Assessing Risk of Interfacility Transport in Pregnant Patients due to Progression of Labor – Lessons from a Specialized Maternal-Fetal Transport Program

Assessing Risk of Interfacility Transport in Pregnant Patients due to Progression of Labor – Lessons from a Specialized Maternal-Fetal Transport Program | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessing Risk of Interfacility Transport in Pregnant Patients due to Progression of Labor – Lessons from a Specialized Maternal-Fetal Transport Program Thomas Lardaro, Adhitya Balaji, Diane Kuhn, Nancy Glober, Christine M Brent, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4345052/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Pregnant laboring patients sometimes require interfacility transfer to a higher level of care. There is a paucity of evidence to inform when it is safe to transfer a laboring patient and when delivery may be too imminent to transfer. Methods This is a retrospective study of pregnant patients undergoing interfacility transfer with a specialized obstetric transport team deployed from a large Midwest regional healthcare system. The primary outcome was delivery prior to or within 1 hour of arrival at the receiving institution due to progression of labor. Data collected included basic demographics, vital signs, gravity, parity, gestational age, contraction frequency if contractions were present, and cervical dilation. We sought to define the association between these variables and the primary outcome to inform risk assessment for precipitous delivery among patients being considered for interfacility transfer. Results Of 370 pregnant patients for whom the specialized transfer team was requested, 11 (3%) met the primary outcome. Those with more advanced cervical dilation and those who did not have regular prenatal care were more likely to meet the criteria for the primary outcome. For every centimeter of cervical dilation, the odds of meeting the primary outcome increased 2.3-fold (95% CI 1.5 to 3.4). Conclusions We identify risk factors for early delivery among pregnant patients for whom an interfacility transfer was requested and describe patients who were high-risk for obstetric interfacility transport due to progression of labor. Our results can help inform risk assessments for the transfer of potentially high-risk laboring patients. Interfacility transport Labor Obstetric transport Pregnancy Emergency medicine EMTALA EMS Figures Figure 1 Background Pregnant women in labor often present to hospitals that are ill-equipped to deal with obstetric or newborn patients. In these scenarios, clinicians must weigh the risks and benefits of if, when, and how to transfer the patient to a more appropriate hospital or level of care. The inherent risk of a precipitous delivery during transport is of paramount concern for the interfacility transfer of high-risk patients in labor. The limited resources and physical space within which transport crews work present considerable challenges for managing the delivery and subsequent care of a mother and newborn, including any complications that may arise. Given the myriad of factors involved, establishing a set of standards for the appropriateness of interfacility transport for laboring patients is challenging. The incidence of precipitous delivery during transport is low, especially after the 1986 implementation of the Emergency Medical Treatment and Active Labor Act (EMTALA) in the United States (US) 1,2,3 . The screening of patients in labor just before transport appears to play a significant role in this regard 3 . Several studies have investigated the use of physiological signs to predict the duration of active labor 4,5 . Yet, there remains a sparsity of data on how these physiological predictors might inform the decision-making process regarding the transport of high-risk laboring patients. This study aims to inform clinical decision making regarding the timing of interfacility transport with respect to delivery. Methods This is a retrospective case-control analysis including all pregnant patients transported by a specialized obstetric transport team deployed from a 15-hospital healthcare system in the Midwestern US between January 2021 through May 2022. The transport team consisted of a critical care transport nurse with an expanded scope of practice through emergency medical services (EMS) protocols authorized by a physician medical director and an obstetric nurse capable of maternal-fetal monitoring, such as cardiotocography. The team is deployed by air or ground at the discretion of the sending physician (“requesting physician” in this study), with a third team member serving as vehicle operator (pilot or driver). Team deployment is usually requested for high-risk obstetric patients – including for reasons of maternal or fetal distress not necessarily involving progression of labor – in order to transport the patient to a higher level of care for the mother and/or neonate. The transport team has real-time access via telephone to an on-line medical control obstetric physician for any questions or concerns. The on-line medical control physician can place orders and has the authority to decline immediate transport in favor of delivery at the sending hospital prior to transport. Reasons for postponing transport may include imminent delivery and/or fetal or maternal distress – such as eclampsia or prolonged recurrent decelerations on fetal heart tracing – or if the transport team or on-line medical control physician feel delivery at the sending hospital is possible and indicated prior to transport. Patient identification occurred through matching a database of mandatory post-transport maternal-fetal team debrief forms with computer automated dispatch data that identified the specialty team’s deployment. The data sets were matched, linked to their patient care report in the electronic medical record (EMR), and reviewed as part of a quality assurance project. After all transports, the mandatory post-transport debrief form was filed by the obstetric transport nurse and included whether or not the patient was deemed too unstable to transport at the sending hospital and whether or not there was a delivery at the receiving hospital within one hour of arrival. The following data elements of the EMR were reviewed as part of the quality assurance project: demographics, vital signs, gestational age, maternal heart rate, gravidity, parity, obstetric condition requiring specialized transport team, transport distance, fetal status based on fetal heart rate (FHR) and uterine contraction monitoring, cervical dilation, frequency of contractions, prenatal care status, and general notes from the patient narrative. This was collected by 2 authors trained in chart review and data extraction using standardized data extraction forms (TL, AB). Adjudication of any uncertainty was performed by a separate board-certified emergency medicine attending physician (BRH). For the purposes of analysis, the most advanced cervical dilation and the most frequent rate of contractions documented prior to the initiation of transport were utilized. The primary outcome was delivery prior to or within 1 hour of arrival at the receiving institution because of progression of labor. Patients who were too unstable to transport or delivered within one hour at the receiving facility due to only maternal or fetal distress – not progression of labor - prompting cesarean delivery were not counted as having the primary outcome given that our goal was to identify patients at risk of precipitous delivery due to progression of labor. Therefore, the primary outcome did not include patients that needed delivery due to maternal or fetal emergency care situations such as maternal cardiopulmonary instability or persistent fetal bradycardia in the absence of labor. Regular prenatal care was scored as charted by the obstetric transport nurse in the EMR – this did not have formally defined parameters and was subjectively determined by the clinician. In this system, the maternal-fetal nurse had three options for prenatal care documentation in the EMR: none, scant, and regular. The maternal-fetal nurses choose one category based on the history obtained from the patient based on their professional discretion. Critical care transport (CCT) skill utilization was defined as any management of life-support devices beyond typical advanced life support capabilities– such as mechanical ventilation, use of vasopressors, or management of a thrombolytic drug for an acute thromboembolic event. This study was approved by the Indiana University Institutional Review Board, protocol number 20146, as a retrospective analysis of a previously acquired data set for quality assurance and quality improvement purposes. The need for consent to participate for this study was waived by the Institutional Review Board. There was no interaction with the patients by the authors. The odds ratio of high-risk transports due to progression of labor in relation to various factors was estimated using simple logistic regression. Multivariate logistic analysis was not used due to the low frequency of the primary outcome (n = 11). Observations with missing values in the independent variable for the observation were dropped from the analysis. All statistical analyses were performed using Stata 18.0 BE (College Station, Texas). Results Within the entire cohort, the median gestational age was 30-weeks and the interquartile range of maternal ages was 23 to 32 years, with a median of 28. A greater proportion of patients without the primary outcome received regular prenatal care. Patients with the primary outcome tended to have more advanced cervical dilation and longer transport mileage. Less than 3% of the entire cohort required CCT team skills during the encounter (Table 1 ). Of the 370 pregnant patients for whom a transport was requested during the study period, 110 were deemed to be laboring at the time of request. Of those initially deemed laboring, 11 did not have a cervical examination and 15 did not have contraction frequency data charted – none of which had the primary outcome. Eleven (3%) patients of the entire cohort were too unstable to transport or had a delivery within an hour of arrival at the receiving hospital due to progression of labor. Of those not classified as having the primary outcome due to maternal decompensation or fetal distress, three nonlaboring patients experienced cesarean deliveries within an hour of arrival at the receiving hospital due to maternal cardiopulmonary decompensation secondary to COVID-19 pneumonia while another three non-laboring patients had cesarean delivery at the sending hospital due to fetal distress. Table 1 Patient and Transport Characteristics by Outcome No outcome n = 359 Outcome present n = 11 Age in years – median (IQR) 28 (23–32) 28 (23–33) Gestational age in days – median (IQR) 214 (188–233) 203 (178–224) Parity – median (IQR) 1 (0–2) 2 ( 1 – 2 ) Regular prenatal care – number (%) 311 (87) 7 (64) Cervical dilation in centimeters (cm) – median (IQR) 2 ( 1 – 3 ) 4.5 (3.5–9) Transport distance in miles – median (IQR) 23 (9–48) 32 (18–117) CCT team skills utilized – number (%) 9 ( 2 ) 0 (0) *IQR – Interquartile range In patients with the primary outcome, the reason for specialized transport team request was most commonly due to preterm labor or preterm premature rupture of membranes (PPROM). Most had contractions every 5 minutes or more frequently. Additionally, these patients tended to have more advanced cervical dilation. One patient had fetal feet palpable at the entrance of the cervix prompting delivery at the sending hospital (Table 2 ). The odds of having the outcome increased 2.3 times (95% CI 1.5 to 3.4) for every additional centimeter of cervical dilation (Table 3 ). Table 2 High-Risk Interfacility Transport Requests Due to Progression of Labor Age (years) Parity Gestation (weeks, days) Cervical dilation (cm) Contraction frequency (minutes) Regular prenatal care Reason for transport request, comments, and disposition 19 1 34w4d 5.5 2 No PPROM, cervical change more than 1 cm per hour, delivered at sending hospital 28 1 25w3d 4 3 Yes Preterm labor, delivery within one hour at receiving hospital 29 3 22w 3 - No PPROM, fetal feet palpable at entrance of cervix, delivered at sending hospital 33 2 28w 10 1 No PPROM, delivered at sending hospital within 20 minutes of team arrival 27 0 32w 6.5 4 Yes Preterm labor, delivered at sending hospital 32 2 29w6d 3 2 Yes Preterm labor and diabetic ketoacidosis, regular strong contractions with urge to push, delivered at sending hospital 36 2 31w1d 3.5 1.5 Yes Preterm labor, fetal bradycardia with immediate cesarean delivery at the receiving hospital upon arrival 24 1 34w1d 4.5 2 Yes PPROM, regular strong contractions; cervical change over 1.5cm per hour, delivered at sending hospital 23 2 23w4d 4 5 Yes PPROM, strong regular contractions, delivered at sending hospital 21 0 28w1d 9 2 Yes Preterm labor, 3 cm cervical dilation in less than an hour, regular strong contractions, delivered at sending hospital 33 3 unknown 10 2 No Preterm labor and preeclampsia, regular strong contractions, cervix dilating more than 2cm per hour, delivered at sending hospital Table 3 Simple Logistic Regression of Various Factors on the Outcome of High-Risk Interfacility Transport Due to Progression of Labor Number of Observations Odds ratio 95% Confidence interval Regular prenatal care 370 0.27 0.08 to 0.96 Transport distance (miles)* 352 1.01 0.99 to 1.03 Maternal age 359 0.99 0.90 to 1.10 Gestational age (days) 368 0.99 0.97 to 1.01 Parity 370 1.17 0.79 to 1.74 Cervical dilation (centimeters) 139 2.27 1.50 to 3.44 Contraction frequency (minutes) 130 0.96 0.71 to 1.30 * Does not include patients not transported. ** Each analysis does not include observations with missing data in the independent variable Discussion Our findings add context and perspective to the clinical decision-making involved in determining whether or not a pregnant patient is safe for transport between two hospitals. The findings are amenable to formulating triage algorithms, such as Fig. 1 , whereby clinical teams can rapidly assess the best course of action based on the evidence presented. In particular, the findings demonstrate that preterm labor can progress rapidly, and high-risk features for precipitous delivery include rupture of membranes, cervical dilation beyond 3 cm, and frequent contractions that are regular and strong. It is important to note that unanticipated labor or delivery in the patient population requiring interfacility transport is largely different than the controlled progression of labor in a modern hospital labor and delivery unit. The effects of anesthesia and perinatal interventions common on labor and delivery units augment cervical change such that it is less precipitous than would be expected without any such interventions in an unplanned and potentially precipitous delivery encountered in an emergency 6,7 . Furthermore, precipitous deliveries, defined as those occurring in less than 3 hours, have a higher likelihood of happening outside of the controlled environment of a labor and delivery unit 7 . As such, findings from in-hospital labor and delivery units are not necessarily representative of the high-risk and unanticipated deliveries encountered in the prehospital and interfacility transport environments. Our findings help fill in this gap and provide better context for clinical decision-making as it relates to the interfacility transport of high-risk obstetric patients. Another clinical context in which these findings are useful is for clinicians balancing the risk of adverse events during transport, the requirements of the EMTALA in the US, and the potential benefit of a neonate requiring higher-level care being born at an appropriately resourced hospital capable of delivering that care. In this study, nearly all the neonates born in the group with the primary outcome would benefit from advanced neonatology capabilities, as all had gestational age less than 35 weeks, and the majority had gestational ages less than 30 weeks. As healthcare resources within the US continue to consolidate and centralize, accessing prenatal care and obstetric services will remain a challenge. In this dataset, we found an association between high-risk deliveries and absence of prenatal care. Lack of access to care in obstetric patients prevents medical optimization and planning for high-risk pregnancies. Without improved access, adverse events such as unexpected preterm deliveries, could become more frequent with higher morbidity and mortality. Furthermore, patients with difficulty accessing any type of healthcare could also conceivably present later in the course of an acute health crisis, further decreasing the odds for a favorable outcome. Lastly, the results imply that with adequate fetal, uterine, and maternal clinical assessment capabilities, there is limited utility in an obstetric transport nurse program if an appropriate triage mechanism is in place. Furthermore, deployment of the obstetric transport nurse led to a mean increase in response time to the patient of over twenties minutes compared to a standard transport team configuration (data not shown). This was due to the standard transport team having to divert to pick up the obstetric nurse from a centralized labor and delivery unit that was away from the point of ambulance dispatch. In the era of staffing shortages exacerbating a lack adequate nursing coverage within hospitals in the US, these findings may inform more efficient deployment of valuable and limited nursing resources. Limitations This study had several limitations worth consideration. First, there was implicit selection bias in that the obstetric transport team configuration was being deployed at the behest of the requesting physician at the sending hospital for pregnant patients presumably perceived to be high risk. The patient population therefore contained a preponderance of preterm patients with more comorbidities than would be expected in a more generalized sample. Secondly, the outcome was rare and could be subjectively influenced by the clinical decision-making of clinicians at both the sending and receiving hospitals. Practice bias in either group will lead to non-random findings as it relates to the outcome and physiological parameters. For example, the presence of prolonged, recurrent late decelerations often led to cesarean delivery if that capability was present. The same is likely true of varying degrees of cervical dilation and the nature of contractions. Another potential limitation is the speed at which patients who stayed at the sending hospital were delivered. While many of the cases were taken directly to the OR, there is some uncertainly in how precipitous the labor was, although the rate of cervical change in all but three of the cases implies precipitous delivery. Missing data existed in this data set for patients that did not have a cervical exam performed or who did not have contraction frequency measured. These observations were not included in the logistic analysis. This diluted the power of the study and ability to precisely measure the impact of these factors. Lastly, the study took place within a single region of the United States with the least favorable quartile of morbidity and mortality for both maternal and neonatal patients in the perinatal period. Thus, the patient population described may have worse outcomes than would be expected in other regions with better healthcare resources and/or availability thereof. Conclusions The findings of this study imply that patients with regular strong contractions, preterm labor, cervical dilation beyond 3 cm, or rupture of membranes are high-risk for progression of labor and precipitous delivery during interfacility transfer. The findings suggest that real-time obstetric physician consultation with up-to-date clinical context such as cervical dilation, uterine contraction frequency, and fetal heart rate can help mitigate risk prior to transfer at the sending hospital. Developing a local algorithm that supports physician judgment with incorporation of clinical factors and distance to the receiving hospital in the decision of whether or not to undertake these high-risk transfers can help mitigate risk in the transfer of obstetric patients experiencing labor. Abbreviations EMTALA Emergency Medical Treatment and Active Labor Act US United States EMS Emergency medical services EMR Electronic medical record FHR Fetal heart rate cm Centimeters CCT Critical care transport IQR Interquartile range PPROM Preterm premature rupture of membranes Declarations Ethics approval and consent to participate This study was approved by the Indiana University Institutional Review Board, protocol number 20146, as a retrospective analysis of a previously acquired data set for quality assurance and quality improvement purposes. The need for consent to participate for this study was waived by the Institutional Review Board. There was no interaction with the patients by the authors. Consent for publication Not applicable. Availability of data and materials The dataset described and analyzed in this study are available from the corresponding author on reasonable request. However, no patient specific protected health information can be shared externally as stipulated by the Health Insurance Portability and Accountability Act. Competing interests The authors have no competing interests to declare. Funding The authors have no sources of funding for the research to declare. Authors' contributions TL: study design, data acquisition, analysis, interpretation, writing. A. Balaji: study design, data acquisition, interpretation. DK, NG, CMB, KC, AB, JV: drafting, interpretation, writing, and critical review. BRH: adjudication, interpretation, critical review, and writing. Acknowledgements The Indiana University School of Medicine Division of EMS and Department of Emergency Medicine for supporting the advancement of our field and profession. Sven Phillips, medical student at Indiana University School of Medicine, for contributions to the introduction section and literature review of this manuscript. References Akl N, Coghlan EA, Nathan EA, Langford SA, Newnham JP. Aeromedical transfer of women at risk of preterm delivery in remote and rural Western Australia: why are there no births in flight? Aust N Z J Obstet Gynaecol. 2012;52(4):327 – 33. 10.1111/j.1479-828X.2012.01426.x . Epub 2012 Apr 11. PMID: 22494047. Elliott JP, Sipp TL, Balazs KT. Maternal transport of patients with advanced cervical dilatation–to fly or not to fly? Obstet Gynecol. 1992;79(3):380-2. 10.1097/00006250-199203000-00010 . PMID: 1738518. Low RB, Martin D, Brown C. Emergency air transport of pregnant patients: the national experience. J Emerg Med. 1988 Jan-Feb;6(1):41 – 8. 10.1016/0736-4679(88)90250-8 . PMID: 3129490. Incerti M, Locatelli A, Ghidini A, Ciriello E, Malberti S, Consonni S, Pezzullo JC. Prediction of the duration of active labor in nulliparous women at term. Am J Perinatol. 2008;25(2):85–9. 10.1055/s-2007-1004827 . Epub 2007 Dec 12. PMID: 18075962. Gunnarsson B, Skogvoll E, Jónsdóttir IH, et al. On predicting time to completion for the first stage of spontaneous labor at term in multiparous women. BMC Pregnancy Childbirth. 2017;17:183. https://doi.org/10.1186/s12884-017-1345-1 . Friedman EA. Primigravid labor; A graphicostatistical analysis. Obstet Gynecol. 1955;6(6):567 – 89. 10.1097/00006250-195512000-00001 . PMID: 13272981. Chapter 23 - Abnormal Labor, Cunningham F, Leveno KJ, Dashe JS, Hoffman BL, Spong CY, Casey BM. Williams Obstetrics, 26e; 2022. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4345052","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":306755712,"identity":"b81d3f22-6969-41a6-b045-dadb3b8f11c6","order_by":0,"name":"Thomas Lardaro","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsElEQVRIiWNgGAWjYDACdiDmAWJ+ZhCPjQgdPMxQLZLNJGsxOECsFntm5mcf3tTckzM+zmPA8KHsMDG2sBnPnHOs2NjsMI8B44xzRGlhMGbmYUtI3AbUwszbRpQW9s/MPP8SEjc3A7X8JU4LjzHQ8ITEDcxALYxEaTnMU8w4ty/BWOIwW8HBnnPphLWwt7dvZnjzLUGOv//wxgc/yqwJa0EBB0hUPwpGwSgYBaMAFwAAaG0vHCQidxAAAAAASUVORK5CYII=","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Lardaro","suffix":""},{"id":306755713,"identity":"74484408-ad89-4166-9299-d6d5984967fe","order_by":1,"name":"Adhitya Balaji","email":"","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Adhitya","middleName":"","lastName":"Balaji","suffix":""},{"id":306755714,"identity":"57be7b58-647a-4007-91ab-aec264bdcd39","order_by":2,"name":"Diane Kuhn","email":"","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Diane","middleName":"","lastName":"Kuhn","suffix":""},{"id":306755715,"identity":"0f278e4c-a69f-4995-bd26-929b57a635ee","order_by":3,"name":"Nancy Glober","email":"","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Nancy","middleName":"","lastName":"Glober","suffix":""},{"id":306755716,"identity":"0258e679-ae7f-4d46-b9b6-8906db45b041","order_by":4,"name":"Christine M Brent","email":"","orcid":"","institution":"University of Michigan Medical School","correspondingAuthor":false,"prefix":"","firstName":"Christine","middleName":"M","lastName":"Brent","suffix":""},{"id":306755717,"identity":"6cb28cf8-6c87-4f79-bcc0-8a7383988f3f","order_by":5,"name":"Katherine Couturier","email":"","orcid":"","institution":"Yale University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Katherine","middleName":"","lastName":"Couturier","suffix":""},{"id":306755718,"identity":"61a1eb37-bda6-437d-a77d-8c6d1b9a641d","order_by":6,"name":"Amelia Breyre","email":"","orcid":"","institution":"Yale University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Amelia","middleName":"","lastName":"Breyre","suffix":""},{"id":306755719,"identity":"6a393a4e-63a7-4abc-ace4-d4932553283b","order_by":7,"name":"Julia Vaizer","email":"","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Julia","middleName":"","lastName":"Vaizer","suffix":""},{"id":306755720,"identity":"01883e0f-3345-4cf3-bb46-f49480599d75","order_by":8,"name":"Benton R Hunter","email":"","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Benton","middleName":"R","lastName":"Hunter","suffix":""}],"badges":[],"createdAt":"2024-04-29 21:15:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4345052/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4345052/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57874649,"identity":"9d142b50-42f6-4ce4-af23-752b0d5bed42","added_by":"auto","created_at":"2024-06-06 18:47:46","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":247693,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTriage Algorithm for Interfacility Transport of Pregnant Patients\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4345052/v1/d843732b11aefde1faea6c68.jpeg"},{"id":62238261,"identity":"6d54b209-2a02-448a-8275-79c9611c3c80","added_by":"auto","created_at":"2024-08-12 02:16:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":728702,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4345052/v1/ad5cb657-d376-4c45-a692-e1974ced4fd9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessing Risk of Interfacility Transport in Pregnant Patients due to Progression of Labor – Lessons from a Specialized Maternal-Fetal Transport Program","fulltext":[{"header":"Background","content":"\u003cp\u003ePregnant women in labor often present to hospitals that are ill-equipped to deal with obstetric or newborn patients. In these scenarios, clinicians must weigh the risks and benefits of if, when, and how to transfer the patient to a more appropriate hospital or level of care. The inherent risk of a precipitous delivery during transport is of paramount concern for the interfacility transfer of high-risk patients in labor. The limited resources and physical space within which transport crews work present considerable challenges for managing the delivery and subsequent care of a mother and newborn, including any complications that may arise.\u003c/p\u003e \u003cp\u003eGiven the myriad of factors involved, establishing a set of standards for the appropriateness of interfacility transport for laboring patients is challenging. The incidence of precipitous delivery during transport is low, especially after the 1986 implementation of the Emergency Medical Treatment and Active Labor Act (EMTALA) in the United States (US) \u003csup\u003e1,2,3\u003c/sup\u003e. The screening of patients in labor just before transport appears to play a significant role in this regard \u003csup\u003e3\u003c/sup\u003e. Several studies have investigated the use of physiological signs to predict the duration of active labor \u003csup\u003e4,5\u003c/sup\u003e. Yet, there remains a sparsity of data on how these physiological predictors might inform the decision-making process regarding the transport of high-risk laboring patients.\u003c/p\u003e \u003cp\u003eThis study aims to inform clinical decision making regarding the timing of interfacility transport with respect to delivery.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis is a retrospective case-control analysis including all pregnant patients transported by a specialized obstetric transport team deployed from a 15-hospital healthcare system in the Midwestern US between January 2021 through May 2022. The transport team consisted of a critical care transport nurse with an expanded scope of practice through emergency medical services (EMS) protocols authorized by a physician medical director and an obstetric nurse capable of maternal-fetal monitoring, such as cardiotocography. The team is deployed by air or ground at the discretion of the sending physician (\u0026ldquo;requesting physician\u0026rdquo; in this study), with a third team member serving as vehicle operator (pilot or driver). Team deployment is usually requested for high-risk obstetric patients \u0026ndash; including for reasons of maternal or fetal distress not necessarily involving progression of labor \u0026ndash; in order to transport the patient to a higher level of care for the mother and/or neonate. The transport team has real-time access via telephone to an on-line medical control obstetric physician for any questions or concerns. The on-line medical control physician can place orders and has the authority to decline immediate transport in favor of delivery at the sending hospital prior to transport. Reasons for postponing transport may include imminent delivery and/or fetal or maternal distress \u0026ndash; such as eclampsia or prolonged recurrent decelerations on fetal heart tracing \u0026ndash; or if the transport team or on-line medical control physician feel delivery at the sending hospital is possible and indicated prior to transport.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003ePatient identification occurred through matching a database of mandatory post-transport maternal-fetal team debrief forms with computer automated dispatch data that identified the specialty team\u0026rsquo;s deployment. The data sets were matched, linked to their patient care report in the electronic medical record (EMR), and reviewed as part of a quality assurance project.\u003c/p\u003e\u003cp\u003eAfter all transports, the mandatory post-transport debrief form was filed by the obstetric transport nurse and included whether or not the patient was deemed too unstable to transport at the sending hospital and whether or not there was a delivery at the receiving hospital within one hour of arrival.\u003c/p\u003e\u003cp\u003e The following data elements of the EMR were reviewed as part of the quality assurance project: demographics, vital signs, gestational age, maternal heart rate, gravidity, parity, obstetric condition requiring specialized transport team, transport distance, fetal status based on fetal heart rate (FHR) and uterine contraction monitoring, cervical dilation, frequency of contractions, prenatal care status, and general notes from the patient narrative. This was collected by 2 authors trained in chart review and data extraction using standardized data extraction forms (TL, AB). Adjudication of any uncertainty was performed by a separate board-certified emergency medicine attending physician (BRH).\u003c/p\u003e\u003cp\u003eFor the purposes of analysis, the most advanced cervical dilation and the most frequent rate of contractions documented prior to the initiation of transport were utilized.\u003c/p\u003e\u003cp\u003eThe primary outcome was delivery prior to or within 1 hour of arrival at the receiving institution because of progression of labor. Patients who were too unstable to transport or delivered within one hour at the receiving facility due to only maternal or fetal distress \u0026ndash; not progression of labor - prompting cesarean delivery were not counted as having the primary outcome given that our goal was to identify patients at risk of precipitous delivery due to progression of labor. Therefore, the primary outcome did not include patients that needed delivery due to maternal or fetal emergency care situations such as maternal cardiopulmonary instability or persistent fetal bradycardia in the absence of labor.\u003c/p\u003e\u003cp\u003eRegular prenatal care was scored as charted by the obstetric transport nurse in the EMR \u0026ndash; this did not have formally defined parameters and was subjectively determined by the clinician. In this system, the maternal-fetal nurse had three options for prenatal care documentation in the EMR: none, scant, and regular. The maternal-fetal nurses choose one category based on the history obtained from the patient based on their professional discretion. Critical care transport (CCT) skill utilization was defined as any management of life-support devices beyond typical advanced life support capabilities\u0026ndash; such as mechanical ventilation, use of vasopressors, or management of a thrombolytic drug for an acute thromboembolic event.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e This study was approved by the Indiana University Institutional Review Board, protocol number 20146, as a retrospective analysis of a previously acquired data set for quality assurance and quality improvement purposes. The need for consent to participate for this study was waived by the Institutional Review Board. There was no interaction with the patients by the authors.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe odds ratio of high-risk transports due to progression of labor in relation to various factors was estimated using simple logistic regression. Multivariate logistic analysis was not used due to the low frequency of the primary outcome (n\u0026thinsp;=\u0026thinsp;11). Observations with missing values in the independent variable for the observation were dropped from the analysis. All statistical analyses were performed using Stata 18.0 BE (College Station, Texas).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eWithin the entire cohort, the median gestational age was 30-weeks and the interquartile range of maternal ages was 23 to 32 years, with a median of 28. A greater proportion of patients without the primary outcome received regular prenatal care. Patients with the primary outcome tended to have more advanced cervical dilation and longer transport mileage. Less than 3% of the entire cohort required CCT team skills during the encounter (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOf the 370 pregnant patients for whom a transport was requested during the study period, 110 were deemed to be laboring at the time of request. Of those initially deemed laboring, 11 did not have a cervical examination and 15 did not have contraction frequency data charted \u0026ndash; none of which had the primary outcome.\u003c/p\u003e \u003cp\u003eEleven (3%) patients of the entire cohort were too unstable to transport or had a delivery within an hour of arrival at the receiving hospital due to progression of labor. Of those not classified as having the primary outcome due to maternal decompensation or fetal distress, three nonlaboring patients experienced cesarean deliveries within an hour of arrival at the receiving hospital due to maternal cardiopulmonary decompensation secondary to COVID-19 pneumonia while another three non-laboring patients had cesarean delivery at the sending hospital due to fetal distress.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient and Transport Characteristics by Outcome\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo outcome\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;359\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOutcome present n\u0026thinsp;=\u0026thinsp;11\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge in years \u0026ndash; median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (23\u0026ndash;32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (23\u0026ndash;33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational age in days \u0026ndash; median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214 (188\u0026ndash;233)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e203 (178\u0026ndash;224)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParity \u0026ndash; median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0\u0026ndash;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegular prenatal care \u0026ndash; number (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e311 (87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (64)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCervical dilation in centimeters (cm) \u0026ndash; median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.5 (3.5\u0026ndash;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransport distance in miles \u0026ndash; median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (9\u0026ndash;48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (18\u0026ndash;117)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCT team skills utilized \u0026ndash; number (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e*IQR \u0026ndash; Interquartile range\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn patients with the primary outcome, the reason for specialized transport team request was most commonly due to preterm labor or preterm premature rupture of membranes (PPROM). Most had contractions every 5 minutes or more frequently. Additionally, these patients tended to have more advanced cervical dilation. One patient had fetal feet palpable at the entrance of the cervix prompting delivery at the sending hospital (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The odds of having the outcome increased 2.3 times (95% CI 1.5 to 3.4) for every additional centimeter of cervical dilation (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHigh-Risk Interfacility Transport Requests Due to Progression of Labor\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGestation (weeks, days)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCervical dilation (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eContraction frequency (minutes)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRegular prenatal care\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eReason for transport request, comments, and disposition\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34w4d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePPROM, cervical change more than 1 cm per hour, delivered at sending hospital\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25w3d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePreterm labor, delivery within one hour at receiving hospital\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePPROM, fetal feet palpable at entrance of cervix, delivered at sending hospital\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePPROM, delivered at sending hospital within 20 minutes of team arrival\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePreterm labor, delivered at sending hospital\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29w6d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePreterm labor and diabetic ketoacidosis, regular strong contractions with urge to push, delivered at sending hospital\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31w1d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePreterm labor, fetal bradycardia with immediate cesarean delivery at the receiving hospital upon arrival\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34w1d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePPROM, regular strong contractions; cervical change over 1.5cm per hour, delivered at sending hospital\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23w4d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePPROM, strong regular contractions, delivered at sending hospital\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28w1d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePreterm labor, 3 cm cervical dilation in less than an hour, regular strong contractions, delivered at sending hospital\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eunknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePreterm labor and preeclampsia, regular strong contractions, cervix dilating more than 2cm per hour, delivered at sending hospital\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSimple Logistic Regression of Various Factors on the Outcome of High-Risk Interfacility Transport Due to Progression of Labor\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Observations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOdds ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% Confidence interval\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegular prenatal care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08 to 0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransport distance (miles)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99 to 1.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.90 to 1.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational age (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97 to 1.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79 to 1.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCervical dilation (centimeters)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.50 to 3.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContraction frequency (minutes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71 to 1.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e* Does not include patients not transported.\u003c/p\u003e \u003cp\u003e** Each analysis does not include observations with missing data in the independent variable\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings add context and perspective to the clinical decision-making involved in determining whether or not a pregnant patient is safe for transport between two hospitals. The findings are amenable to formulating triage algorithms, such as Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, whereby clinical teams can rapidly assess the best course of action based on the evidence presented. In particular, the findings demonstrate that preterm labor can progress rapidly, and high-risk features for precipitous delivery include rupture of membranes, cervical dilation beyond 3 cm, and frequent contractions that are regular and strong.\u003c/p\u003e \u003cp\u003eIt is important to note that unanticipated labor or delivery in the patient population requiring interfacility transport is largely different than the controlled progression of labor in a modern hospital labor and delivery unit. The effects of anesthesia and perinatal interventions common on labor and delivery units augment cervical change such that it is less precipitous than would be expected without any such interventions in an unplanned and potentially precipitous delivery encountered in an emergency \u003csup\u003e6,7\u003c/sup\u003e. Furthermore, precipitous deliveries, defined as those occurring in less than 3 hours, have a higher likelihood of happening outside of the controlled environment of a labor and delivery unit \u003csup\u003e7\u003c/sup\u003e. As such, findings from in-hospital labor and delivery units are not necessarily representative of the high-risk and unanticipated deliveries encountered in the prehospital and interfacility transport environments. Our findings help fill in this gap and provide better context for clinical decision-making as it relates to the interfacility transport of high-risk obstetric patients.\u003c/p\u003e \u003cp\u003eAnother clinical context in which these findings are useful is for clinicians balancing the risk of adverse events during transport, the requirements of the EMTALA in the US, and the potential benefit of a neonate requiring higher-level care being born at an appropriately resourced hospital capable of delivering that care. In this study, nearly all the neonates born in the group with the primary outcome would benefit from advanced neonatology capabilities, as all had gestational age less than 35 weeks, and the majority had gestational ages less than 30 weeks.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAs healthcare resources within the US continue to consolidate and centralize, accessing prenatal care and obstetric services will remain a challenge. In this dataset, we found an association between high-risk deliveries and absence of prenatal care. Lack of access to care in obstetric patients prevents medical optimization and planning for high-risk pregnancies. Without improved access, adverse events such as unexpected preterm deliveries, could become more frequent with higher morbidity and mortality. Furthermore, patients with difficulty accessing any type of healthcare could also conceivably present later in the course of an acute health crisis, further decreasing the odds for a favorable outcome.\u003c/p\u003e\u003cp\u003eLastly, the results imply that with adequate fetal, uterine, and maternal clinical assessment capabilities, there is limited utility in an obstetric transport nurse program if an appropriate triage mechanism is in place. Furthermore, deployment of the obstetric transport nurse led to a mean increase in response time to the patient of over twenties minutes compared to a standard transport team configuration (data not shown). This was due to the standard transport team having to divert to pick up the obstetric nurse from a centralized labor and delivery unit that was away from the point of ambulance dispatch. In the era of staffing shortages exacerbating a lack adequate nursing coverage within hospitals in the US, these findings may inform more efficient deployment of valuable and limited nursing resources.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eThis study had several limitations worth consideration. First, there was implicit selection bias in that the obstetric transport team configuration was being deployed at the behest of the requesting physician at the sending hospital for pregnant patients presumably perceived to be high risk. The patient population therefore contained a preponderance of preterm patients with more comorbidities than would be expected in a more generalized sample. Secondly, the outcome was rare and could be subjectively influenced by the clinical decision-making of clinicians at both the sending and receiving hospitals. Practice bias in either group will lead to non-random findings as it relates to the outcome and physiological parameters. For example, the presence of prolonged, recurrent late decelerations often led to cesarean delivery if that capability was present. The same is likely true of varying degrees of cervical dilation and the nature of contractions. Another potential limitation is the speed at which patients who stayed at the sending hospital were delivered. While many of the cases were taken directly to the OR, there is some uncertainly in how precipitous the labor was, although the rate of cervical change in all but three of the cases implies precipitous delivery. Missing data existed in this data set for patients that did not have a cervical exam performed or who did not have contraction frequency measured. These observations were not included in the logistic analysis. This diluted the power of the study and ability to precisely measure the impact of these factors. Lastly, the study took place within a single region of the United States with the least favorable quartile of morbidity and mortality for both maternal and neonatal patients in the perinatal period. Thus, the patient population described may have worse outcomes than would be expected in other regions with better healthcare resources and/or availability thereof.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe findings of this study imply that patients with regular strong contractions, preterm labor, cervical dilation beyond 3 cm, or rupture of membranes are high-risk for progression of labor and precipitous delivery during interfacility transfer. The findings suggest that real-time obstetric physician consultation with up-to-date clinical context such as cervical dilation, uterine contraction frequency, and fetal heart rate can help mitigate risk prior to transfer at the sending hospital. Developing a local algorithm that supports physician judgment with incorporation of clinical factors and distance to the receiving hospital in the decision of whether or not to undertake these high-risk transfers can help mitigate risk in the transfer of obstetric patients experiencing labor.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEMTALA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEmergency Medical Treatment and Active Labor Act\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEmergency medical services\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEMR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eElectronic medical record\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFetal heart rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ecm\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCentimeters\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCritical care transport\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePPROM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePreterm premature rupture of membranes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Indiana University Institutional Review Board, protocol number 20146, as a retrospective analysis of a previously acquired data set for quality assurance and quality improvement purposes. The need for consent to participate for this study was waived by the Institutional Review Board. There was no interaction with the patients by the authors.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset described and analyzed in this study are available from the corresponding author on reasonable request. However, no patient specific protected health information can be shared externally as stipulated by the Health Insurance Portability and Accountability Act.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no sources of funding for the research to declare.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthors' contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTL: study design, data acquisition, analysis, interpretation, writing. A. Balaji: study design, data acquisition, interpretation. DK, NG, CMB, KC, AB, JV: drafting, interpretation, writing, and critical review. BRH: adjudication, interpretation, critical review, and writing.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe Indiana University School of Medicine Division of EMS and Department of Emergency Medicine for supporting the advancement of our field and profession. Sven Phillips, medical student at Indiana University School of Medicine, for contributions to the introduction section and literature review of this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAkl N, Coghlan EA, Nathan EA, Langford SA, Newnham JP. Aeromedical transfer of women at risk of preterm delivery in remote and rural Western Australia: why are there no births in flight? Aust N Z J Obstet Gynaecol. 2012;52(4):327\u0026thinsp;\u0026ndash;\u0026thinsp;33. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1479-828X.2012.01426.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1479-828X.2012.01426.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2012 Apr 11. PMID: 22494047.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElliott JP, Sipp TL, Balazs KT. Maternal transport of patients with advanced cervical dilatation\u0026ndash;to fly or not to fly? Obstet Gynecol. 1992;79(3):380-2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/00006250-199203000-00010\u003c/span\u003e\u003cspan address=\"10.1097/00006250-199203000-00010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 1738518.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLow RB, Martin D, Brown C. Emergency air transport of pregnant patients: the national experience. J Emerg Med. 1988 Jan-Feb;6(1):41\u0026thinsp;\u0026ndash;\u0026thinsp;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/0736-4679(88)90250-8\u003c/span\u003e\u003cspan address=\"10.1016/0736-4679(88)90250-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 3129490.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIncerti M, Locatelli A, Ghidini A, Ciriello E, Malberti S, Consonni S, Pezzullo JC. Prediction of the duration of active labor in nulliparous women at term. Am J Perinatol. 2008;25(2):85\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1055/s-2007-1004827\u003c/span\u003e\u003cspan address=\"10.1055/s-2007-1004827\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2007 Dec 12. PMID: 18075962.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGunnarsson B, Skogvoll E, J\u0026oacute;nsd\u0026oacute;ttir IH, et al. On predicting time to completion for the first stage of spontaneous labor at term in multiparous women. BMC Pregnancy Childbirth. 2017;17:183. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12884-017-1345-1\u003c/span\u003e\u003cspan address=\"10.1186/s12884-017-1345-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFriedman EA. Primigravid labor; A graphicostatistical analysis. Obstet Gynecol. 1955;6(6):567\u0026thinsp;\u0026ndash;\u0026thinsp;89. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/00006250-195512000-00001\u003c/span\u003e\u003cspan address=\"10.1097/00006250-195512000-00001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 13272981.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChapter 23 - Abnormal Labor, Cunningham F, Leveno KJ, Dashe JS, Hoffman BL, Spong CY, Casey BM. Williams Obstetrics, 26e; 2022.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Interfacility transport, Labor, Obstetric transport, Pregnancy, Emergency medicine, EMTALA, EMS","lastPublishedDoi":"10.21203/rs.3.rs-4345052/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4345052/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePregnant laboring patients sometimes require interfacility transfer to a higher level of care. There is a paucity of evidence to inform when it is safe to transfer a laboring patient and when delivery may be too imminent to transfer.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis is a retrospective study of pregnant patients undergoing interfacility transfer with a specialized obstetric transport team deployed from a large Midwest regional healthcare system. The primary outcome was delivery prior to or within 1 hour of arrival at the receiving institution due to progression of labor. Data collected included basic demographics, vital signs, gravity, parity, gestational age, contraction frequency if contractions were present, and cervical dilation. We sought to define the association between these variables and the primary outcome to inform risk assessment for precipitous delivery among patients being considered for interfacility transfer.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf 370 pregnant patients for whom the specialized transfer team was requested, 11 (3%) met the primary outcome. Those with more advanced cervical dilation and those who did not have regular prenatal care were more likely to meet the criteria for the primary outcome. For every centimeter of cervical dilation, the odds of meeting the primary outcome increased 2.3-fold (95% CI 1.5 to 3.4).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eWe identify risk factors for early delivery among pregnant patients for whom an interfacility transfer was requested and describe patients who were high-risk for obstetric interfacility transport due to progression of labor. Our results can help inform risk assessments for the transfer of potentially high-risk laboring patients.\u003c/p\u003e","manuscriptTitle":"Assessing Risk of Interfacility Transport in Pregnant Patients due to Progression of Labor – Lessons from a Specialized Maternal-Fetal Transport Program","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-06 18:47:42","doi":"10.21203/rs.3.rs-4345052/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e8c644eb-f085-4c24-9a25-03ea52cbc4b6","owner":[],"postedDate":"June 6th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-08-12T02:08:25+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-06 18:47:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4345052","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4345052","identity":"rs-4345052","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}