Literature DB >> 28699938

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

Takayuki Komatsu1, Erika Takahashi1, Kentaro Mishima1, Takeo Toyoda2, Fumihiro Saitoh3, Akari Yasuda4, Joe Matsuoka5, Manabu Sugita1, Joel Branch6, Makoto Aoki7, Lawrence Tierney8, Kenji Inoue9.   

Abstract

BACKGROUND: Predicting the presence of true bacteremia based on clinical examination is unreliable.
OBJECTIVE: We aimed to construct a simple algorithm for predicting true bacteremia by using food consumption and shaking chills.
DESIGN: A prospective multicenter observational study.
SETTING: Three hospital centers in a large Japanese city. PARTICIPANTS: In total, 1,943 hospitalized patients aged 14 to 96 years who underwent blood culture acquisitions between April 2013 and August 2014 were enrolled. Patients with anorexia-inducing conditions were excluded.
INTERVENTIONS: We assessed the patients' oral food intake based on the meal immediately prior to the blood culture with definition as "normal food consumption" when >80% of a meal was consumed and "poor food consumption" when <80% was consumed. We also concurrently evaluated for a history of shaking chills. MEASUREMENTS: We calculated the statistical characteristics of food consumption and shaking chills for the presence of true bacteremia, and subsequently built the algorithm by using recursive partitioning analysis.
RESULTS: Among 1,943 patients, 223 cases were true bacteremia. Among patients with normal food consumption, without shaking chills, the incidence of true bacteremia was 2.4% (13/552). Among patients with poor food consumption and shaking chills, the incidence of true bacteremia was 47.7% (51/107). The presence of poor food consumption had a sensitivity of 93.7% (95% confidence interval [CI], 89.4%-97.9%) for true bacteremia, and the absence of poor food consumption (ie, normal food consumption) had a negative likelihood ratio (LR) of 0.18 (95% CI, 0.17-0.19) for excluding true bacteremia, respectively. Conversely, the presence of the shaking chills had a specificity of 95.1% (95% CI, 90.7%-99.4%) and a positive LR of 4.78 (95% CI, 4.56-5.00) for true bacteremia.
CONCLUSION: A 2-item screening checklist for food consumption and shaking chills had excellent statistical properties as a brief screening instrument for predicting true bacteremia.
© 2017 Society of Hospital Medicine

Entities:  

Mesh:

Year:  2017        PMID: 28699938     DOI: 10.12788/jhm.2764

Source DB:  PubMed          Journal:  J Hosp Med        ISSN: 1553-5592            Impact factor:   2.960


  7 in total

1.  A bacteraemia risk prediction model: development and validation in an emergency medicine population.

Authors:  Agustín Julián-Jiménez; Juan González Del Castillo; Eric Jorge García-Lamberechts; Itziar Huarte Sanz; Carmen Navarro Bustos; Rafael Rubio Díaz; Josep María Guardiola Tey; Ferrán Llopis-Roca; Pascual Piñera Salmerón; Mikel de Martín-Ortiz de Zarate; Jesús Álvarez-Manzanares; Julio Javier Gamazo-Del Rio; Marta Álvarez Alonso; Begoña Mora Ordoñez; Oscar Álvarez López; María Del Mar Ortega Romero; María Del Mar Sousa Reviriego; Ramón Perales Pardo; Henrique Villena García Del Real; María José Marchena González; José María Ferreras Amez; Félix González Martínez; Francisco Javier Martín-Sánchez; Pedro Beneyto Martín; Francisco Javier Candel González; Antonio Jesús Díaz-Honrubia
Journal:  Infection       Date:  2021-09-06       Impact factor: 3.553

2.  Internal medicine residents' evaluation of fevers overnight.

Authors:  Jessica Howard-Anderson; Kristin E Schwab; Sandy Chang; Holly Wilhalme; Christopher J Graber; Roswell Quinn
Journal:  Diagnosis (Berl)       Date:  2019-06-26

3.  [Predictive factors of bacteraemia in the patients seen in emergency departments due to infections].

Authors:  S Z Iqbal-Mirza; R Estévez-González; V Serrano-Romero de Ávila; E de Rafael González; E Heredero-Gálvez; A Julián-Jiménez
Journal:  Rev Esp Quimioter       Date:  2019-11-29       Impact factor: 1.553

4.  Bandemia as an Early Predictive Marker of Bacteremia: A Retrospective Cohort Study.

Authors:  Taku Harada; Yukinori Harada; Kohei Morinaga; Takanobu Hirosawa; Taro Shimizu
Journal:  Int J Environ Res Public Health       Date:  2022-02-17       Impact factor: 3.390

5.  Diagnostic accuracy of quick SOFA score and inflammatory biomarkers for predicting community-onset bacteremia.

Authors:  Takashi Matono; Maki Yoshida; Hidenobu Koga; Rie Akinaga
Journal:  Sci Rep       Date:  2022-07-01       Impact factor: 4.996

Review 6.  [New predictive models of bacteremia in the emergency department: a step forward].

Authors:  A Julián-Jiménez; R Rubio-Díaz; J González Del Castillo; F J Candel
Journal:  Rev Esp Quimioter       Date:  2022-04-13       Impact factor: 2.515

7.  Stability of intrinsic rhythm in pacemaker-dependent patients during pacemaker replacement: Can we predict the need for temporary pacing?

Authors:  Yuki Kimura; Masataka Sumiyoshi; Kenji Inoue; Masayuki Shiozaki; Kentaro Fukuda; Yasumasa Fujiwara; Haruna Tabuchi; Hidemori Hayashi; Gaku Sekita; Takashi Tokano; Yuji Nakazato; Hiroyuki Daida
Journal:  J Arrhythm       Date:  2018-05-28
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.