Lessons in clinical reasoning - pitfalls, myths, and pearls: shoulder pain as the first and only manifestation of lung cancer.

OBJECTIVES: Lung cancer is the leading cause of cancer-related death and poses significant challenges in diagnosis and management. Although muscle metastases are exceedingly rare and typically not the initial clinical manifestation of neoplastic processes, their recognition is crucial for optimal patient care. CASE PRESENTATION: We present a case report in which we identify the unique scenario of a 60-year-old man with shoulder pain and a deltoid muscle mass, initially suggestive of an undifferentiated pleomorphic sarcoma. However, further investigations, including radiological findings and muscle biopsy, revealed an unexpected primary lung adenocarcinoma. We performed a systematic literature search to identify the incidence of SMM and reflect on how to improve and build on better diagnosis for entities as atypical as this. This atypical presentation highlights the importance of recognizing and addressing cognitive biases in clinical decision-making, as acknowledging the possibility of uncommon presentations is vital. By embracing a comprehensive approach that combines imaging studies with histopathological confirmation, healthcare providers can ensure accurate prognoses and appropriate management strategies, ultimately improving patient outcomes. CONCLUSIONS: This case serves as a reminder of the need to remain vigilant, open-minded, and aware of cognitive biases when confronted with uncommon clinical presentations, emphasizing the significance of early recognition and prompt evaluation in achieving optimal patient care.

Demystifying AI: Current State and Future Role in Medical Education Assessment.

ABSTRACT: Medical education assessment faces multifaceted challenges, including data complexity, resource constraints, bias, feedback translation, and educational continuity. Traditional approaches often fail to adequately address these issues, creating stressful and inequitable learning environments. This article introduces the concept of precision education, a data-driven paradigm aimed at personalizing the educational experience for each learner. It explores how artificial intelligence (AI), including its subsets machine learning (ML) and deep learning (DL), can augment this model to tackle the inherent limitations of traditional assessment methods.AI can enable proactive data collection, offering consistent and objective assessments while reducing resource burdens. It has the potential to revolutionize not only competency assessment but also participatory interventions, such as personalized coaching and predictive analytics for at-risk trainees. The article also discusses key challenges and ethical considerations in integrating AI into medical education, such as algorithmic transparency, data privacy, and the potential for bias propagation.AI's capacity to process large datasets and identify patterns allows for a more nuanced, individualized approach to medical education. It offers promising avenues not only to improve the efficiency of educational assessments but also to make them more equitable. However, the ethical and technical challenges must be diligently addressed. The article concludes that embracing AI in medical education assessment is a strategic move toward creating a more personalized, effective, and fair educational landscape. This necessitates collaborative, multidisciplinary research and ethical vigilance to ensure that the technology serves educational goals while upholding social justice and ethical integrity.

Development and Validation of a Machine Learning Model for Automated Assessment of Resident Clinical Reasoning Documentation.

BACKGROUND: Residents receive infrequent feedback on their clinical reasoning (CR) documentation. While machine learning (ML) and natural language processing (NLP) have been used to assess CR documentation in standardized cases, no studies have described similar use in the clinical environment. OBJECTIVE: The authors developed and validated using Kane's framework a ML model for automated assessment of CR documentation quality in residents' admission notes. DESIGN, PARTICIPANTS, MAIN MEASURES: Internal medicine residents' and subspecialty fellows' admission notes at one medical center from July 2014 to March 2020 were extracted from the electronic health record. Using a validated CR documentation rubric, the authors rated 414 notes for the ML development dataset. Notes were truncated to isolate the relevant portion; an NLP software (cTAKES) extracted disease/disorder named entities and human review generated CR terms. The final model had three input variables and classified notes as demonstrating low- or high-quality CR documentation. The ML model was applied to a retrospective dataset (9591 notes) for human validation and data analysis. Reliability between human and ML ratings was assessed on 205 of these notes with Cohen's kappa. CR documentation quality by post-graduate year (PGY) was evaluated by the Mantel-Haenszel test of trend. KEY RESULTS: The top-performing logistic regression model had an area under the receiver operating characteristic curve of 0.88, a positive predictive value of 0.68, and an accuracy of 0.79. Cohen's kappa was 0.67. Of the 9591 notes, 31.1% demonstrated high-quality CR documentation; quality increased from 27.0% (PGY1) to 31.0% (PGY2) to 39.0% (PGY3) (p < .001 for trend). Validity evidence was collected in each domain of Kane's framework (scoring, generalization, extrapolation, and implications). CONCLUSIONS: The authors developed and validated a high-performing ML model that classifies CR documentation quality in resident admission notes in the clinical environment-a novel application of ML and NLP with many potential use cases.

Pharmacists can improve diagnosis and help prevent diagnostic errors.

We present two cases that highlight the role of pharmacists in the diagnostic process and illustrate how a culture of safety and teamwork between pharmacists and physicians can help prevent diagnostic errors.

Development of a Clinical Reasoning Documentation Assessment Tool for Resident and Fellow Admission Notes: a Shared Mental Model for Feedback.

BACKGROUND: Residents and fellows receive little feedback on their clinical reasoning documentation. Barriers include lack of a shared mental model and variability in the reliability and validity of existing assessment tools. Of the existing tools, the IDEA assessment tool includes a robust assessment of clinical reasoning documentation focusing on four elements (interpretive summary, differential diagnosis, explanation of reasoning for lead and alternative diagnoses) but lacks descriptive anchors threatening its reliability. OBJECTIVE: Our goal was to develop a valid and reliable assessment tool for clinical reasoning documentation building off the IDEA assessment tool. DESIGN, PARTICIPANTS, AND MAIN MEASURES: The Revised-IDEA assessment tool was developed by four clinician educators through iterative review of admission notes written by medicine residents and fellows and subsequently piloted with additional faculty to ensure response process validity. A random sample of 252 notes from July 2014 to June 2017 written by 30 trainees across several chief complaints was rated. Three raters rated 20% of the notes to demonstrate internal structure validity. A quality cut-off score was determined using Hofstee standard setting. KEY RESULTS: The Revised-IDEA assessment tool includes the same four domains as the IDEA assessment tool with more detailed descriptive prompts, new Likert scale anchors, and a score range of 0-10. Intraclass correlation was high for the notes rated by three raters, 0.84 (95% CI 0.74-0.90). Scores ≥6 were determined to demonstrate high-quality clinical reasoning documentation. Only 53% of notes (134/252) were high-quality. CONCLUSIONS: The Revised-IDEA assessment tool is reliable and easy to use for feedback on clinical reasoning documentation in resident and fellow admission notes with descriptive anchors that facilitate a shared mental model for feedback.

Lessons in clinical reasoning ‒ pitfalls, myths and pearls: a case of recurrent pancreatitis.

OBJECTIVES: Cognitive biases can result in clinical reasoning failures that can lead to diagnostic errors. Autobrewery syndrome is a rare, but likely underdiagnosed, condition in which gut flora ferment glucose, producing ethanol. It most frequently presents with unexplained episodes of inebriation, though more case studies are necessary to better characterize the syndrome. CASE PRESENTATION: This is a case of a 41-year old male with a past medical history notable only for frequent sinus infections, who presented with recurrent episodes of acute pancreatitis. In the week prior to his first episode of pancreatitis, he consumed four beers, an increase from his baseline of 1-2 drinks per month. At home, he had several episodes of confusion, which he attributed to fatigue. He underwent laparoscopic cholecystectomy and testing for genetic and autoimmune causes of pancreatitis, which were non-revealing. He was hospitalized 10 more times during that 9-month period for acute pancreatitis with elevated transaminases. During these admissions, he had elevated triglycerides requiring an insulin drip and elevated alcohol level despite abstaining from alcohol for the prior eight months. His alcohol level increased after consumption of complex carbohydrates, confirming the diagnosis of autobrewery syndrome. CONCLUSIONS: Through integrated commentary on the diagnostic reasoning process, this case underscores how overconfidence can lead to premature closure and anchoring resulting in diagnostic error. Using a metacognitive overview, case discussants describe the importance of structured reflection and a standardized approach to early hypothesis generation to navigate these cognitive biases.

Hickam's dictum, Occam's razor, and Crabtree's bludgeon: a case of renal failure and a clavicular mass.

OBJECTIVES: Our discussant's thoughtful consideration of the patient's case allows for review of three maxims of medicine: Occam's razor (the simplest diagnosis is the most likely to be correct), Hickam's dictum (multiple disease entities are more likely than one), and Crabtree's bludgeon (the tendency to make data fit to an explanation we hold dear). CASE PRESENTATION: A 66-year-old woman with a history of hypertension presented to our hospital one day after arrival to the United States from Guinea with chronic daily vomiting, unintentional weight loss and progressive shoulder pain. Her labs are notable for renal failure, nephrotic range proteinuria and normocytic anemia while her shoulder X-ray shows osseous resorption in the lateral right clavicle. Multiple myeloma became the team's working diagnosis; however, a subsequent shoulder biopsy was consistent with follicular thyroid carcinoma. Imaging suggested the patient's renal failure was more likely a result of a chronic, unrelated process. CONCLUSIONS: It is tempting to bludgeon diagnostic possibilities into Occam's razor. Presumption that a patient's signs and symptoms are connected by one disease process often puts us at a cognitive advantage. However, atypical presentations, multiple disease processes, and unique populations often lend themselves more to Hickam's dictum than to Occam's razor. Diagnostic aids include performing a metacognitive checklist, engaging analytic thinking, and acknowledging the imperfections of these axioms.

Comorbidity and clinical factors associated with COVID-19 critical illness and mortality at a large public hospital in New York City in the early phase of the pandemic (March-April 2020).

BACKGROUND: Despite evidence of socio-demographic disparities in outcomes of COVID-19, little is known about characteristics and clinical outcomes of patients admitted to public hospitals during the COVID-19 outbreak. OBJECTIVE: To assess demographics, comorbid conditions, and clinical factors associated with critical illness and mortality among patients diagnosed with COVID-19 at a public hospital in New York City (NYC) during the first month of the COVID-19 outbreak. DESIGN: Retrospective chart review of patients diagnosed with COVID-19 admitted to NYC Health + Hospitals / Bellevue Hospital from March 9th to April 8th, 2020. RESULTS: A total of 337 patients were diagnosed with COVID-19 during the study period. Primary analyses were conducted among those requiring supplemental oxygen (n = 270); half of these patients (135) were admitted to the intensive care unit (ICU). A majority were male (67.4%) and the median age was 58 years. Approximately one-third (32.6%) of hypoxic patients managed outside the ICU required non-rebreather or non-invasive ventilation. Requirement of renal replacement therapy occurred in 42.3% of ICU patients without baseline end-stage renal disease. Overall, 30-day mortality among hypoxic patients was 28.9% (53.3% in the ICU, 4.4% outside the ICU). In adjusted analyses, risk factors associated with mortality included dementia (adjusted risk ratio (aRR) 2.11 95%CI 1.50-2.96), age 65 or older (aRR 1.97, 95%CI 1.31-2.95), obesity (aRR 1.37, 95%CI 1.07-1.74), and male sex (aRR 1.32, 95%CI 1.04-1.70). CONCLUSION: COVID-19 demonstrated severe morbidity and mortality in critically ill patients. Modifications in care delivery outside the ICU allowed the hospital to effectively care for a surge of critically ill and severely hypoxic patients.

Evolving oxygenation management reasoning in COVID-19.

The initial phase of the SARS-CoV-2 pandemic in the United States saw rapidly-rising patient volumes along with shortages in personnel, equipment, and intensive care unit (ICU) beds across many New York City hospitals. As our hospital wards quickly filled with unstable, hypoxemic patients, our hospitalist group was forced to fundamentally rethink the way we triaged and managed cases of hypoxemic respiratory failure. Here, we describe the oxygenation protocol we developed and implemented in response to changing norms for acuity on inpatient wards. By reflecting on lessons learned, we re-evaluate the applicability of these oxygenation strategies in the evolving pandemic. We hope to impart to other providers the insights we gained with the challenges of management reasoning in COVID-19.

Theory-guided teaching: Implementation of a clinical reasoning curriculum in residents.

Introduction: Educators have theorized that interventions grounded in dual process theory (DPT) and script theory (ST) may improve the diagnostic reasoning process of physicians but little empirical evidence exists. Methods: In this quasi-experimental study, we assessed the impact of a clinical reasoning (CR) curriculum grounded in DPT and ST on medicine residents participating in one of three groups during a 6-month period: no, partial, or full intervention. Residents completed the diagnostic thinking inventory (DTI) at baseline and 6 months. At 6 months, participants also completed a post-survey assessing application of concepts to cases. Results: There was a significant difference between groups in application of concepts (no intervention 1.6 (0.65) compared to partial 2.3 (0.81) and full 2.2 (0.91), p = 0.05), as well as describing cases in problem representation format (no intervention 1.2 (0.38) and partial 1.5 (0.55) compared to full 2.1 (0.93), p = 0.004). There was no significant difference in change in DTI scores (no intervention 7.0 (16.3), partial 8.8 (9.8), full 7.8 (12.0)). Conclusions: Residents who participated in a CR curriculum grounded in DPT and ST were effective in applying principles of CR in cases from their practice. To our knowledge, this is the first workplace-based CR educational intervention study showing differences in the reasoning process residents apply to patients.

A workshop to train medicine faculty to teach clinical reasoning.

Background Clinical reasoning (CR) is a core competency in medical education. Few studies have examined efforts to train faculty to teach CR and lead CR curricula in medical schools and residencies. In this report, we describe the development and preliminary evaluation of a faculty development workshop to teach CR grounded in CR theory. Methods Twenty-six medicine faculty (nine hospitalists and 17 subspecialists) participated in a workshop that introduced a framework to teach CR using an interactive, case-based didactic followed by role-play exercises. Faculty participated in pre- and post-Group Observed Structured Teaching Exercises (GOSTE), completed retrospective pre-post assessments (RPPs), and made commitment to change statements (CTCs). Results In the post-GOSTE, participants significantly improved in their use of problem representation and illness scripts to teach CR. RPPs revealed that faculty were more confident in their ability and more likely to teach CR using educational strategies grounded in CR educational theory. At 2-month follow-up, 81% of participants reported partially implementing these teaching techniques. Conclusions After participating in this 3-h workshop, faculty demonstrated increased ability to use these teaching techniques and expressed greater confidence and an increased likelihood to teach CR. The majority of faculty reported implementing these newly learned educational strategies into practice.

Lap-band impact on the function of the esophagus.

BACKGROUND: The laparoscopic adjustable gastric band (LAGB) has been widely used to treat morbid obesity. There is conflicting data on its long-term effect on esophageal function. Our aim was to assess the long-term impact of the LAGB on esophageal motility and pH-metry in patients who had LAGB who had normal and abnormal esophageal function at baseline. METHODS: Consecutive patients referred for bariatric surgery were prospectively enrolled. A detailed medical history was obtained, and esophageal manometric and 24-h pH evaluations were performed in standard fashion preoperatively and 6 and 12 months postoperatively; patients served as their own controls. RESULTS: Twenty-two patients completed manometric evaluation. Ten patients had normal manometric parameters at baseline; at 6 months, mean lower esophageal sphincter (LES) residual pressure increased significantly from baseline (3.9 +/- 2 vs. 8.9 +/- 4 mmHg, p = 0.014). At 12 months, the mean peristaltic wave duration increased from 3.6 +/- 1 at baseline to 6.8 +/- 2 s, p = 0.025 and wave amplitude decreased during the same period (98.7 +/- 22 vs. 52.3 +/- 24, p = 0.013). LES pressure and percent peristalsis did not differ significantly pre- and post-LAGB. Twelve patients had one or more abnormal manometric findings at baseline; at 12 months, LES pressure in these 12 patients decreased significantly (31.1 +/- 10 vs 23.6 +/- 7, p = 0.011) and wave amplitude was significantly reduced (125.9 +/- 117 vs 103 +/- 107, p = 0.039). LES residual pressure did not change significantly pre- and post-LAGB. Twenty-two individuals were evaluated for impact of Lap-Band on esophageal acid exposure. Sixteen of these patients had normal esophageal pH-metry values at baseline and had no significant changes in 12 months in any pH-metry measurement. Six patients had abnormal pH-metry values at baseline. Among these patients, time with pH < 4.0 and Johnson/DeMeester score did not change significantly during follow-up. There was a significant decrease in the number of reflux episodes from baseline to 6 months (159 +/- 48 vs. 81 +/- 61, p = 0.016). CONCLUSIONS: Abnormal manometric findings are frequently encountered post-LAGB. Increases in LES residual pressure and peristaltic wave duration were the most significant changes. LAGB is not associated with an increase in total esophageal acidification time. Further evaluation of the clinical significance of manometric abnormalities is warranted.