Clinician Conceptualization of the Benefits of Treatments for Individual Patients
Importance/UNASSIGNED:Knowing the expected effect of treatment on an individual patient is essential for patient care. Objective/UNASSIGNED:To explore clinicians' conceptualizations of the chance that treatments will decrease the risk of disease outcomes. Design, Setting, and Participants/UNASSIGNED:This survey study of attending and resident physicians, nurse practitioners, and physician assistants was conducted in outpatient clinical settings in 8 US states from June 2018 to November 2019. The survey was an in-person, paper, 26-item survey in which clinicians were asked to estimate the probability of adverse disease outcomes and expected effects of therapies for diseases common in primary care. Main Outcomes and Measures/UNASSIGNED:Estimated chance that treatments would benefit an individual patient. Results/UNASSIGNED:Of 723 clinicians, 585 (81%) responded, and 542 completed all the questions necessary for analysis, with a median (interquartile range [IQR]) age of 32 (29-44) years, 287 (53%) women, and 294 (54%) White participants. Clinicians consistently overestimated the chance that treatments would benefit an individual patient. The median (IQR) estimated chance that warfarin would prevent a stroke in the next year was 50% (5%-80%) compared with scientific evidence, which indicates an absolute risk reduction (ARR) of 0.2% to 1.0% based on a relative risk reduction (RRR) of 39% to 50%. The median (IQR) estimated chance that antihypertensive therapy would prevent a cardiovascular event within 5 years was 30% (10%-70%) vs evidence of an ARR of 0% to 3% based on an RRR of 0% to 28%. The median (IQR) estimated chance that bisphosphonate therapy would prevent a hip fracture in the next 5 years was 40% (10%-60%) vs evidence of ARR of 0.1% to 0.4% based on an RRR of 20% to 40%. The median (IQR) estimated chance that moderate-intensity statin therapy would prevent a cardiovascular event in the next 5 years was 20% (IQR 5%-50%) vs evidence of an ARR of 0.3% to 2% based on an RRR of 19% to 33%. Estimates of the chance that a treatment would prevent an adverse outcome exceeded estimates of the absolute chance of that outcome for 60% to 70% of clinicians. Clinicians whose overestimations were greater were more likely to report using that treatment for patients in their practice (eg, use of warfarin: correlation coefficient, 0.46; 95% CI, 0.40-0.53; Pâ€‰<â€‰.001). Conclusions and Relevance/UNASSIGNED:In this survey study, clinicians significantly overestimated the benefits of treatment to individual patients. Clinicians with greater overestimates were more likely to report using treatments in actual patients.
Accuracy of Practitioner Estimates of Probability of Diagnosis Before and After Testing
Importance/UNASSIGNED:Accurate diagnosis is essential to proper patient care. Objective/UNASSIGNED:To explore practitioner understanding of diagnostic reasoning. Design, Setting, and Participants/UNASSIGNED:In this survey study, 723 practitioners at outpatient clinics in 8 US states were asked to estimate the probability of disease for 4 scenarios common in primary care (pneumonia, cardiac ischemia, breast cancer screening, and urinary tract infection) and the association of positive and negative test results with disease probability from June 1, 2018, to November 26, 2019. Of these practitioners, 585 responded to the survey, and 553 answered all of the questions. An expert panel developed the survey and determined correct responses based on literature review. Results/UNASSIGNED:A total of 553 (290 resident physicians, 202 attending physicians, and 61 nurse practitioners and physician assistants) of 723 practitioners (76.5%) fully completed the survey (median age, 32 years; interquartile range, 29-44 years; 293 female [53.0%]; 296 [53.5%] White). Pretest probability was overestimated in all scenarios. Probabilities of disease after positive results were overestimated as follows: pneumonia after positive radiology results, 95% (evidence range, 46%-65%; comparison Pâ€‰<â€‰.001); breast cancer after positive mammography results, 50% (evidence range, 3%-9%; Pâ€‰<â€‰.001); cardiac ischemia after positive stress test result, 70% (evidence range, 2%-11%; Pâ€‰<â€‰.001); and urinary tract infection after positive urine culture result, 80% (evidence range, 0%-8.3%; Pâ€‰<â€‰.001). Overestimates of probability of disease with negative results were also observed as follows: pneumonia after negative radiography results, 50% (evidence range, 10%-19%; Pâ€‰<â€‰.001); breast cancer after negative mammography results, 5% (evidence range, <0.05%; Pâ€‰<â€‰.001); cardiac ischemia after negative stress test result, 5% (evidence range, 0.43%-2.5%; Pâ€‰<â€‰.001); and urinary tract infection after negative urine culture result, 5% (evidence range, 0%-0.11%; Pâ€‰<â€‰.001). Probability adjustments in response to test results varied from accurate to overestimates of risk by type of test (imputed median positive and negative likelihood ratios [LRs] for practitioners for chest radiography for pneumonia: positive LR, 4.8; evidence, 2.6; negative LR, 0.3; evidence, 0.3; mammography for breast cancer: positive LR, 44.3; evidence range, 13.0-33.0; negative LR, 1.0; evidence range, 0.05-0.24; exercise stress test for cardiac ischemia: positive LR, 21.0; evidence range, 2.0-2.7; negative LR, 0.6; evidence range, 0.5-0.6; urine culture for urinary tract infection: positive LR, 9.0; evidence, 9.0; negative LR, 0.1; evidence, 0.1). Conclusions and Relevance/UNASSIGNED:This survey study suggests that for common diseases and tests, practitioners overestimate the probability of disease before and after testing. Pretest probability was overestimated in all scenarios, whereas adjustment in probability after a positive or negative result varied by test. Widespread overestimates of the probability of disease likely contribute to overdiagnosis and overuse.
Association of SARS-CoV-2 Genomic Load with COVID-19 Patient Outcomes
Association of SARS-CoV-2 genomic load in nasopharyngeal samples with adverse COVID-19 patient outcomes: A retrospective analysis from an academic hospital center in New York City [Meeting Abstract]
Background: SARS-CoV-2, the cause of COVID-19 pneumonia, is associated with heterogenous presentations ranging from asymptomatic infection to severe respiratory failure. We explored the association of SARS-CoV-2 genomic load as a risk factor for adverse patient outcomes.
Method(s): We included adult patients admitted to the hospital with clinical and radiographic findings of pneumonia and a confirmatory polymerase chain reaction (PCR) test of SARS-CoV-2 within 24 hours of admission. We segregated patients into 3 genomic load status groups: low (Cycle threshold (Ct) >=35) intermediate (25< Ct< 35) and high (Ct <=25) using real-time PCR. The primary outcome was a composite outcome of death, intubation and/or use of extracorporeal membrane oxygenation. Secondary outcomes included severity of pneumonia on admission, as measured by the Pneumonia Severity Index (PSI). Sensitivity analyses were performed to include Acute Respiratory Distress Syndrome (ARDS) in the composite outcome and varying Ct classification breakpoints.
Result(s): Of 457 patients positive for SARS-CoV-2 assay from March 31st to April 10th 2020, 316 met inclusion criteria and were included in the final analysis. Included patients were followed for a median of 25 days (IQR 21-28). High genomic load at presentation was associated with higher Charlson Comorbidity Index scores (p=0.005), transplant recipient status (p< 0.001) and duration of illness less than 7 days (p=0.005). Importantly, patients with high genomic load were more likely to reach the primary endpoint (p=0.001), and had higher PSI scores on admission (p=0.03). In multivariate analysis, high genomic load remained an independent predictor of primary outcome. Results remained significant in sensitivity analyses.
Conclusion(s): High genomic load of SARS-CoV-2 in nasopharyngeal samples at the time of admission is independently associated with mortality and intubation. This finding should prompt further research on the role of viral load as a clinical predictor and possible modifiable risk factor for adverse outcomes as treatment strategies evolve in this global pandemic. (Table Presented)
Association of SARS-CoV-2 genomic load trends with clinical status in COVID-19:A retrospective analysis from an academic hospital center in New York City [Meeting Abstract]
Background: The Infectious Diseases Society of America has identified the potential use of SARS-CoV-2 genomic load for prognostication purposes as a key research question.
Method(s): We designed a retrospective cohort study that included adult patients with COVID-19 pneumonia who had at least 2 positive nasopharyngeal tests at least 24 hours apart to study the correlation between the change in the genomic load of SARS-CoV-2 in nasopharyngeal samples, as reflected by the Cycle threshold (Ct) value of the real-time Polymerase Chain Reaction (PCR) assay, with change in clinical status. The Sequential Organ Failure Assessment (SOFA) score was used as a surrogate for patients' clinical status. A linear mixed-effects regression analysis was performed.
Result(s): Among 457 patients who presented to the emergency department between 3/31/2020- 4/10/2020, we identified 42 patients who met the inclusion criteria. The median initial SOFA score was 2 (IQR 2-3). 20 out of 42 patients had a lower SOFA score on their subsequent tests. We identified a statistically significant inverse correlation between the change in SOFA score and change in the Ct value with a decrease in SOFA score by 0.05 (SE 0.02; p < 0.05) for an increase in Ct values by 1. This correlation was independent of the duration of symptoms.
Conclusion(s): Our findings suggest that an increasing Ct value in sequential tests may be of prognostic value for patients diagnosed with COVID-19 pneumonia. Before repeat testing can be recommended routinely in clinical practice as a predictor of disease outcomes, prospective studies with a standardized interval between repeat tests should confirm our findings. (Table Presented)
Association of SARS-CoV-2 Genomic Load with COVID-19 Patient Outcomes
Association of SARS-CoV-2 genomic load trends with clinical status in COVID-19: A retrospective analysis from an academic hospital center in New York City
The Infectious Diseases Society of America has identified the use of SARS-CoV-2 genomic load for prognostication purposes as a key research question. We designed a retrospective cohort study that included adult patients with COVID-19 pneumonia who had at least 2 positive nasopharyngeal tests at least 24 hours apart to study the correlation between the change in the genomic load of SARS-CoV-2, as reflected by the Cycle threshold (Ct) value of the RT-PCR, with change in clinical status. The Sequential Organ Failure Assessment (SOFA) score was used as a surrogate for patients' clinical status. Among 457 patients with COVID-19 pneumonia between 3/31/2020-4/10/2020, we identified 42 patients who met the inclusion criteria. The median initial SOFA score was 2 (IQR 2-3). 20 out of 42 patients had a lower SOFA score on their subsequent tests. We identified a statistically significant inverse correlation between the change in SOFA score and change in the Ct value with a decrease in SOFA score by 0.05 (SE 0.02; p<0.05) for an increase in Ct values by 1. This correlation was independent of the duration of symptoms. Our findings suggest that an increasing Ct value in sequential tests may be of prognostic value for patients diagnosed with COVID-19 pneumonia.
Understanding travel medicine provider's risk assessment of travel-associated diseases [Meeting Abstract]
Background. Pre-travel medical consultations attempt to reduce travel-associated risks by behavioral modification, vaccination, and medications. Provider understanding of quantitative risk of commonly discussed travel topics is poorly characterized. We investigated travel medicine provider understanding of quantitative risk of common travel-associated diseases, and explored how providers relay risk estimates to travelers. Methods. After institutional review board (IRB) approval, an online anonymous survey was sent to the International Society for Travel Medicine Listserv. Travel medicine experience, practice patterns and demographics were recorded. Respondents estimated quantitative risk of various destination-specific diseases. Descriptive statistics were completed. Results. Of 114 respondents, most were experienced travel medicine providers (79% saw >6 travel visits monthly). Overall risk estimates are in Table 1. Compared with published literature, providers gave accurate risk estimates for some diseases (yellow fever, traveler's diarrhea), but overestimated quantitative risk for others (Japanese encephalitis, hepatitis A, cholera). Interquartile range was greatest for Japanese encephalitis and cholera, reflecting a wider range of risk estimates. Most (81%) providers used general risk descriptions (high, low, none) and a minority (14%) discussed quantitative risk with travelers. Conclusion. Experienced travel medicine providers overestimated risk of several vaccine preventable illnesses, though risk estimates for others were close to published estimates. Most providers do not use quantitative risk in pre-travel consultations. Improved quantitative risk understanding may improve the quality of pre-travel consultations. (Table Presented)
Coccidioides immitis septic knee arthritis
A 78-year-old man developed right knee pain and swelling without other systemic symptoms. He had travelled frequently to the Central Valley of California. He was diagnosed with coccidioidomycosis based on joint fluid culture. Coccidioidal complement fixation antibody titres were extremely elevated. Arthroscopic debridement and fluconazole therapy did not lead to satisfactory improvement. Subsequent open debridement and change to itraconazole was followed by resolution of clinical signs of infection.
Chronic strongyloidiasis with recurrent asthma exacerbations and steroid-associated 'hives'
A 74-year-old man experienced worsening asthma for several years. Oral steroids were required on multiple occasions for asthma treatment. During his steroid courses, he developed a hive-like rash, which would resolve after completion of each steroid course. He was from Romania, and had lived in the USA for many years. Laboratory testing had shown eosinophilia. He was eventually diagnosed with strongyloidiasis by serology. Treatment with ivermectin led to marked improvement but not resolution of his long-term asthma. His hive-like rash, which was likely larva currens, did not recur with a subsequent steroid course. Improved recognition of strongyloidiasis, particularly in steroid-treated patients, is needed.