Prediction models in CMI

Scoping review of risk-scoring tools for early prediction of bloodstream infections caused by carbapenem-resistant Enterobacterales: do we really have a reliable risk-scoring tool?

Background

Bloodstream infections (BSIs) caused by carbapenem-resistant Enterobacterales (CRE) are a global health concern. Rapid identification of CRE may improve patient outcomes and reduce inappropriate antibiotic prescription. The use of risk-scoring tools (RSTs) can be valuable for optimizing the decision-making process for empirical antibiotic therapy of suspected CRE bacteraemia. These tools can also be used to triage use of expensive rapid diagnostic methods.

Methods

We systematically reviewed the relevant literature in PubMed/MEDLINE, CINAHL, Cochrane, Web of Science, Embase and Scopus up to 1 November 2022 to identify RSTs that predict CRE BSIs. The literature review and analysis of the articles were performed by two researchers; any inconsistencies were resolved through discussion.

Results

We identified 9 RSTs developed for early prediction of CRE BSIs and only logistic regression was used for most studies. These RSTs were quite different from each other in terms of their performance and the variables they included. They also had notable limitations and very few of them were externally validated.

Conclusions

RSTs for early prediction of CRE BSIs have limitations and lack of external validity outside the local setting in which they were developed. Future studies to identify optimal RSTs in high and low CRE-endemic settings are warranted. Approaches based on rapid diagnostics and RSTs should be compared with a treatment approach using both methods in a randomized controlled trial.

Predictors of survival in elderly patients with coronavirus disease 2019 admitted to the hospital: derivation and validation of the FLAMINCOV score

OBJECTIVE

To identify predictors of 30-day survival in elderly patients with coronavirus disease 2019 (COVID-19).

METHODS

Retrospective cohort study including patients with COVID-19 aged ≥65 years hospitalized in six European sites (January 2020 to May 2021). Data on demographics, comorbidities, clinical characteristics, and outcomes were collected. A predictive score (FLAMINCOV) was developed using logistic regression. Regression coefficients were used to calculate the score. External validation was performed in a cohort including elderly patients from a major COVID-19 centre in Israel. Discrimination was evaluated using the area under the receiver operating characteristic curve (AUC) in the derivation and validation cohorts. Survival risk groups based on the score were derived and applied to the validation cohort.

RESULTS

Among 3010 patients included in the derivation cohort, 30-day survival was 74.5% (2242/3010). The intensive care unit admission rate was 7.6% (228/3010). The model predicting survival included independent functional status (OR, 4.87; 95% CI, 3.93-6.03), a oxygen saturation to fraction of inspired oxygen (SpO₂/FiO₂₎ ratio of >235 (OR, 3.75; 95% CI, 3.04-4.63), a C-reactive protein level of <14 mg/dL (OR, 2.41; 95% CI, 1.91-3.04), a creatinine level of <1.3 (OR, 2.02; 95% CI, 1.62-2.52) mg/dL, and absence of fever (OR, 1.34; 95% CI, 1.09-1.66). The score was validated in 1174 patients. The FLAMINCOV score ranges from 0 to 15 and showed good discrimination in the derivation (AUC, 0.79; 95% CI, 0.77-0.81; p < 0.001) and validation cohorts (AUC, 0.79; 95% CI, 0.76-0.81; p < 0.001). Thirty-day survival ranged from 39.4% (203/515) to 95.3% (634/665) across four risk groups according to score quartiles in the derivation cohort. Similar proportions were observed in the validation set.

DISCUSSION

The FLAMINCOV score identifying elderly with higher or lower chances of survival may allow better triage and management, including intensive care unit admission/exclusion.