Inter-observer agreement in clinical decision-making for abnormal cardiotocogram (CTG) during labour: a comparison
C Vayssière1, V Tsatsaris, O Pirrello
1Department of Obstetrics and Gynaecology, CMCO-SIHCUS, Louis Pasteur University, Strasbourg, France. cvayssiere@club-internet.fr
Insights
Adding ST-segment analysis (STAN) to cardiotocography (CTG) improved consistency in clinical decisions for abnormal fetal heart rate tracings. This approach may reduce unnecessary interventions during labor, though rare unjustified non-interventions can occur.
Area of Science:
- Obstetrics and Gynecology
- Fetal Monitoring
- Clinical Decision-Making
Background:
- Cardiotocography (CTG) is a standard method for fetal monitoring during labor.
- Inter-observer agreement in interpreting CTG tracings can be variable, impacting clinical decisions.
- ST-segment analysis (STAN) is a complementary technique to CTG that analyzes fetal electrocardiogram signals.
Purpose of the Study:
- To compare the inter-observer agreement in clinical decision-making between using cardiotocography (CTG) alone and using CTG combined with ST-segment analysis (STAN).
- To evaluate the impact of STAN on obstetricians' decisions to intervene or not intervene during labor based on fetal monitoring data.
Main Methods:
- An experimental study involving seven obstetricians assessing 30 non-reassuring CTG recordings.
- Recordings were assessed independently in two sessions: first with CTG alone, then with CTG + STAN.
- Intervention decisions were analyzed based on predefined pH criteria for justified intervention or non-intervention.
Main Results:
- Inter-observer agreement (Kappa) increased from 0.50 with CTG to 0.67 with CTG + STAN.
- Agreement for justified non-intervention significantly improved with CTG + STAN (84%) compared to CTG alone (56%).
- Agreement for justified intervention decreased slightly with CTG + STAN (85%) compared to CTG alone (94%).
Conclusions:
- Combining CTG with STAN enhances consistency in clinical decision-making for abnormal fetal monitoring.
- STAN may help reduce unnecessary interventions, but careful consideration is needed to avoid potential unjustified non-intervention decisions.
- Further research may be warranted to optimize the use of STAN in clinical practice.
Objective:
To compare inter-observer agreement for clinical decision-making with cardiotocography (CTG) and combined CTG with ST-segment analysis (STAN).
Design:
Experimental study.
Setting:
Three hospital obstetrics departments in France.
Population:
Thirty randomly selected nonreassuring CTG recordings during labour of women with singleton term pregnancies in cephalic position.
Methods:
Seven obstetricians independently assessed the tracings, displayed in a random order on their computers, on two separate sessions, the first without and the second with STAN information. The observers received clinical information about the labour as the tracings continued and were asked whether they would intervene. For analysis, we considered that intervention was justified for the neonates with pH < 7.05 and that nonintervention was justified for those with a pH > 7.10 after spontaneous delivery.
Main Outcome Measures:
Kappa values and rates of inter-observer agreement for intervention and for nonintervention.
Results:
Kappa for inter-observer agreement was 0.50 (0.29-0.69) with CTG, and 0.67 (0.48-0.81) with CTG + STAN. The rate of inter-observer agreement for the decision to intervene was 73% (68-77%) with CTG and 70% (66-75%) with CTG + STAN (P = 0.4), and for the nonintervention decision it was 48% (42-54%) and 69% (64-74%), respectively (P < 0.0001). The rate of agreement for justified intervention was 94% (91-97%) with CTG and 85% (80-90%) with CTG + STAN (P < 0.001) and for justified nonintervention, 56% (48-63%) with CTG and 84% (79-89%) with CTG + STAN (P < 0.0001).
Conclusions:
In cases with abnormal CTG, ST analysis may improve consistency in clinical decision-making and decrease unnecessary interventions, but may also lead on rare occasions to unjustified decisions not to intervene.
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