Abstract

Classification of persons with long COVID (LC) or post-COVID-19 condition must encompass the complexity and heterogeneity of the condition. Iterative refinement of the classification index for research is needed to incorporate newly available data as the field rapidly evolves.To update the 2023 research index for adults with LC using additional participant data from the Researching COVID to Enhance Recovery (RECOVER-Adult) study and an expanded symptom list based on input from patient communities.Prospective, observational cohort study including adults 18 years or older with or without known prior SARS-CoV-2 infection who were enrolled at 83 sites in the US and Puerto Rico. Included participants had at least 1 study visit taking place 4.5 months after first SARS-CoV-2 infection or later, and not within 30 days of a reinfection. The study visits took place between October 2021 and March 2024.SARS-CoV-2 infection.Presence of LC and participant-reported symptoms.A total of 13 647 participants (11 743 with known SARS-CoV-2 infection and 1904 without known prior SARS-CoV-2 infection; median age, 45 years [IQR, 34-69 years]; and 73% were female) were included. Using the least absolute shrinkage and selection operator analysis regression approach from the 2023 model, symptoms contributing to the updated 2024 index included postexertional malaise, fatigue, brain fog, dizziness, palpitations, change in smell or taste, thirst, chronic cough, chest pain, shortness of breath, and sleep apnea. For the 2024 LC research index, the optimal threshold to identify participants with highly symptomatic LC was a score of 11 or greater. The 2024 index classified 20% of participants with known prior SARS-CoV-2 infection and 4% of those without known prior SARS-CoV-2 infection as having likely LC (vs 21% and 5%, respectively, using the 2023 index) and 39% of participants with known prior SARS-CoV-2 infection as having possible LC, which is a new category for the 2024 model. Cluster analysis identified 5 LC subtypes that tracked quality-of-life measures.The 2024 LC research index for adults builds on the 2023 index with additional data and symptoms to help researchers classify symptomatic LC and its symptom subtypes. Continued future refinement of the index will be needed as the understanding of LC evolves.

View details for DOI 10.1001/jama.2024.24184

View details for PubMedID 39693079

View details for DOI 10.1182/blood-2023-181459

View details for Web of Science ID 001159740307053

Abstract

To evaluate the effects of physician familiarity with current evidence and guidelines on inferior vena cava (IVC) filter use and the availability of IVC filter tracking infrastructure on retrieval rates.Fourteen continuing medical education-approved in-hospital grand rounds covering evidence-based review of the literature on IVC filter efficacy, patient-centered outcomes, guidelines for IVC filter indications, and complications were performed across a large United States (US) health care region serving more than 3.5 million members. A computer-based IVC filter tracking system was deployed simultaneously. IVC filter use, rates of attempted retrieval, and fulfillment of guidelines for IVC filter indications were retrospectively evaluated at each facility for 12 months before intervention (n = 427) and for 12 months after intervention (n = 347).After education, IVC filter use decreased 18.7%, with a member enrollment-adjusted decrease of 22.2%, despite an increasing IVC filter use trend for 4 years. Reduction in IVC filter use at each facility strongly correlated with physician attendance at grand rounds (r = -0.69; P = .007). Rates of attempted retrieval increased from 38.9% to 54.0% (P = .0006), with similar rates of successful retrieval (82.3% before education and 85.8% after education on first attempt). Improvement in IVC filter retrieval attempts correlated with physician attendance at grand rounds (r = 0.51; P = .051). IVC filter dwell times at first retrieval attempt were similar (10.2 wk before and 10.8 wk after).Physician education dramatically reduced IVC filter use across a large US health care region, and represents a learning opportunity for physicians who request and place them. Education and a novel tracking system improved rates of retrieval for IVC filter devices.

View details for DOI 10.1016/j.jvir.2016.01.130

View details for PubMedID 27017122

View details for DOI 10.7759/cureus.9537

View details for Web of Science ID 000554830700009

View details for Web of Science ID 001053772002374

Abstract

Optimizing insulin therapy for patients with type 2 diabetes can be challenging given the need for frequent dose adjustments. Most patients receive suboptimal doses and do not achieve glycemic control.To examine whether a voice-based conversational artificial intelligence (AI) application can help patients with type 2 diabetes titrate basal insulin at home to achieve rapid glycemic control.In this randomized clinical trial conducted at 4 primary care clinics at an academic medical center from March 1, 2021, to December 31, 2022, 32 adults with type 2 diabetes requiring initiation or adjustment of once-daily basal insulin were followed up for 8 weeks. Statistical analysis was performed from January to February 2023.Participants were randomized in a 1:1 ratio to receive basal insulin management with a voice-based conversational AI application or standard of care.Primary outcomes were time to optimal insulin dose (number of days needed to achieve glycemic control), insulin adherence, and change in composite survey scores measuring diabetes-related emotional distress and attitudes toward health technology and medication adherence. Secondary outcomes were glycemic control and glycemic improvement. Analysis was performed on an intent-to-treat basis.The study population included 32 patients (mean [SD] age, 55.1 [12.7] years; 19 women [59.4%]). Participants in the voice-based conversational AI group more quickly achieved optimal insulin dosing compared with the standard of care group (median, 15 days [IQR, 6-27 days] vs >56 days [IQR, >29.5 to >56 days]; a significant difference in time-to-event curves; P = .006) and had better insulin adherence (mean [SD], 82.9% [20.6%] vs 50.2% [43.0%]; difference, 32.7% [95% CI, 8.0%-57.4%]; P = .01). Participants in the voice-based conversational AI group were also more likely than those in the standard of care group to achieve glycemic control (13 of 16 [81.3%; 95% CI, 53.7%-95.0%] vs 4 of 16 [25.0%; 95% CI, 8.3%-52.6%]; difference, 56.3% [95% CI, 21.4%-91.1%]; P = .005) and glycemic improvement, as measured by change in mean (SD) fasting blood glucose level (-45.9 [45.9] mg/dL [95% CI, -70.4 to -21.5 mg/dL] vs 23.0 [54.7] mg/dL [95% CI, -8.6 to 54.6 mg/dL]; difference, -68.9 mg/dL [95% CI, -107.1 to -30.7 mg/dL]; P = .001). There was a significant difference between the voice-based conversational AI group and the standard of care group in change in composite survey scores measuring diabetes-related emotional distress (-1.9 points vs 1.7 points; difference, -3.6 points [95% CI, -6.8 to -0.4 points]; P = .03).In this randomized clinical trial of a voice-based conversational AI application that provided autonomous basal insulin management for adults with type 2 diabetes, participants in the AI group had significantly improved time to optimal insulin dose, insulin adherence, glycemic control, and diabetes-related emotional distress compared with those in the standard of care group. These findings suggest that voice-based digital health solutions can be useful for medication titration.ClinicalTrials.gov Identifier: NCT05081011.

View details for DOI 10.1001/jamanetworkopen.2023.40232

View details for PubMedID 38039007

Abstract

Increasing use of EHRs has generated interest in the potential of computerized clinical decision support to improve treatment of sepsis. Electronic sepsis alerts have had mixed results due to poor test characteristics, the inability to detect sepsis in a timely fashion and the use of outside software limiting widespread adoption. We describe the development, evaluation and validation of an accurate and timely severe sepsis alert with the potential to impact sepsis management.To develop, evaluate, and validate an accurate and timely severe sepsis alert embedded in a commercial EHR.The sepsis alert was developed by identifying the most common severe sepsis criteria among a cohort of patients with ICD 9 codes indicating a diagnosis of sepsis. This alert requires criteria in three categories: indicators of a systemic inflammatory response, evidence of suspected infection from physician orders, and markers of organ dysfunction. Chart review was used to evaluate test performance and the ability to detect clinical time zero, the point in time when a patient develops severe sepsis.Two physicians reviewed 100 positive cases and 75 negative cases. Based on this review, sensitivity was 74.5%, specificity was 86.0%, the positive predictive value was 50.3%, and the negative predictive value was 94.7%. The most common source of end-organ dysfunction was MAP less than 70 mm/Hg (59%). The alert was triggered at clinical time zero in 41% of cases and within three hours in 53.6% of cases. 96% of alerts triggered before a manual nurse screen.We are the first to report the time between a sepsis alert and physician chart-review clinical time zero. Incorporating physician orders in the alert criteria improves specificity while maintaining sensitivity, which is important to reduce alert fatigue. By leveraging standard EHR functionality, this alert could be implemented by other healthcare systems.

View details for DOI 10.4338/ACI-2015-11-RA-0159

View details for PubMedID 27437061

View details for PubMedCentralID PMC4941860

Abstract

Patients hospitalized for COVID-19 frequently develop hypoxemia and acute respiratory distress syndrome (ARDS) after admission. In non-COVID-19 ARDS studies, admission to hospital wards with subsequent transfer to intensive care unit (ICU) is associated with worse outcomes. We hypothesized that initial admission to the ward may affect outcomes in patient with COVID-19 ARDS.This was a retrospective study of consecutive adults admitted for COVID-19 ARDS between March 2020 and March 2021 at Stanford Health Care. Mortality scores at hospital admission (Coronavirus Clinical Characterization Consortium Mortality Score [4C score]) and ICU admission (Simplified Acute Physiology Score III [SAPS-III]) were calculated, as well as ROX index for patients on high flow nasal oxygen. Patients were classified by emergency department (ED) disposition (ward-first vs. ICU-direct), and 28- and 60-day mortality and highest level of respiratory support within 1 day of ICU admission were compared. A second cohort (April 2021‒July 2022, n = 129) was phenotyped to validate mortality outcome.A total of 157 patients were included, 48% of whom were first admitted to the ward (n = 75). Ward-first patients had more comorbidities, including lung disease. Ward-first patients had lower 4C and similar SAPS-III score, yet increased mortality at 28 days (32% vs. 17%, hazard ratio [HR] 2.0, 95% confidence interval [95% CI] 1.0‒3.7, p = 0.039) and 60 days (39% vs. 23%, HR 1.83, 95% CI 1.04‒3.22, p = 0.037) compared to ICU-direct patients. More ward-first patients escalated to mechanical ventilation on day 1 of ICU admission (36% vs. 14%, p = 0.002) despite similar ROX index. Ward-first patients who upgraded to ICU within 48 h of ED presentation had the highest mortality. Mortality findings were replicated in a sensitivity analysis.Despite similar baseline risk scores, ward-first patients with COVID-19 ARDS had increased mortality and escalation to mechanical ventilation compared to ICU-direct patients. Ward-first patients requiring ICU upgrade within 48 h were at highest risk, highlighting a need for improved identification of this group at ED admission.

View details for DOI 10.1002/emp2.13192

View details for PubMedID 38887225

View details for PubMedCentralID PMC11180691

View details for DOI 10.4236/ce.2022.134082

Abstract

Since the nationally televised cardiac arrest of American National Football League player Damar Hamlin in January 2023, commotio cordis has come to the forefront of public attention. Commotio cordis is defined as sudden cardiac arrest due to direct trauma to the precordium resulting in ventricular fibrillation or ventricular tachycardia. While the precise incidence of commotio cordis is not known due to a lack of standardized, mandated reporting, it is the third most common cause of sudden cardiac death in young athletes, with more than 75% of cases occurring during organized and recreational sporting events. Given that survival is closely tied to how quickly victims receive cardiopulmonary resuscitation and defibrillation, it is crucial to raise awareness of commotio cordis so that athletic trainers, coaches, team physicians, and emergency medical personnel can rapidly diagnose and treat this often-fatal condition. Broader distribution of automated external defibrillators in sporting facilities as well as increased presence of medical personnel during sporting events would also likely lead to higher survival rates.

View details for DOI 10.1007/s40279-023-01873-6

View details for Web of Science ID 001020188900002

View details for PubMedID 37382827

View details for PubMedCentralID PMC10356869

Abstract

The goal of this report was to find the frequency of synchronous airway lesions (SAL) identified during microdirect laryngoscopy and bronchoscopy (MDLB) that influenced treatment decisions beyond the information provided by drug induced sleep endoscopy (DISE) alone in children with obstructive sleep apnea (OSA) at a tertiary care pediatric hospital.This was a retrospective chart review of all pediatric patients who underwent drug induced sleep endoscopy in conjunction with direct laryngoscopy and bronchoscopy as part of a comprehensive airway evaluation for obstructive sleep apnea at a tertiary care pediatric hospital.Three hundred thirty-five patients with obstructive sleep apnea were evaluated with both sleep endoscopy and direct laryngoscopy with bronchoscopy. Five percent of patients had SAL identified on MDLB contributing to airway obstruction. Three patients (0.9%) who underwent MDLB for OSA required surgical correction of SAL that was identified.In a limited subset of patients, direct laryngoscopy with bronchoscopy provides additional positive findings to aid with treatment planning for obstructive sleep apnea.

View details for PubMedID 29859583

View details for DOI 10.4300/JGME-D-24-00067.1

View details for PubMedID 39677901

View details for PubMedCentralID PMC11644571

Abstract

SARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or other health effects after the acute phase of infection; termed post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are ill-defined. The objectives of the Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC in Adults (RECOVER-Adult) are to: (1) characterize PASC prevalence; (2) characterize the symptoms, organ dysfunction, natural history, and distinct phenotypes of PASC; (3) identify demographic, social and clinical risk factors for PASC onset and recovery; and (4) define the biological mechanisms underlying PASC pathogenesis.RECOVER-Adult is a combined prospective/retrospective cohort currently planned to enroll 14,880 adults aged ≥18 years. Eligible participants either must meet WHO criteria for suspected, probable, or confirmed infection; or must have evidence of no prior infection. Recruitment occurs at 86 sites in 33 U.S. states, Washington, DC and Puerto Rico, via facility- and community-based outreach. Participants complete quarterly questionnaires about symptoms, social determinants, vaccination status, and interim SARS-CoV-2 infections. In addition, participants contribute biospecimens and undergo physical and laboratory examinations at approximately 0, 90 and 180 days from infection or negative test date, and yearly thereafter. Some participants undergo additional testing based on specific criteria or random sampling. Patient representatives provide input on all study processes. The primary study outcome is onset of PASC, measured by signs and symptoms. A paradigm for identifying PASC cases will be defined and updated using supervised and unsupervised learning approaches with cross-validation. Logistic regression and proportional hazards regression will be conducted to investigate associations between risk factors, onset, and resolution of PASC symptoms.RECOVER-Adult is the first national, prospective, longitudinal cohort of PASC among US adults. Results of this study are intended to inform public health, spur clinical trials, and expand treatment options.NCT05172024.

View details for DOI 10.1371/journal.pone.0286297

View details for PubMedID 37352211

View details for PubMedCentralID PMC10289397

Abstract

Aldosterone sensitivity is defined as an outcome variable for a given circulating level of aldosterone. In basic and translational studies, this has been measured in differential tissue responses, e.g. lower urine sodium and higher urine potassium, as an index of renal response; and in clinical studies has been measured in differential blood pressure. This concept of aldosterone sensitivity disrupts the conventional wisdom of the renin-angiotensin-aldosterone system and has the potential to uncover novel mechanisms of hypertension. We review basic and translational science studies that uncovered differential renal responses to aldosterone and connect this earlier work to more recent observational and randomized trials that have demonstrated differential blood pressure for a given level of aldosterone in healthy and hypertensive subjects. Black race and age are associated with higher aldosterone sensitivity and blood pressure. We also discuss gaps in the field and how future basic and clinical studies can inform mechanisms of differential sensitivity.

View details for DOI 10.1152/ajprenal.00415.2020

View details for PubMedID 33491565

Abstract

Brief hospital course (BHC) summaries are clinical documents that summarize a patient's hospital stay. While large language models (LLMs) depict remarkable capabilities in automating real-world tasks, their capabilities for healthcare applications such as synthesizing BHCs from clinical notes have not been shown. We introduce a novel preprocessed dataset, the MIMIC-IV-BHC, encapsulating clinical note and BHC pairs to adapt LLMs for BHC synthesis. Furthermore, we introduce a benchmark of the summarization performance of 2 general-purpose LLMs and 3 healthcare-adapted LLMs.Using clinical notes as input, we apply prompting-based (using in-context learning) and fine-tuning-based adaptation strategies to 3 open-source LLMs (Clinical-T5-Large, Llama2-13B, and FLAN-UL2) and 2 proprietary LLMs (Generative Pre-trained Transformer [GPT]-3.5 and GPT-4). We evaluate these LLMs across multiple context-length inputs using natural language similarity metrics. We further conduct a clinical study with 5 clinicians, comparing clinician-written and LLM-generated BHCs across 30 samples, focusing on their potential to enhance clinical decision-making through improved summary quality. We compare reader preferences for the original and LLM-generated summary using Wilcoxon signed-rank tests. We further request optional qualitative feedback from clinicians to gain deeper insights into their preferences, and we present the frequency of common themes arising from these comments.The Llama2-13B fine-tuned LLM outperforms other domain-adapted models given quantitative evaluation metrics of Bilingual Evaluation Understudy (BLEU) and Bidirectional Encoder Representations from Transformers (BERT)-Score. GPT-4 with in-context learning shows more robustness to increasing context lengths of clinical note inputs than fine-tuned Llama2-13B. Despite comparable quantitative metrics, the reader study depicts a significant preference for summaries generated by GPT-4 with in-context learning compared to both Llama2-13B fine-tuned summaries and the original summaries (P<.001), highlighting the need for qualitative clinical evaluation.We release a foundational clinically relevant dataset, the MIMIC-IV-BHC, and present an open-source benchmark of LLM performance in BHC synthesis from clinical notes. We observe high-quality summarization performance for both in-context proprietary and fine-tuned open-source LLMs using both quantitative metrics and a qualitative clinical reader study. Our research effectively integrates elements from the data assimilation pipeline: our methods use (1) clinical data sources to integrate, (2) data translation, and (3) knowledge creation, while our evaluation strategy paves the way for (4) deployment.

View details for DOI 10.1093/jamia/ocae312

View details for PubMedID 39786555

Abstract

Mechanical circulatory support (MCS) has made rapid progress over the last 3 decades. This was driven by the need to develop acute and chronic circulatory support as well as by the limited organ availability for heart transplantation. The growth of MCS was also driven by the use of extracorporeal membrane oxygenation (ECMO) after the worldwide H1N1 influenza outbreak of 2009. The majority of mechanical pumps (ECMO and left ventricular assist devices) are currently based on continuous flow pump design. It is interesting to note that in the current era, we have reverted from the mammalian pulsatile heart back to the continuous flow pumps seen in our simple multicellular ancestors. This review will highlight key physiological concepts of the assisted circulation from its effects on cardiac dynamic to principles of cardiopulmonary fitness. We will also examine the physiological principles of the ECMO-assisted circulation, anticoagulation, and the haemocompatibility challenges that arise when the blood is exposed to a foreign mechanical circuit. Finally, we conclude with a perspective on smart design for future development of devices used for MCS.

View details for DOI 10.1016/j.cjca.2019.11.002

View details for PubMedID 32036862

Abstract

BACKGROUND: Time spent awaiting discharge after the acute need for hospitalization has resolved is an important potential contributor to hospital length of stay (LOS).OBJECTIVE: To measure the prevalence, impact, and context of patients who remain hospitalized for prolonged periods after completion of acute care needs.DESIGN, SETTING, AND PARTICIPANTS: We conducted a cross-sectional "point-in-time" survey at each of 15 academic US hospitals using a structured data collection tool with on-service acute care medicine attending physicians in fall 2022.MAIN OUTCOMES AND MEASURES: Primary outcomes were number and percentage of patients considered "medically ready for discharge" with emphasis on those who had experienced a "major barrier to discharge" (medically ready for discharge for ≥1 week). Estimated LOS attributable to major discharge barriers, contributory discharge needs, and associated hospital characteristics were measured.RESULTS: Of 1928 patients sampled, 35.0% (n=674) were medically ready for discharge including 9.8% (n=189) with major discharge barriers. Many patients with major discharge barriers (44.4%; 84/189) had spent a month or longer medically ready for discharge and commonly (84.1%; 159/189) required some form of skilled therapy or daily living support services for discharge. Higher proportions of patients experiencing major discharge barriers were found in public versus private, nonprofit hospitals (12.0% vs. 7.2%; p=.001) and county versus noncounty hospitals (14.5% vs. 8.8%; p=.002).CONCLUSIONS: Patients experience major discharge barriers in many US hospitals and spend prolonged time awaiting discharge, often for support needs that may be outside of clinician control.

View details for DOI 10.1002/jhm.13184

View details for PubMedID 37553979

View details for DOI 10.1016/j.jaip.2024.11.016

View details for PubMedID 39615749

Abstract

Exposure to the breadth of healthcare opportunities is crucial to high-school and college students considering a career in medicine. Most programs revolve around research or subspecialties, limiting exposure to the richness within medicine.We conducted a program evaluation of the Stanford Clinical Summer Internship (CSI) 2-week program, to understand learner viewpoints around CSI program utility, and to assess long term impact. We assess viewpoints by learner level (high school versus college) and participation mode (in-person versus virtual).In 2016 we launched a two-week premedical internship, incorporating AAMC core competencies. In 2022 and 2023, we surveyed past participants, collecting demographic data and evaluating/comparing CSI's impact on educational and career paths, future preferences in healthcare careers, and influential factors of matriculation for high-school and college participants.Of 411 past participants, 42% responded (n = 173). We found minimal significant differences between high school and college students. The primary reason for joining was exploring a career in health professions. Notably, 82% acknowledged Stanford-CSI broadened their medical perspectives, 79% gained clarity on healthcare professionals' daily life, 79% heightened their interest in healthcare careers, 71% enhanced their resumes, and 72% learned valuable clinical skills. In-person participants reported developing more friendships (agree/strongly agree: 60% vs 35%, unpaired t-test: p = 0.01), while virtual participants reported having more interest in research careers (40% vs 68%, p = 0.01). Amongst high school matriculants (n = 133), 46% are now in college and 4% in medical or nursing school. Amongst collegiate matriculants (n = 40), 89% have graduated and 11% are now in graduate or medical school. All respondents believed Stanford-CSI was a worthwhile investment of time and resources, with nearly all reporting subsequent increased interest in medicine.Stanford-CSI's summer internship gives premedical students real-world medical profession exposure and fosters meaningful connections. Our findings and teaching framework can guide similar program developments, supporting future medical education initiatives.

View details for DOI 10.1186/s12909-024-06301-5

View details for PubMedID 39609765

Abstract

The increasing linguistic and cultural diversity in the United States underscores the necessity of enhancing healthcare professionals' cross-cultural communication skills. This study focuses on incorporating interpreter and limited-English proficiency (LEP) patient training into the medical and physician assistant student curriculum. This aims to improve equitable care provision, addressing the vulnerability of LEP patients to healthcare disparities, including errors and reduced access. Though training is recognized as crucial, opportunities in medical curricula remain limited.To bridge this gap, a novel initiative was introduced in a medical school, involving second-year students in clinical sessions with actual LEP patients and interpreters. These sessions featured interpreter input, patient interactions, and feedback from interpreters and clinical preceptors. A survey assessed the perspectives of students, preceptors, and interpreters.Outcomes revealed positive reception of interpreter and LEP patient integration. Students gained confidence in working with interpreters and valued interpreter feedback. Preceptors recognized the sessions' value in preparing students for future clinical interactions.This study underscores the importance of involving experienced interpreters in training students for real-world interactions with LEP patients. Early interpreter training enhances students' communication skills and ability to serve linguistically diverse populations. Further exploration could expand languages and interpretation modes and assess long-term effects on students' clinical performance. By effectively training future healthcare professionals to navigate language barriers and cultural diversity, this research contributes to equitable patient care in diverse communities.

View details for DOI 10.1186/s12909-024-05173-z

View details for PubMedID 38395858

View details for PubMedCentralID 9932446

View details for DOI 10.1001/jamainternmed.2024.3053

View details for PubMedID 39037786

Abstract

Limitation declarations are commonly deemed essential to uphold intellectual humility for scientific research, but little has been reported about the limitation statements in published original research articles. This meta-research study aims to investigate the trends of limitation statements among three leading general medical journals in the US.This cross-sectional study will compile a data set of full-length original research articles published in the New England Journal of Medicine, Journal of the American Medical Association, and Annals of Internal Medicine between 2002 and 2022. Limitation statement will be recognized by two investigators, and a predefined set of sensitive keywords is used for sensitivity analysis. Frequency of limitation statements within the main text of research articles and trends for different study designs, including their association with the corresponding reporting guidelines, are the main measurements. We employ the Cochran-Armitage test for trend analysis.The findings of this study will provide an overview of the limitation statements in leading general medical journals in the US. The results may contribute to future research to identify factors that are associated with the presence of limitation statements.

View details for DOI 10.1371/journal.pone.0305970

View details for PubMedID 39485763

Abstract

Although several therapeutic agents have been evaluated for the treatment of coronavirus disease 2019 (Covid-19), none have yet been shown to be efficacious.We conducted a double-blind, randomized, placebo-controlled trial of intravenous remdesivir in adults hospitalized with Covid-19 with evidence of lower respiratory tract involvement. Patients were randomly assigned to receive either remdesivir (200 mg loading dose on day 1, followed by 100 mg daily for up to 9 additional days) or placebo for up to 10 days. The primary outcome was the time to recovery, defined by either discharge from the hospital or hospitalization for infection-control purposes only.A total of 1063 patients underwent randomization. The data and safety monitoring board recommended early unblinding of the results on the basis of findings from an analysis that showed shortened time to recovery in the remdesivir group. Preliminary results from the 1059 patients (538 assigned to remdesivir and 521 to placebo) with data available after randomization indicated that those who received remdesivir had a median recovery time of 11 days (95% confidence interval [CI], 9 to 12), as compared with 15 days (95% CI, 13 to 19) in those who received placebo (rate ratio for recovery, 1.32; 95% CI, 1.12 to 1.55; P<0.001). The Kaplan-Meier estimates of mortality by 14 days were 7.1% with remdesivir and 11.9% with placebo (hazard ratio for death, 0.70; 95% CI, 0.47 to 1.04). Serious adverse events were reported for 114 of the 541 patients in the remdesivir group who underwent randomization (21.1%) and 141 of the 522 patients in the placebo group who underwent randomization (27.0%).Remdesivir was superior to placebo in shortening the time to recovery in adults hospitalized with Covid-19 and evidence of lower respiratory tract infection. (Funded by the National Institute of Allergy and Infectious Diseases and others; ACCT-1 ClinicalTrials.gov number, NCT04280705.).

View details for DOI 10.1056/NEJMoa2007764

View details for PubMedID 32445440

View details for PubMedCentralID PMC7262788

Abstract

Diabetes impacts tens of millions of people in the United States of America and 9 % of the worldwide population. Given the public health implications and economic burden of diabetes, the needs of people with diabetes must be addressed through strategic and effective advocacy efforts. Diabetes advocacy aims to increase public awareness about diabetes, raise funds for research and care, influence policy impacting people with diabetes, and promote optimal individual outcomes. We present a framework for diabetes advocacy activities by individuals and at the community, national, and international levels and identify challenges and gaps in current diabetes advocacy. Various groups have organized successful diabetes advocacy campaigns toward these goals, and lessons for further advancing diabetes advocacy can be learned from other health-related populations. Finally, we discuss the role of healthcare providers and mental/behavioral health professionals in advocacy efforts that can benefit their patients and the broader population of people with diabetes.

View details for DOI 10.1007/s11892-015-0636-z

View details for Web of Science ID 000377953300003

View details for PubMedID 26194156

View details for PubMedCentralID PMC4581582

Abstract

Hypnotizability is a stable trait that moderates the benefit of hypnosis for treating pain, but limited availability of hypnotizability testing deters widespread use of hypnosis. Inexpensive genotyping of 4 single nucleotide polymorphisms in the catechol-o-methyltransferase (COMT) gene was performed using giant magnetoresistive biosensors to determine if hypnotizable individuals can be identified for targeted hypnosis referrals. For individuals with the proposed 'optimal' COMT diplotypes, 89.5% score highly on the Hypnotic Induction Profile (OR = 6.12, 95%CI = 1.26-28.75), which identified 40.5% of the treatable population. Mean hypnotizability scores of the optimal group were significantly higher than the total population (p = 0.015 effect size = 0.60), an effect that was present in females (p = 0.0015, effect size = 0.83), but not in males (p = 0.28). In an exploratory cohort, optimal individuals also reported significantly higher postoperative pain scores (p = 0.00030, effect size = 1.93), indicating a greater need for treatment.

View details for DOI 10.1016/j.jmoldx.2023.01.002

View details for PubMedID 36702396

View details for DOI 10.1007/s11606-024-08784-w

View details for PubMedID 38689120

View details for PubMedCentralID 10589311

Abstract

Immune checkpoint inhibitor (ICI) therapy has improved survivals with a favorable toxicity profile in a variety of cancer patients. We hypothesized that hospitalized cancer patients who have acute or chronic comorbidities may have suppressed immune systems and poor clinical outcomes to ICIs. The objective of this study was to explore clinical outcomes and predictive factors of hospitalized cancer patients who received ICI therapy at an NCI-designated Comprehensive Cancer Center.A retrospective review of electronic medical records was conducted for adult cancer patients who received an FDA-approved ICI during admission from 08/2016 to 01/2022. For each patient we extracted demographics, cancer histology, comorbidities, reasons for hospitalization, ICI administered, time from treatment to discharge, time from treatment to progression or death, and complete blood counts. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared using the log-rank test. The 95% confidence interval for survival was calculated using the exact binomial distribution. Statistical significance was defined as 2-sided p<0.05.Of 37 patients identified, 2 were excluded due to lack of complete blood counts on admission. Average hospital stay was 24.2 (95% CI 16.5, 31.9) days. Ten (27.0%) patients died during the same hospitalization as treatment. Of those who followed up, 22 (59.5%) died within 90 days of inpatient therapy. The median PFS was 0.86 (95% CI 0.43, 1.74) months and median OS was 1.55 (95% CI 0.76, 3.72) months. Patients with ≥3 comorbidities had poorer PFS (2.4 vs. 0.4 months; p=0.0029) and OS (5.5 vs. 0.6 months; p=0.0006). Pre-treatment absolute lymphocyte counts (ALC) <600 cells/µL were associated with poor PFS (0.33 vs. 1.35 months; p=0.0053) and poor OS (0.33 vs. 2.34 months; p=0.0236). Pre-treatment derived neutrophil to lymphocyte ratio (dNLR) <4 was associated with good median PFS (1.6 vs. 0.4 months; p=0.0157) and OS (2.8 vs. 0.9 months; p=0.0375).Administration of ICI therapy was associated with poor clinical outcomes and high rates of both inpatient mortality and 90-day mortality after inpatient ICI therapy. The presence of ≥3 comorbidities, ALC <600/μL, or dNLR >4 in hospitalized patients was associated with poor survival outcomes.

View details for DOI 10.3389/fonc.2022.980181

View details for PubMedID 36185315

View details for PubMedCentralID PMC9515784

Abstract

Right ventricular (RV) dysfunction is common among patients hospitalized with COVID-19; however, its epidemiology may depend on the echocardiographic parameters used to define it.To evaluate the prevalence of abnormalities in three common echocardiographic parameters of RV function among COVID-19 patients admitted to the intensive care unit, as well as the effect of RV dilatation on differential parameter abnormality and the association of RV dysfunction with 60-day mortality.Retrospective cohort study of COVID-19 ICU patients between March 4th,2020 to March 4th, 2021, who received a transthoracic echocardiogram within 48 hours before to at most 7 days after ICU admission. RV dysfunction and dilatation respectively defined by guideline thresholds for tricuspid annular plane systolic excursion (TAPSE), RV fractional area change (RVFAC), RV free wall longitudinal strain (RVFWS), and RV basal dimension or RV end-diastolic area. Association of RV dysfunction with 60-day mortality assessed through logistic regression adjusting for age, prior history of congestive heart failure, invasive ventilation at time of TTE and APACHE II score.116 patients were included, of which 69% had RV dysfunction by > 1 parameter and 36.3% of these had RV dilatation. The three most common patterns of RV dysfunction included: Presence of 3 abnormalities, the combination of abnormal RVFWS and TAPSE, and isolated TAPSE abnormality. Patients with RV dilatation had worse RVFAC (24% vs 36%, p = 0.001), worse RVFWS (16.3% vs 19.1%, p = 0.005), higher RVSP (45mmHg vs 31mmHg, p = 0.001) but similar TAPSE (13mm vs 13mm, p = 0.30) compared to those with normal RV size. After multivariable adjustment, 60-day mortality was significantly associated with RV dysfunction (OR 2.91, 95% CI 1.01 - 9.44), as was the presence of at least 2 parameter abnormalities.ICU patients with COVID-19 had significant heterogeneity in RV function abnormalities present with different patterns associated with RV dilatation. RV dysfunction by any parameter was associated with increased mortality. Therefore, a multiparameter evaluation may be critical in recognizing RV dysfunction in COVID-19.

View details for DOI 10.1513/AnnalsATS.202303-235OC

View details for PubMedID 37478340

Abstract

To quantify utilization and impact on documentation time of a large language model-powered ambient artificial intelligence (AI) scribe.This prospective quality improvement study was conducted at a large academic medical center with 45 physicians from 8 ambulatory disciplines over 3 months. Utilization and documentation times were derived from electronic health record (EHR) use measures.The ambient AI scribe was utilized in 9629 of 17 428 encounters (55.25%) with significant interuser heterogeneity. Compared to baseline, median time per note reduced significantly by 0.57 minutes. Median daily documentation, afterhours, and total EHR time also decreased significantly by 6.89, 5.17, and 19.95 minutes/day, respectively.An early pilot of an ambient AI scribe demonstrated robust utilization and reduced time spent on documentation and in the EHR. There was notable individual-level heterogeneity.Large language model-powered ambient AI scribes may reduce documentation burden. Further studies are needed to identify which users benefit most from current technology and how future iterations can support a broader audience.

View details for DOI 10.1093/jamia/ocae304

View details for PubMedID 39688515

View details for DOI 10.1200/OP.24.00172

View details for PubMedID 39793555

View details for DOI 10.1111/joim.13501

View details for PubMedID 35417053

View details for Web of Science ID 001275557403539

Abstract

Large language model (LLM) artificial intelligence (AI) systems have shown promise in diagnostic reasoning, but their utility in management reasoning with no clear right answers is unknown.To determine whether LLM assistance improves physician performance on open-ended management reasoning tasks compared to conventional resources.Prospective, randomized controlled trial conducted from 30 November 2023 to 21 April 2024.Multi-institutional study from Stanford University, Beth Israel Deaconess Medical Center, and the University of Virginia involving physicians from across the United States.92 practicing attending physicians and residents with training in internal medicine, family medicine, or emergency medicine.Five expert-developed clinical case vignettes were presented with multiple open-ended management questions and scoring rubrics created through a Delphi process. Physicians were randomized to use either GPT-4 via ChatGPT Plus in addition to conventional resources (e.g., UpToDate, Google), or conventional resources alone.The primary outcome was difference in total score between groups on expert-developed scoring rubrics. Secondary outcomes included domain-specific scores and time spent per case.Physicians using the LLM scored higher compared to those using conventional resources (mean difference 6.5 %, 95% CI 2.7-10.2, p<0.001). Significant improvements were seen in management decisions (6.1%, 95% CI 2.5-9.7, p=0.001), diagnostic decisions (12.1%, 95% CI 3.1-21.0, p=0.009), and case-specific (6.2%, 95% CI 2.4-9.9, p=0.002) domains. GPT-4 users spent more time per case (mean difference 119.3 seconds, 95% CI 17.4-221.2, p=0.02). There was no significant difference between GPT-4-augmented physicians and GPT-4 alone (-0.9%, 95% CI -9.0 to 7.2, p=0.8).LLM assistance improved physician management reasoning compared to conventional resources, with particular gains in contextual and patient-specific decision-making. These findings indicate that LLMs can augment management decision-making in complex cases.ClinicalTrials.gov Identifier: NCT06208423 ; https://classic.clinicaltrials.gov/ct2/show/NCT06208423.Question: Does large language model (LLM) assistance improve physician performance on complex management reasoning tasks compared to conventional resources?Findings: In this randomized controlled trial of 92 physicians, participants using GPT-4 achieved higher scores on management reasoning compared to those using conventional resources (e.g., UpToDate).Meaning: LLM assistance enhances physician management reasoning performance in complex cases with no clear right answers.

View details for DOI 10.1101/2024.08.05.24311485

View details for PubMedID 39148822

View details for PubMedCentralID PMC11326321

View details for DOI 10.1097/MCG.0000000000001742

Abstract

We identified that Stanford Health Care had a significant number of patients who after discharge are found by the utilization review committee not to meet Center for Mediare and Medicaid Services (CMS) 2-midnight benchmark for inpatient status. Some of the charges incurred during the care of these patients are written-off and known as Medicare 1-day write-offs. This study which aims to evaluate the use of a Best Practice Alert (BPA) feature on the electronic medical record, EPIC, to ensure appropriate designation of a patient's hospitalization status as either inpatient or outpatient in accordance with Center for Medicare and Medicaid services (CMS) 2 midnight length of stay benchmark thereby reducing the number of associated write-offs.We incorporated a best practice alert (BPA) into the Epic Electronic Medical Record (EMR) that would prompt the discharging provider and the case manager to review the patients' inpatient designation prior to discharge and change the patient's designation to observation when deemed appropriate. Patients who met the inclusion criteria (Patients must have Medicare fee-for-service insurance, inpatient length of stay (LOS) less than 2 midnights, inpatient designation as hospitalization status at time of discharge, was hospitalized to an acute level of care and belonged to one of 37 listed hospital services at the time of signing of the discharge order) were randomized to have the BPA either silent or active over a three-month period from July 18, 2019, to October 18, 2019.A total of 88 patients were included in this study: 40 in the control arm and 48 in the intervention arm. In the intervention arm, 8 (8/48, 16.7%) had an inpatient status designation despite potentially meeting Medicare guidelines for an observation stay, comparing to 23 patients (23/40, 57.5%) patients in the control group (p = 0.001). The estimated number of write-offs in the control arm was 17 (73.9%, out of 23 inpatient patients) while in the intervention arm was 1 (12.5%, out of 8 inpatient patient) after accounting for patients who may have met inpatient criteria for other reasons based on case manager note review.This is the first time to our knowledge that a BPA has been used in this manner to reduce the number of Medicare 1-day write-offs.

View details for DOI 10.1186/s12913-024-10594-z

View details for PubMedID 38355492

View details for PubMedCentralID 6181108

Abstract

Whether patients with defecatory disorders (DDs) with favorable response to a footstool have distinctive anorectal pressure characteristics is unknown. We aimed to identify the clinical phenotype and anorectal pressure profile of patients with DDs who benefit from a footstool.This is a retrospective review of patients with high resolution anorectal manometry (HR-ARM) and balloon expulsion test (BET) from a tertiary referral center. BET was repeated with a 7-inch-high footstool in those who failed it after 120 s. Data were compared among groups with respect to BET results.Of the 667 patients with DDs, a total of 251 (38%) had failed BET. A footstool corrected BET in 41 (16%) of those with failed BET. Gender-specific differences were noted in anorectal pressures, among patients with and without normal BET, revealing gender-based nuances in pathophysiology of DDs. Comparing patients who passed BET with footstool with those who did not, the presence of optimal stool consistency, with reduced instances of loose stools and decreased reliance on laxatives were significant. Additionally, in women who benefited from a footstool, lower anal pressures at rest and simulated defecation were observed. Independent factors associated with a successful BET with a footstool in women included age <50, Bristol 3 or 4 stool consistency, lower anal resting pressure and higher rectoanal pressure gradient.Identification of distinctive clinical and anorectal phenotype of patients who benefited from a footstool could provide insight into the factors influencing the efficacy of footstool utilization and allow for an individualized treatment approach in patients with DDs.

View details for DOI 10.1111/nmo.14781

View details for PubMedID 38488172

Abstract

Technological burden and medical complexity are significant drivers of clinician burnout. Electronic health record(EHR)-based population health management tools can be used to identify high-risk patient populations and implement prophylactic health practices. Their impact on clinician burnout, however, is not well understood. Our objective was to assess the relationship between ratings of EHR-based population health management tools and clinician burnout.We conducted cross-sectional analyses of 2018 national Veterans Health Administration(VA) primary care personnel survey, administered as an online survey to all VA primary care personnel (n = 4257, response rate = 17.7%), using bivariate and multivariate logistic regressions. Our analytical sample included providers (medical doctors, nurse practitioners, physicians' assistants) and nurses (registered nurses, licensed practical nurses). The outcomes included two items measuring high burnout. Primary predictors included importance ratings of 10 population health management tools (eg. VA risk prediction algorithm, recent hospitalizations and emergency department visits, etc.).High ratings of 9 tools were associated with lower odds of high burnout, independent of covariates including VA tenure, team role, gender, ethnicity, staffing, and training. For example, clinicians who rated the risk prediction algorithm as important were less likely to report high burnout levels than those who did not use or did not know about the tool (OR 0.73; CI 0.61-0.87), and they were less likely to report frequent burnout (once per week or more) (OR 0.71; CI 0.60-0.84).Burned-out clinicians may not consider the EHR-based tools important and may not be using them to perform care management. Tools that create additional technological burden may need adaptation to become more accessible, more intuitive, and less burdensome to use. Finding ways to improve the use of tools that streamline the work of population health management and/or result in less workload due to patients with poorly managed chronic conditions may alleviate burnout. More research is needed to understand the causal directional of the association between burnout and ratings of population health management tools.

View details for DOI 10.1186/s12875-024-02410-8

View details for PubMedID 38750457

View details for PubMedCentralID PMC11094957

View details for DOI 10.3389/fdgth.2022.943768

Abstract

With 15 drugs currently approved for the treatment of metastatic renal cell carcinoma (mRCC) and even more combination regimens with immunotherapy on the horizon, there remains a distinct lack of molecular biomarkers for therapeutic efficacy. Our study reports on real-world clinical outcomes of mRCC patients from a tertiary academic medical center treated with empirically selected standard-of-care therapy. We utilized the Stanford Renal Cell Carcinoma Database (RCCD) to report on various outcome measures, including overall survival (OS) and the median number of lines of targeted therapies received from the time of metastatic diagnosis. We found that most metastatic patients did not survive long enough to attempt even half of the available targeted therapies. We also noted that patients who failed to receive a clinical benefit within the first two lines of therapy could still go on to experience clinical benefit in later lines of therapy. The term, "clinical benefit" was assigned to a line of therapy if a patient remained on drug treatment for three months or longer. Moreover, patients with clinical benefit in at least one line of therapy experienced significantly longer OS compared to those who did not have clinical benefit in at least one line of therapy. Developing biomarkers that identify patients who will receive clinical benefit in individual lines of therapy is one potential strategy for achieving rational drug sequencing in mRCC.

View details for DOI 10.3390/cancers11071000

View details for PubMedID 31319594

Abstract

Following the adoption of an acuity-adaptable unit model in an academic medical center, a