Comparison of artificial intelligence versus real-time physician assessment of pulmonary edema with lung ultrasound.

BACKGROUND: Lung ultrasound can evaluate for pulmonary edema, but data suggest moderate inter-rater reliability among users. Artificial intelligence (AI) has been proposed as a model to increase the accuracy of B line interpretation. Early data suggest a benefit among more novice users, but data are limited among average residency-trained physicians. The objective of this study was to compare the accuracy of AI versus real-time physician assessment for B lines. METHODS: This was a prospective, observational study of adult Emergency Department patients presenting with suspected pulmonary edema. We excluded patients with active COVID-19 or interstitial lung disease. A physician performed thoracic ultrasound using the 12-zone technique. The physician recorded a video clip in each zone and provided an interpretation of positive (≥3 B lines or a wide, dense B line) or negative (<3 B lines and the absence of a wide, dense B line) for pulmonary edema based upon the real-time assessment. A research assistant then utilized the AI program to analyze the same saved clip to determine if it was positive versus negative for pulmonary edema. The physician sonographer was blinded to this assessment. The video clips were then reviewed independently by two expert physician sonographers (ultrasound leaders with >10,000 prior ultrasound image reviews) who were blinded to the AI and initial determinations. The experts reviewed all discordant values and reached consensus on whether the field (i.e., the area of lung between two adjacent ribs) was positive or negative using the same criteria as defined above, which served as the gold standard. RESULTS: 71 patients were included in the study (56.3% female; mean BMI: 33.4 [95% CI 30.6-36.2]), with 88.3% (752/852) of lung fields being of adequate quality for assessment. Overall, 36.1% of lung fields were positive for pulmonary edema. The physician was 96.7% (95% CI 93.8%-98.5%) sensitive and 79.1% (95% CI 75.1%-82.6%) specific. The AI software was 95.6% (95% CI 92.4%-97.7%) sensitive and 64.1% (95% CI 59.8%-68.5%) specific. CONCLUSION: Both the physician and AI software were highly sensitive, though the physician was more specific. Future research should identify which factors are associated with increased diagnostic accuracy.

Under the Microscope: A Look Into the Role of Critical Care Pharmacists During the COVID-19 Pandemic.

Among disciplines, the COVID-19 pandemic has reinforced the importance of critical care pharmacists in assuming responsibility for managing medication therapy in direct patient care settings. Historically, pharmacists have been relied upon for prospective evaluation of drug therapy for appropriate indications, dosage, drug interactions, and drug allergies; monitoring patients' pharmacotherapeutic regimens for effectiveness and adverse effects; providing drug information to providers; and educating health professionals regarding drug therapies. Specific to COVID-19, pharmacists have been an integral member of the multidisciplinary rounding team, assisting with drug shortages and strategies for drug conservation; participating in emergencies, such as advanced cardiac life support (ACLS) and rapid sequence intubations; and creating as well as integrating evidence-based guidelines and pathways during the pandemic into clinical practice. The purpose of this article is to demonstrate the various roles of critical care pharmacists among the healthcare team in caring for critically ill COVID-19 patients.

Urinary tract infection pocket card effect on preferred antimicrobial prescribing for cystitis among patients discharged from the emergency department.

PURPOSE: To evaluate the impact of a urinary tract infection (UTI) pocket card on preferred antibiotic prescribing for patients discharged from the emergency department (ED) with a diagnosis of cystitis. METHODS: A multicenter, retrospective, pre-post study was conducted to compare outcomes following the introduction of a UTI pocket card. The primary outcome was prescribing rates for institutional first-line preferred antibiotics (cephalexin and nitrofurantoin) versus other antimicrobials for cystitis. Secondary outcomes included prescriber adherence to recommended therapy in regards to discharge dose, frequency, duration, and healthcare utilization rates. RESULTS: The study included 915 patients in total, 407 in the preintervention group and 508 in the postintervention group. The frequency of preferred antibiotic prescribing was significantly increased after the introduction of a UTI pocket card compared to prior to its introduction (81.7% vs 72.0%, P = 0.001). Significant increases in prescribing of an appropriate antibiotic dose (78.0% vs 66.8%, P < 0.0001) and frequency (64.2% vs 47.4%, P < 0.0001) were also found post intervention. No significant differences were seen between the pre- and postintervention groups with regards to healthcare utilization rates. CONCLUSION: A UTI pocket card increased preferred antibiotic prescribing for cystitis in the ED. This study provides data on a successful antimicrobial stewardship intervention in the ED setting.