Development of a Consensus Derived Synoptic Operative Report for Rectal Prolapse: A Report From the Pelvic Floor Disorders Consortium.

BACKGROUND: Narrative operative reports may frequently omit or obscure data from an operation. OBJECTIVE: We aim to develop a synoptic operative report for rectal prolapse that includes core descriptors as developed by an international consensus of expert pelvic floor surgeons. DESIGN: Descriptors for patients undergoing rectal prolapse surgery were generated through review. Members of the Pelvic Floor Disorders Consortium were recruited to participate in a 3 round Delphi process using a 9-point Likert scale. Descriptors that achieved 70% agreement were kept from the first round, descriptors scoring 40-70% agreement were recirculated in subsequent rounds. A final list of operative descriptors was determined at a consensus meeting, with a final consensus meeting more than 70% agreement. SETTINGS: This was a survey administered to members of the Pelvic Floor Disorders Consortium. MAIN OUTCOME MEASURES: Descriptors meeting greater than 70% agreement were selected. RESULTS: One-hundred seventy six surgeons representing colorectal surgeons, urogynecologists, and urologists distributed throughout North America (56%), Latin America (4%), Western Europe (29%), Asia (4%), and Africa (1%) participated in the first round of Delphi voting. After two additional rounds and a final consensus meeting, 16 of 30 descriptors met 70% consensus. Descriptors that met consensus were: surgery type, posterior dissection, ventral dissection, mesh used, type of mesh used, mesh location, sutures used, suture type, pouch of Douglas and peritoneum reclosed, length of rectum imbricated, length of bowel resected, levatoroplasty, simultaneous vaginal procedure, simultaneous gynecologic procedure, simultaneous enterocele repair, and simultaneous urinary incontinence procedure. LIMITATIONS: Survey represents views of members of the Delphi panel, and may not represent viewpoints of all surgeons. CONCLUSIONS/DISCUSSION: This Delphi survey establishes international consensus descriptors for intraoperative variables that have been used to produce a synoptic operative report. This will help establish defined operative reporting to improve clinical communication, quality measures, and clinical research. See Video Abstract.

Factors that determine patients considering medication for the disease of obesity: an IMI2 SOPHIA study.

OBJECTIVE: Obesity-related problems can now be managed with effective nutritional therapy, pharmacotherapy, and surgeries that achieve >10% weight loss. Assessing patient preferences, treatment choices, and factors affecting patients can improve treatment compliance and efficacy. Our aim was to identify factors affecting patient preference and subsequent choice of pharmacotherapy among those seeking treatment for obesity-related disorders. METHODS: A participatory action study using purposeful sampling recruited 33 patients with obesity complications. They were referred to specialist clinics in non-alcoholic fatty liver disease, diabetes mellitus, hypertension, and chronic kidney disease. Sixteen males and seventeen females aged 18-70 years, with BMI > 35 kg/m2 were recruited. Before the interview, participants watched a 60-minute video explaining nutritional therapy, pharmacotherapy, and surgery in equipoise. Data were collected in semi-structured interviews; Reflective thematic analysis was used. This sub study focuses only on patients who expressed specific attitudes (positive or negative) towards pharmacotherapy. RESULTS: Ten (30%) patients expressed a view on pharmacotherapy. Eight (24%) patients chose pharmacotherapy alone, whereas two (6%) patients chose pharmacotherapy combined with nutritional therapy. In this sub study focusing on pharmacotherapy, five themes were identified related to choosing whether or not to take medication: (1) attitudes towards pharmacotherapy, (2) attitudes toward size of obesity and its complications, (3) weighing the benefits and risks of treatment, (4) knowledge and reassurance of health professionals, and (5) costs associated with drug therapy. CONCLUSION: The primary concerns regarding pharmacotherapy for intentional weight loss were efficacy, side effects, lifelong dosing, pharmacokinetics, and cost. Providing access to information about all the pharmacotherapies and the benefits is likely to result in greater penetrance of treatment.

Hospital Readmissions in Patients Supported with Durable Centrifugal-Flow Left Ventricular Assist Devices.

Background: Centrifugal-flow left ventricular assist devices (CF-LVADs) have improved morbidity and mortality for their recipients. Hospital readmissions remain common, negatively impacting quality of life and survival. We sought to identify risk factors associated with hospital readmissions among patients with CF-LVADs. Methods: Consecutive patients receiving a CF-LVAD between February 2011 and March 2021 were retrospectively evaluated using prospectively maintained institutional databases. Hospital readmissions within three years post-LVAD implantation were dichotomized into heart failure (HF)/LVAD-related or non-HF/LVAD-related readmissions. Multivariable Cox regression models augmented using a machine learning algorithm, the least absolute shrinkage and selection operator (LASSO) method, for variable selection were used to estimate associations between HF/LVAD-related readmissions and pre-, intra- and post-operative clinical variables. Results: A total of 204 CF-LVAD recipients were included, of which 138 (67.7%) had at least one HF/LVAD-related readmission. HF/LVAD-related readmissions accounted for 74.4% (436/586) of total readmissions. The main reasons for HF/LVAD-related readmissions were major bleeding, major infection, HF exacerbation, and neurological dysfunction. Using pre-LVAD variables, HF/LVAD-related readmissions were associated with substance use, previous cardiac surgery, HF duration, pre-LVAD inotrope dependence, percutaneous LVAD/VA-ECMO support, LVAD type, and the left ventricular ejection fraction in multivariable analysis (Harrell's concordance c-statistic; 0.629). After adding intra- and post-operative variables in the multivariable model, LVAD implant hospitalization length of stay was an additional predictor of readmission. Conclusions: Using machine learning-based techniques, we generated models identifying pre-, intra-, and post-operative variables associated with a higher likelihood of rehospitalizations among patients on CF-LVAD support. These models could provide guidance in identifying patients with increased readmission risk for whom clinical strategies to mitigate this risk may further improve LVAD recipient outcomes.

Health equity assessment of machine learning performance (HEAL): a framework and dermatology AI model case study.

Background: Artificial intelligence (AI) has repeatedly been shown to encode historical inequities in healthcare. We aimed to develop a framework to quantitatively assess the performance equity of health AI technologies and to illustrate its utility via a case study. Methods: Here, we propose a methodology to assess whether health AI technologies prioritise performance for patient populations experiencing worse outcomes, that is complementary to existing fairness metrics. We developed the Health Equity Assessment of machine Learning performance (HEAL) framework designed to quantitatively assess the performance equity of health AI technologies via a four-step interdisciplinary process to understand and quantify domain-specific criteria, and the resulting HEAL metric. As an illustrative case study (analysis conducted between October 2022 and January 2023), we applied the HEAL framework to a dermatology AI model. A set of 5420 teledermatology cases (store-and-forward cases from patients of 20 years or older, submitted from primary care providers in the USA and skin cancer clinics in Australia), enriched for diversity in age, sex and race/ethnicity, was used to retrospectively evaluate the AI model's HEAL metric, defined as the likelihood that the AI model performs better for subpopulations with worse average health outcomes as compared to others. The likelihood that AI performance was anticorrelated to pre-existing health outcomes was estimated using bootstrap methods as the probability that the negated Spearman's rank correlation coefficient (i.e., "R") was greater than zero. Positive values of R suggest that subpopulations with poorer health outcomes have better AI model performance. Thus, the HEAL metric, defined as p (R >0), measures how likely the AI technology is to prioritise performance for subpopulations with worse average health outcomes as compared to others (presented as a percentage below). Health outcomes were quantified as disability-adjusted life years (DALYs) when grouping by sex and age, and years of life lost (YLLs) when grouping by race/ethnicity. AI performance was measured as top-3 agreement with the reference diagnosis from a panel of 3 dermatologists per case. Findings: Across all dermatologic conditions, the HEAL metric was 80.5% for prioritizing AI performance of racial/ethnic subpopulations based on YLLs, and 92.1% and 0.0% respectively for prioritizing AI performance of sex and age subpopulations based on DALYs. Certain dermatologic conditions were significantly associated with greater AI model performance compared to a reference category of less common conditions. For skin cancer conditions, the HEAL metric was 73.8% for prioritizing AI performance of age subpopulations based on DALYs. Interpretation: Analysis using the proposed HEAL framework showed that the dermatology AI model prioritised performance for race/ethnicity, sex (all conditions) and age (cancer conditions) subpopulations with respect to pre-existing health disparities. More work is needed to investigate ways of promoting equitable AI performance across age for non-cancer conditions and to better understand how AI models can contribute towards improving equity in health outcomes. Funding: Google LLC.

Brentuximab vedotin and chemotherapy in relapsed/refractory Hodgkin lymphoma: a propensity score-matched analysis.

ABSTRACT: Several single-arm studies have explored the inclusion of brentuximab vedotin (BV) in salvage chemotherapy followed by autologous stem cell transplantation (ASCT) for relapsed/refractory (R/R) classical Hodgkin lymphoma (cHL). However, no head-to-head comparisons with standard salvage chemotherapy have been performed. This study presents a propensity score-matched analysis encompassing individual patient data from 10 clinical trials to evaluate the impact of BV in transplant-eligible patients with R/R cHL. We included 768 patients, of whom 386 were treated with BV with or without chemotherapy (BV cohort), whereas 382 received chemotherapy alone (chemotherapy cohort). Propensity score matching resulted in balanced cohorts of 240 patients each. No significant differences were observed in pre-ASCT complete metabolic response (CMR) rates (P = .69) or progression free survival (PFS; P = .14) between the BV and chemotherapy cohorts. However, in the BV vs chemotherapy cohort, patients with relapsed disease had a significantly better 3-year PFS of 80% vs 70%, respectively (P = .02), whereas there was no difference for patients with primary refractory disease (56% vs 62%, respectively; P = .67). Patients with stage IV disease achieved a significantly better 3-year PFS in the BV cohort (P = .015). Post-ASCT PFS was comparable for patients achieving a CMR after BV monotherapy and those receiving BV followed by sequential chemotherapy (P = .24). Although 3-year overall survival was higher in the BV cohort (92% vs 80%, respectively; P < .001), this is likely attributed to the use of other novel therapies in later lines for patients experiencing progression, given that studies in the BV cohort were conducted more recently. In conclusion, BV with or without salvage chemotherapy appears to enhance PFS in patients with relapsed disease but not in those with primary refractory cHL.

Core Descriptor Sets for Rectal Prolapse Outcomes Research Using a Modified Delphi Consensus.

BACKGROUND: There is wide variation in prolapse care. OBJECTIVE: To determine core descriptor sets for rectal prolapse to enhance outcomes research. DESIGN: Descriptors for patients undergoing rectal prolapse surgery were generated through a systematic review and expert opinion. Stakeholders were recruited internationally via listserv and social media. Experts were encouraged to consider the minimum descriptors that could be considered during clinical care, and descriptors were grouped into core descriptor sets. Consensus was defined as greater than 70% agreement. SETTING: A 3-round Delphi process using a 9-point Likert scale based on expert results was distributed via survey. The final interactive meeting used a polling platform. PARTICIPANTS: The Pelvic Floor Disorders Consortium interdisciplinary group convened to advance the clinical care of pelvic floor disorders. MAIN OUTCOME MEASURES: To achieve expert consensus for core descriptor sets for rectal prolapse using a modified Delphi method. RESULTS: A total of 206 providers participated, with survey response rates of 82% and 88%, respectively. Responders were from North America (56%), Europe (29%), and Latin America, Asia, Australia, New Zealand, and Africa (15%). Ninety-one percent of participants identified as colorectal surgeons and 80% reported >5 years of experience (35% reported >15 years). Fifty-seven attendees participated in the final meeting and voted on core descriptor sets. Ninety-three percent of participants agreed that descriptors such as age, BMI, frailty, nutrition, and the American Society of Anesthesiology score correlated to physiologic status. One hundred percent of participants agreed to include baseline bowel function. One hundred percent of participants reported willingness to complete a synoptic operative report. Follow-up intervals 1, 3, and 5 years after surgery (76%) with a collection of recurrence and functional outcomes at those time periods reached an agreement. LIMITATIONS: Individual bias, self-identification of experts, and paucity of knowledge related to rectal prolapse. CONCLUSIONS: This represents the first steps toward international consensus to unify language and data collection processes for rectal prolapse. See Video Abstract . CONJUNTOS DE DESCRIPTORES BSICOS PARA LA INVESTIGACIN DE RESULTADOS DE PROLAPSO RECTAL MEDIANTE UN CONSENSO DELPHI MODIFICADO: ANTECEDENTES:Existe una amplia variación en la atención del prolapso.OBJETIVO:Determinar conjuntos de descriptores básicos para el prolapso rectal para mejorar los resultados de la investigación.DISEÑO:Los descriptores para pacientes sometidos a cirugía de prolapso rectal se generaron a través de una revisión sistemática y la opinión de expertos. Las partes interesadas fueron reclutadas internacionalmente a través de listas de servicio y redes sociales. Se animó a los expertos a considerar los descriptores mínimos que podrían considerarse durante la atención clínica, y los descriptores se agruparon en conjuntos de descriptores básicos. El consenso se definió como > 70% de acuerdo.AJUSTE:Se distribuyó mediante encuesta un proceso Delphi de tres rondas que utiliza una escala Likert de 9 puntos basada en resultados de expertos. La reunión interactiva final utilizó una plataforma de votación.PARTICIPANTES:El grupo interdisciplinario del Consorcio de Trastornos del Suelo Pélvico se reunió para avanzar en la atención clínica de los trastornos del suelo pélvico.MEDIDAS PRINCIPALES DE RESULTADOS:Lograr el consenso de expertos para los conjuntos de descriptores básicos para el prolapso rectal utilizando un método Delphi modificado.RESULTADOS:Participaron 206 proveedores con tasas de respuesta a la encuesta del 82% y 88% respectivamente. Los encuestados procedían de América del Norte (56%), Europa (29%) y América Latina, Asia, Australia, Nueva Zelanda y África (15%). El noventa y uno por ciento se identificó como cirujanos colorrectales y el 80% reportó más de 5 años de experiencia (35% > 15 años). Cincuenta y siete asistentes participaron en la reunión final y votaron sobre conjuntos de descriptores básicos. El noventa y tres por ciento estuvo de acuerdo en que descriptores como edad, índice de masa corporal, fragilidad, nutrición y puntuación de la Sociedad Estadounidense de Anestesiología se correlacionaban con el estado fisiológico. El cien por ciento estuvo de acuerdo en incluir la función intestinal inicial. El 100% refirió disposición para realizar un informe operativo sinóptico. Los intervalos de seguimiento 1,3,5 años después de la cirugía (76%) con un conjunto de recurrencias y los resultados funcionales en esos períodos de tiempo coincidieron.LIMITACIONES:Sesgo individual, autoidentificación de los expertos y escasez de conocimientos relacionados con el prolapso rectal.CONCLUSIONES:Esto representa los primeros pasos hacia un consenso internacional para unificar el lenguaje y los procesos de recolección de datos para el prolapso rectal. (Traducción-Yesenia Rojas-Khalil ).

Matched control analysis suggests that R-CHOP followed by (R)-ICE may improve outcome in non-GCB DLBCL compared with R-CHOP.

ABSTRACT: Rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) is considered the standard-of-care for patients with advanced-stage diffuse large B-cell lymphoma (DLBCL), despite findings that patients with nongerminal center B-cell like (non-GCB) have significantly worse outcome with this regimen. We evaluated the prognostic significance of baseline risk factors, including cell of origin (COO) classified by the Hans algorithm, within an alternative chemoimmunotherapy program. At Memorial Sloan Kettering Cancer Center (MSK), 151 patients with DLBCL received sequential R-CHOP induction and (R)-ICE (rituximab, ifosfamide, carboplatin, and etoposide) consolidation. Outcome analysis based on COO was validated with a propensity score-matched cohort treated with R-CHOP from the Mayo Clinic component of the Molecular Epidemiology Resource (MER). Among the patients with GCB (n = 69) and non-GCB (n = 69) at MSK, event-free survival (EFS) of non-GCB was superior to that of GCB (hazard ratio [HR], 0.53; 95% confidence interval [CI], 0.29-0.98). Overall survival (OS) demonstrated an association in the same direction but was not statistically significant (HR, 0.68; 95% CI, 0.33-1.42). Propensity score-matched patients from MSK (n = 108) demonstrated a small attenuation in the HRs for EFS (HR, 0.57; 95% CI, 0.27-1.18) and OS (HR, 0.76; 95% CI, 0.33-1.79) and were no longer statistically significant. In contrast, the matched MER cohort (n = 108) demonstrated an EFS association (HR, 1.17; 95% CI, 0.70-1.95) and OS association (HR, 1.13; 95% CI, 0.64-2.00) in the opposite direction, but were also not statistically significant. R-CHOP induction and (R)-ICE consolidation may overcome the negative prognostic impact of the non-GCB phenotype, per the Hans algorithm, and can be preferentially selected for this population. This trial was registered at www.ClinicalTrials.gov as #NCT00039195 and #NCT00712582.

Immunochemotherapy plus lenalidomide for high-risk mantle cell lymphoma with measurable residual disease evaluation.

Chemoimmunotherapy followed by consolidative high-dose therapy with autologous stem cell rescue was a standard upfront treatment for fit patients with mantle cell lymphoma (MCL) in first remission; however, treatment paradigms are evolving in the era of novel therapies. Lenalidomide is an immunomodulatory agent with known efficacy in treating MCL. We conducted a single-center, investigator-initiated, phase II study of immunochemotherapy incorporating lenalidomide, without autologous stem cell transplant consolidation, enriching for patients with high-risk MCL (clinicaltrials gov. Identifier: NCT02633137). Patients received four cycles of lenalidomide-R-CHOP, two cycles of R-HiDAC, and six cycles of R-lenalidomide. The primary endpoint was rate of 3-year progression-free survival. We measured measurable residual disease (MRD) using a next-generation sequencing-based assay after each phase of treatment and at 6 months following end-oftreatment. We enrolled 49 patients of which 47 were response evaluable. By intent-to-treat, rates of overall and complete response were equivalent at 88% (43/49), one patient with stable disease, and two patients had disease progression during study; 3-year progression-free survival was 63% (primary endpoint not met) and differed by TP53 status (78% wild-type vs. 38% ALT; P=0.043). MRD status was prognostic and predicted long-term outcomes following R-HiDAC and at 6 months following end-of-treatment. In a high-dose therapy-sparing, intensive approach, we achieved favorable outcomes in TP53- wild-type MCL, including high-risk cases. We confirmed that sequential MRD assessment is a powerful prognostic tool in patients with MCL.

PET/CT Biomarkers Enable Risk Stratification of Patients with Relapsed/Refractory Diffuse Large B-cell Lymphoma Enrolled in the LOTIS-2 Clinical Trial.

PURPOSE: Significant progress has occurred in developing quantitative PET/CT biomarkers in diffuse large B-cell lymphoma (DLBCL). Total metabolic tumor volume (MTV) is the most extensively studied, enabling assessment of FDG-avid tumor burden associated with outcomes. However, prior studies evaluated the outcome of cytotoxic chemotherapy or chimeric antigen receptor T-cell therapy without data on recently approved FDA agents. Therefore, we aimed to assess the prognosis of PET/CT biomarkers in patients treated with loncastuximab tesirine. EXPERIMENTAL DESIGN: We centrally reviewed screening PET/CT scans of patients with relapsed/refractory DLBCL enrolled in the LOTIS-2 (NCT03589469) study. MTV was obtained by computing individual volumes using the SUV ≥4.0 threshold. Other PET/CT metrics, clinical factors, and the International Metabolic Prognostic Index (IMPI) were evaluated. Logistic regression was used to assess the association between biomarkers and treatment response. Cox regression was used to determine the effect of biomarkers on time-to-event outcomes. We estimated biomarker prediction as continuous and binary variables defined by cutoff points. RESULTS: Across 138 patients included in this study, MTV with a cutoff point of 96 mL was the biomarker associated with the highest predictive performance in univariable and multivariable models to predict failure to achieve complete metabolic response (OR, 5.42; P = 0.002), progression-free survival (HR, 2.68; P = 0.002), and overall survival (HR, 3.09; P < 0.0001). IMPI demonstrated an appropriate performance, however, not better than MTV alone. CONCLUSIONS: Pretreatment MTV demonstrated robust risk stratification, with those patients demonstrating high MTV achieving lower responses and survival to loncastuximab tesirine in relapsed/refractory DLBCL.

A randomized, double-blinded, placebo-controlled clinical trial of sterile filtered human amniotic fluid for treatment of COVID-19.

IMPORTANCE: Acellular human amniotic fluid (hAF) is an antimicrobial and anti-inflammatory fluid that has been used to treat various pro-inflammatory conditions. In a feasibility study, we have previously demonstrated that hAF could be safely administered to severely ill patients with coronavirus disease-19 (COVID-19). The impact of acellular hAF on markers of systemic inflammation and clinical outcomes during COVID-19 infection remain unknown. OBJECTIVE: To determine the safety and efficacy of acellular, sterile processed intravenously administered hAF on markers of systemic inflammation during COVID-19. DESIGN, SETTINGS AND PARTICIPANTS: This single-center Phase I/II randomized, placebo controlled clinical trial enrolled adult (age ≥ 18 years) patients hospitalized for respiratory symptoms of COVID-19, including hypoxemia, tachypnea or dyspnea. The study was powered for outcomes with an anticipated enrollment of 60 patients. From 09/28/2020 to 02/04/2022 we enrolled and randomized 47 (of an anticipated 60) patients hospitalized due to COVID-19. One patient withdrew consent after randomization but prior to treatment. Safety outcomes to 30 days were collected through hospital discharge and were complete by the end of screening on 6/30/2022. INTERVENTIONS: Intravenous administration of 10 cc sterile processed acellular hAF once daily for up to 5 days vs placebo. MAIN OUTCOME AND MEASURES: Blood biomarkers of inflammation, including C-Reactive protein (CRP), lactate dehydrogenase, D-dimer, and interleukin-6 (IL-6), as well as safety outcomes. RESULTS: Patients who were randomized to hAF (n = 23) were no more likely to have improvements in CRP from baseline to Day 6 than patients who were randomized to placebo (n = 24) hAF: -5.9 [IQR -8.2, -0.6] vs placebo: -5.9 [-9.4, -2.05]; p = 0.6077). There were no significant differences in safety outcomes or adverse events. Secondary measures of inflammation including lactate dehydrogenase, D-dimer and IL-6 were not statistically different from baseline to day 6. CONCLUSIONS AND RELEVANCE: In this randomized clinical trial involving hospitalized patients with COVID-19, the intravenous administration of 10 cc of hAF daily for 5 days did not result in statistically significant differences in either safety or markers of systemic inflammation compared to placebo, though we did not achieve our enrollment target of 60 patients. TRIAL REGISTRATION: This trial was registered at ClinicalTrials.gov as #NCT04497389 on 04/08/2020.

Utility of routine pulmonary function test after autologous hematopoietic cell transplantation in lymphoma.

This study aims to evaluate the predictive value of routine pulmonary function testing (PFT) at the 12-month mark post-autologous hematopoietic cell transplant (AHCT) in identifying clinically significant lung disease in lymphoma survivors. In 247 patients, 173 (70%) received BEAM (carmustine, etoposide, cytarabine, melphalan), and 49 (20%) received TBC (thiotepa, busulfan, cyclophosphamide) conditioning regimens. Abnormal baseline PFT was noted in 149 patients (60%). Thirty-four patients had a significant decline (reduction of >/= 20% in DLCO or FEV1 or FVC) in post-AHCT PFT, with the highest incidence in the CNS lymphoma group (39%). The incidence of clinically significant lung disease post-transplant was low at 2% and there was no association between abnormal pre- and 1-year post-transplant PFTs with the development of clinical lung disease. While this study illustrates the impact of treatment regimens on PFT changes, it did not demonstrate a predictive value of scheduled PFTs in identifying clinically significant post-AHCT lung disease.

Probability of Cavitation in a Custom Iron-Based Coupling Medium for Transcranial Magnetic Resonance-Guided Focused Ultrasound Procedures.

OBJECTIVE: A coupling bath of circulating, chilled, degassed water is essential to safe and precise acoustic transmittance during transcranial magnetic resonance-guided focused ultrasound (tMRgFUS) procedures, but the circulating water impairs the critical real-time magnetic resonance imaging (MRI). An iron-based coupling medium (IBCM) using iron oxide nanoparticles previously developed by our group increased the relaxivity of the coupling bath such that it appears to be invisible on MRI compared with degassed water. However, the nanoparticles also reduced the pressure threshold for cavitation. To address this concern for prefocal cavitation, our group recently developed an IBCM of electrosterically stabilized and aggregation-resistant poly(methacrylic acid)-coated iron oxide nanoparticles (PMAA-FeOX) with a similar capability to reduce the MR signal of degassed water. This study examines the effect of the PMAA-FeOX IBCM on the cavitation threshold. METHODS: Increasing concentrations of PMAA-FeOX nanoparticles in degassed, deionized water were placed at the focus of two different transducers to assess low and high duty-cycle pulsing parameters which are representative of two modes of focused ultrasound being investigated for tMRgFUS. Passive cavitation detection and high-speed optical imaging were used to measure cavitation threshold pressures. RESULTS: The mean cavitation threshold was determined in both cases to be indistinguishable from the degassed water control, between 6-8 MPa for high duty-cycle pulsing (CW) and between 25.5-26.5 MPa for very low duty-cycle pulsing. CONCLUSION: The findings of this study indicate that an IBCM of PMAA-FeOX nanoparticles is a possible solution to reducing MRI interference from the coupling bath without increasing the risk of prefocal cavitation.

Prognostic model using 18F-FDG PET radiomics predicts progression-free survival in relapsed/refractory Hodgkin lymphoma.

Investigating prognostic factors in patients with relapsed or primary refractory classical Hodgkin lymphoma (R/R cHL) is essential to optimize risk-adapted treatment strategies. We built a prognostic model using baseline quantitative 18F-fluorodeoxyglucose positron emission tomography (PET) radiomics features and clinical characteristics to predict the progression-free survival (PFS) among patients with R/R cHL treated with salvage chemotherapy followed by autologous stem cell transplantation. Metabolic tumor volume and several novel radiomics dissemination features, representing interlesional differences in distance, volume, and standard uptake value, were extracted from the baseline PET. Machine learning using backward selection and logistic regression were applied to develop and train the model on a total of 113 patients from 2 clinical trials. The model was validated on an independent external cohort of 69 patients. In addition, we validated 4 different PET segmentation methods to calculate radiomics features. We identified a subset of patients at high risk for progression with significant inferior 3-year PFS outcomes of 38.1% vs 88.4% for patients in the low-risk group in the training cohort (P < .001) and 38.5% vs 75.0% in the validation cohort (P = .015), respectively. The overall survival was also significantly better in the low-risk group (P = .022 and P < .001). We provide a formula to calculate a risk score for individual patients based on the model. In conclusion, we developed a prognostic model for PFS combining radiomics and clinical features in a large cohort of patients with R/R cHL. This model calculates a PET-based risk profile and can be applied to develop risk-stratified treatment strategies for patients with R/R cHL. These trials were registered at www.clinicaltrials.gov as #NCT02280993, #NCT00255723, and #NCT01508312.

Differential absolute plasma IL-6 concentrations between two immunoassay platforms in intensive care unit patients with COVID-19.

Objectives: Explore whether plasma IL-6 levels are similar across biomarker platforms and association with COVID-19 clinical outcomes. Methods: Plasma IL-6 concentrations were measured on 191 COVID-19 patients using the Roche Elecsys IL-6 assay and the Meso Scale Discovery assay. Results: Correlation of IL-6 levels between platforms was high (r = 0.87; 95% CI: 0.82-0.89); however, agreement was low (bias: 147.2 pg/ml; 95% limits of agreement: -489.5-783.9 pg/ml). The optimal IL-6 threshold to predict invasive mechanical ventilation and in-hospital mortality were 3- and 3.4-fold higher in Roche compared with Meso Scale Discovery, respectively. Conclusion: The absolute IL-6 threshold to predict outcomes was consistently higher using the Roche platform, and IL-6 thresholds to inform prognosis vary based on the biomarker platform.

A Case Report of Triple Organ Transplantation From a Donor After Circulatory Death Using Thoraco-Abdominal Normothermic Regional Perfusion.

Organ transplantation with donation after circulatory death can potentially increase the donor pool. Here, we report the rare case of triple-organ (heart/liver/kidney) transplantation from a donor after circulatory death using thoraco-abdominal normothermic regional perfusion. The recipient was a 61-year-old man with end-stage heart failure, liver failure, and kidney failure secondary to arrhythmogenic right ventricular dysplasia. He received a heart/liver/kidney transplantation from a donor after circulatory death. The course was complicated with primary graft dysfunction of the heart that resolved on postoperative day 3. The patient was discharged on postoperative day 39. He has no evidence for rejection on heart biopsy, and all 3 organs exhibit stable function. The use of donation after cardiac death donors greatly increases the donor pool and should be considered for patients requiring multiorgan transplantation. The use of thoraco-abdominal normothermic reperfusion is not only a feasible method for multiorgan procurement but also provides enhanced protection for all transplanted organs.

Quantitative PET-based biomarkers in lymphoma: getting ready for primetime.

The use of functional quantitative biomarkers extracted from routine PET-CT scans to characterize clinical responses in patients with lymphoma is gaining increased attention, and these biomarkers can outperform established clinical risk factors. Total metabolic tumour volume enables individualized estimation of survival outcomes in patients with lymphoma and has shown the potential to predict response to therapy suitable for  risk-adapted treatment approaches in clinical trials. The deployment of machine learning tools in molecular imaging research can assist in recognizing complex patterns and, with image classification, in tumour identification and segmentation of data from PET-CT scans. Initial studies using fully automated approaches to calculate metabolic tumour volume and other PET-based biomarkers have demonstrated appropriate correlation with calculations from experts, warranting further testing in large-scale studies. The extraction of computer-based quantitative tumour characterization through radiomics can provide a comprehensive view of phenotypic heterogeneity that better captures the molecular and functional features of the disease. Additionally, radiomics can be integrated with genomic data to provide more accurate prognostic information. Further improvements in PET-based biomarkers are imminent, although their incorporation into clinical decision-making currently has methodological shortcomings that need to be addressed with confirmatory prospective validation in selected patient populations. In this Review, we discuss the current knowledge, challenges and opportunities in the integration of quantitative PET-based biomarkers in clinical trials and the routine management of patients with lymphoma.

Biomarker Signatures of Severe Acute Kidney Injury in a Critically Ill Cohort of COVID-19 and Non-COVID-19 Acute Respiratory Illness.

Kidney and lung injury are closely inter-related during acute respiratory illness, but the molecular risk factors that these organ injuries share are not well defined. OBJECTIVES: We identified plasma biomarkers associated with severe acute kidney injury (AKI) during acute respiratory illness, and compared them to biomarkers associated with severe acute respiratory failure (ARF). DESIGN SETTINGS AND PARTICIPANTS: Prospective observational cohort study enrolling March 2020 through May 2021, at three hospitals in a large academic health system. We analyzed 301 patients admitted to an ICU with acute respiratory illness. MAIN OUTCOMES AND MEASURES: Outcomes were ascertained between ICU admission and day 14, and included: 1) severe AKI, defined as doubling of serum creatinine or new dialysis and 2) severe ARF, which included new or persistent need for high-flow oxygen or mechanical ventilation. We measured biomarkers of immune response and endothelial function, pathways related to adverse kidney and lung outcomes, in plasma collected within 24 hours of ICU admission. Severe AKI occurred in 48 (16%), severe ARF occurred in 147 (49%), and 40 (13%) patients experienced both. Two-fold higher concentrations of soluble tumor necrosis factor receptor-1 (sTNFR-1) (adjusted relative risk [aRR], 1.56; 95% CI, 1.24-1.96) and soluble triggering receptor on myeloid cells-1 (sTREM-1) (aRR, 1.85; 95% CI, 1.42-2.41), biomarkers of innate immune activation, were associated with higher risk for severe AKI after adjustment for age, sex, COVID-19, and Acute Physiology and Chronic Health Evaluation-III. These biomarkers were not significantly associated with severe ARF. Soluble programmed cell death receptor-1 (sPDL-1), a checkpoint pathway molecule, as well as soluble intercellular adhesion molecule-1 (sICAM-1) and soluble vascular adhesion molecule-1 (sVCAM-1), molecules involved with endothelial-vascular leukocyte adhesion, were associated with both severe AKI and ARF. CONCLUSIONS AND RELEVANCE: sTNFR-1 and sTREM-1 were linked strongly to severe AKI during respiratory illness, while sPDL-1, sICAM-1 and sVCAM-1 were associated with both severe AKI and ARF. These biomarker signatures may shed light on pathophysiology of lung-kidney interactions, and inform precision medicine strategies for identifying patients at high risk for these organ injuries.

Five-year follow-up of KEYNOTE-087: pembrolizumab monotherapy for relapsed/refractory classical Hodgkin lymphoma.

Previous analyses of the phase 2 KEYNOTE-087 (NCT02453594) trial of pembrolizumab monotherapy demonstrated effective antitumor activity with acceptable safety in patients with relapsed or refractory (R/R) classical Hodgkin lymphoma (cHL). However, long-term response durability and outcome of patients who receive a second course after treatment discontinuation after complete response (CR) remain of clinical interest. We present KEYNOTE-087 data after >5 years of median follow-up. Patients with R/R cHL and progressive disease (PD) after autologous stem cell transplantation (ASCT) and brentuximab vedotin (BV; cohort 1), salvage chemotherapy and BV without ASCT (cohort 2), or ASCT without subsequent BV (cohort 3), received pembrolizumab for ≤2 years. Patients in CR who discontinued treatment and subsequently experienced PD were eligible for second-course pembrolizumab. Primary end points were the objective response rate (ORR) using blinded central review and safety. The median follow-up was 63.7 months. ORR was 71.4% (95% confidence interval [CI], 64.8-77.4; CR, 27.6%; partial response, 43.8%). Median duration of response (DOR) was 16.6 months; median progression-free survival was 13.7 months. A quarter of responders, including half of complete responders, maintained a response for ≥4 years. Median overall survival was not achieved. Among 20 patients receiving second-course pembrolizumab, ORR for 19 evaluable patients was 73.7% (95% CI, 48.8-90.8); median DOR was 15.2 months. Any-grade treatment-related adverse events occurred in 72.9% of patients and grade 3 or 4 adverse events occurred in 12.9% of patients; no treatment-related deaths occurred. Single-agent pembrolizumab can induce durable responses, particularly in patients achieving CR. Second-course pembrolizumab frequently reinduced sustained responses after relapse from initial CR.

Antitachycardia pacing at the His bundle is safer than conventional right ventricular antitachycardia pacing in a canine myocardial ischemic injury model.

INTRODUCTION: Antitachycardia pacing (ATP) is used to terminate ventricular tachycardia (VT) by delivering rapid, low energy pacing to the right ventricle (RV). Unfortunately, ATP is not effective against all VT episodes and can result in adverse outcomes, such as VT acceleration and degeneration into ventricular fibrillation (VF). Improving ATP is therefore desirable. Our objective was to compare the efficacy and safety of ATP delivered at the His bundle to traditional ATP. METHODS: Six dogs were anesthetized and pacing leads were implanted in the RV and His bundle. The left anterior descending artery was occluded for 2 h to create an ischemic injury. In a study 4-7 days later, a 128-electrode sock was placed snugly around the ventricles and VT was induced using rapid pacing. ATP was delivered from either the His bundle or RV lead, then attempted at the other location if unsuccessful. Success rates and instances of VT acceleration and degeneration into VF were calculated. RESULTS: We induced 83 runs of VT and attempted ATP 128 times. RV ATP was successful in 36% of attempts; His ATP was successful in 38% of attempts. RV ATP resulted in significantly more adverse outcomes. RV and His ATP induced VT acceleration in 9% and 3% of trains, respectively, and induced degeneration into VF in 5% and 1% of trains, respectively. CONCLUSION: His bundle ATP is safer, but not significantly more effective, than RV ATP.

Predicting lymph node metastasis from primary tumor histology and clinicopathologic factors in colorectal cancer using deep learning.

BACKGROUND: Presence of lymph node metastasis (LNM) influences prognosis and clinical decision-making in colorectal cancer. However, detection of LNM is variable and depends on a number of external factors. Deep learning has shown success in computational pathology, but has struggled to boost performance when combined with known predictors. METHODS: Machine-learned features are created by clustering deep learning embeddings of small patches of tumor in colorectal cancer via k-means, and then selecting the top clusters that add predictive value to a logistic regression model when combined with known baseline clinicopathological variables. We then analyze performance of logistic regression models trained with and without these machine-learned features in combination with the baseline variables. RESULTS: The machine-learned extracted features provide independent signal for the presence of LNM (AUROC: 0.638, 95% CI: [0.590, 0.683]). Furthermore, the machine-learned features add predictive value to the set of 6 clinicopathologic variables in an external validation set (likelihood ratio test, p < 0.00032; AUROC: 0.740, 95% CI: [0.701, 0.780]). A model incorporating these features can also further risk-stratify patients with and without identified metastasis (p < 0.001 for both stage II and stage III). CONCLUSION: This work demonstrates an effective approach to combine deep learning with established clinicopathologic factors in order to identify independently informative features associated with LNM. Further work building on these specific results may have important impact in prognostication and therapeutic decision making for LNM. Additionally, this general computational approach may prove useful in other contexts.

When colorectal cancers spread to the lymph nodes, it can indicate a poorer prognosis. However, detecting lymph node metastasis (spread) can be difficult and depends on a number of factors such as how samples are taken and processed. Here, we show that machine learning, which involves computer software learning from patterns in data, can predict lymph node metastasis in patients with colorectal cancer from the microscopic appearance of their primary tumor and the clinical characteristics of the patients. We also show that the same approach can predict patient survival. With further work, our approach may help clinicians to inform patients about their prognosis and decide on appropriate treatments.