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Research
Analysis of Risk Factors Progression of Preterm Delivery Using Electronic Health Records
Sabri Boughorbel
Sidra Medicine Department of Emergency Medicine
Corresponding Author
ORCiD: https://orcid.org/0000-0003-2734-3356
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Preterm deliveries have many negative health implications on both mother and child. Identifying the population level factors that increase the risk of preterm deliveries is an important step in the direction of mitigating the impact and reducing the frequency of occurrence of preterm deliveries. The purpose of this work is to identify preterm delivery risk factors and their progression throughout the pregnancy from a large collection of Electronic Health Records (EHR).
Results: The study cohort includes more than 60,000 deliveries in the USA with the complete medical history from EHR for diagnoses, medications, procedures and demographics. We propose a temporal analysis of risk factors by estimating and comparing risk ratios at different time points prior to the delivery event. We selected the following time points before delivery: 9, 6, 3 and 1 month(s). We did so by conducting a retrospective cohort study of patient history for a selected set of mothers who delivered preterm and a control group of mothers that delivered full-term. We analyzed the extracted data using a logistic regression model. The results of our analyses showed that the highest risk ratio corresponds to history of previous preterm delivery. Other risk factors were identified, some of which are consistent with those that are reported in the literature, others need further investigation.
Conclusions: The comparative analysis of the risk factors at different time points showed that risk factors in the early pregnancy related to patient history and chronic condition, while the risk factors in late pregnancy are specific to the current pregnancy. Our analysis unifies several previously reported studies on preterm risk factors. It also gives important insights on the changes of risk factors in the course of pregnancy.
Keywords
preterm, pregnancy, EHR, epidemiology, risk factors, progression, temporal analysis, precision medicine, predictive models
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CURRENT STATUS: Under Revision
Version 1
Posted 28 Sep, 2020
No community comments so far
Editorial decision: Major revision
On 13 Nov, 2020
Review #2 received
Received 03 Nov, 2020
Review #3 received
Received 03 Nov, 2020
Review #1 received
Received 25 Oct, 2020
Reviewer #3 agreed
On 22 Oct, 2020
Reviewer #2 agreed
On 20 Oct, 2020
Reviewers invited
Invitations sent on 10 Oct, 2020
Reviewer #1 agreed
On 10 Oct, 2020
Editor assigned
On 24 Sep, 2020
First submitted
On 23 Sep, 2020
Submission checks complete
On 23 Sep, 2020
Editor invited
On 23 Sep, 2020
Metrics
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PDF Downloads: ...
HTML Views: ...
Subject Areas
Maternal & Fetal Medicine
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This preprint is under consideration at BioData Mining. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Analysis of Risk Factors Progression of Preterm Delivery Using Electronic Health Records
Sabri Boughorbel
Sidra Medicine Department of Emergency Medicine
Corresponding Author
ORCiD: https://orcid.org/0000-0003-2734-3356
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Revision
Version 1
Posted 28 Sep, 2020
No community comments so far
Editorial decision: Major revision
On 13 Nov, 2020
Review #2 received
Received 03 Nov, 2020
Review #3 received
Received 03 Nov, 2020
Review #1 received
Received 25 Oct, 2020
Reviewer #3 agreed
On 22 Oct, 2020
Reviewer #2 agreed
On 20 Oct, 2020
Reviewers invited
Invitations sent on 10 Oct, 2020
Reviewer #1 agreed
On 10 Oct, 2020
Editor assigned
On 24 Sep, 2020
First submitted
On 23 Sep, 2020
Submission checks complete
On 23 Sep, 2020
Editor invited
On 23 Sep, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Maternal & Fetal Medicine
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Preterm deliveries have many negative health implications on both mother and child. Identifying the population level factors that increase the risk of preterm deliveries is an important step in the direction of mitigating the impact and reducing the frequency of occurrence of preterm deliveries. The purpose of this work is to identify preterm delivery risk factors and their progression throughout the pregnancy from a large collection of Electronic Health Records (EHR).
Results: The study cohort includes more than 60,000 deliveries in the USA with the complete medical history from EHR for diagnoses, medications, procedures and demographics. We propose a temporal analysis of risk factors by estimating and comparing risk ratios at different time points prior to the delivery event. We selected the following time points before delivery: 9, 6, 3 and 1 month(s). We did so by conducting a retrospective cohort study of patient history for a selected set of mothers who delivered preterm and a control group of mothers that delivered full-term. We analyzed the extracted data using a logistic regression model. The results of our analyses showed that the highest risk ratio corresponds to history of previous preterm delivery. Other risk factors were identified, some of which are consistent with those that are reported in the literature, others need further investigation.
Conclusions: The comparative analysis of the risk factors at different time points showed that risk factors in the early pregnancy related to patient history and chronic condition, while the risk factors in late pregnancy are specific to the current pregnancy. Our analysis unifies several previously reported studies on preterm risk factors. It also gives important insights on the changes of risk factors in the course of pregnancy.
Figure 1
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.