tetano
Editor, Senior Moderator
Am J Emerg Med. 2013 Feb 1. pii: S0735-6757(12)00535-9. doi: 10.1016/j.ajem.2012.10.010. [Epub ahead of print]
Derivation of a clinical prediction rule to predict hospitalization for influenza in EDs.
Chen KF, Hsieh YH, Gaydos CA, Valsamakis A, Rothman RE.
Source
Department of Emergency Medicine, Chang Gung University and Chang Gung Memorial Hospital, Keelung, Taiwan. Electronic address: kfchen@cgmh.org.tw.
Abstract
BACKGROUND:
Early, rapid, and accurate identification of those patients who have severe influenza is important for emergency physicians. Influenza viral load, which has been proposed as a predictor of severe influenza, could be useful in facilitating decision making of resource use. We aimed to derive a clinical prediction rule to indicate probability for inpatient hospitalization for patients with influenza, which includes influenza viral load in addition to other clinical information commonly collected in the emergency department (ED).
METHODS:
We conducted a 3-year prospective cohort study (2007-2009) of patients with probable influenza infection as suspected by the emergency physician from 3 study sites. Eligible patients were those with excess nasopharyngeal aspirate samples. Influenza viral load was measured using reverse transcription polymerase chain reaction and electrospray ionization mass spectrometry. Clinical information including demographics, underlying illness, vaccination history, hospitalization, and results from clinical laboratory were abstracted from electronic patient records and questionnaires. The prediction rule for hospitalization was derived by the recursive partitioning algorithm (decision tree-type approach) and evaluated by internal 10-fold cross-validation for performance characteristics.
RESULTS:
Of 424 ED patients with nasopharyngeal aspirates, 146 infected with influenza were enrolled (median age, 10 years [interquartile range, 4-26]; race, 55% African American; median inpatient length of stay, 3 days [interquartile range, 1-4]; high viral load group [defined as >2.5 million genome copies/mL], 34%). Predictors for hospitalization included underlying illness, age, influenza viral load level, and vaccination history (c statistics, 0.84; sensitivity, 83%; specificity, 76%).
CONCLUSIONS:
The clinical prediction rule incorporating influenza viral load into the clinical information was indicative of hospitalization and merits further evaluation for determination of ED resource use for patients with influenza.
Copyright ? 2012 Elsevier Inc. All rights reserved.
PMID:
23380103
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/23380103
Derivation of a clinical prediction rule to predict hospitalization for influenza in EDs.
Chen KF, Hsieh YH, Gaydos CA, Valsamakis A, Rothman RE.
Source
Department of Emergency Medicine, Chang Gung University and Chang Gung Memorial Hospital, Keelung, Taiwan. Electronic address: kfchen@cgmh.org.tw.
Abstract
BACKGROUND:
Early, rapid, and accurate identification of those patients who have severe influenza is important for emergency physicians. Influenza viral load, which has been proposed as a predictor of severe influenza, could be useful in facilitating decision making of resource use. We aimed to derive a clinical prediction rule to indicate probability for inpatient hospitalization for patients with influenza, which includes influenza viral load in addition to other clinical information commonly collected in the emergency department (ED).
METHODS:
We conducted a 3-year prospective cohort study (2007-2009) of patients with probable influenza infection as suspected by the emergency physician from 3 study sites. Eligible patients were those with excess nasopharyngeal aspirate samples. Influenza viral load was measured using reverse transcription polymerase chain reaction and electrospray ionization mass spectrometry. Clinical information including demographics, underlying illness, vaccination history, hospitalization, and results from clinical laboratory were abstracted from electronic patient records and questionnaires. The prediction rule for hospitalization was derived by the recursive partitioning algorithm (decision tree-type approach) and evaluated by internal 10-fold cross-validation for performance characteristics.
RESULTS:
Of 424 ED patients with nasopharyngeal aspirates, 146 infected with influenza were enrolled (median age, 10 years [interquartile range, 4-26]; race, 55% African American; median inpatient length of stay, 3 days [interquartile range, 1-4]; high viral load group [defined as >2.5 million genome copies/mL], 34%). Predictors for hospitalization included underlying illness, age, influenza viral load level, and vaccination history (c statistics, 0.84; sensitivity, 83%; specificity, 76%).
CONCLUSIONS:
The clinical prediction rule incorporating influenza viral load into the clinical information was indicative of hospitalization and merits further evaluation for determination of ED resource use for patients with influenza.
Copyright ? 2012 Elsevier Inc. All rights reserved.
PMID:
23380103
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/23380103