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A Simple Algorithm for Predicting Bacteremia Using Food Consumption and Shaking Chills: A Prospective Observational

Takayuki Komatsu¹, Erika Takahashi¹, Kentaro Mishima¹

¹Department of Emergency and Critical Care Medicine, Juntendo University Nerima Hospital, Tokyo, Japan.

Journal of Hospital Medicine

|July 13, 2017

Summary

Clinical prediction of bacteremia is unreliable. A simple algorithm using food consumption and shaking chills effectively predicts true bacteremia, aiding in early diagnosis.

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Area of Science:

Infectious Diseases
Clinical Diagnostics
Medical Algorithms

Background:

Clinical examination alone is insufficient for reliably predicting true bacteremia.
Accurate prediction of bacteremia is crucial for timely and appropriate patient management.

Purpose of the Study:

To develop a simple, effective algorithm for predicting true bacteremia.
To utilize readily available clinical indicators: food consumption and shaking chills.

Main Methods:

A prospective, multicenter observational study involving 1,943 hospitalized patients.
Assessment of oral food intake (normal vs. poor consumption) and presence of shaking chills prior to blood culture.
Recursive partitioning analysis to construct the predictive algorithm.

Main Results:

Poor food consumption and shaking chills were strongly associated with true bacteremia (47.7% incidence).
Poor food consumption demonstrated high sensitivity (93.7%) for true bacteremia.
Normal food consumption had a low negative likelihood ratio (0.18), effectively excluding bacteremia.

Conclusions:

A 2-item screening checklist (food consumption and shaking chills) shows excellent statistical properties.
This simple instrument can reliably predict the presence or absence of true bacteremia.