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Filename: drivers/Session_files_driver.php
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Function: strpos
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Function: insertAPISummary
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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File: /var/www/html/index.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
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Objective: To develop a model that uses cervical effacement, fetal station, and parity to predict progress during the first stage of labor.
Study Design: This was a secondary analysis of a cohort of 1,128 parturients delivering after 34 weeks. Timed cervical exams from each patient were fit with a biexponential model. Methods for consideration of fetal station, cervical effacement and parity were developed and validated.
Results: The biexponential model fit the data in an unbiased manner with a median absolute prediction error of 1.1 cm. Although nulliparous women had slower active labor, they did not differ from multiparous women in their rate of latent labor or the cervical dilation at which they transitioned to active labor. In addition, nulliparous women began laboring with a more effaced cervix (45 vs. 31%) and lower fetal station (-2.8 vs. -3.2).
Conclusion: We validated a biexponential model for labor progress using a large mixed parity cohort. We demonstrated that parity and initial fetal station add important clinical information that can be used to make a labor model more accurate. As such, parity and fetal station can be utilized in such structural models to predict normal labor progress and potentially identify abnormalities in labor progress.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1055/s-0033-1359721 | DOI Listing |
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