Diagnostic Performance of Physician Gestalt for Bacteremia in Patients in the Process of Being Admitted With Suspected Infection.
Clin Infect Dis
; 76(6): 1074-1079, 2023 03 21.
Article
in En
| MEDLINE
| ID: mdl-36306421
BACKGROUND: Due to potentially fatal consequences of missed bacteremia, blood cultures are often overused. While there are several prediction models that can be used to identify patients who truly need blood cultures, physicians often rely on their gestalt. We evaluated the diagnostic performance of physician gestalt for bacteremia in comparison with 2 existing prediction models: Takeshima and Shapiro. METHODS: The study enrolled consecutive adult patients with suspected infection who were in the process of being admitted to the general medicine department at 2 hospitals between April 2017 and January 2019. Attending physicians provided gestalt regarding risk of bacteremia (0%-100%). Patients with a <10% risk estimated via each strategy (ie, physician gestalt or 2 existing models) were categorized as bacteremia excluded (ie, blood cultures were considered unnecessary). Strategies were compared in terms of safety (proportion of patients with bacteremia among those classified as bacteremia excluded) and efficiency (proportion of patients classified as bacteremia excluded among the total cohort). RESULTS: Among 2014 patients, 292 (14.5%) were diagnosed with bacteremia. The safety of physician gestalt and the Takeshima and Shapiro models was 3.7% (95% confidence interval [CI], 2.2% to 5.7%), 6.5% (95% CI, 5.0% to 7.9%), and 10.8% (95% CI, 9.4% to 12.3%), whereas the efficiency of each strategy was 22.4% (95% CI, 22.5% to 26.3%), 52.7% (95% CI, 50.5% to 54.9%), and 87.8% (95% CI, 86.3% to 89.2%), respectively. CONCLUSIONS: Physician gestalt was safer but less efficient than existing models. Clinical prediction models could help reduce the overuse of blood cultures.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Physicians
/
Bacteremia
Type of study:
Diagnostic_studies
/
Prognostic_studies
Limits:
Adult
/
Humans
Language:
En
Journal:
Clin Infect Dis
Journal subject:
DOENCAS TRANSMISSIVEIS
Year:
2023
Type:
Article
Affiliation country:
Japan