TWELVE HOUR OBSERVATION UNIT DIAGNOSIS OF TUBERCULOSIS
TWELVE HOUR OBSERVATION UNIT DIAGNOSIS OF TUBERCULOSIS
批准号:
2236886
负责人:
DANIEL MURPHY
金额:
$7.37万
依托单位国家:
美国
项目类别:
财政年份:
1994
资助国家:
美国
项目状态:
已结题
起止时间:
1994-09-30 至 1996-09-29
中文摘要
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英文摘要
The broad, longterm objective of this project is to improve the allocation
of scarce tuberculosis (TB) isolation beds for patients who present to a
hospital Emergency Department (ED) with suspected TB. By providing an
accurate classification of sputum acid-fast bacilli (AFB) positive or
negative TB from the ED, we would decrease the costs of construction and
management of in-hospital isolation bed units, and decrease the risk to
health care workers (HCWs) and other patients to TB transmission. We
hypothesize that the recommendation for isolation or no isolation after a
12 hour encounter in an Emergency Department Observation Unit (EDOU) is
more accurate than routine ED recommendation, and has high concordance
rates with the more prolonged inpatient diagnostic assessment period,
during which the patient is maintained in TB isolation. The first
specific aim is to compare the sensitivity, specificity, positive
predictive value and negative predictive value of direct microscopic
detection of AFB when performed on 3 serial sputum samples obtained within
12 hours in an EDOU versus 3 early morning sputum samples obtained during
consecutive hospital days, The second specific aim is to determine the
accuracy of a standardized clinical assessment obtained in the ED that
considers patient history, risk factors, physical exam and chest
radiograph at presentation in predicting the diagnosis of active pulmonary
TB. The third specific aim is to compare the sensitivity and specificity
of the diagnosis of TB in the EDOU versus In-Patient Isolation Unit (IPIU)
assessing the diagnostic capability of the EDOU as a rapid identifier of
new TB cases allowing more precise indications for hospitalization and the
use of TB isolation beds. We will evaluate independent variables obtained
in the EDOU to examine which are most closely associated with either smear
positive or culture positive TB. We will perform multivariate logistic
regression data in order to develop a model for diagnosis of both culture
proven and infectious TB.
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