CRP (22.4 to 11.9 mg/l; p = 0.01), and copeptin (103 to 94 pmol/l; p = 0.003) but not NGAL (132 to 135 ng/ml; p = 0.06). Despite improvement over time, absolute values of each biomarker remained extremely abnormal. Greater reductions in biomarkers were noted in individuals with >25% decrease in NT-proBNP concentrations but reached statistical significance only in the case of galectin-3 (p = 0.01). CONCLUSIONS: The biomarker profile in patients after LVAD placement improves but nonetheless remains significantly abnormal. Our results suggest the need for targeted therapeutic interventions to mitigate such abnormalities and potentially increase rates of myocardial recovery.

Computed tomography correlates with cardiopulmonary hemodynamics in pulmonary hypertension in adults with sickle cell disease.

Our objective was to determine whether computed tomography angiography (CTA) measurements of pulmonary artery size can noninvasively assess hemodynamics and diagnose pulmonary hypertension (PH) secondary to sickle cell disease (SCD). Twenty SCD patients with confirmed PH were compared with 20 matched controls. Diameters of the pulmonary artery trunk and branches were measured with CTA and a semiautomatic segmentation algorithm. Measurements were normalized by body size and correlated (Spearman rank) with hemodynamic markers from right-heart catheterization. Receiver operating characteristic (ROC) curves were used to investigate the role of pulmonary artery sizes in diagnosing PH. Analysis of pulmonary artery sizes adjusted for body surface area (BSA) resulted in the most significant discrimination between subjects with PH secondary to SCD and controls (P < 0.001); PH was diagnosed accurately with an area under the ROC curve of 0.99. There was significant correlation between pulmonary artery sizes and body mass index (BMI) and BSA only in controls (r = 0.46-0.68, P < 0.04 for all). The most significant correlations with hemodynamic markers were found between BMI-adjusted pulmonary artery sizes and high systolic pulmonary arterial pressure, high pulmonary vascular resistance, high systemic vascular resistance, and low cardiac output (r = 0.47, 0.62, 0.61, and 0.66, respectively; P < 0.04 for all). BMI-adjusted CTA measures of the pulmonary artery relate to high pulmonary vascular resistance and reduced cardiac output in patients with SCD and PH. CTA with quantitative image analysis is a powerful noninvasive diagnostic tool for PH in SCD and shows promise as estimator of hemodynamic markers.

Patterns of recurrence after trimodality therapy for esophageal cancer.

BACKGROUND: Patterns of failure after neoadjuvant chemoradiotherapy and surgery for esophageal cancer are poorly defined. METHODS: All patients in the current study were treated with trimodality therapy for nonmetastatic esophageal cancer from 1995 to 2009. Locoregional failure included lymph node failure (NF), anastomotic failure, or both. Abdominal paraaortic failure (PAF) was defined as disease recurrence at or below the superior mesenteric artery. RESULTS: Among 155 patients, the primary tumor location was the upper/middle esophagus in 18%, the lower esophagus in 32%, and the gastroesophageal junction in 50% (adenocarcinoma in 79% and squamous cell carcinoma in 21%) of patients. Staging methods included endoscopic ultrasound (73%), computed tomography (46%), and positron emission tomography/computed tomography (54%). Approximately 40% of patients had American Joint Committee on Cancer stage II disease and 60% had stage III disease. The median follow-up was 1.3 years. The 2-year locoregional control, event-free survival, and overall survival rates were 86%, 36%, and 48%, respectively. The 2-year NF rate was 14%, the isolated NF rate was 3%, and the anastomotic failure rate was 6%. The 2-year PAF rate was 9% and the isolated PAF rate was 5%. PAF was found to be increased among patients with gastroesophageal junction tumors (12% vs 6%), especially for the subset with ≥ 2 clinically involved lymph nodes at the time of diagnosis (19% vs 4%). CONCLUSIONS: Few patients experience isolated NF or PAF as their first disease recurrence. Therefore, it is unlikely that targeting additional regional lymph node basins with radiotherapy would significantly improve clinical outcomes.

Phase 1 trial of neoadjuvant radiation therapy before prostatectomy for high-risk prostate cancer.

PURPOSE: To evaluate, in a phase 1 study, the safety of neoadjuvant whole-pelvis radiation therapy (RT) administered immediately before radical prostatectomy in men with high-risk prostate cancer. METHODS AND MATERIALS: Twelve men enrolled and completed a phase 1 single-institution trial between 2006 and 2010. Eligibility required a previously untreated diagnosis of localized but high-risk prostate cancer. Median follow-up was 46 months (range, 14-74 months). Radiation therapy was dose-escalated in a 3 × 3 design with dose levels of 39.6, 45, 50.4, and 54 Gy. The pelvic lymph nodes were treated up to 45 Gy with any additional dose given to the prostate and seminal vesicles. Radical prostatectomy was performed 4-8 weeks after RT completion. Primary outcome measure was intraoperative and postoperative day-30 morbidity. Secondary measures included late morbidity and oncologic outcomes. RESULTS: No intraoperative morbidity was seen. Chronic urinary grade 2+ toxicity occurred in 42%; 2 patients (17%) developed a symptomatic urethral stricture requiring dilation. Two-year actuarial biochemical recurrence-free survival was 67% (95% confidence interval 34%-86%). Patients with pT3 or positive surgical margin treated with neoadjuvant RT had a trend for improved biochemical recurrence-free survival compared with a historical cohort with similar adverse factors. CONCLUSIONS: Neoadjuvant RT is feasible with moderate urinary morbidity. However, oncologic outcomes do not seem to be substantially different from those with selective postoperative RT. If this multimodal approach is further evaluated in a phase 2 setting, 54 Gy should be used in combination with neoadjuvant androgen deprivation therapy to improve biochemical outcomes.

Statistical 4D graphs for multi-organ abdominal segmentation from multiphase CT.

The interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis applications. Diagnosis also relies on the comprehensive analysis of multiple organs and quantitative measures of soft tissue. An automated method optimized for medical image data is presented for the simultaneous segmentation of four abdominal organs from 4D CT data using graph cuts. Contrast-enhanced CT scans were obtained at two phases: non-contrast and portal venous. Intra-patient data were spatially normalized by non-linear registration. Then 4D convolution using population training information of contrast-enhanced liver, spleen and kidneys was applied to multiphase data to initialize the 4D graph and adapt to patient-specific data. CT enhancement information and constraints on shape, from Parzen windows, and location, from a probabilistic atlas, were input into a new formulation of a 4D graph. Comparative results demonstrate the effects of appearance, enhancement, shape and location on organ segmentation. All four abdominal organs were segmented robustly and accurately with volume overlaps over 93.6% and average surface distances below 1.1mm.

Multi-organ segmentation from multi-phase abdominal CT via 4D graphs using enhancement, shape and location optimization.

The interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis (CAD) applications. Diagnosis also relies on the comprehensive analysis of multiple organs and quantitative measures of soft tissue. An automated method optimized for medical image data is presented for the simultaneous segmentation of four abdominal organs from 4D CT data using graph cuts. Contrast-enhanced CT scans were obtained at two phases: non-contrast and portal venous. Intra-patient data were spatially normalized by non-linear registration. Then 4D erosion using population historic information of contrast-enhanced liver, spleen, and kidneys was applied to multi-phase data to initialize the 4D graph and adapt to patient specific data. CT enhancement information and constraints on shape, from Parzen windows, and location, from a probabilistic atlas, were input into a new formulation of a 4D graph. Comparative results demonstrate the effects of appearance and enhancement, and shape and location on organ segmentation.

Segmentation and quantification of pulmonary artery for noninvasive CT assessment of sickle cell secondary pulmonary hypertension.

PURPOSE: Pulmonary arterial hypertension (PAH) is a progressive vascular disease that results in high mortality and morbidity in sickle cell disease (SCD) patients. PAH diagnosis is invasive via right heart catheterization, but manual measurements of the main pulmonary artery (PA) diameters from computed tomography (CT) have shown promise as noninvasive surrogate marker of PAH. The authors propose a semiautomated computer-assisted diagnostic (CAD) tool to quantify the main PA size from pulmonary CT angiography (CTA). METHODS: A follow-up retrospective study investigated the potential of CT and image analysis to quantify the presence of PAH secondary to SCD based on PA size. The authors segmented the main pulmonary arteries using a combination of fast marching level sets and geodesic active contours from smoothed pulmonary CTA images of 20 SCD patients with proven PAH by right heart catheterization and 20 matched negative controls. From the PA segmentation, a Euclidean distance map was calculated and an algorithm based on fast marching methods was used to compute subvoxel precise centerlines of the PA trunk (PT) and main left/right PA (PM). Maximum distentions of PT and PM were automatically quantified using the centerline and validated with manual measurements from two observers. RESULTS: The pulmonary trunk and main were significantly larger (p < 0.001) in PAH/SCD patients (33.73 +/- 3.92 mm for PT and 25.17 +/- 2.90 for PM) than controls (27.03 +/- 2.94 mm for PT and 20.62 +/- 3.06 for PM). The discrepancy was qualitatively improved when vessels' diameters were normalized by body surface area (p < 0.001). The validation of the method showed high correlation (mean R=0.9 for PT and R = 0.91 for PM) and Bland-Altman agreement (0.4 +/- 3.6 mm for PT and 0.5 +/- 2.9 mm for PM) between CAD and manual measurements. Quantification errors were comparable to intraobserver and interobserver variability. CAD measurements between two different users were robust and reproducible with correlations of R = 0.99 for both PT and PM and Bland-Altman agreements of -0.13 +/- 1.33 mm for PT and -0.08 +/- 0.84 mm for PM. CONCLUSION: Results suggest that the semiautomated quantification of pulmonary artery has sufficient accuracy and reproducibility for clinical use. CT with image processing and extraction of PA biomarkers show great potential as a surrogate indicator for diagnosis or quantification of PAH, and could be an important tool for drug discovery and noninvasive clinical surveillance.

Atlas-based automated segmentation of spleen and liver using adaptive enhancement estimation.

The paper presents the automated segmentation of spleen and liver from contrast-enhanced CT images of normal and hepato/splenomegaly populations. The method used 4 steps: (i) a mean organ model was registered to the patient CT; (ii) the first estimates of the organs were improved by a geodesic active contour; (iii) the contrast enhancements of liver and spleen were estimated to adjust to patient image characteristics, and an adaptive convolution refined the segmentations; (iv) lastly, a normalized probabilistic atlas corrected for shape and location for the precise computation of each organ's volume and height (mid-hepatic liver height and cephalocaudal spleen height). Results from test data demonstrated the method's ability to accurately segment the spleen (RMS error = 1.09 mm; DICE/Tanimoto overlaps = 95.2/91) and liver (RMS error = 2.3 mm, and DICE/Tanimoto overlaps = 96.2/92.7). The correlations (R2) with clinical/manual height measurements were 0.97 and 0.93 for the spleen and liver respectively.

Atlas-based Automated Segmentation of Spleen and Liver using Adaptive Enhancement Estimation.

The paper presents the automated segmentation of spleen and liver from contrast-enhanced CT images of normal and hepato/splenomegaly populations. The method used 4 steps: (i) a mean organ model was registered to the patient CT; (ii) the first estimates of the organs were improved by a geodesic active contour; (iii) the contrast enhancements of liver and spleen were estimated to adjust to patient image characteristics, and an adaptive convolution refined the segmentations; (iv) lastly, a normalized probabilistic atlas corrected for shape and location for the precise computation of each organ's volume and height (mid-hepatic liver height and cephalocaudal spleen height). Results from test data demonstrated the method's ability to accurately segment the spleen (RMS error = 1.09mm; DICE/Tanimoto overlaps = 95.2/91) and liver (RMS error = 2.3mm, and DICE/Tanimoto overlaps = 96.2/92.7). The correlations (R(2)) with clinical/manual height measurements were 0.97 and 0.93 for the spleen and liver respectively.