Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT00086151 |
| Other study ID # |
1258 |
| Secondary ID |
R21HL075521 |
| Status |
Completed |
| Phase |
N/A
|
| First received |
June 25, 2004 |
| Last updated |
July 28, 2016 |
| Start date |
July 2004 |
| Est. completion date |
June 2007 |
Study information
| Verified date |
January 2008 |
| Source |
National Heart, Lung, and Blood Institute (NHLBI) |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
United States: Federal Government |
| Study type |
Observational
|
Clinical Trial Summary
To develop a clinical prediction rule to identify patients with acute pulmonary embolism who
are at very low risk for short-term adverse outcomes.
Description:
BACKGROUND:
Pulmonary embolism (PE) is a common, costly, and potentially lethal disease in the US. While
patients with PE are almost universally treated as inpatients and their length of hospital
stay (LOS) varies widely, there is evidence that outpatient care with low-molecular-weight
heparins or early discharge of hospitalized patients are effective and safe options for up
to 50% of patients with PE. However, physicians may be reluctant to treat patients with PE
on an outpatient basis or with brief hospitalization when the perceived risk of mortality or
experiencing a short-term adverse outcome is not well quantified. The study will develop a
clinical prediction rule to identify patients with acute pulmonary embolism who are at very
low risk for short-term adverse outcomes.
DESIGN NARRATIVE:
The retrospective cohort study will develop a clinical prediction rule that accurately
identifies low-risk patients with PE who are potential candidates for outpatient care or
early discharge. The specific aims are 1) to derive a clinical prediction rule that
identifies patients with PE who have a very low 30-day mortality risk (<= 2%), and 2) to
assess the performance of this rule in predicting other relevant outcomes (i.e., major
bleeding, respiratory failure [RF], cardiogenic shock, cardiac arrest) or processes of care
(i.e., thrombolysis, mechanical ventilation [MV], intensive care unit (ICU) admission,
length of hospital stay, hospital readmission).
The study uses 3 large and reliable databases, the PHC4 database, the MediQual Atlas
database, and the National Death Index (NDI). These databases contain a rich set of clinical
information and outcomes data. The prediction rule for prognosis will be derived from 8,000
patients discharged with a diagnosis of PE from all acute care hospitals in Pennsylvania
during the calendar years 2000-2001. Patients with PE will be identified using primary
ICD-9-CM discharge codes for PE or secondary discharge codes for PE coupled with primary
discharge codes that represent complications or treatments of PE. Baseline data that include
35 potential clinical predictors of short-term mortality in PE will be abstracted from the
PHC4/Atlas databases.
The primary outcome will be 30-day mortality ascertained from the NDI; secondary outcomes
will be major bleeding, respiratory failure, cardiogenic shock, cardiac arrest,
thrombolysis, mechanical ventilation, ICU admission, length of hospital stay, and
readmission. Classification tree analysis will be used to construct a simple clinical
prediction rule that identifies a 20% subgroup of all patients with a 30-day mortality rate
of 2% or less. The predictive accuracy of this rule will be externally validated in an
independent cohort of 4,000 patients with PE from calendar year 2002 using identical patient
identification strategies as for the derivation cohort. The safety of this rule will be
tested in the validation cohort by computing the proportion of very low-risk patients who
die within 30-days or have another adverse outcome. This innovative application will derive
a clinical prediction rule for prognosis that has the potential to improve the
cost-effectiveness of the management for PE. The long-term goal of this project will be to
validate and implement this rule in prospective studies to test its safety and effectiveness
and to establish future admission/early hospital discharge recommendations for patients with
PE.
