Long-term mortality due to infection associated with elevated liver enzymes: a population-based cohort study

Development and derivation of bacteremia prediction model in patients with hepatobiliary infection

INTRODUCTION

Hepatobiliary infections are common in the emergency department (ED), and the mortality rate for this condition is high. A suitable bacteremia prediction model would support prompt identification of bacteremia and appropriate management of hepatobiliary infections in the ED. Therefore, we attempted to produce a bacteremia prediction model with both internal and external validation for hepatobiliary infections in the ED.

METHODS

Patients with hepatobiliary infection were extracted from retrospective cohort databases of two tertiary hospitals from January 2018 to December 2019 and from January 2016 to December 2019, respectively. Independent risk factors were determined using multivariable logistic regression in a developmental cohort. We assigned a weighted value to predictive factors and developed a prediction model, which was validated both internally and externally. We assessed discrimination using the area under the receiver operating characteristics curve (AUC).

RESULTS

One hospital cohort of 1568 patients was randomly divided into a developmental group of 927 patients (60%) and an internal validation group of 641 patients (40%), and 736 people from the other hospital cohort were used for external validation. Bacteremia rates were 20.5%, 18.1%, and 23.1% in the developmental, internal, and external validation cohorts, respectively. Nine significant factors were used for predicting bacteremia, including age, three vital signs, and five laboratory tests. After applying our bacteremia prediction rule to the validation cohort, 56.5% and 53.8% of the internal and external validation groups were classified as low-risk bacteremia groups (bacteremia rates: 8.6% and 13.9%, respectively). The AUCs were 0.727 (95% confidence interval [CI]: 0.686-0.767), 0.730 (95% CI: 0.679-0.781), and 0.715 (95% CI: 0.672-0.758) for the developmental, internal, and external validation cohorts, respectively. The sensitivity and specificity for internal validation/external validation was 73.2%/67.6% and 63.0%/60.2%, respectively.

CONCLUSION

A bacteremia prediction model for hepatobiliary infection might be useful to predict the risk of bacteremia. It might also reduce the need for blood culture in low-risk patients.

Official health communications are failing PFAS-contaminated communities

BACKGROUND

Environmental health agencies are critical sources of information for communities affected by chemical contamination. Impacted residents and their healthcare providers often turn to federal and state agency webpages, fact sheets, and other documents to weigh exposure risks and interventions.

MAIN BODY

This commentary briefly reviews scientific evidence concerning per- and polyfluoroalkyl substances (PFAS) for health outcomes that concern members of affected communities and that have compelling or substantial yet differing degree of scientific evidence. It then features official documents in their own language to illustrate communication gaps, as well as divergence from scientific evidence and from best health communication practice. We found official health communications mostly do not distinguish between the needs of heavily contaminated communities characterized by high body burdens and the larger population with ubiquitous but substantially smaller exposures. Most health communications do not distinguish levels of evidence for health outcomes and overemphasize uncertainty, dismissing legitimate reasons for concern in affected communities. Critically, few emphasize helpful approaches to interventions. We also provide examples that can be templates for improvement.

CONCLUSIONS

Immediate action should be undertaken to review and improve official health communications intended to inform the public and health providers about the risks of PFAS exposure and guide community and medical decisions.