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2014 ; 211
(5
): 530.e1-4
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gab.com Text
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Spontaneous and indicated preterm birth subtypes: interobserver agreement and
accuracy of classification
#MMPMID24844852
Stout MJ
; Busam R
; Macones GA
; Tuuli MG
Am J Obstet Gynecol
2014[Nov]; 211
(5
): 530.e1-4
PMID24844852
show ga
OBJECTIVE: The purpose of this study was to estimate interobserver variability
and correct classification of preterm birth into spontaneous and indicated
subtypes. STUDY DESIGN: This was a cross-sectional study in which a trained
obstetric nurse, maternal fetal medicine (MFM) fellow, and MFM faculty member
independently reviewed discharge summaries and full medical records to classify
preterm birth into "spontaneous" and "indicated" subtypes. Consensus
classification was obtained with a senior faculty member and was considered the
correct classification. Proportions of correct classification by both discharge
summary and full medical record review and by level of reviewer were compared
with the use of the ?(2) test. Interobserver variability was estimated with the
use of Fleiss' kappa. RESULTS: Of 132 preterm births, 58.8% were spontaneous.
Interrater agreement for classification of preterm birth subtype based on the
full medical record review was substantial (0.79; 95% confidence interval,
0.76-0.80). Interrater agreement was slightly less, based on discharge summary
classification alone (Kappa, 0.73; 95% confidence interval, 0.71-0.79) compared
with a full medical record review, but this difference was not significant (P =
.3). Correct classifications for research nurse, MFM fellow, and MFM faculty
member were 85%, 95%, and 93%, respectively, for the full medical records and
85%, 93%, and 92%, respectively, for the discharge summaries alone. There was no
significant improvement in correct classification based on full medical record
review compared with discharge summary alone for any level of reviewer (P > .6).
CONCLUSION: There is substantial, but imperfect, agreement between reviewers for
classification of preterm birth into spontaneous and indicated subtypes.
Incorrect classification may occur 5-15% of the time, even with experienced
research personnel. Discharge summaries that are populated with pertinent
clinical data may streamline accuracy for research efficiency.
|Cesarean Section/statistics & numerical data
[MESH]
|Clinical Competence/*statistics & numerical data
[MESH]