Rethinking the consultation paradigm: Validity evidence for a new framework, a multimethods study.

BACKGROUND: In-hospital consultation is essential for patient care. We previously proposed a framework of seven specific consultation types to classify consult requests to improve communication, workflow, and provider satisfaction. METHODS: This multimethods study's aim was to evaluate the applicability of the consult classification framework to real internal medicine (IM) consults. We sought validity evidence using Kane's validity model with focus groups and classifying consult requests from five IM specialties. Participants attended five 1 h semi-structured focus groups that were recorded, transcribed, and coded for thematic saturation. For each specialty, three specialists and three hospitalists categorized 100 (total 500) random anonymized consult requests. The primary outcome was concordance in the classification of consult requests, defined as the sum of partial concordance and perfect concordance, where respectively 4-5/6 and 6/6 participants classified a consult in the same category. We used χ2 tests to compare concordance rates across specialties and between specialists and hospitalists. RESULTS: Five major themes were identified in the qualitative analysis of the focus groups: (1) consult question, (2) interpersonal interactions, (3) value, (4) miscommunication, (5) consult framework application, barriers, and iterative development. In the quantitative analysis, the overall concordance rate was 88.8% (95% confidence interval [CI]: 85.7-91.4), and perfect concordance was 46.6% (95% CI: 42.2-51.1). Concordance differed significantly between hospitalists and specialists overall (p = .01), with a higher proportion of hospitalists having perfect concordance compared to specialists (67.2% vs. 57.8%, p = .002). CONCLUSIONS: The consult classification framework was found to be applicable to consults from five different IM specialties, and could improve communication and education.

A methodological review of the high-dimensional propensity score in comparative-effectiveness and safety-of-interventions research finds incomplete reporting relative to algorithm development and robustness.

OBJECTIVES: The use of secondary databases has become popular for evaluating the effectiveness and safety of interventions in real-life settings. However, the absence of important confounders in these databases is challenging. To address this issue, the high-dimensional propensity score (hdPS) algorithm was developed in 2009. This algorithm uses proxy variables for mitigating confounding by combining information available across several healthcare dimensions. This study assessed the methodology and reporting of the hdPS in comparative effectiveness and safety research. STUDY DESIGN AND SETTING: In this methodological review, we searched PubMed and Google Scholar from July 2009 to May 2022 for studies that used the hdPS for evaluating the effectiveness or safety of healthcare interventions. Two reviewers independently extracted study characteristics and assessed how the hdPS was applied and reported. Risk of bias was evaluated with the Rrisk Of Bias In Non-randomised Studies - of Interventions (ROBINS-I) tool. RESULTS: In total, 136 studies met the inclusion criteria; the median publication year was 2018 (Q1-Q3 2016-2020). The studies included 192 datasets, mostly North American databases (n = 132, 69%). The hdPS was used in primary analysis in 120 studies (88%). Dimensions were defined in 101 studies (74%), with a median of 5 (Q1-Q3 4-6) dimensions included. A median of 500 (Q1-Q3 200-500) empirically identified covariates were selected. Regarding hdPS reporting, only 11 studies (8%) reported all recommended items. Most studies (n = 81, 60%) had a moderate overall risk of bias. CONCLUSION: There is room for improvement in the reporting of hdPS studies, especially regarding the transparency of methodological choices that underpin the construction of the hdPS.

Who Is Teaching Residents in the Intensive Care Unit? Perceptions of Interprofessional Teaching at an Academic Medical Center.

Background: Teamwork is essential for high-quality care in the intensive care unit (ICU). Interprofessional education has been widely endorsed as a way of promoting collaborative practice. Interprofessional providers (IPPs), including nurses, pharmacists, and respiratory therapists (RTs), routinely participate in multidisciplinary rounds in the ICU, but their role in teaching residents at academic medical centers has yet to be characterized. Objective: To characterize perceptions of interprofessional teaching during and outside of rounds in the ICU. Methods: The authors conducted a cross-sectional survey of critical care physicians, internal medicine residents, nurses, pharmacists, and RTs across three ICUs at a tertiary academic medical center from September 2019 to March 2020. The frequency of different types of rounds contributions was rated on a Likert scale. Means and medians were compared across groups. Results: A total of 221 of 285 participants completed the survey (78% response rate). All IPPs described that they report data, provide clinical observations, and make recommendations frequently during ICU rounds, but teaching occurred infrequently (mean values, nurses = 2.9; pharmacists = 3.5; RTs = 3.7; 1 = not at all; 5 = always). Nurses were least likely to report teaching (P = 0.0017). From residents' and attendings' perspectives, pharmacists taught most frequently (mean values, 3.7 and 3.4, respectively). RTs self-report of teaching was higher than physicians' reports of RT teaching (P < 0.0001). Outside of rounds, residents reported a low frequency of teaching by nurses and RTs (means, nurses = 3.1; RTs = 3.1), but they reported a high rate of teaching by pharmacists (mean, 4.4). Conclusion: Nonphysician IPPs routinely participate in ICU rounds but teach medical trainees infrequently. Physicians' perception of IPP teaching frequency was generally lower than self-reports by IPPs. Exploring modifiers of interprofessional teaching may enhance education and collaboration.

"A Lot to Offer": Nurses as Educators for Medical Residents in an Academic Medical Center Intensive Care Unit.

INTRODUCTION: The role of fully trained interprofessional clinicians in educating residents has not been rigorously explored. The intensive care unit (ICU), where multiprofessional teamwork is essential to patient care, represents an ideal training environment in which to study this role. This study aimed to describe the practices, perceptions, and attitudes of ICU nurses regarding teaching medical residents and to identify potential targets to facilitate nurse teaching. METHODS: Using a concurrent mixed-methods approach, we administered surveys and focus groups to ICU nurses from September to November 2019 at a single, urban, tertiary, academic medical center. Survey data were analyzed with descriptive and comparative statistics. Focus group data were analyzed using the Framework method of content analysis. RESULTS: Of nurses surveyed, 75 of 96 (78%) responded. Nurses generally held positive attitudes about teaching residents, describing it as both important (52%, 36/69) and enjoyable (64%, 44/69). Nurses reported confidence in both clinical knowledge base (80%, 55/69) and teaching skills (71%, 49/69), but identified time, uncertainty about teaching topics, and trainee receptiveness as potential barriers. Ten nurses participated in focus groups. Qualitative analysis revealed three major themes: nurse-specific factors that impact teaching, the teaching environment, and facilitators of teaching. DISCUSSION: ICU nurses carry positive attitudes about teaching residents, particularly when facilitated by the attending, but this enthusiasm can be attenuated by the learning environment, unknown learner needs, and trainee attitudes. Identified facilitators of nurse teaching, including resident presence at the bedside and structured opportunities for teaching, represent potential targets for interventions to promote interprofessional teaching.

Survival and health economic outcomes in heart failure diagnosed at hospital admission versus community settings: a propensity-matched analysis.

BACKGROUND AND AIMS: Most patients with heart failure (HF) are diagnosed following a hospital admission. The clinical and health economic impacts of index HF diagnosis made on admission to hospital versus community settings are not known. METHODS: We used the North West London Discover database to examine 34 208 patients receiving an index diagnosis of HF between January 2015 and December 2020. A propensity score-matched (PSM) cohort was identified to adjust for differences in socioeconomic status, cardiovascular risk and pre-diagnosis health resource utilisation cost. Outcomes were stratified by two pathways to index HF diagnosis: a 'hospital pathway' was defined by diagnosis following hospital admission; and a 'community pathway' by diagnosis via a general practitioner or outpatient services. The primary clinical and health economic endpoints were all-cause mortality and cost-consequence differential, respectively. RESULTS: The diagnosis of HF was via hospital pathway in 68% (23 273) of patients. The PSM cohort included 17 174 patients (8582 per group) and was matched across all selected confounders (p>0.05). The ratio of deaths per person-months at 24 months comparing community versus hospital diagnosis was 0.780 (95% CI 0.722 to 0.841, p<0.0001). By 72 months, the ratio of deaths was 0.960 (0.905 to 1.020, p=0.18). Diagnosis via hospital pathway incurred an overall extra longitudinal cost of £2485 per patient. CONCLUSIONS: Index diagnosis of HF through hospital admission continues to dominate and is associated with a significantly greater short-term risk of mortality and substantially increased long-term costs than if first diagnosed in the community. This study highlights the potential for community diagnosis-early, before symptoms necessitate hospitalisation-to improve both clinical and health economic outcomes.

The Case for Interprofessional Teaching in Graduate Medical Education.

Interprofessional education has been promoted as a strategy to dismantle professional silos and promote collaborative patient care. Citing this, medical educators have emphasized the widespread integration of interprofessional education into undergraduate medical education curricula. However, in the current residency training environment, little reinforcement exists for principles gleaned from interprofessional education, and little is known about the role that interprofessional providers have in resident education. In this perspective, we offer the concept and practice of interprofessional teaching to bolster the benefits of interprofessional education during residency training. Interprofessional teaching, relatively unexplored and potentially underutilized, may offer many of the same benefits of interprofessional education but is more readily adapted for the graduate medical education setting. The intensive care unit, characterized by a culture of multidisciplinary teamwork and complex patient care, is an ideal setting in which to use interprofessional teaching. Prior to enthusiastically implementing interprofessional teaching interventions, careful consideration should be paid to the setting, strategies, and impact on all key stakeholders.

Automatic Diagnosis Labeling of Cardiovascular MRI by Using Semisupervised Natural Language Processing of Text Reports.

PURPOSE: To assess whether the semisupervised natural language processing (NLP) of text from clinical radiology reports could provide useful automated diagnosis categorization for ground truth labeling to overcome manual labeling bottlenecks in the machine learning pipeline. MATERIALS AND METHODS: In this retrospective study, 1503 text cardiac MRI reports from 2016 to 2019 were manually annotated for five diagnoses by clinicians: normal, dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy, myocardial infarction (MI), and myocarditis. A semisupervised method that uses bidirectional encoder representations from transformers (BERT) pretrained on 1.14 million scientific publications was fine-tuned by using the manually extracted labels, with a report dataset split into groups of 801 for training, 302 for validation, and 400 for testing. The model's performance was compared with two traditional NLP models: a rule-based model and a support vector machine (SVM) model. The models' F1 scores and receiver operating characteristic curves were used to analyze performance. RESULTS: After 15 epochs, the F1 scores on the test set of 400 reports were as follows: normal, 84%; DCM, 79%; hypertrophic cardiomyopathy, 86%; MI, 91%; and myocarditis, 86%. The pooled F1 score and area under the receiver operating curve were 86% and 0.96, respectively. On the same test set, the BERT model had a higher performance than the rule-based model (F1 score, 42%) and SVM model (F1 score, 82%). Diagnosis categories classified by using the BERT model performed the labeling of 1000 MR images in 0.2 second. CONCLUSION: The developed model used labels extracted from radiology reports to provide automated diagnosis categorization of MR images with a high level of performance.Keywords: Semisupervised Learning, Diagnosis/Classification/Application Domain, Named Entity Recognition, MRI Supplemental material is available for this article. © RSNA, 2021.

Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study.

BACKGROUND: Most patients who have heart failure with a reduced ejection fraction, when left ventricular ejection fraction (LVEF) is 40% or lower, are diagnosed in hospital. This is despite previous presentations to primary care with symptoms. We aimed to test an artificial intelligence (AI) algorithm applied to a single-lead ECG, recorded during ECG-enabled stethoscope examination, to validate a potential point-of-care screening tool for LVEF of 40% or lower. METHODS: We conducted an observational, prospective, multicentre study of a convolutional neural network (known as AI-ECG) that was previously validated for the detection of reduced LVEF using 12-lead ECG as input. We used AI-ECG retrained to interpret single-lead ECG input alone. Patients (aged ≥18 years) attending for transthoracic echocardiogram in London (UK) were recruited. All participants had 15 s of supine, single-lead ECG recorded at the four standard anatomical positions for cardiac auscultation, plus one handheld position, using an ECG-enabled stethoscope. Transthoracic echocardiogram-derived percentage LVEF was used as ground truth. The primary outcome was performance of AI-ECG at classifying reduced LVEF (LVEF ≤40%), measured using metrics including the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity, with two-sided 95% CIs. The primary outcome was reported for each position individually and with an optimal combination of AI-ECG outputs (interval range 0-1) from two positions using a rule-based approach and several classification models. This study is registered with ClinicalTrials.gov, NCT04601415. FINDINGS: Between Feb 6 and May 27, 2021, we recruited 1050 patients (mean age 62 years [SD 17·4], 535 [51%] male, 432 [41%] non-White). 945 (90%) had an ejection fraction of at least 40%, and 105 (10%) had an ejection fraction of 40% or lower. Across all positions, ECGs were most frequently of adequate quality for AI-ECG interpretation at the pulmonary position (979 [93·3%] of 1050). Quality was lowest for the aortic position (846 [80·6%]). AI-ECG performed best at the pulmonary valve position (p=0·02), with an AUROC of 0·85 (95% CI 0·81-0·89), sensitivity of 84·8% (76·2-91·3), and specificity of 69·5% (66·4-72·6). Diagnostic odds ratios did not differ by age, sex, or non-White ethnicity. Taking the optimal combination of two positions (pulmonary and handheld positions), the rule-based approach resulted in an AUROC of 0·85 (0·81-0·89), sensitivity of 82·7% (72·7-90·2), and specificity of 79·9% (77·0-82·6). Using AI-ECG outputs from these two positions, a weighted logistic regression with l2 regularisation resulted in an AUROC of 0·91 (0·88-0·95), sensitivity of 91·9% (78·1-98·3), and specificity of 80·2% (75·5-84·3). INTERPRETATION: A deep learning system applied to single-lead ECGs acquired during a routine examination with an ECG-enabled stethoscope can detect LVEF of 40% or lower. These findings highlight the potential for inexpensive, non-invasive, workflow-adapted, point-of-care screening, for earlier diagnosis and prognostically beneficial treatment. FUNDING: NHS Accelerated Access Collaborative, NHSX, and the National Institute for Health Research.

Lung Histopathology in Coronavirus Disease 2019 as Compared With Severe Acute Respiratory Sydrome and H1N1 Influenza: A Systematic Review.

BACKGROUND: Patients with severe coronavirus disease 2019 (COVID-19) have respiratory failure with hypoxemia and acute bilateral pulmonary infiltrates, consistent with ARDS. Respiratory failure in COVID-19 might represent a novel pathologic entity. RESEARCH QUESTION: How does the lung histopathology described in COVID-19 compare with the lung histopathology described in SARS and H1N1 influenza? STUDY DESIGN AND METHODS: We conducted a systematic review to characterize the lung histopathologic features of COVID-19 and compare them against findings of other recent viral pandemics, H1N1 influenza and SARS. We systematically searched MEDLINE and PubMed for studies published up to June 24, 2020, using search terms for COVID-19, H1N1 influenza, and SARS with keywords for pathology, biopsy, and autopsy. Using PRISMA-Individual Participant Data guidelines, our systematic review analysis included 26 articles representing 171 COVID-19 patients; 20 articles representing 287 H1N1 patients; and eight articles representing 64 SARS patients. RESULTS: In COVID-19, acute-phase diffuse alveolar damage (DAD) was reported in 88% of patients, which was similar to the proportion of cases with DAD in both H1N1 (90%) and SARS (98%). Pulmonary microthrombi were reported in 57% of COVID-19 and 58% of SARS patients, as compared with 24% of H1N1 influenza patients. INTERPRETATION: DAD, the histologic correlate of ARDS, is the predominant histopathologic pattern identified in lung pathology from patients with COVID-19, H1N1 influenza, and SARS. Microthrombi were reported more frequently in both patients with COVID-19 and SARS as compared with H1N1 influenza. Future work is needed to validate this histopathologic finding and, if confirmed, elucidate the mechanistic underpinnings and characterize any associations with clinically important outcomes.

Management of Sedation and Analgesia in Critically Ill Patients Receiving Long-Acting Naltrexone Therapy for Opioid Use Disorder.

The explosion of the opioid epidemic in the United States and across the world has been met with advances in pharmacologic therapy for the treatment of opioid use disorder. Long-acting naltrexone is a promising strategy, but its use has important implications for critical care, as it may interfere with or complicate sedation and analgesia. Currently, there are two available formulations of long-acting naltrexone, which are distinguished by different administration routes and distinct pharmacokinetics. The use of long-acting naltrexone may be identified through a variety of strategies (such as physical examination, laboratory testing, and medical record review), and is key to the safe provision of sedation and analgesia during critical illness. Perioperative experience caring for patients receiving long-acting naltrexone informs management in the intensive care unit. Important lessons include the use of multimodal analgesia strategies and anticipating patients' demonstrating variable sensitivity to opioids. For the critically ill patient, however, there are important distinctions to emphasize, including changes in drug metabolism and medication interactions. By compiling and incorporating the currently available literature, we provide critical care physicians with recommendations for the sedation and analgesia for critically ill patients receiving long-acting naltrexone therapy.

Treatment guidelines of metastatic colorectal cancer in older patients from the French Society of Geriatric Oncology (SoFOG).

BACKGROUND: Several guidelines dedicated to metastatic colorectal cancer (mCRC) are available. Since 2013 no recent guidelines are specifically dedicated to older patients and based on a systematic review. MATERIALS AND METHODS: A multidisciplinary Task Force with digestive oncologists, geriatricians and methodologists from the SoFOG was formed in 2016 to update recommendations on medical treatment of mCRC based on a systematic review of publications from 2000 to 2018. Search strategy has followed a standardized protocol from the formulation of clinical questions and definition of a search algorithm to the selection of complete articles for recommendations. RESULTS: The four selected key questions were: For which older patients with mCRC can we considered: (1) Any chemotherapy, (2) Mono or poly-chemotherapy, (3) Anti-angiogenic therapy, (4) Other targeted therapy. Main recommendations for older patients are: (1) Omission of chemotherapy should be discussed with a geriatrician for patients with severe comorbidities, advanced dementia, uncontrolled psychiatric disorder or severe loss of autonomy. (2) If tumor response is not the main aim, a mono-chemotherapy with 5-fluorouracil combined with bevacizumab is recommended as first-line. (3) For patients with symptoms related to metastases or with a planned metastasis ablation, a doublet chemotherapy combined with bevacizumab or anti-EGFR antibody in the context of a RAS wild type tumor is recommended as first-line. Preliminary data suggest that regorafenib may be used, in its registered indication, in patients under 80 with a performance status of 0 and no autonomy alterations and that trifluridine-tipiracil may be used with a tight supervising of hematological function.

A Retrospective Review of Angiotensin II Use in Adult Patients With Refractory Distributive Shock.

PURPOSE: Catecholamines are first-line vasopressors for hemodynamic support in distributive shock but are associated with adverse effects, which may be mitigated with noncatecholamine vasopressors. Angiotensin II (ATII) is a noncatecholamine vasopressor recently approved for the management of distributive shock, but limited data support its clinical utility. The purpose of this study was to describe our institution's usage of ATII including patient outcomes (eg, response to therapy, safety profile). MATERIALS AND METHODS: Patients who received ATII at our institution were included. Patient demographics, degree of concordance with institutional ATII use guidelines, safety profile of ATII, and response to therapy (1 and 3 hours after ATII initiation) were collected. RESULTS: A total of 16 patients received ATII for distributive shock. The median Sequential Organ Failure Assessment score at the time of ATII initiation was 16.5 (interquartile range: 15.8-20.0). Fourteen (87.5%) patients met institutional guidelines for ATII use; 10 (62.5%) and 8 (50.0%) patients met our definition for response at 1 and 3 hours, respectively. No patients developed thrombotic or infectious complications after receiving ATII. CONCLUSIONS: In this cohort, ATII appears to be well tolerated in patients with a high predicted mortality. Future studies evaluating the clinical efficacy of ATII are needed to determine its role in the management of distributive shock.

The Fast Literature Assessment and Review (FLARE) Initiative. A Collaborative Effort for Timely Literature Appraisal during the Coronavirus Disease Pandemic.

The emergence and worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused major disruptions to the healthcare system and medical education. In response, the scientific community has been acquiring, releasing, and publishing data at a remarkable pace. At the same time, medical practitioners are taxed with greater professional duties than ever before, making it challenging to stay current with the influx of medical literature.To address the above mismatch between data release and provider capacity and to support our colleagues, physicians at the Massachusetts General Hospital have engaged in an electronic collaborative effort focused on rapid literature appraisal and dissemination regarding SARS-CoV-2 with a focus on critical care.Members of the Division of Pulmonary and Critical Care, the Division of Cardiology, and the Department of Medicine at Massachusetts General Hospital established the Fast Literature Assessment and Review (FLARE) team. This group rapidly compiles, appraises, and synthesizes literature regarding SARS-CoV-2 as it pertains to critical care, relevant clinical questions, and anecdotal reports. Daily, FLARE produces and disseminates highly curated scientific reviews and opinion pieces, which are distributed to readers using an online newsletter platform.Interest in our work has escalated rapidly. FLARE was quickly shared with colleagues outside our division, and, in a short time, our audience has grown to include more than 4,000 readers across the globe.Creating a collaborative group with a variety of expertise represents a feasible and acceptable way of rapidly appraising, synthesizing, and communicating scientific evidence directly to frontline clinicians in this time of great need.

Severe pulmonary toxicity from immune checkpoint inhibitor treated successfully with intravenous immunoglobulin: Case report and review of the literature.

Immune checkpoint inhibitors are known to cause a variety of immune-related adverse events, including pneumonitis. When symptomatic, treatment typically consists of temporary or permanent cessation of the checkpoint inhibitor and several weeks of corticosteroid therapy. However, a subset of patients may suffer from severe pneumonitis, and the optimal treatment for this group is not known. Here we describe the case of a patient receiving pembrolizumab for non-small cell lung cancer who developed severe checkpoint inhibitor pneumonitis. After treatment with high-dose corticosteroids failed to produce a response, a course of intravenous immunoglobulin catalyzed rapid and durable improvement. In this review, we discuss the current evidence regarding the incidence and outcomes of severe checkpoint inhibitor pneumonitis and propose a role for intravenous immunoglobulin as a possible treatment strategy.