Emerging role of angle of progression and head-perineum distance in predicting labor outcome: original research supported by a mini-review

Emerging role of angle of progression and head-perineum distance in predicting labor outcome: original research supported by a mini-review | 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 Emerging role of angle of progression and head-perineum distance in predicting labor outcome: original research supported by a mini-review Nipasa Sarma, Deepa Reddy, Asha Kamath, Jyothi Shetty This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7051979/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 : Intrapartum ultrasound (ITU) has garnered significant attention in recent years. While its use is well-documented in developed countries, it has not yet gained popularity in under- resourced countries. Despite the widespread availability of ultrasound (US) in most labor and delivery centers, its use is predominantly limited to identifying obstetric emergencies, with minimal application in assessing labor progress. The use of ITU has not been sufficiently tested in labor and delivery settings within developing countries. Aim : To evaluate the diagnostic performance of ITU parameters of 1. Angle of progression (AOP) and 2. Head perineum distance (HPD) in predicting a vaginal delivery in term singleton pregnant women in early labor and to provide a comprehensive review of literature. Methods : Prospective observational study conducted in South India. Singleton pregnant women over 37 weeks of gestation in early labor were included. AOP and HPD were measured using trans-perineal ultrasound in addition to clinical vaginal assessment. Two trained obstetricians performed the ultrasound examination on initial 22 women. ITU measurements were analysed to identify the best possible predictive value for the outcome vaginal delivery. Results : Among 113 parturients, the mean AOP was narrower in women who underwent Caesarean CD (27%, n= 31), compared to those who has a vaginal delivery (VD), (72.5%, n=82). An AOP > 104.5° was predictive of VD with a sensitivity 94% and specificity 95%. HPD of ≤39.5mm was predictive of VD with a sensitivity 64% and specificity 65%. Conclusion : Measuring AOP and HPD during labor provides valuable insights into the likelihood of a vaginal delivery with AOP being a more reliable indicator than HPD. Implementing the use of these measurements in labor management could empower obstetricians to confidently await a vaginal delivery, particularly in situations where labor duration exceeds the expected timeframe, while maternal and fetal conditions are satisfactory. Trial Registration: Reg No. CTRI/2021/02/030936, Reg Date: 02.02.2021, URL: www.ctri.nic.in Angle of progression AOP Head-perineum distance HPD Intrapartum ultrasound Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Cervical dilatation and fetal head descent are the two most important requirements for a successful vaginal delivery. A digital vaginal examination has been the standard way to identify and monitor descent. However, the bony landmarks in the pelvis are challenging to discern on palpation, which makes this method subjective to the individual examiner, resulting in a biased assessment.(1,2) Traditional partogram has worked out as an excellent tool to monitor labor. However, whether it continues to remain a scientifically valid tool to decide on an obstetric intervention such as a Caesarean section (CS), has been a point of debate in the last decade. In this light, the WHO has published new recommendations on intrapartum care using the Labor Care Guide (LCG).(3) It is now understood that the duration of first and second stage of labor is highly variable among women and the current stipulated rates of dilatation and descent may be unrealistically fast for some. More and more studies suggest that prolonged labor or a protracted second stage, per se, is not directly related to neonatal or maternal morbidity but may be related to various other things including health-care provider actions and interventions in response to the understood delay. In the era of superior fetal monitoring techniques and supervised institutional deliveries, the absolute risks of fetal and neonatal consequences of increasing the duration of labor appear to be, at worst, low or incremental. (4) In light of caesarean deliveries rising to an unacceptable rate in the recent years, it is now time for obstetricians all over, to contemplate on whether set points and defined labor progress cut- offs need to be made less stringent to maintain an acceptable vaginal delivery rate, and also to identify newer methods to predict a successful vaginal delivery. One such is the use of intrapartum transperineal ultrasound (ITU). The descent and position of the fetal head and determining arrest of labor are some of the things that can be done with ITU assessments particularly AOP and HPD, in a more precise and propagative manner.(5) There is mounting evidence that AOP offers unbiased information on fetal haed station and may prognosticate the outcome of operative vaginal delivery.(6) Although US is now easily available at most centres even in LMICs, its use in labour is not standard practice. This study aimed at understanding the usefulness of AOP and HPD in predicting vaginal delivery in labour settings of under-resourced countries. Methods This prospective observational study was carried out in a tertiary care centre in South India between 2021 and 2022 on term pregnant women in labor. The study was approved by the Institutional Ethics Committee (IEC number: 685/2020) and registered with CTRI (No: CTRI/2021/02/030936). The sample size was calculated as 117 using the formula N = ((Z_alpha/2 + Z_beta)^2 * (1 + k)) / ((AUC - AUC_0)^2 * k), with an expected AUC of 0.75, α=0.05, power of 80% and k=1. Included cohort of women were primigravidas and multigravidas with not more than one prior vaginal delivery at a gestational age over 37 weeks in early labor (presence of regular uterine contractions and a cervix dilated by not more than 4cm, on digital vaginal examination), secondary to both spontaneous onset and labor induction. The mode of induction was standardized using Propess (PGE2) gel. We included multigravidas with one prior vaginal delivery as the spacing between pregnancies was over 6 years, and we observed that labor progression and intervals in this group of women at our centre is identical to primigravidas. Pregnant women with PROM, multiple gestation, more than 1 prior vaginal delivery, non-cephalic presentation, previous Caesarean section and a non-reassuring fetal heart on CTG were excluded. In addition, women who did not go into labor despite induction and those with fetal head above pelvic brim at the time of recruitment were also excluded due to the non-feasibility of obtaining an accurate HPD in these cases. Informed consent was obtained individually from all participants included in the study. On admission, a detailed medical history, clinical examination and digital vaginal examination, Bishop’s score calculation were conducted for all study participants by the obstetrician in labor room. Women satisfying the inclusion criteria were subjected to a transperineal ultrasound. Ultrasound was performed with the Philips Clear Vue 350 ultrasound system equipped with C5-2 broadband curved array transducer of frequency range 2-5 MHz, by an experienced obstetrician who was blinded to the findings derived by digital examination. To measure the AOP, the transducer was positioned in between the labia in a mid-sagittal plane. The obtained image was frozen, and a tangent was drawn from the deepest bony part on the fetal skull to the lower border of pubic symphysis. (7) The angle formed between these lines was measured as AOP (Figure 1a). To measure HPD, the transducer was positioned over the vulva at the level of posterior commissure on a transverse plane and pressed gently against pubic rami. A caliper drawn between the perineum and the outer bony limit of the fetal skull on a transverse plane gave the HPD in millimeters. (8) (Figure 1b). The team of obstetricians involved in labor monitoring and delivery were blinded to the findings of the intrapartum TPU. Maternal monitoring was done hourly and on a need basis as stipulated by the WHO labor guidelines. Fetal surveillance was done in the form of second hourly CTGs till 4cm of dilatation, and continuously thereafter till delivery, in line with the institutional labor protocol. Antibiotic prophylaxis was provided for all with Inj. Amoxicillin 2g IV at rupture of membranes. Women at or beyond 6cm of cervical dilatation with ruptured membranes who failed to progress, despite 4 hours of good uterine activity or 6 hours of oxytocin administration and no cervical change, were said to be in active phase arrest. Second stage arrest was diagnosed at a maximum of 2 hours in multiparous women and 3 hours in nulliparous women where maternal and fetal conditions were acceptable. (4) Means, standard deviations and medians, IQRs were used to comprehend continuous variables for descriptive analysis depending on skewness which was assessed using Shapiro Wilks’ test. Frequencies and percentages were used for categorical variables. Independent sample ‘t’ test was used for comparing two groups in which the data was continuously distributed data. Non-parametric tests such as Wilcoxon-Mann Whitney U Test were used to compare groups where the data was not normally distributed. A best discriminatory AOP and HPD cut off for predicting those likely to have a vaginal delivery was determined by receiver operating characteristics (ROC) curve. P- value of <0.05 was considered statistically significant. Data were analyzed using the software package SPSS 23.0 (IBM Corp.). Results The study initially included 118 participants. However, 5 participants were excluded: 3 presented with premature rupture of membranes (PROM), and 2 underwent emergency cesarean sections (CS)—one due to meconium-stained amniotic fluid (MSAF) and the other because of fetal distress, leaving a total of 113 participants for analysis. Of these, 86 were primigravidas, and 27 were second gravidas with one previous vaginal delivery (VD). Among the participants, 55.7% (63) women went into spontaneous labor, while 44.2% (50) underwent induction using Propess (PGE2 gel). Position was either occipito- anterior or transverse in all cases. For the inital 22 participants, there was a good correlation for both AOP and HPD between the two obstetricians [Intra-class correlation coefficient (ICC): 0.85, 95% CI (0.80- 0.89) and ICC: 0.90, 95% CI (0.86-0.94)] for AOP and HPD respectively. A total of 72.5% (55 primigravida and all 27 multigravida) had a vaginal delivery (n=82), while 27.4% (n=31) had a CS. In the VD group, the mean duration of 1 st stage of labor was 11.70(3.28) hours in women who went into spontaneous labor and 13.4(3.02) hours in women who required labor induction, which was not statistically significant. This assured us that, once onset was established, spontaneous or induced, labour progression did not differ to an extent that was clinically relevant, and a separate group analysis for the spontaneous and induced was not performed. The indications for CS were labor arrest in 1 st stage in 96.6% (29) women and arrest in second stage in 3.3% (2) women. Epidural analgesia was administered to 3 women, all of whom subsequently had vaginal deliveries. Maternal and perinatal outcomes were similar in both the groups. There was no significant statistical difference in age, height and body mass index (BMI) between the VD and the CS groups. (Table 1) Table 1: Participant characteristics and perinatal outcomes in this cohort (n=113) Variable Total (n=113) VD (n=82) CD (n=31) P value Age (y) 28.34 ± 3.64 28.57 ± 3.71 27.71± 3.42 0.25 1 Height (cm) 157.83 ± 5.32 158.05± 4.69 157.27± 6.78 0.13 1 Weight (kg) 64.49 ± 9.57 64.63± 9.95 64.12± 8.62 0.86 1 BMI (kg/m2) 25.84 ± 3.58 25.84± 3.74 25.86± 3.18 0.75 1 Gestational age(weeks) 38.85 ± 0.64 38.81± 0.67 38.98± 0.53 0.16 1 Parity n (%) Primigravida Multigravida 55 (67.1%) 27 (32.9%) 31 (100.0%) 0 (0.0%) <0.001 2 Labor onset n (%) Spontaneous Propess (PGE2) 55(48.6%) 27(23.8%) 8(7.07%) 23(20.35%) p< 0.05 2 Birth weight (g) 3024.87± 353.60 3003.60± 340.90 3081.13± 385.35 0.32 1 APGAR score 1min 8.63± 0.66 8.71± 0.51 8.42± 0.92 0.14 1 APGAR score 5 min 9.60± 0.49 9.06 ± 0.36 9.10 ± 0.30 0.648 3 1.Independent t test, 2. Chi-square test, 3. Wilcoxon Mann Whitney U test The intrapartum characteristics of the study cohort is presented in Table 2. Women with greater cervical dilatation at admission (2.04 ± 1.47 cm vs. 1.41 ± 0.82 cm, p < 0.0013) were significantly more likely to have a vaginal delivery. In contrast, cervical length and fetal head station showed no significant differences between the groups, indicating that these parameters, though part of the traditional Bishop's score, may not reliably predict labor outcomes. Aditionally, our data suggests that all multigravidas and those who entered labor spontaneously (56.6% vs. 13.3%, p < 0.0052) were more likely to achieve a vaginal delivery. The mean AOP was significantly wider and was statistically significant (p <0.001) among the participants who had vaginal delivery. The mean HPD among the participants was 38.16 (8.57) mm. The mean HPD was higher among the participants who had Caesarean deliveries 41.48(8.28) mm as compared to the group who had vaginal delivery 36.90(8.39) mm. p<0.05. Table 2: Intrapartum characteristics in the study cohort (n=113) Variable VD (n=82) CD (n=31) P value Clinical examination Cervical dilatation(cm) 2.04 ± 1.47 1.41 ± 0.82 <0.001 1 Cervical length(cm) 1.35 ± 0.50 1.67 ± 0.39 0.24 1 Clinical Head Station -2.51 ± 1.09 -2.39 ± 0.88 0.23 1 ITU AOP (degree) Mean Median 120.21 (9.50) 120 (100-140) 92.32(5.57) 90 (84-107) <0.001 1 HPD (mm) Mean Median 36.90(8.39) 37 (21-63) 41.48(8.28) 41 (23-60) 0.011 2 1. Wilcoxon Mann Whitney U test, 2. Independent t test The association between AOP and cervical dilatation was conducted with Spearmans’ correlation analysis. There was moderate positive correlation between cervical dilatation (cm) and AOP and this being statistically significant (rho=0.46, p= <0.001). It was observed that as AOP increases, the cervical dilatation increases as well, causing the fetal head to descend. Similarly, correlation analysis was done between HPD and cervical dilatation. There was a moderate negative correlation between cervical dilatation (cm) and HPD (mm), and this correlation was statistically significant (rho = -0.34, p = <0.001). As HPD decreases, there is a descent of fetal head and cervical dilatates leading to vaginal delivery. (Figure 2a, 2b) Fetal head station is a critical parameter that enables obstetricians to assess labor progress alongside cervical dilatation. Clinical decisions to perform a CD or instrumental delivery are often based on the head station, with the understanding that higher head stations are less likely to result in vaginal delivery. B. Tutschek et al. proposed an objective method to determine fetal head station through the conversion of AOP and HPD. (9) The agreement between clinical head station and the station derived from AOP in our cohort is presented in Table 3, Figure 3. Although there was a fair agreement between the two methods, with a kappa of 0.289 and a statistically significant p-value (<0.001), the two methods were in complete agreement in only 12.4% of cases. Similarly, the agreement between clinical head station and the station derived from HPD is shown in Table 4, Figure 4. Complete agreement between these two methods was observed in only 10.4% of cases, despite a weighted kappa of 0.235 and a p-value <0.00. We believe the modest agreement between these methods observed in our cohort may be attributed to the digital vaginal examinations being performed by multiple obstetricians, introducing subjective error. This subjective error in assessing fetal head station is challenging to eliminate as it is operator-dependent and poorly reproducible. In contrast, stations derived from ITU are objective, standardized, reproducible, and capable of identifying subtle changes that might be missed or misinterpreted during digital examination. This underscores the importance of incorporating and standardizing the use of ITU in clinical practice. Table 3: Comparison of station derived from AOD and clinical station(n=113) Clinical Station Weighted Kappa Station -3 Station -2 Station -1 Station 0 Station 1 Station 2 Total k P Value Station (conversion from AOP) Station -3 10 (8.8%) 7 (6.2%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 17 (15.0%) 0.289 <0.001 Station -2 6 (5.3%) 1 (0.9%) 2 (1.8%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 9 (8.0%) Station -1 5 (4.4%) 4 (3.5%) 0 (0.0%) 1 (0.9%) 0 (0.0%) 0 (0.0%) 10 (8.8%) Station 0 9 (8.0%) 13 (11.5%) 7 (6.2%) 2 (1.8%) 0 (0.0%) 0 (0.0%) 31 (27.4%) Station 1 2 (1.8%) 13 (11.5%) 10 (8.8%) 11 (9.7%) 1 (0.9%) 1 (0.9%) 38 (33.6%) Station 2 1 (0.9%) 2 (1.8%) 3 (2.7%) 2 (1.8%) 0 (0.0%) 0 (0.0%) 8 (7.1%) Total 33 (29.2%) 40 (35.4%) 22 (19.5%) 16 (14.2%) 1 (0.9%) 1 (0.9%) 113 (100.0%) Table 4: Comparison of clinical head station and station from HPD Clinical Station Weighted Kappa Station -3 Station -2 Station -1 Station 0 Station 1 Station 2 Total k P Value Station (conversion from HPD) Station -3 3 (2.7%) 2 (1.8%) 0 (0.0%) 1 (0.9%) 0 (0.0%) 0 (0.0%) 6 (5.3%) 0.235 <0.001 Station -2 7 (6.2%) 4 (3.5%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 11 (9.7%) Station -1 11 (9.7%) 6 (5.3%) 1 (0.9%) 1 (0.9%) 0 (0.0%) 0 (0.0%) 19 (16.8%) Station 0 9 (8.0%) 14 (12.4%) 8 (7.1%) 2 (1.8%) 0 (0.0%) 0 (0.0%) 33 (29.2%) Station 1 1 (0.9%) 8 (7.1%) 7 (6.2%) 5 (4.4%) 1 (0.9%) 0 (0.0%) 22 (19.5%) Station 2 2 (1.8%) 6 (5.3%) 6 (5.3%) 7 (6.2%) 0 (0.0%) 1 (0.9%) 22 (19.5%) Total 33 (29.2%) 40 (35.4%) 22 (19.5%) 16 (14.2%) 1 (0.9%) 1 (0.9%) 113 (100.0%) Receiver Operating Characteristics (ROC) curve analysis was done for analysing the diagnostic performance of AOP and HPD in predicting vaginal delivery. The area under the ROC curve for AOP for predicting vaginal delivery was 0.996 (95% CI: 0.99- 1.00). At a cut off > 104.5 degree, AOP predicts vaginal delivery with a sensitivity of 95.1% and specificity of 96.8%. The area under the ROC curve for HPD for predicting vaginal delivery was 0.666 (95% CI: 0.55- 0.77). At a cut-off of HPD ≤39.5mm, it predicts vaginal delivery with a sensitivity of 63.4%, and a specificity of 64.5%. 78 (95.1%). Out of 82 participants with vaginal delivery, 78 (95.1%) had AOP > 104.5 degree while 4 (4.87%) participants had AOP 104.5 degree. 52 (63.4%) out of 82 participants with vaginal delivery had HPD ≤39.5mm while 30 (36.5%) participants had HPD> 40mm. 11(35.4 %) participants out of 31 underwent caesarean delivery in whom HPD ≤39.5mm. (Figure 5a, 5b.) Discussion & Review The use of ultrasound for studying fetal head descent dates back to 1977, pioneered by Lewin et al. (10) AOP was first described by Barbera et all in 2009 (7). Ever since, numerous observational studies have demonstrated that AOP can be a useful tool for predicting labor outcomes before labor induction, as an admission test, and during both the first and second stages of labor. The pre labour assessment of AOP has shown conflicting results. While a study by Minajagi et all (11) claims that pre labour AOP < 96° predicts a high chance of CD, Chan et all (12) reported that pre-labor measurement of AOP is not a reliable predictor of the outcomes of induction of labor, and that it is multifactorial. Our study included parturients in established early labor, and our decision to perform a cesarean section (CS) was guided not by traditional partogram suggestions, but by the guidelines from the American College of Obstetricians and Gynecologists (ACOG) and the Society for Maternal-Fetal Medicine (SMFM) on the safe prevention of primary cesarean delivery.(4) The optimal cutoff for the Angle of Progression (AOP) in predicting vaginal delivery (VD) in our study was 104°, which is slightly lower than other studies. This discrepancy may be due to the fact that most previous studies were conducted at a much advanced phase of the first stage of labor. Two other studies conducted in LMICs such as ours also had a lower cut off for AOP (> 89° and >99.6°). However, the sensitivity and predictive accuracy were moderate at best. (13, 14) Table 5 summarises key findings of several studies related to AOP in the 1 st stage of labour. The International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) recommends the use of intrapartum ultrasound in cases of prolonged or arrested labor, in both the first and second stages, particularly when fetal malpositions or malpresentations are suspected, and prior to operative vaginal delivery. (6) However, the recommended cutoff levels for instrumentation during the second stage of labor vary across studies, ranging from 120° to 145.5°. (29-32) Table 6 shows a summary of available studies on utility of AOP in second stage of labour, with a few studies focussing on role of AOP in predicting the success rates of instrumental delivery. Also, the predictive accuracy of AOP may vary between fetuses in OA and OP positions. In OP positions, the fetal head tends to descend deeper into the birth canal before the third cardinal movement, flexion, begins, in contrast with the OA position. Even when completely flexed, a fetus in OP cannot traverse through the birth canal as effectively as a fetus in OA position. Having understood this, it becomes clear that a significant limitation in the current literature is the variation in inclusion criteria and outcomes across studies, and the absence of randomized designs in the available publications. (41) Frick et all. (20) found that a model incorporating maternal height, parity, gestational age, fetal weight, and AOP achieved the highest AUC at 0.8. Therefore, to establish an optimal cutoff value for AOP, further studies are needed to explore more comprehensive models that account for the interaction of multiple factors. A recent meta-analysis by Nassr AA et all. (42) comprised of seven studies involving 782 pregnant women revealed that AOP is a reliable predictor of uncomplicated operative vaginal delivery (OVD), with a sensitivity of 80% (95% CI, 59-92%), specificity of 89% (95% CI, 76-95%), and a positive likelihood ratio (LR+) of 7.3 (95% CI, 3.1-15.8) during the resting phase. During the pushing phase, AOP showed a sensitivity of 91% (95% CI, 85-94%) and a specificity of 83% (95% CI, 69-92%), with an LR+ of 5.4 (95% CI, 2.7-10.6), further highlighting its predictive strength. In nulliparous women at rest, AOP exhibited strong performance, with a sensitivity of 87% (95% CI, 75-94%) and a specificity of 90% (95% CI, 82-94%). An AOP exceeding 145.5° was linked with a 98% probability of successful vaginal delivery, while an AOP below 120° reduced the likelihood of uncomplicated OVD from 85% to 57%. These findings underscore AOP's value as a predictive tool for uncomplicated OVD, reinforcing its potential in clinical decision-making and labor management optimization. HPD was first described by Eggebo et all in 2009. (8) HPD of 60 mm corresponds to head station at the pelvic inlet, 36 mm corresponds to mid-cavity, and 20 mm corresponds to the pelvic outlet. (9,43) HPD of 40 mm has been reported as cutoff level for high chance for a vaginal delivery in nulliparous women with a prolonged first stage of labor, and HPD of 35 mm for a successful vacuum extraction. (28,29,44). Table 7 summarises the available studies on HPD in labour prediction. Our study was consistent with these findings in that at a HPD of <39mm, VD was predicted with a sensitivity of 63.4% (AUC 66.6%). Although intrapartum ultrasound (ITU) has proven its role in labour care, no studies have yet established that ITU is superior to traditional vaginal examinations. Nevertheless, comparative studies between role of vaginal examination alone and vaginal examination combined with ITU have demonstrated that the combined models are superior. It is crucial to acknowledge that while ITU plays an invaluable role in enhancing clinical examinations, it cannot fully substitute for them just yet. Although the technique is standard, lack of standardized inferential cut-offs is the main hindrance to the use of ITU in everyday clinical practice especially in under resourced countries. No validations have been performed in specific populations that are needed to interpret the findings even in a situation where one is trained to perform the assessment. Standardizing inferential values for ITU could promote the widespread adoption of this non-invasive technique. Additionally, as it is easily reproducible, it can serve as a valuable tool for junior obstetricians in institutional settings, helping to enhance their confidence and proficiency in managing labor. Table 5: Summary of studies: Role of AOP in 1 st stage of labour Study Characteristics of study Participants No. and Type Fetal head position Outcome Time to Delivery (TTD) Nouri-Khasheh-Heiran et al. (2023) (15) 1st stage, Group 1 - Vaginal examination, Group 2 - Vaginal examination + ITU 392, Group 1-196, Group 2-196, Nulliparous (42.34%) multiparous (57.66%) OA (97.7%) OP (2.3%) AOP 135° VD: sensitivity: 91.2%, P<0.001 NA Vinod et al. (2022)(14) 1st stage 185, Nulliparous (74.1%) multiparous (25.9%) OA AOP ≥89°: VD: AUC 0.789; sensitivity: 79.3%; specificity: 65.6%; PPV 81.3% NPV: 62.7% NA Hjartardóttir et al. (2021)(16) 1st stage >4cm 99, Nulliparous N.A. AOP: ≥93°- VD: AUC 0.67 (95% CI 0.55–0.80) sensitivity: 79% AOP 110°: 5.2 hours (95% CI 4.7-5.7 hours), AOP 125°: 3.0 hours (95% CI 2.4-3.7 hours), AOP 95°: 7.4 hours, AOP 80°: 9.5 hours Kandil et al. (2021)(17) 1st stage 80, Nulliparous N.A. AOP: >104°- VD: AUC 0.962; sensitivity: 90%; specificity: 86%; PPV: 95%; NPV: 76%; Accuracy: 88% NA Elkadi et al. (2021)(18) 1st stage 56, Nulliparous OA AOP ≥97.0° VD: AUC 0.902 (95% CI 0.817–1.000; P=0.002); sensitivity: 92.2% (95% CI 81.1–97.8); specificity: 80.0% (95% CI 28.4–99.5); PPV: 97.9% (95% CI 88.9–99.9); NPV: 50.0% (95% CI 15.7–84.3) NA Priya et al. (2021)(13) 1st stage 200, Nulliparous (67.5%) multiparous (32.5%) N.A. AOP: >99.6° for VD AUC 0.920 (95% CI 0.88–0.95) NA Bulut et al. (2020)(19) 1st stage 122, Nulliparous (34.3%) multiparous (63.7%) N.A. AOP: >132.5° VD: 91% (95% CI 0.62–0.93 P=0.002) sensitivity: 70% specificity: 75% NA Frick et al. (2020)(20) 1st stage 512, Nulliparous (41.3%) multiparous (58.7%) OA AOP >113°- decreases CD likelihood OR: 0.96 (95% CI 0.94–0.99) Median TTD at AOP: 125°, 9.7 hours for nulliparous with epidural, 5.3 hours for nulliparous without epidural, 3.3 hours for parous with oxytocin use, 1.5 hours for parous without oxytocin use Solaiman et al. (2020)(21) Prolonged 1st & 2nd stage 28, Nulliparous (25%) Multiparous (75%) LOP: 64.3%, ROP & LOT: 10.7% each, LOA & ROA: 7.1% each AOP: 115° VD: 91% AUC: 0.913 sensitivity: 93%; specificity: 84% PPV: 87% NPV: 91% NA Ibrahim et al. (2021)(22) Active 1st stage 600, Nulliparous N.A. AOP: 107.5°- VD: sensitivity: 52%; specificity: 81%; PPV 89.8% P<0.001 NA Chor et al. (2019) (23) Active 1st stage 183, Nulliparous N.A. VD: median AOP of 115.1° (IQR: 103.9°–126.1°), CD: median AOP of 108.3° (IQR: 100.9°–114.2°), P = 0.008 NA Ingeberg et al. (2017)(24) 1st stage 36, Nulliparous N.A. AOP: ≥105° 58.33% VD, AOP <105° 19.2% VD (p125°- VD: AUC 0.85 (95% CI 0.77–0.92) sensitivity: 67.1% NA Nishimura et al. (2016)(26) 1st stage – to identify labor arrest 63, Nulliparous (54%) multiparous (46%) N.A. AOP: <105° CD: 95% CI 79°–105° P=0.035 sensitivity: 40.4% specificity: 90.9% NA Marsoosi et al. (2015)(27) 1st stage 70, Nulliparous (64.3%) multiparous (35.7%) OA VD: 92.9%, Mean AOP: 103.02° ± 10.727°, CD: 7.1%, Mean AOP: 88.60° ± 5.857° NA Eggebo et al. (2014)(28) Prolonged 1st stage 150, Nulliparous N.A. AOP ≥110°: VD: 88% (95% CI 79–93%), OR: 3.11 (95% CI 1.01–9.56), AOP <110°: VD: 57% (95% CI 45–69%), OR: 3.36 (95% CI 1.24–9.12) AOP ≥110°: significant shorter time to delivery Torkildsen et al. (2011)(29) Prolonged 1st stage (crossed action line) 110, Nulliparous OA AOP ≥110°: VD: 87% (95% CI 75–93%), AOP 100–110°: VD: 82% (95% CI 66–91%), AOP <100°: VD: 38% (95% CI 21–57%) NA Table 6: Summary of Studies: Role of AOP in 2 nd stage of labour Study Characteristics of study Participants No. and Type Fetal head position Outcome Time to Delivery (TTD) Katzir et al. (2023) (33) Second stage 181, Nulliparous N.A. AOP ≥127° VD: 88.6% OR: 1.070 95% CI: 1.031–1.111; P<0.001 AOP <127°: 95 ± 8.8 min AOP 127–137°: 72 ± 5.6 min AOP 138–147°: 56 ± 6.6 min Zarean et al. (2022) (34) 2nd stage 80, Nulliparous (55.0%) multiparous (45.0%) N.A. Mean AOP: VD: 149.47° ± 4.47° CD: 124.20° ± 6.81° Vacuum VD: 137.48° ± 1.51° P <0.01 Significant inverse correlation with the duration of the second stage of labor and AOP: Correlation Coefficient: -0.642 (P 118.5°- predictive of CD Sensitivity: 82% Specificity: 87% AUC: 0.866 (95% CI: 0.761–0.972) P < 0.001 NA Barros et al. (2021) (36) RCT- To study role of ITU before instrumentation in reducing maternal and neonatal morbidity 222, Experimental arm-113 Control arm- 109, Nulliparous (65.5%) multiparous (34.5%) OA (65.3%) Non-OA (34.7%) Median AOP148° 95% CI 137°-160°-ID with a single instrument Median AOP 139° 95% CI 125°-150°) (P = .036)- ID with two instruments or CS NA Carvalho Neto et al. (2021)(37) 2nd stage 221, Nulliparous (65.5%) multiparous (34.5%) OA: 62.5% OP: 6.9% OT: 30.6% AOP >129.9°: VD: sensitivity 85%; specificity 63% AUC 0.76 (95% CI: 0.64-0.88 p=0.003) Mean ±SD for VD 129.9°: 55±44 min Hadad S. et al (2021)(38) Active 2nd stage At rest & at pushing 197, Nulliparous OA (90%) OP (10%) For spontaneous VD At Rest: AOP of 138° (sensitivity:71.6 specificity: 83.7 PPV: 96) p116° VD: AUC: 0.989 sensitivity: 96.49%; specificity:96.43% AOP 121°-150°: Mean TTD = 54.44 minutes AOD 151°-180°: Mean TTD = 20.79 minutes Sainz JA et al. (2017)(31) Vacuum VD 52, Nulliparous OA (100%) AOP >127.3 VD at rest: ICC 0.96 (95% CI: 0.89-0.99) P139.7° VD on pushing: ICC 0.98 (95% CI: 0.96-0.99) P132° AOP >138° (second stage) VD: AUC 0.97 (95% CI 0.90–0.99); sensitivity 91.38% NA Cuerva et al. (2014)(30) 2nd stage To predict complicated forceps delivery in non-OP 30, Nulliparous LOT (10%) ROT (3.3%) LOA (46.7%) ROA (30%) OA (10%) AOP (between contractions): 120°: Vaginal delivery (100%) ≤ 135°- median 45.5 (range 23–48) min 136◦ –167◦: median 16.5 (range 12–27) min 168◦ –200◦: median 8.0 (range 5–17) min > 200◦: median 5.0 (range 1–9) min Kalache et al. (2009)(29) Prolonged 2nd stage 26, Nulliparous OA AOP: >120°: VD or Easy vacuum: 90% AOP > 100°: 25% probability of successful delivery (R2 measure of fit=55%; LR chi-square P<0.0001) NA Table 7: Summary of studies: Role of HPD in labour Study Characteristics of study Participants No. and Type Fetal head position Cut off HPD Outcome Hadad S. et al (2021)(38) Active 2nd stage At rest & at pushing 197, Nulliparous OA (90%) OP (10%) Mean HPD at rest (mm) (28.60±9.10) (35.80±7.70) HPD at active pushing (mm) 23.00±9.30 31.60±8.10 Spontaneous VD, ID, p<0.05 Spontaneous VD ID p4cm 99, Nulliparous N.A. ≤45mm VD: AUC: 0.68 (95% CI 0.55 −0.80) Kandil et al. (2021)(17) 1st stage 80, Nulliparous N.A. <45mm VD: AUC: 0.917 sensitivity ~88% specificity 91% Ibrahim et al. (2021)(22) Active 1st stage 600, Nulliparous N.A. 39.5mm VD: sensitivity: 62% specificity: 63% PPV: 84.5% P 4.3 cm Surgical (CD + ID) Sensitivity: 69% Specificity: 89% AUC 0.80 (95% CI: 0.66–0.93 p = 0.001) Andrea Dall’Asta et al. (2019)(45) Prolonged second stage of labor 109, Nulliparous OA (100%) Mean HPD 33.2 mm ± 7.8 mm 40.1 mm ± 9.5 mm Spontaneous VD CD/vacuum VD p 3.16 cm 100% VD 45% VD Arithmetic mean HPD in VD group: 3.0cm CD group: 4.12cm Antonio Sainz J et al. (2016)(48) Vacuum VD 75, Nulliparous OA (100%) Mean HPD at pushing 38.2mm 47mm 48.4mm Easy vacuum VD, Difficult vacuum VD, Failed vacuum VD Ingeberg et al. (2017)(24) 1st stage 36, Nulliparous N.A. ≤40 mm >40mm 50% VD 22.2% (P <0.001). Solaiman et al. (2020)(21) Prolonged 1st & 2nd stage 28, Nulliparous (25%) Multiparous (75%) LOP :64.3% ROP & LOT: 10.7% each LOA & ROA: 7.1% each 42mm VD: 84% AUC: 0.841; sensitivity 80% specificity 84% PPV 85% NPV 78% Eggebo et al. (2014) (28) Prolonged 1st stage 150, Nulliparous NA ≤ 40 mm >40mm VD: 92%; (95% CI 84–96%) VD: 52%; (95% CI 40–63%) Torkildsen et al. (2011)(29) Prolonged 1st stage (crossed action line) 110, Nulliparous OA ≤ 40 mm 40-50mm >50mm VD: 93% (95% CI 83–97%) VD: 67% (95% CI 53–80%) VD 18% (95% CI 5–48%) Strengths and limitations : While most studies have focused on analyzing the role of the AOP during the late first stage and the second stage of labor, our research highlights that a favorable AOP at the onset of labor can itself predict labor outcomes, a key finding of this study. Caesarean rate at our centre currently exceeds 50% due to the high volume of patients and the high-risk nature of the referrals we receive. By incorporating ITU into routine labor care, we were able to significantly lower the Caesarean rate to 25%. We could ensure uniformity in ITU findings, as the interobserver variation was minimal. However, we found that there occured some minor variations in HPD measurements in women with higher BMI, as the ultrasound transducer needs to be positioned at the perineum and pressed firmly against pubic bone. A small sample size and different obstetricians managing labor room on different days are some of the confounding factors that could not be controlled, limiting the generalizability of the study findings. Conclusion ITU, particularly AOP and HPD can improve labor outcomes. At cut offs > 104 and < 39mm in early labour, AOP and HPD hold good predictive accuracy for vaginal delivery. Although ITU cannot yet replace clinical vaginal examination, incorporating it into routine labor management could significantly reduce the burden of morbidity related to CD. Efforts should be made to standardise the use of ITU & to overcome the barriers to its adoption in LMICs, ensuring that all women, regardless of geographic location or socioeconomic status, have access to safe and effective labor monitoring tools. Declarations Ethics approval and consent to participate: This prospective observational study was carried out in a tertiary care centre in South India. The study was approved by the Kasturba Medical College & Kasturba Hospital Institutional Ethics Committee (Study number: 685/2020) on 10.11.2020. Written and informed consent was obtained individually from all participants included in the study. Consent for publication: Departmental and institutional consents to publish have been obtained. Availability of data and material: Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0) Name of the repository: Mendeley Data DOI:10.17632/z6c4272sd3.1 Reddy D, Sharma N. AOD and HPD in predicting vaginal delivery. Mendeley Data. 2024; V1. (https://data.mendeley.com/datasets/z6c4272sd3/1) Competing interests: There are no competing interests for this study. Funding: No external funding agency has supported this work. 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08:54:27","extension":"html","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":250872,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7051979/v1/670d51548472472dc14fea7f.html"},{"id":93918598,"identity":"ce5e669f-b9d4-44c0-8980-adf21325d649","added_by":"auto","created_at":"2025-10-20 09:18:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1182960,"visible":true,"origin":"","legend":"\u003cp\u003ea- Trasperineal ultrasound image showing angle of progression- between the long axis of pubic bone and a line from the lowest edge of the pubis tangential to the deepest bony part of fetal skull.\u003c/p\u003e\n\u003cp\u003eb: With the ultrasound beam perpendicular to the fetal skull, HPD is measured as the shortest distance from the outer bony limit of fetal skull to perineum.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7051979/v1/173646a4dd3e486435617ea3.png"},{"id":93916988,"identity":"e0d090d8-ccc2-47c6-bffe-e70b03095911","added_by":"auto","created_at":"2025-10-20 08:54:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81001,"visible":true,"origin":"","legend":"\u003cp\u003ea: Scatterplot depicting the correlation between AOP and HPD in the study cohort\u003c/p\u003e\n\u003cp\u003eb: Scatterplot depicting the correlation between AOP and cervical dilatation\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7051979/v1/20439ab2f2585b3fb099c271.png"},{"id":93918282,"identity":"55b9a5c8-68a2-44e9-8e4b-cb49775007cf","added_by":"auto","created_at":"2025-10-20 09:10:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":86347,"visible":true,"origin":"","legend":"\u003cp\u003eStacked bar graph showing head station (clinical vs AOD derived)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7051979/v1/b6017ea3dac17ed17e924437.png"},{"id":93916995,"identity":"8cf013b3-6665-40bc-96b5-8c977cbbf1f7","added_by":"auto","created_at":"2025-10-20 08:54:27","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":85717,"visible":true,"origin":"","legend":"\u003cp\u003eStacked bar graph showing head station (clinical vs HPD derived)\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7051979/v1/54b0de964f65f27312e5464e.png"},{"id":93916993,"identity":"02d92430-9d26-440a-915e-940614888eb1","added_by":"auto","created_at":"2025-10-20 08:54:27","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":110900,"visible":true,"origin":"","legend":"\u003cp\u003eROC Curve Analysis Showing Diagnostic Performance of\u003c/p\u003e\n\u003cp\u003ea. AOP in Predicting Mode of Delivery b. HPD in Predicting Mode of Delivery (NVD Vs LSCS)\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7051979/v1/848d11d9171b697de2ad6c7b.png"},{"id":95818823,"identity":"1819465d-706d-45c8-bfad-df7ddbc854d0","added_by":"auto","created_at":"2025-11-13 10:33:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3133558,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7051979/v1/140e7db4-f449-4260-8ec0-bd976663d29c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Emerging role of angle of progression and head-perineum distance in predicting labor outcome: original research supported by a mini-review","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCervical dilatation and fetal head descent are the two most important requirements for a successful vaginal delivery. \u0026nbsp;A digital vaginal examination has been the standard way to identify and monitor descent. However, the bony landmarks in the pelvis are challenging to discern on palpation, which makes this method subjective to the individual examiner, resulting in a biased assessment.(1,2) Traditional partogram has worked out as an excellent tool to monitor labor. However, whether it continues to remain a scientifically valid tool to decide on an obstetric intervention such as a Caesarean section (CS), has been a point of debate in the last decade. In this light, the WHO has published new recommendations on intrapartum care using the Labor Care Guide (LCG).(3) It is now understood that the duration of first and second stage of labor is highly variable among women and the current stipulated rates of dilatation and descent may be unrealistically fast for some. More and more studies suggest that prolonged labor or a protracted second stage, per se, is not directly related to neonatal or maternal morbidity but may be related to various other things including health-care provider actions and interventions in response to the understood delay. In the era of superior fetal monitoring techniques and supervised institutional deliveries, the absolute risks of fetal and neonatal consequences of increasing the duration of labor appear to be, at worst, low or incremental. (4) In light of caesarean deliveries rising to an unacceptable rate in the recent years, it is now time for obstetricians all over, to contemplate on whether set points and defined labor progress cut- offs need to be made less stringent to maintain an acceptable vaginal delivery rate, and also to identify newer methods to predict a successful vaginal delivery. One such is the use of intrapartum transperineal ultrasound (ITU). The descent and position of the fetal head and determining arrest of labor are some of the things that can be done with ITU assessments particularly AOP and HPD, in a more precise and propagative manner.(5) There is mounting evidence that AOP offers unbiased information on fetal haed station and may prognosticate the outcome of operative vaginal delivery.(6) Although US is now easily available at most centres even in LMICs, its use in labour is not standard practice. This study aimed at understanding the usefulness of AOP and HPD in predicting vaginal delivery in labour settings of under-resourced countries.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis prospective observational study was carried out in a tertiary care centre in South India between 2021 and 2022 on term pregnant women in labor. The study was approved by the Institutional Ethics Committee (IEC number: 685/2020) and registered with CTRI (No: CTRI/2021/02/030936).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe sample size was calculated as 117 using the formula\u0026nbsp;N = ((Z_alpha/2 + Z_beta)^2 * (1 + k)) / ((AUC - AUC_0)^2 * k), with an expected AUC of 0.75, \u0026alpha;=0.05, power of 80% and k=1.\u003c/p\u003e\n\u003cp\u003eIncluded cohort of women were primigravidas and multigravidas with not more than one prior vaginal delivery at a gestational age over 37 weeks in early labor (presence of regular uterine contractions and a cervix dilated by not more than 4cm, on digital vaginal examination), secondary to both spontaneous onset and labor induction. The mode of induction was standardized using Propess (PGE2) gel. We included multigravidas with one prior vaginal delivery as the spacing between pregnancies was over 6 years, and we observed that labor progression and intervals in this group of women at our centre is identical to primigravidas. Pregnant women with PROM, multiple gestation, more than 1 prior vaginal delivery, non-cephalic presentation, previous Caesarean section and a non-reassuring fetal heart on CTG were excluded. In addition, women who did not go into labor despite induction and those with fetal head above pelvic brim at the time of recruitment were also excluded due to the non-feasibility of obtaining an accurate HPD in these cases. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained individually from all participants included in the study. On admission, a detailed medical history, clinical examination and digital vaginal examination, Bishop\u0026rsquo;s score calculation were conducted for all study participants by the obstetrician in labor room. Women satisfying the inclusion criteria were subjected to a transperineal ultrasound. Ultrasound was performed with the Philips Clear Vue 350 ultrasound system equipped with C5-2 broadband curved array transducer of frequency range 2-5 MHz, by an experienced obstetrician who was blinded to the findings derived by digital examination.\u003c/p\u003e\n\u003cp\u003eTo measure the AOP, the transducer was positioned in between the labia in a mid-sagittal plane. The obtained image was frozen, and a tangent was drawn from the deepest bony part on the fetal skull to the lower border of pubic symphysis. (7)\u0026nbsp;The angle formed between these lines was measured as AOP (Figure 1a). To measure HPD, the transducer was positioned over the vulva at the level of posterior commissure on a transverse plane and pressed gently against pubic rami. A caliper drawn between the perineum and the outer bony limit of the fetal skull on a transverse plane gave the HPD in millimeters. (8) (Figure 1b).\u003c/p\u003e\n\u003cp\u003eThe team of obstetricians involved in labor monitoring and delivery were blinded to the findings of the intrapartum TPU. Maternal monitoring was done hourly and on a need basis as stipulated by the WHO labor guidelines. Fetal surveillance was done in the form of second hourly CTGs till 4cm of dilatation, and continuously thereafter till delivery, in line with the institutional labor protocol. Antibiotic prophylaxis was provided for all with Inj. Amoxicillin 2g IV at rupture of membranes. Women at or beyond 6cm of cervical dilatation with ruptured membranes who failed to progress, despite 4 hours of good uterine activity or 6 hours of oxytocin administration and no cervical change, were said to be in active phase arrest. Second stage arrest was diagnosed at a maximum of 2 hours in multiparous women and 3 hours in nulliparous women where maternal and fetal conditions were acceptable. (4)\u003c/p\u003e\n\u003cp\u003eMeans, standard deviations and medians, IQRs were used to comprehend continuous variables for descriptive analysis depending on skewness which was assessed using Shapiro Wilks\u0026rsquo; test. Frequencies and percentages were used for categorical variables. Independent sample \u0026lsquo;t\u0026rsquo; test was used for comparing two groups in which the data was continuously distributed data. Non-parametric tests such as Wilcoxon-Mann Whitney U Test were used to compare groups where the data was not normally distributed. A best discriminatory AOP and HPD cut off for predicting those likely to have a vaginal delivery was determined by receiver operating characteristics (ROC) curve. P- value of \u0026lt;0.05 was considered statistically significant. Data were analyzed using the software package SPSS 23.0 (IBM Corp.).\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe study initially included 118 participants. However, 5 participants were excluded: 3 presented with premature rupture of membranes (PROM), and 2 underwent emergency cesarean sections (CS)\u0026mdash;one due to meconium-stained amniotic fluid (MSAF) and the other because of fetal distress, leaving a total of 113 participants for analysis. Of these, 86 were primigravidas, and 27 were second gravidas with one previous vaginal delivery (VD). Among the participants, 55.7% (63) women went into spontaneous labor, while 44.2% (50) underwent induction using Propess (PGE2 gel). Position was either occipito- anterior or transverse in all cases. For the inital 22 participants, there was a good correlation for both AOP and HPD between the two obstetricians [Intra-class correlation coefficient (ICC): 0.85, 95% CI (0.80- 0.89) and ICC: 0.90, 95% CI (0.86-0.94)] for AOP and HPD respectively. A total of 72.5% (55 primigravida and all 27 multigravida) had a vaginal delivery (n=82), while 27.4% (n=31) had a CS. In the VD group, the mean duration of 1\u003csup\u003est\u003c/sup\u003e stage of labor was 11.70(3.28) hours in women who went into spontaneous labor and 13.4(3.02) hours in women who required labor induction, which was not statistically significant. This assured us that, once onset was established, spontaneous or induced, labour progression did not differ to an extent that was clinically relevant, and a separate group analysis for the spontaneous and induced was not performed. The indications for CS were labor arrest in 1\u003csup\u003est\u003c/sup\u003e stage in 96.6% (29) women and arrest in second stage in 3.3% (2) women. Epidural analgesia was administered to 3 women, all of whom subsequently had vaginal deliveries. Maternal and perinatal outcomes were similar in both the groups. There was no significant statistical difference in age, height and body mass index (BMI) between the VD and the CS groups. (Table 1)\u003c/p\u003e\n\u003cp\u003eTable 1: \u0026nbsp;Participant characteristics and perinatal outcomes in this cohort (n=113)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"598\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal (n=113)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVD (n=82)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCD (n=31)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (y)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e28.34 \u0026plusmn;\u0026nbsp;3.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e28.57 \u0026plusmn;\u0026nbsp;3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e27.71\u0026plusmn;\u0026nbsp;3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.25 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e157.83 \u0026plusmn;\u0026nbsp;5.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e158.05\u0026plusmn;\u0026nbsp;4.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e157.27\u0026plusmn;\u0026nbsp;6.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.13 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight (kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e64.49 \u0026plusmn;\u0026nbsp;9.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e64.63\u0026plusmn;\u0026nbsp;9.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e64.12\u0026plusmn;\u0026nbsp;8.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.86\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (kg/m2)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e25.84 \u0026plusmn;\u0026nbsp;3.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e25.84\u0026plusmn;\u0026nbsp;3.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e25.86\u0026plusmn;\u0026nbsp;3.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.75\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGestational age(weeks)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e38.85 \u0026plusmn;\u0026nbsp;0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e38.81\u0026plusmn;\u0026nbsp;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e38.98\u0026plusmn;\u0026nbsp;0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.16\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParity n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;Primigravida\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;Multigravida\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e55 (67.1%)\u003c/p\u003e\n \u003cp\u003e27 (32.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e31 (100.0%)\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLabor onset n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;Spontaneous \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;Propess (PGE2)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e55(48.6%)\u003c/p\u003e\n \u003cp\u003e27(23.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8(7.07%)\u003c/p\u003e\n \u003cp\u003e23(20.35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep\u0026lt; 0.05\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBirth weight (g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e3024.87\u0026plusmn;\u0026nbsp;353.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e3003.60\u0026plusmn;\u0026nbsp;340.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e3081.13\u0026plusmn;\u0026nbsp;385.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.32\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAPGAR score 1min\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e8.63\u0026plusmn;\u0026nbsp;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e8.71\u0026plusmn;\u0026nbsp;0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e8.42\u0026plusmn;\u0026nbsp;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.14\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAPGAR score 5 min\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e9.60\u0026plusmn;\u0026nbsp;0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e9.06 \u0026plusmn; 0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e9.10 \u0026plusmn; 0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.648\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 598px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.Independent t test, 2. Chi-square test, 3. Wilcoxon Mann Whitney U test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe intrapartum characteristics of the study cohort is presented in Table 2. Women with greater cervical dilatation at admission (2.04 \u0026plusmn; 1.47 cm vs. 1.41 \u0026plusmn; 0.82 cm, p \u0026lt; 0.0013) were significantly more likely to have a vaginal delivery. In contrast, cervical length and fetal head station showed no significant differences between the groups, indicating that these parameters, though part of the traditional Bishop\u0026apos;s score, may not reliably predict labor outcomes. Aditionally, our data suggests that all multigravidas and those who entered labor spontaneously (56.6% vs. 13.3%, p \u0026lt; 0.0052) \u0026nbsp;were more likely to achieve a vaginal delivery.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe mean AOP was significantly wider and was statistically significant (p \u0026lt;0.001) among the participants who had vaginal delivery. The mean HPD among the participants was 38.16 (8.57) mm. The mean HPD was higher among the participants who had Caesarean deliveries 41.48(8.28) mm as compared to the group who had vaginal delivery 36.90(8.39) mm. p\u0026lt;0.05.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2: \u0026nbsp;Intrapartum characteristics in the study cohort (n=113)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"571\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVD (n=82)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCD (n=31)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical examination\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCervical dilatation(cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003e2.04 \u0026plusmn; 1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e1.41 \u0026plusmn; 0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCervical length(cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003e1.35 \u0026plusmn; 0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e1.67 \u0026plusmn; 0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.24\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical Head Station\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003e-2.51 \u0026plusmn; 1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e-2.39 \u0026plusmn; 0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.23\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eITU\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAOP (degree)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMedian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e120.21 (9.50)\u003c/p\u003e\n \u003cp\u003e120 (100-140)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e92.32(5.57)\u003c/p\u003e\n \u003cp\u003e90 (84-107)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHPD (mm)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMedian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e36.90(8.39)\u003c/p\u003e\n \u003cp\u003e37 (21-63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e41.48(8.28)\u003c/p\u003e\n \u003cp\u003e41 (23-60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.011\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 571px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1. Wilcoxon Mann Whitney U test, 2. Independent t test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe association between AOP and cervical dilatation was conducted with Spearmans\u0026rsquo; correlation analysis. There was moderate positive correlation between cervical dilatation (cm) and AOP and this being statistically significant (rho=0.46, p= \u0026lt;0.001). It was observed that as AOP increases, the cervical dilatation increases as well, causing the fetal head to descend. Similarly, correlation analysis was done between HPD and cervical dilatation. There was a moderate negative correlation between cervical dilatation (cm) and HPD (mm), and this correlation was statistically significant (rho = -0.34, p = \u0026lt;0.001). As HPD decreases, there is a descent of fetal head and cervical dilatates leading to vaginal delivery. (Figure 2a, 2b)\u003c/p\u003e\n\u003cp\u003eFetal head station is a critical parameter that enables obstetricians to assess labor progress alongside cervical dilatation. Clinical decisions to perform a CD or instrumental delivery are often based on the head station, with the understanding that higher head stations are less likely to result in vaginal delivery. B. Tutschek et al. proposed an objective method to determine fetal head station through the conversion of AOP and HPD. (9) The agreement between clinical head station and the station derived from AOP in our cohort is presented in Table 3, Figure 3. \u0026nbsp;Although there was a fair agreement between the two methods, with a kappa of 0.289 and a statistically significant p-value (\u0026lt;0.001), the two methods were in complete agreement in only 12.4% of cases. Similarly, the agreement between clinical head station and the station derived from HPD is shown in Table 4, Figure 4. Complete agreement between these two methods was observed in only 10.4% of cases, despite a weighted kappa of 0.235 and a p-value \u0026lt;0.00. We believe the modest agreement between these methods observed in our cohort may be attributed to the digital vaginal examinations being performed by multiple obstetricians, introducing subjective error. This subjective error in assessing fetal head station is challenging to eliminate as it is operator-dependent and poorly reproducible. In contrast, stations derived from ITU are objective, standardized, reproducible, and capable of identifying subtle changes that might be missed or misinterpreted during digital examination. This underscores the importance of incorporating and standardizing the use of ITU in clinical practice.\u003c/p\u003e\n\u003cp\u003eTable 3: Comparison of station derived from AOD and clinical station(n=113)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"667\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"7\" style=\"width: 433px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical Station\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted Kappa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;-3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;-2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation 0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ek\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Station (conversion from AOP)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation -3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e10 (8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e7 (6.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e17 (15.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation -2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e6 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e2 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e9 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation -1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e5 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e4 (3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e10 (8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation 0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e9 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e13 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e7 (6.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e2 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e31 (27.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e13 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e10 (8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e11 (9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e38 (33.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e2 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e3 (2.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e2 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e8 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e33 (29.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e40 (35.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e22 (19.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e16 (14.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e113 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4: Comparison of clinical head station and station from HPD\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"662\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"7\" style=\"width: 460px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical Station\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted Kappa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation -3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation -2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation -1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation 0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ek\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Station (conversion from HPD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation -3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e3 (2.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e2 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e6 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" style=\"width: 31px;\"\u003e\n \u003cp\u003e0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation -2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e7 (6.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e4 (3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e11 (9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation -1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e11 (9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e6 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e19 (16.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation 0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e9 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e14 (12.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e8 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e33 (29.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e8 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e7 (6.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e5 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e22 (19.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e6 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e6 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e7 (6.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e22 (19.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e33 (29.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e40 (35.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e22 (19.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e16 (14.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e113 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eReceiver Operating Characteristics (ROC) curve analysis was done for analysing the diagnostic performance of AOP and HPD in predicting vaginal delivery. The area under the ROC curve for AOP for predicting vaginal delivery was 0.996 (95% CI: 0.99- 1.00). At a cut off \u003cu\u003e\u0026gt;\u003c/u\u003e 104.5 degree, AOP predicts vaginal delivery with a sensitivity of 95.1% and specificity of 96.8%. The area under the ROC curve for HPD for predicting vaginal delivery was 0.666 (95% CI: 0.55- 0.77). At a cut-off of HPD \u0026le;39.5mm, it predicts vaginal delivery with a sensitivity of 63.4%, and a specificity of 64.5%. 78 (95.1%). Out of 82 participants with vaginal delivery, 78 (95.1%) had AOP \u003cu\u003e\u0026gt;\u003c/u\u003e 104.5 degree while 4 (4.87%) participants had AOP\u0026lt;104.5 degree. \u0026nbsp;One (3.22%) out of 31 participants who underwent caesarean delivery due to second stage arrest, had AOP \u003cu\u003e\u0026gt;\u003c/u\u003e 104.5 degree. 52 (63.4%) out of 82 participants with vaginal delivery had HPD \u0026le;39.5mm while 30 (36.5%) participants had HPD\u0026gt; 40mm. 11(35.4 %) participants out of 31 underwent caesarean delivery in whom HPD \u0026le;39.5mm. (Figure 5a, 5b.)\u003c/p\u003e"},{"header":"Discussion \u0026 Review ","content":"\u003cp\u003eThe use of ultrasound for studying fetal head descent dates back to 1977, pioneered by Lewin et al. (10) AOP was first described by Barbera et all in 2009 (7). Ever since, numerous observational studies have demonstrated that AOP can be a useful tool for predicting labor outcomes before labor induction, as an admission test, and during both the first and second stages of labor. The pre labour assessment of AOP has shown conflicting results. While a study by Minajagi et all (11) claims that pre labour AOP \u0026lt; 96\u0026deg; predicts a high chance of CD, Chan et all (12) reported that pre-labor measurement of AOP is not a reliable predictor of the outcomes of induction of labor, and that it is multifactorial. Our study included parturients in established early labor, and our decision to perform a cesarean section (CS) was guided not by traditional partogram suggestions, but by the guidelines from the American College of Obstetricians and Gynecologists (ACOG) and the Society for Maternal-Fetal Medicine (SMFM) on the safe prevention of primary cesarean delivery.(4) The optimal cutoff for the Angle of Progression (AOP) in predicting vaginal delivery (VD) in our study was 104\u0026deg;, which is slightly lower than other studies. This discrepancy may be due to the fact that most previous studies were conducted at a much advanced phase of the first stage of labor. Two other studies conducted in LMICs such as ours also had a lower cut off for AOP (\u0026gt; 89\u0026deg; and \u0026gt;99.6\u0026deg;). However, the sensitivity and predictive accuracy were moderate at best. (13, 14) Table 5 summarises key findings of several studies related to AOP in the 1\u003csup\u003est\u003c/sup\u003e stage of labour.\u003c/p\u003e\n\u003cp\u003eThe International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) recommends the use of intrapartum ultrasound in cases of prolonged or arrested labor, in both the first and second stages, particularly when fetal malpositions or malpresentations are suspected, and prior to operative vaginal delivery. (6) However, the recommended cutoff levels for instrumentation during the second stage of labor vary across studies, ranging from 120\u0026deg; to 145.5\u0026deg;. (29-32) Table 6 shows a summary of available studies on utility of AOP in second stage of labour, with a few studies focussing on role of AOP in predicting the success rates of instrumental delivery. Also, the predictive accuracy of AOP may vary between fetuses in OA and OP positions. In OP positions, the fetal head tends to descend deeper into the birth canal before the third cardinal movement, flexion, begins, in contrast with the OA position. \u0026nbsp;Even when completely flexed, a fetus in OP cannot traverse through the birth canal as effectively as a fetus in OA position. Having understood this, it becomes clear that a significant limitation in the current literature is the variation in inclusion criteria and outcomes across studies, and the absence of randomized designs in the available publications. (41) Frick et all. (20) found that a model incorporating maternal height, parity, gestational age, fetal weight, and AOP achieved the highest AUC at 0.8. Therefore, to establish an optimal cutoff value for AOP, further studies are needed to explore more comprehensive models that account for the interaction of multiple factors.\u003c/p\u003e\n\u003cp\u003eA recent meta-analysis by Nassr AA et all. (42) comprised of seven studies involving 782 pregnant women revealed that AOP is a reliable predictor of uncomplicated operative vaginal delivery (OVD), with a sensitivity of 80% (95% CI, 59-92%), specificity of 89% (95% CI, 76-95%), and a positive likelihood ratio (LR+) of 7.3 (95% CI, 3.1-15.8) during the resting phase. During the pushing phase, AOP showed a sensitivity of 91% (95% CI, 85-94%) and a specificity of 83% (95% CI, 69-92%), with an LR+ of 5.4 (95% CI, 2.7-10.6), further highlighting its predictive strength. In nulliparous women at rest, AOP exhibited strong performance, with a sensitivity of 87% (95% CI, 75-94%) and a specificity of 90% (95% CI, 82-94%). An AOP exceeding 145.5\u0026deg; was linked with a 98% probability of successful vaginal delivery, while an AOP below 120\u0026deg; reduced the likelihood of uncomplicated OVD from 85% to 57%. These findings underscore AOP\u0026apos;s value as a predictive tool for uncomplicated OVD, reinforcing its potential in clinical decision-making and labor management optimization.\u003c/p\u003e\n\u003cp\u003eHPD was first described by Eggebo et all in 2009. (8) HPD of 60 mm corresponds to head station at the pelvic inlet, 36 mm corresponds to mid-cavity, and 20 mm corresponds to the pelvic outlet. (9,43) HPD of 40 mm has been reported as cutoff level for high chance for a vaginal delivery in nulliparous women with a prolonged first stage of labor, and HPD of 35 mm for a successful vacuum extraction. (28,29,44). Table 7 summarises the available studies on HPD in labour prediction. Our study was consistent with these findings in that at a HPD of \u0026lt;39mm, VD was predicted with a sensitivity of 63.4% (AUC 66.6%).\u003c/p\u003e\n\u003cp\u003eAlthough intrapartum ultrasound (ITU) has proven its role in labour care, no studies have yet established that ITU is superior to traditional vaginal examinations. Nevertheless, comparative studies between role of vaginal examination alone and vaginal examination combined with ITU have demonstrated that the combined models are superior. It is crucial to acknowledge that while ITU plays an invaluable role in enhancing clinical examinations, it cannot fully substitute for them just yet. Although the technique is standard, lack of standardized inferential cut-offs is the main hindrance to the use of ITU in everyday clinical practice especially in under resourced countries. No validations have been performed in specific populations that are needed to interpret the findings even in a situation where one is trained to perform the assessment. Standardizing inferential values for ITU could promote the widespread adoption of this non-invasive technique. Additionally, as it is easily reproducible, it can serve as a valuable tool for junior obstetricians in institutional settings, helping to enhance their confidence and proficiency in managing labor.\u003c/p\u003e\n\u003cp\u003eTable 5: Summary of studies: Role of AOP in 1\u003csup\u003est\u003c/sup\u003e stage of labour\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"874\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Study\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCharacteristics of study\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eParticipants No. and Type\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eFetal head position\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOutcome\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTime to Delivery (TTD)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eNouri-Khasheh-Heiran et al. (2023) (15)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage, Group 1 - Vaginal examination, Group 2 - Vaginal examination + ITU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e392, Group 1-196, Group 2-196, Nulliparous (42.34%) multiparous (57.66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA (97.7%) OP (2.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP 135\u0026deg; VD: sensitivity: 91.2%, P\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVinod et al. (2022)(14)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e185, Nulliparous (74.1%) multiparous (25.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP \u0026ge;89\u0026deg;: VD: AUC 0.789; sensitivity: 79.3%; specificity: 65.6%; PPV 81.3% NPV: 62.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eHjartard\u0026oacute;ttir et al. (2021)(16)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage \u0026gt;4cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP: \u0026ge;93\u0026deg;- VD: AUC 0.67 (95% CI 0.55\u0026ndash;0.80) sensitivity: 79%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP 110\u0026deg;: 5.2 hours (95% CI 4.7-5.7 hours), AOP 125\u0026deg;: 3.0 hours (95% CI 2.4-3.7 hours), AOP 95\u0026deg;: 7.4 hours, AOP 80\u0026deg;: 9.5 hours\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eKandil et al. (2021)(17)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP: \u0026gt;104\u0026deg;- VD: AUC 0.962; sensitivity: 90%; specificity: 86%; PPV: 95%; NPV: 76%; Accuracy: 88%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eElkadi et al. (2021)(18)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP \u0026ge;97.0\u0026deg; VD: AUC 0.902 (95% CI 0.817\u0026ndash;1.000; P=0.002); sensitivity: 92.2% (95% CI 81.1\u0026ndash;97.8); specificity: 80.0% (95% CI 28.4\u0026ndash;99.5); PPV: 97.9% (95% CI 88.9\u0026ndash;99.9); NPV: 50.0% (95% CI 15.7\u0026ndash;84.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ePriya et al. (2021)(13)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e200, Nulliparous (67.5%) multiparous (32.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP: \u0026gt;99.6\u0026deg; for VD AUC 0.920 (95% CI 0.88\u0026ndash;0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBulut et al. (2020)(19)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e122, Nulliparous (34.3%) multiparous (63.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP: \u0026gt;132.5\u0026deg; VD: 91% (95% CI 0.62\u0026ndash;0.93 P=0.002) sensitivity: 70% specificity: 75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eFrick et al. (2020)(20)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e512, Nulliparous (41.3%) multiparous (58.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP \u0026gt;113\u0026deg;- decreases CD likelihood OR: 0.96 (95% CI 0.94\u0026ndash;0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMedian TTD at AOP: 125\u0026deg;, 9.7 hours for nulliparous with epidural, 5.3 hours for nulliparous without epidural, 3.3 hours for parous with oxytocin use, 1.5 hours for parous without oxytocin use\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSolaiman et al. (2020)(21)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProlonged 1st \u0026amp; 2nd stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28, Nulliparous (25%) Multiparous (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLOP: 64.3%, ROP \u0026amp; LOT: 10.7% each, LOA \u0026amp; ROA: 7.1% each\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP: 115\u0026deg; VD: 91% AUC: 0.913 sensitivity: 93%; specificity: 84% PPV: 87% NPV: 91%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eIbrahim et al. (2021)(22)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eActive 1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e600, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP: 107.5\u0026deg;- VD: sensitivity: 52%; specificity: 81%; PPV 89.8% P\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eChor et al. (2019) (23)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eActive 1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e183, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVD: median AOP of 115.1\u0026deg; (IQR: 103.9\u0026deg;\u0026ndash;126.1\u0026deg;), CD: median AOP of 108.3\u0026deg; (IQR: 100.9\u0026deg;\u0026ndash;114.2\u0026deg;), P = 0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eIngeberg et al. (2017)(24)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP: \u0026ge;105\u0026deg; 58.33% VD, AOP \u0026lt;105\u0026deg; 19.2% VD (p\u0026lt;0.001).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u0026eacute;rez et al. (2017)(25)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e101, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP: \u0026gt;125\u0026deg;- VD: AUC 0.85 (95% CI 0.77\u0026ndash;0.92) sensitivity: 67.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eNishimura et al. (2016)(26)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage \u0026ndash; to identify labor arrest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63, Nulliparous (54%) multiparous (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP: \u0026lt;105\u0026deg; CD: 95% CI 79\u0026deg;\u0026ndash;105\u0026deg; P=0.035 sensitivity: 40.4% specificity: 90.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMarsoosi et al. (2015)(27)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e70, Nulliparous (64.3%) multiparous (35.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVD: 92.9%, Mean AOP: 103.02\u0026deg; \u0026plusmn; 10.727\u0026deg;, CD: 7.1%, Mean AOP: 88.60\u0026deg; \u0026plusmn; 5.857\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eEggebo et al. (2014)(28)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProlonged 1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e150, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP \u0026ge;110\u0026deg;: VD: 88% (95% CI 79\u0026ndash;93%), OR: 3.11 (95% CI 1.01\u0026ndash;9.56), AOP \u0026lt;110\u0026deg;: VD: 57% (95% CI 45\u0026ndash;69%), OR: 3.36 (95% CI 1.24\u0026ndash;9.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP \u0026ge;110\u0026deg;: significant shorter time to delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTorkildsen et al. (2011)(29)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProlonged 1st stage (crossed action line)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e110, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP \u0026ge;110\u0026deg;: VD: 87% (95% CI 75\u0026ndash;93%), AOP 100\u0026ndash;110\u0026deg;: VD: 82% (95% CI 66\u0026ndash;91%), AOP \u0026lt;100\u0026deg;: VD: 38% (95% CI 21\u0026ndash;57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 6: Summary of Studies: Role of AOP in 2\u003csup\u003end\u003c/sup\u003e stage of labour\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1204\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Study\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Characteristics of study\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eParticipants No. and Type\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eFetal head position\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOutcome\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTime to Delivery (TTD)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eKatzir et al. (2023) (33)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSecond stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e181, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP \u0026ge;127\u0026deg; VD: 88.6% OR: 1.070 95% CI: 1.031\u0026ndash;1.111; P\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP \u0026lt;127\u0026deg;: 95 \u0026plusmn; 8.8 min AOP 127\u0026ndash;137\u0026deg;: 72 \u0026plusmn; 5.6 min AOP 138\u0026ndash;147\u0026deg;: 56 \u0026plusmn; 6.6 min\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eZarean et al. (2022) (34)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2nd stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80, Nulliparous (55.0%) multiparous (45.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean AOP: VD: 149.47\u0026deg; \u0026plusmn; 4.47\u0026deg; CD: 124.20\u0026deg; \u0026plusmn; 6.81\u0026deg; Vacuum VD: 137.48\u0026deg; \u0026plusmn; 1.51\u0026deg; P \u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSignificant inverse correlation with the duration of the second stage of labor and AOP: Correlation Coefficient: -0.642 (P \u0026lt; 0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBrunelli et al. (2021) (35)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOccipito- posterior position in second stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63, Nulliparous (46.0%) multiparous (54.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOP (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP: \u0026gt;118.5\u0026deg;- predictive of CD Sensitivity: 82% Specificity: 87% AUC: 0.866 (95% CI: 0.761\u0026ndash;0.972) P \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBarros et al. (2021) (36)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRCT- To study role of ITU before instrumentation in reducing maternal and neonatal morbidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e222, Experimental arm-113 Control arm- 109, Nulliparous (65.5%) multiparous (34.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA (65.3%)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNon-OA (34.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMedian AOP148\u0026deg; 95% CI 137\u0026deg;-160\u0026deg;-ID with a single instrument Median AOP 139\u0026deg; 95% CI 125\u0026deg;-150\u0026deg;) (P = .036)- ID with two instruments or CS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCarvalho Neto et al. (2021)(37)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2nd stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e221, Nulliparous (65.5%) multiparous (34.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA: 62.5% OP: 6.9% OT: 30.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP \u0026gt;129.9\u0026deg;: VD: sensitivity 85%; specificity 63% AUC 0.76 (95% CI: 0.64-0.88 p=0.003)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean \u0026plusmn;SD for VD \u0026lt; 129.9\u0026deg;: 103\u0026plusmn;88 min \u0026gt;129.9\u0026deg;: 55\u0026plusmn;44 min\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eHadad S. et al (2021)(38)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eActive 2nd stage At rest \u0026amp; at pushing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e197, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA (90%) OP (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFor spontaneous VD At Rest: AOP of 138\u0026deg; (sensitivity:71.6 specificity: 83.7 PPV: 96) p\u0026lt;0.0001 Delta AOP of 11\u0026deg; (sensitivity 87.3%; specificity 45.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMalik et al. (2020)(39)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLate 1st stage and second stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP: \u0026gt;116\u0026deg; VD: AUC: 0.989 sensitivity: 96.49%; specificity:96.43%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP 121\u0026deg;-150\u0026deg;: Mean TTD = 54.44 minutes AOD 151\u0026deg;-180\u0026deg;: Mean TTD = 20.79 minutes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSainz JA et al. (2017)(31)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVacuum VD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP \u0026gt;127.3 VD at rest: ICC 0.96 (95% CI: 0.89-0.99) P\u0026lt;0.005 AOP \u0026gt;139.7\u0026deg; VD on pushing: ICC 0.98 (95% CI: 0.96-0.99) P\u0026lt;0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u0026eacute;rez et al. (2017)(40)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIn first stage (above 3cm) and 2nd stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e101(above 3 cm) 66(second stage subgroup), Nulliparous (44.5%) multiparous (55.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP \u0026gt;132\u0026deg; AOP \u0026gt;138\u0026deg; (second stage) VD: AUC 0.97 (95% CI 0.90\u0026ndash;0.99); sensitivity 91.38%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCuerva et al. (2014)(30)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2nd stage To predict complicated forceps delivery in non-OP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLOT (10%) ROT (3.3%) LOA (46.7%) ROA (30%) OA (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP (between contractions): \u0026lt;138\u0026deg; sensitivity: 85.7% specificity of 100%. AUC: 98.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBarbera et al. (2009)(7)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2nd stage \u0026amp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e88, Nulliparous (42.0%) multiparous (58.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP \u0026gt;120\u0026deg;: Vaginal delivery (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026le; 135\u0026deg;- median 45.5 (range 23\u0026ndash;48) min 136◦ \u0026ndash;167◦: median 16.5 (range 12\u0026ndash;27) min 168◦ \u0026ndash;200◦: median 8.0 (range 5\u0026ndash;17) min \u0026gt; 200◦: median 5.0 (range 1\u0026ndash;9) min\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eKalache et al. (2009)(29)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProlonged 2nd stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP: \u0026gt;120\u0026deg;: VD or Easy vacuum: 90% AOP \u0026gt; 100\u0026deg;: 25% probability of successful delivery (R2 measure of fit=55%; LR chi-square P\u0026lt;0.0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 7: Summary of studies: Role of HPD in labour\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1206\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Study\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCharacteristics of study\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eParticipants No. and Type\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eFetal head position\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCut off HPD\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOutcome\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eHadad S. et al (2021)(38)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eActive 2nd stage\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eAt rest \u0026amp; at pushing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e197, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA (90%) OP (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean HPD at rest (mm) (28.60\u0026plusmn;9.10)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(35.80\u0026plusmn;7.70)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eHPD at active pushing (mm) 23.00\u0026plusmn;9.30 31.60\u0026plusmn;8.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSpontaneous VD,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eID, p\u0026lt;0.05\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSpontaneous VD\u003c/p\u003e\n \u003cp\u003eID\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eHjartard\u0026oacute;ttir et al. (2021)(16)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage \u0026gt;4cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026le;45mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVD: AUC: 0.68 (95% CI 0.55 \u0026minus;0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eKandil et al. (2021)(17)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;45mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVD: AUC: 0.917 sensitivity ~88% specificity 91%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eIbrahim et al. (2021)(22)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eActive 1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e600, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39.5mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVD: sensitivity: 62% specificity: 63% PPV: 84.5% P\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCarvalho Neto et al. (2021)(37)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2nd stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e221, Nulliparous (65.5%) multiparous (34.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA: 62.5% OP: 6.9%\u003c/p\u003e\n \u003cp\u003eOT: 30.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt; 4.3 cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSurgical (CD + ID) Sensitivity: 69% Specificity: 89% AUC 0.80 (95% CI: 0.66\u0026ndash;0.93 p = 0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eAndrea Dall\u0026rsquo;Asta et al. (2019)(45)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProlonged second stage of labor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e109, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean HPD\u003c/p\u003e\n \u003cp\u003e33.2 mm \u0026plusmn; 7.8 mm\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e40.1 mm \u0026plusmn; 9.5 mm\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSpontaneous VD\u003c/p\u003e\n \u003cp\u003eCD/vacuum VD\u003c/p\u003e\n \u003cp\u003ep\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMagdalena Ciaciura et al. (2016)(46)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2nd stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e68, Nulliparous (52.9%) Multiparous (47.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026le; 3.16 cm\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026gt; 3.16 cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100% VD\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e45% VD\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eArithmetic mean HPD in VD group: 3.0cm CD group: 4.12cm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eAntonio Sainz J et al. (2016)(48)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVacuum VD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean HPD at pushing\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e38.2mm\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e47mm\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e48.4mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eEasy vacuum VD,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDifficult vacuum VD,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eFailed vacuum VD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eIngeberg et al. (2017)(24)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026le;40 mm\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026gt;40mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50% VD\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e22.2% (P \u0026lt;0.001).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSolaiman et al. (2020)(21)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProlonged 1st \u0026amp; 2nd stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28, Nulliparous (25%) Multiparous (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLOP :64.3% ROP \u0026amp; LOT: 10.7% each LOA \u0026amp; ROA: 7.1% each\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVD: 84% AUC: 0.841; sensitivity 80% specificity 84% PPV 85% NPV 78%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eEggebo et al. (2014) (28)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProlonged 1st stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e150, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026le; 40 mm\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026gt;40mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVD: 92%; (95% CI 84\u0026ndash;96%)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eVD: 52%; (95% CI 40\u0026ndash;63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTorkildsen et al. (2011)(29)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProlonged 1st stage (crossed action line)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e110, Nulliparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026le; 40 mm\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e40-50mm\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u0026gt;50mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVD: 93% (95% CI 83\u0026ndash;97%)\u003c/p\u003e\n \u003cp\u003eVD: 67% (95% CI 53\u0026ndash;80%)\u003c/p\u003e\n \u003cp\u003eVD 18% (95% CI 5\u0026ndash;48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eStrengths and limitations :\u003c/h2\u003e\n\u003cp\u003eWhile most studies have focused on analyzing the role of the AOP during the late first stage and the second stage of labor, our research highlights that a favorable AOP at the onset of labor can itself predict labor outcomes, a key finding of this study. Caesarean rate at our centre currently exceeds 50% due to the high volume of patients and the high-risk nature of the referrals we receive. By incorporating ITU into routine labor care, we were able to significantly lower the Caesarean rate to 25%. We could ensure uniformity in ITU findings, as the interobserver variation was minimal. However, we found that there occured some minor variations in HPD measurements in women with higher BMI, as the ultrasound transducer needs to be positioned at the perineum and pressed firmly against pubic bone. A small sample size and different obstetricians managing labor room on different days are some of the confounding factors that could not be controlled, limiting the generalizability of the study findings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eITU, particularly AOP and HPD can improve labor outcomes. At cut offs\u0026thinsp;\u0026gt;\u0026thinsp;104 and \u0026lt;\u0026thinsp;39mm in early labour, AOP and HPD hold good predictive accuracy for vaginal delivery. Although ITU cannot yet replace clinical vaginal examination, incorporating it into routine labor management could significantly reduce the burden of morbidity related to CD. Efforts should be made to standardise the use of ITU \u0026amp; to overcome the barriers to its adoption in LMICs, ensuring that all women, regardless of geographic location or socioeconomic status, have access to safe and effective labor monitoring tools.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate:\u003c/p\u003e\n\u003cp\u003eThis prospective observational study was carried out in a tertiary care centre in South India. The study was approved by the Kasturba Medical College \u0026amp; Kasturba Hospital Institutional Ethics Committee (Study number: 685/2020) on 10.11.2020.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWritten and informed consent was obtained individually from all participants included in the study.\u003c/p\u003e\n\u003cp\u003eConsent for publication: Departmental and institutional consents to publish have been obtained.\u003c/p\u003e\n\u003cp\u003eAvailability of data and material:\u003c/p\u003e\n\u003cp\u003eData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eName of the repository: Mendeley Data\u003c/p\u003e\n\u003cp\u003eDOI:10.17632/z6c4272sd3.1\u003c/p\u003e\n\u003cp\u003eReddy D, Sharma N. AOD and HPD in predicting vaginal delivery. Mendeley Data. 2024; V1. (https://data.mendeley.com/datasets/z6c4272sd3/1)\u003c/p\u003e\n\u003cp\u003eCompeting interests: There are no competing interests for this study.\u003c/p\u003e\n\u003cp\u003eFunding: No external funding agency has supported this work.\u003c/p\u003e\n\u003cp\u003eAcknowledgements: NA\u003c/p\u003e\n\u003cp\u003eAuthors Contributions:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData Collection: NS\u003c/p\u003e\n\u003cp\u003eWriting manuscript: DR, NS\u003c/p\u003e\n\u003cp\u003eInterpretation of data: DR, JS\u003c/p\u003e\n\u003cp\u003eAnalysis of data: AK\u003c/p\u003e\n\u003cp\u003eRevision of manuscript: DR, JS\u003c/p\u003e\n\u003cp\u003eTables and figures: DR, NS\u003c/p\u003e\n\u003cp\u003eAll authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003ePanda S, Begley C, Daly D. 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The role of the angle of progression in the prediction of the outcome of occiput posterior position in the second stage of labor. \u003cem\u003eAm J Obstet Gynecol\u003c/em\u003e. 2021;225(1):81.e1-81.e9. doi:10.1016/j.ajog.2021.01.017\u003c/li\u003e\n \u003cli\u003eBarros JG, Afonso M, Martins AT, et al. Transabdominal and transperineal ultrasound vs routine care before instrumental vaginal delivery - A randomized controlled trial. \u003cem\u003eActa Obstet Gynecol Scand\u003c/em\u003e. 2021;100(6):1075-1081. doi:10.1111/aogs.14065\u003c/li\u003e\n \u003cli\u003eCarvalho Neto RH, Viana Junior AB, Moron AF, Araujo J\u0026uacute;nior E, Carvalho FHC, Feitosa HN. Assessment of the angle of progression and distance perineum-head in the prediction of type of delivery and duration of labor using intrapartum ultrasonography. \u003cem\u003eJ Matern Fetal Neonatal Med\u003c/em\u003e. 2021;34(14):2340-2348. doi:10.1080/14767058.2019.1666818\u003c/li\u003e\n \u003cli\u003eHadad S, Oberman M, Ben-Arie A, Sacagiu M, Vaisbuch E, Levy R. Intrapartum ultrasound at the initiation of the active second stage of labor predicts spontaneous vaginal delivery. \u003cem\u003eAm J Obstet Gynecol MFM\u003c/em\u003e. 2021;3(1):100249. doi:10.1016/j.ajogmf.2020.100249\u003c/li\u003e\n \u003cli\u003eMalik R, Singh S. Measurement of Angle of Descent (AOD) by Transperineal Ultrasound in Labour to Predict Successful Vaginal Delivery. \u003cem\u003eJ Obstet Gynaecol India\u003c/em\u003e. 2020;70(2):126-132. doi:10.1007/s13224-019-01300-9\u003c/li\u003e\n \u003cli\u003eP\u0026eacute;rez SP, Seguer JJ, Pujadas AR, Azuara LS, Juanos JL, Sagrist\u0026agrave; OA. 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Structured clinical examinations in labor: rekindling the craft of obstetrics. \u003cem\u003eJ Matern Fetal Neonatal Med\u003c/em\u003e. 2021;34(12):1963-1969. doi:10.1080/14767058.2019.1651283\u003c/li\u003e\n \u003cli\u003eKahrs BH, Usman S, Ghi T, et al. Sonographic prediction of outcome of vacuum deliveries: a multicenter, prospective cohort study. \u003cem\u003eAm J Obstet Gynecol\u003c/em\u003e. 2017;217(1):69.e1-69.e10. doi:10.1016/j.ajog.2017.03.009\u003c/li\u003e\n \u003cli\u003eDall\u0026apos;Asta A, Angeli L, Masturzo B, et al. Prediction of spontaneous vaginal delivery in nulliparous women with a prolonged second stage of labor: the value of intrapartum ultrasound. \u003cem\u003eAm J Obstet Gynecol\u003c/em\u003e. 2019;221(6):642.e1-642.e13. doi:10.1016/j.ajog.2019.09.045\u003c/li\u003e\n \u003cli\u003eCiaciura-Jarno M, Cnota W, W\u0026oacute;jtowicz D, et al. Evaluation of selected ultrasonography parameters in the second stage of labor in prediction mode of delivery. \u003cem\u003eGinekol Pol\u003c/em\u003e. 2016;87(6):448-453. doi:10.5603/GP.2016.0024\u003c/li\u003e\n \u003cli\u003eAntonio Sainz J, Borrero C, Aquise A, Garc\u0026iacute;a-Mejido JA, Gutierrez L, Fern\u0026aacute;ndez-Palac\u0026iacute;n A. Intrapartum translabial ultrasound with pushing used to predict the difficulty in vacuum-assisted delivery of fetuses in non-occiput posterior position. \u003cem\u003eJ Matern Fetal Neonatal Med\u003c/em\u003e. 2016;29(20):3400-3405. doi:10.3109/14767058.2015.1130816\u003c/li\u003e\n\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":"Angle of progression, AOP, Head-perineum distance, HPD, Intrapartum ultrasound","lastPublishedDoi":"10.21203/rs.3.rs-7051979/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7051979/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Intrapartum ultrasound (ITU) has garnered significant attention in recent years. While its use is well-documented in developed countries, it has not yet gained popularity in under- resourced countries. Despite the widespread availability of ultrasound (US) in most labor and delivery centers, its use is predominantly limited to identifying obstetric emergencies, with minimal application in assessing labor progress. The use of ITU has not been sufficiently tested in labor and delivery settings within developing countries.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAim\u003c/strong\u003e: To evaluate the diagnostic performance of ITU parameters of 1. Angle of progression (AOP) and 2. Head perineum distance (HPD) in predicting a vaginal delivery in term singleton pregnant women in early labor and to provide a comprehensive review of literature.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Prospective observational study conducted in South India. Singleton pregnant women over 37 weeks of gestation in early labor were included. AOP and HPD were measured using trans-perineal ultrasound in addition to clinical vaginal assessment. Two trained obstetricians performed the ultrasound examination on initial 22 women. ITU measurements were analysed to identify the best possible predictive value for the outcome vaginal delivery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Among 113 parturients, the mean AOP was narrower in women who underwent Caesarean CD (27%, n= 31), compared to those who has a vaginal delivery (VD), (72.5%, n=82). An AOP \u003cu\u003e\u0026gt;\u003c/u\u003e 104.5° was predictive of VD with a sensitivity 94% and specificity 95%. HPD of ≤39.5mm was predictive of VD with a sensitivity 64% and specificity 65%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: Measuring AOP and HPD during labor provides valuable insights into the likelihood of a vaginal delivery with AOP being a more reliable indicator than HPD. Implementing the use of these measurements in labor management could empower obstetricians to confidently await a vaginal delivery, particularly in situations where labor duration exceeds the expected timeframe, while maternal and fetal conditions are satisfactory.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial Registration: Reg No.\u003c/strong\u003e CTRI/2021/02/030936, Reg Date: 02.02.2021, URL: www.ctri.nic.in\u003c/p\u003e","manuscriptTitle":"Emerging role of angle of progression and head-perineum distance in predicting labor outcome: original research supported by a mini-review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-20 08:54:22","doi":"10.21203/rs.3.rs-7051979/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":"f3ec1432-8990-4d7a-bf12-8aaf705ed3e4","owner":[],"postedDate":"October 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-12T06:39:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-20 08:54:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7051979","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7051979","identity":"rs-7051979","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}