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Clinical prediction rules for bacteremia and in‐hospital death based on clinical data at the time of blood withdrawal for culture: an evaluation of their development and use
Author(s) -
Nakamura Tsukasa,
Takahashi Osamu,
Matsui Kunihiko,
Shimizu Shiro,
Setoyama Motoichi,
Nakagawa Masahisa,
Fukui Tsuguya,
Morimoto Takeshi
Publication year - 2006
Publication title -
journal of evaluation in clinical practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.737
H-Index - 73
eISSN - 1365-2753
pISSN - 1356-1294
DOI - 10.1111/j.1365-2753.2006.00637.x
Subject(s) - bacteremia , medicine , blood culture , logistic regression , emergency medicine , intensive care medicine , antibiotics , microbiology and biotechnology , biology
Rationale, aims and objectives  To develop clinical prediction rules for true bacteremia, blood culture positive for gram‐negative rods, and in‐hospital death using the data at the time of blood withdrawal for culture. Methods  Data on all hospitalized adults who underwent blood cultures at a tertiary care hospital in Japan were collected from an integrated medical computing system. Logistic regression was used for developing prediction rules followed by the jackknife cross validation. Results  Among 739 patients, 144 (19.5%) developed true bacteremia, 66 (8.9) were positive for gram‐negative rods, and 203 (27.5%) died during hospitalization. Prediction rule based on the data at the time of blood withdrawal for culture stratified them into five groups with probabilities of true bacteremia 6.5, 9.6, 21.9, 30.1, and 59.6%. For blood culture positive for gram‐negative rods, the probabilities were 0.6, 4.7, 8.6, and 31.7%, and for in‐hospital death, those were 6.7, 15.5, 26.0, 35.5, and 56.1%. The area of receiver operating characteristic for true bacteremia, blood culture positive for gram‐negative rods, and in‐hospital death were 0.73, 0.64, and 0.64, respectively, in original cohort and 0.72, 0.64, and 0.64 in validation respectively. Conclusions  The clinical prediction rules are helpful for improved clinical decision making for bacteremia patients.

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