Membrane stripping in group B streptococcus carriers does not impede adequate intrapartum antibiotic prophylaxis: a retrospective study.

Objective: Membrane stripping in group B streptococcus (GBS) carriers poses an increased risk of inadequate antibiotic prophylaxis, potentially due to accelerated labor, thereby potentially impacting the management of GBS colonization during delivery. We compared the adequacy of intrapartum antibiotic prophylaxis between pregnant women colonized with GBS, who underwent membrane stripping and those who did not. The study aimed to determine whether the performance of membrane stripping, by potentially shortening labor duration, increases the risk of inadequate antibiotic prophylaxis dispensation. Study design: A retrospective cohort study was conducted on GBS screen-positive women with a full-term singleton pregnancy in cephalic presentation, who were eligible for vaginal delivery. The exposed group consisted of women who underwent membrane stripping, while the unexposed group consisted of women who did not undergo membrane stripping. The primary outcome was defined as inadequate duration of antibiotic prophylaxis during labor, wherein less than 4 h of beta-lactam antibiotics were administered prior to delivery. Neonatal outcome was compared between the groups. Results: This retrospective cohort study comprised 1,609 women, with 129 in the exposed group (stripping group) and 1,480 in the unexposed group (no stripping group). Adequate intrapartum antibiotic prophylaxis was received by 64.3% (83/129) of the exposed group, compared to 46.9% (694/1,480) of the unexposed group (p = 0.003). Membrane stripping was associated with increased odds of receiving adequate prophylaxis (OR 1.897, 95% CI 1.185-3.037, p = 0.008). After excluding women who presented to the labor ward in active labor and delivered in less than 4 h, both the exposed and unexposed groups had similarly high rates of adequate intrapartum antibiotic prophylaxis (87.5% vs. 85.8%, respectively). No significant difference was observed in adverse neonatal outcomes between the groups. Conclusion: The provision of membrane stripping did not impede adequate intrapartum antibiotic prophylaxis and was correlated with a higher rate of sufficient prophylaxis in comparison to non-swept patients. These observations suggest that membrane stripping can be considered a safe option for ensuring adequate antibiotic prophylaxis in women colonized with GBS.

Maternal hybrid immunity and risk of infant COVID-19 hospitalizations: national case-control study in Israel.

Hybrid immunity, acquired through vaccination followed or preceded by a COVID-19 infection, elicits robust antibody augmentation. We hypothesize that maternal hybrid immunity will provide greater infant protection than other forms of COVID-19 immunity in the first 6 months of life. We conducted a case-control study in Israel, enrolling 661 infants up to 6 months of age, hospitalized with COVID-19 (cases) and 59,460 age-matched non-hospitalized infants (controls) between August 24, 2021, and March 15, 2022. Infants were grouped by maternal immunity status at delivery: Naïve (never vaccinated or tested positive, reference group), Hybrid-immunity (vaccinated and tested positive), Natural-immunity (tested positive before or during the study period), Full-vaccination (two-shot regimen plus 1 booster), and Partial-vaccination (less than full three shot regimen). Applying Cox proportional hazards models to estimate the hazard ratios, which was then converted to percent vaccine effectiveness, and using the Naïve group as the reference, maternal hybrid-immunity provided the highest protection (84% [95% CI 75-90]), followed by full-vaccination (66% [95% CI 56-74]), natural-immunity (56% [95% CI 39-68]), and partial-vaccination (29% [95% CI 15-41]). Maternal hybrid-immunity was associated with a reduced risk of infant hospitalization for Covid-19, as compared to natural-immunity, regardless of exposure timing or sequence. These findings emphasize the benefits of vaccinating previously infected individuals during pregnancy to reduce COVID-19 hospitalizations in early infancy.

Women's attitudes towards disclosure of genetic information in pregnancy with varying levels of penetrance.

BACKGROUND: Chromosomal-microarray-analysis (CMA) may reveal susceptibility-loci (SL) of varied penetrance for autism-spectrum-disorder (ASD) and other neurodevelopmental conditions. Attitudes of women/parents to disclosure of SL during pregnancy are understudied. METHODS: A multiple-choice questionnaire was distributed to postpartum women. Data were collected on women's interest to receive prenatal genetic information with various levels of penetrance. RESULTS: Women's (n = 941) disclosure choices were dependent on the magnitude of risk: approximately 70% supported disclosure of either full or 40% penetrance, 53% supported disclosure at a 20% risk threshold, and 40% supported disclosure at 10% or less. Although most women supported, rejected or were indecisive about disclosure consistently across all risk levels, nearly one-quarter (24%) varied their responses based on penetrance, and this was associated with religiosity, education, parity and concern about fetal health (p-values <0.04). Among those who varied their choices, the risk threshold was lower among secular women (20%) than among ultraorthodox women (40%). In a multivariable analysis, ultraorthodox women were much less likely to vary their choices on ASD disclosure compared with secular women (aOR = 0.37, p < 0.001). CONCLUSION: Women's attitudes toward disclosure are influenced by the level of risk and their individual characteristics. We therefore encourage engaging women/couples in disclosure decisions regarding uncertain and probabilistic results from prenatal genomic tests.

Timing of midstream urine culture before endourological procedure-can we do better?-A comparative study.

Endourological procedures are the mainstay of treatment for stone disease in the upper urinary system. Infection is a common complication, and urine cultures (UC) are often obtained preoperatively. In this study, we sought to investigate the role of positive UC in the 90 days prior to surgery (90PreOp) in predicting postoperative infectious complications in comparison to a single positive preoperative UC (PreOP). We compared the correlation between positive PreOp UCs and positive 90PreOp UCs with postoperative urosepsis, and a positive UC obtain proximal to obstruction (Prox UC) during percutaneous nephrolithotomy, ureteroscopy and a placement of nephrostomy tube or ureteral stent. Data from 140 consecutive patients were collected. PreOp UCs were positive in 15 (11%) of patients versus 31 of 140 (22%) positive 90PreOp UCs. All six sepsis events had a positive 90PreOp UC, and five had a positive PreOp UC. Fourteen (93.3%) out of 15 positive Prox UC had a positive 90PreOp UC, whereas only 7 (38.9%) had a positive 90PreOp UC. Positive 90PreOp UC outperformed PreOp UC in predicting positive Prox UC, OR = 12.8 (95% CI 3.70-44.30, p < 0.001), versus OR of 88.9 (95% CI 11.0-720.7, p < 0.001); sensitivity 93%(95% CI 68-100%) versus 47%(95% CI 21-73%); as well as area under the ROC curve(AUC), 0.90 (CI 0.80-0.95) for 90PreOp versus 0.70 (CI 0.56-0.82) for positive Prox UC. Uropathogen persistence was better identified when using 90PreOp UC (27%) than using PreOp UC (12%). We suggest reviewing UCs taken within 90 days preoperatively as this was found superior to a single preoperative midstream UCs in predicting postoperative infectious sequela after stone procedure.

The effectiveness of vaginal progesterone in reducing preterm birth in high-risk patients diagnosed with short cervical length after 24 weeks: A retrospective cohort study.

Objective: To assess the impact of progesterone treatment on maternal and neonatal outcomes in women with a history of preterm birth and short cervical length diagnosed after 24 weeks of gestation. Methods: A retrospective cohort study included women with a history of preterm birth and a transvaginal sonographic cervical length measurement of ≤ 25 mm, diagnosed between 24+0 and 33+6 weeks of gestation. Exclusion criteria included prior progesterone treatment, cervical cerclage, or pessary. The study population was divided into the progesterone treatment group and the non-treatment group. Results: The study included 104 women, with 46.2% (48/104) receiving progesterone treatment and 53.8% (56/104) not receiving treatment. The rate of spontaneous preterm birth before 37 weeks of gestation was 43% (24/56) in the non-treatment group and 31% (15/48) in the progesterone treatment group (P = 0.14); the rate of spontaneous preterm birth before 34 weeks was 7% (4/56) in the non-treatment group and 0% (0/48) in the progesterone treatment group (P = 0.05). Progesterone treatment was associated with a significant decrease in neonatal intensive care unit admissions (OR 0.20, 95% CI 0.05-0.74) and in the neonatal hospitalization period (mean difference in days 2.43, 95% CI 0.44-4.42). The risk of recurrent spontaneous preterm birth was highest (71%) among women with two or more previous preterm deliveries who did not receive progesterone treatment, and lowest (24%) among women with one previous preterm delivery who received progesterone treatment. Conclusion: Progesterone treatment was associated with a reduction in rates of spontaneous preterm birth before 34 weeks of gestation, neonatal intensive care unit admission, and neonatal length of stay in high-risk patients, even when initiated after 24 weeks of gestation.

Maternal third dose of BNT162b2 mRNA vaccine and risk of infant COVID-19 hospitalization.

Infants are at a higher risk of Coronavirus Disease 2019 (COVID-19)-related hospitalizations compared to older children. In this study, we investigated the effect of the recommended third maternal dose of BNT162b2 COVID-19 vaccine during pregnancy on rates of infant COVID-19-related hospitalizations. We conducted a nationwide cohort study of all live-born infants delivered in Israel between 24 August 2021 and 15 March 2022 to estimate the effectiveness of the third booster dose versus the second dose against infant COVID-19-related hospitalizations. Data were analyzed for the overall study period, and the Delta and Omicron periods were analyzed separately. Cox proportional hazard regression models estimated hazard ratios and 95% confidence intervals (CIs) for infant hospitalizations according to maternal vaccination status at delivery. Among 48,868 live-born infants included in the analysis, rates of COVID-19 hospitalization were 0.4%, 0.6% and 0.7% in the third-dose, second-dose and unvaccinated groups, respectively. Compared to the second dose, the third dose was associated with reduced infant hospitalization with estimated effectiveness of 53% (95% CI: 36-65%). Greater protection was associated with a shorter interval between vaccination and delivery. A third maternal dose during pregnancy reduced the risk of infant hospitalization for COVID-19 during the first 4 months of life, supporting clinical and public health guidance for maternal booster vaccination to prevent infant COVID-19 hospitalization.

Effectiveness of a third BNT162b2 mRNA COVID-19 vaccination during pregnancy: a national observational study in Israel.

The Centers for Disease Control (CDC) recommend a third dose of COVID-19 vaccine for pregnant women, although data regarding effectiveness during pregnancy are lacking. This national, population-based, historical cohort study of pregnant women in Israel, delivering between August 1, 2021 and March 22, 2022, aims to analyze and compare the third and second doses' vaccine effectiveness in preventing COVID-19-related hospitalizations during pregnancy during two COVID-19 waves (Delta variant in the summer of 2021 and Omicron, BA.1, variant in the winter of 2022). Time-dependent Cox proportional-hazards regression models estimate the hazard ratios (HR) and 95% confidence intervals (CI) for COVID-related outcomes according to vaccine dose, and vaccine effectiveness as 1-HR. Study includes 82,659 and 33,303 pregnant women from the Delta and Omicron waves, respectively. Compared with the second dose, the third dose effectively prevents overall hospitalizations with SARS-CoV-2 infections, with estimated effectiveness of 92% (95% CI 83-96%) during Delta, and enhances protection against significant disease during Omicron, with effectiveness of 92% (95% CI 26-99%), and 48% (95% CI 37-57%) effectiveness against hospitalization overall. A third dose of the BNT162b2 mRNA COVID-19 vaccine during pregnancy, given at least 5 months after the second vaccine dose, enhances protection against adverse COVID-19-related outcomes.

Postpartum women's attitudes to disclosure of adult-onset conditions in pregnancy.

BACKGROUND: Advanced prenatal genomic technologies can identify risks for adult-onset (AO) conditions in the fetus, challenging the traditional purpose of prenatal testing. Professional guidelines commonly support disclosure of high-penetrance AO actionable conditions, yet attitudes of women/parents to these findings and factors affecting their attitudes are understudied. METHODS: We explored 941 (77% response rate) postpartum women's attitudes towards receiving prenatal genetic information, and associations of sociodemographic, medical and psychological characteristics with their choices, focusing on AO conditions. RESULTS: Women largely support the disclosure of actionable AO findings (58.4%), in line with professional guidelines. A third of the women also supported the disclosure of non-actionable AO conditions. Stronger religious observance (p < 0.001) and higher psychological distress (p = 0.024) were associated with decreased interest in receiving actionable AO conditions, whereas higher concern for fetal health yielded increased interest (p = 0.032). Attitudes towards disclosure were strongly associated with women's perceived benefit of such information for their own, partner's, and future child's health. Termination of pregnancy based on such information received very little support. CONCLUSION: In-light of the demonstrated understanding of nuanced genetic information and the observed diversity in attitudes, a culturally competent opt-in/out policy could be considered. If full-disclosure is practiced, support should be provided to those expressing higher levels of distress.

Transporting an Artificial Intelligence Model to Predict Emergency Cesarean Delivery: Overcoming Challenges Posed by Interfacility Variation.

Research using artificial intelligence (AI) in medicine is expected to significantly influence the practice of medicine and the delivery of health care in the near future. However, for successful deployment, the results must be transported across health care facilities. We present a cross-facilities application of an AI model that predicts the need for an emergency caesarean during birth. The transported model showed benefit; however, there can be challenges associated with interfacility variation in reporting practices.

Real-time data analysis using a machine learning model significantly improves prediction of successful vaginal deliveries.

BACKGROUND: The process of childbirth is one of the most crucial events in the future health and development of the offspring. The vulnerability of parturients and fetuses during the delivery process led to the development of intrapartum monitoring methods and to the emergence of alternative methods of delivery. However, current monitoring methods fail to accurately discriminate between cases in which intervention is unnecessary, partly contributing to the high rates of cesarean deliveries worldwide. Machine learning methods are applied in various medical fields to create personalized prediction models. These methods are used to analyze abundant, complex data with intricate associations to aid in decision making. Initial attempts to predict vaginal delivery vs cesarean deliveries using machine learning tools did not utilize the vast amount of data recorded during labor. The data recorded during labor represent the dynamic process of labor and therefore may be invaluable for dynamic prediction of vaginal delivery. OBJECTIVE: We aimed to create a personalized machine learning-based prediction model to predict successful vaginal deliveries using real-time data acquired during the first stage of labor. STUDY DESIGN: Electronic medical records of labor occurring during a 12-year period in a tertiary referral center were explored and labeled. Four different models were created using input from multiple maternal and fetal parameters. Initial risk assessments for vaginal delivery were calculated using data available at the time of admission to the delivery unit, followed by models incorporating cervical examination data and fetal heart rate data, and finally, a model that integrates additional data available during the first stage of labor was created. RESULTS: A total of 94,480 cases in which a trial of labor was attempted were identified. Based on approximately 180 million data points from the first stage of labor, machine learning models were developed to predict successful vaginal deliveries. A model using data available at the time of admission to the delivery unit yielded an area under the curve of 0.817 (95% confidence interval, 0.811-0.823). Models that used real-time data increased prediction accuracy. A model that includes real-time cervical examination data had an initial area under the curve of 0.819 (95% confidence interval, 0.813-0.825) at first examination, which increased to an area under the curve of 0.917 (95% confidence interval, 0.913-0.921) by the end of the first stage. Adding the real-time fetal heart monitor data provided an area under the curve of 0.824 (95% confidence interval, 0.818-0.830) at first examination, which increased to an area under the curve of 0.928 (95% confidence interval, 0.924-0.932) by the end of the first stage. Finally, adding additional real-time data increased the area under the curve initially to 0.833 (95% confidence interval, 0.827-0.838) at the first cervical examination and up to 0.932 (95% confidence interval, 0.928-0.935) by the end of the first stage. CONCLUSION: Real-time data acquired throughout the process of labor significantly increased the prediction accuracy for vaginal delivery using machine learning models. These models enable translation and quantification of the data gathered in the delivery unit into a clinical tool that yields a reliable personalized risk score and helps avoid unnecessary interventions.

[UTERINE PRESERVING METHODS FOR TREATING PLACENTA ACCRETA SPECTRUM: A PROPOSAL FOR A SURGICAL PROTOCOL].

INTRODUCTION: Placenta accrete spectrum (PAS) is a complicated obstetrical condition arising from abnormal implantation of the placenta into the myometrium. The placenta might partially or completely adhere to the myometrium and in rare cases invade adjacent organs (placenta percreta). The abnormal placentation might cause life-threatening hemorrhages during pregnancy and birth, increasing maternal and neonatal mortality and morbidity. Detachment of the placenta after delivery in PAS might be difficult and requires manual removal of the placenta as well as advanced surgical procedures in more serious cases. In the past decades, several studies have demonstrated that removing the uterus while the placenta is still in situ avoided massive hemorrhage. However, in some cases, preserving the uterus and the fertility of the patient is desired and therefore advanced surgical procedures have been developed. Several techniques for uterine preserving procedures have been described: conservative management - closing the uterus while the placenta is still in situ and complementary procedures to remove the placenta, using interventional radiology to reduce the blood supply to the uterus and other surgical approaches to reduce the blood supply to the uterus. In this article we will review the different methods for uterine preserving techniques in treating advanced cases of PAS and propose a surgical protocol for such a method we use in our medical center.

Prediction of vaginal birth after cesarean deliveries using machine learning.

BACKGROUND: Efforts to reduce cesarean delivery rates to 12-15% have been undertaken worldwide. Special focus has been directed towards parturients who undergo a trial of labor after cesarean delivery to reduce the burden of repeated cesarean deliveries. Complication rates are lowest when a vaginal birth is achieved and highest when an unplanned cesarean delivery is performed, which emphasizes the need to assess, in advance, the likelihood of a successful vaginal birth after cesarean delivery. Vaginal birth after cesarean delivery calculators have been developed in different populations; however, some limitations to their implementation into clinical practice have been described. Machine-learning methods enable investigation of large-scale datasets with input combinations that traditional statistical analysis tools have difficulty processing. OBJECTIVE: The aim of this study was to evaluate the feasibility of using machine-learning methods to predict a successful vaginal birth after cesarean delivery. STUDY DESIGN: The electronic medical records of singleton, term labors during a 12-year period in a tertiary referral center were analyzed. With the use of gradient boosting, models that incorporated multiple maternal and fetal features were created to predict successful vaginal birth in parturients who undergo a trial of labor after cesarean delivery. One model was created to provide a personalized risk score for vaginal birth after cesarean delivery with the use of features that are available as early as the first antenatal visit; a second model was created that reassesses this score after features are added that are available only in proximity to delivery. RESULTS: A cohort of 9888 parturients with 1 previous cesarean delivery was identified, of which 75.6% of parturients (n=7473) attempted a trial of labor, with a success rate of 88%. A machine-learning-based model to predict when vaginal delivery would be successful was developed. When features that are available at the first antenatal visit are used, the model showed a receiver operating characteristic curve with area under the curve of 0.745 (95% confidence interval, 0.728-0.762) that increased to 0.793 (95% confidence interval, 0.778-0.808) when features that are available in proximity to the delivery process were added. Additionally, for the later model, a risk stratification tool was built to allocate parturients into low-, medium-, and high-risk groups for failed trial of labor after cesarean delivery. The low- and medium-risk groups (42.4% and 25.6% of parturients, respectively) showed a success rate of 97.3% and 90.9%, respectively. The high-risk group (32.1%) had a vaginal delivery success rate of 73.3%. Application of the model to a cohort of parturients who elected a repeat cesarean delivery (n=2145) demonstrated that 31% of these parturients would have been allocated to the low- and medium-risk groups had a trial of labor been attempted. CONCLUSION: Trial of labor after cesarean delivery is safe for most parturients. Success rates are high, even in a population with high rates of trial of labor after cesarean delivery. Application of a machine-learning algorithm to assign a personalized risk score for a successful vaginal birth after cesarean delivery may help in decision-making and contribute to a reduction in cesarean delivery rates. Parturient allocation to risk groups may help delivery process management.

The Sex Specific Association Between Maternal Gestational Diabetes and Offspring Metabolic Status at 1 Year of Age.

Previous studies showed the association between maternal GDM and long-term effects of overweight in offspring. However, the nature of this association in the early postnatal period is still undetermined. The aim of this prospective cohort study was to evaluate whether maternal GDM is associated with overweight and obesity status in offspring at age 1 year. We studied 1167 infants born at a large obstetrical care hospital including 778 normal glucose tolerance (NGT) and 389 GDM pregnancies, matched in a 1:2 ratio according to offspring's gender, during the years 2016-2017. Overweight and obesity status in offspring of both groups were evaluated at 1 year of age through questionnaires. Infant outcomes were defined according to the WHO Child Growth Standards based on the length-based BMI-for-age. Female offspring from the GDM group exhibited a higher mean BMI (17.2 vs. 16.6, p < 0.01), a higher rate of obesity (13.9% vs. 7.7%; p < 0.05), and overweight (33.1% vs. 23.5%; p < 0.05) as compared to the NGT female group. In the multivariable regression model, maternal GDM was found to be independently and significantly associated with overweight or obesity in 1-year aged female offspring only (OR 1.61, 95% CI 1.09-2.37, p < 0.05). We found a sex specific association between maternal GDM and the overweight risk only in female offspring at 1 year of age.

A novel purgative protocol for capsule endoscopy of the small bowel produces better quality of visibility than 2 l of PEG: Timing is of the essence.

INTRODUCTION: The ideal way of preparing patients for small-bowel capsule endoscopy has been controversial. Previous studies have shown that ingestion of 2 l of polyethylenglycol (PEG) 12 hours prior to capsule ingestion leads to improved visibility in comparison to no preparation at all. We speculated that using a post-ingestion (PI), booster-based cleansing protocol might provide an alternative to the PEG cleansing protocol. METHODS: This randomized, blinded, prospective study enrolled 45 individuals. Patients were allocated to either of two groups. The PEG group ingested 2 l PEG 12 hours prior to the exam (n = 22) and the PI group ingested one sachet of Picolax® dissolved in 250 ml of water one hour after swallowing the capsule with 500 ml of water (n = 18). Primary endpoints were overall small bowel and distal third of small bowel cleansing levels. Secondary endpoints were average gastric and small-bowel transit time. RESULTS: Forty-five patients participated in this study. Five individuals were excluded because of incomplete study. Percentage of patients with adequate visibility in the distal third of the small bowel in the PEG group was 9% vs 72% in the PI group (p < 0.0001). Average gastric time and total transit time were shorter in the PI group vs the PEG group (p = 0.0065). CONCLUSION: Timing of ingestion of the Picolax® purgative 60 minutes after swallowing the capsule endoscopy delivers better visibility in the distal third of the small bowel than the accepted cleansing protocol of ingesting 2 l PEG 12 hours prior to the capsule endoscopy procedure.

Second-generation colon capsule endoscopy is feasible in the out-of-clinic setting.

BACKGROUND: No colorectal imaging test may be performed on an out-of-clinic basis. This represents a major drawback compared with fecal tests. Because colon capsule endoscopy (CCE) automatically detects small bowel mucosa, it has the potential to become the first colorectal imaging test to be performed out-of-clinic. This study aimed to evaluate the feasibility and efficiency of CCE when offered as an out-of-clinic procedure. METHODS: Patients with known or suspected colonic diseases who had up to 40 min of travel time from clinic to home were offered CCE as an out-of-clinic procedure. These patients were provided with four numbered vials (1 with metoclopramide, 2 with sodium phosphate, 1 with bisacodyl) and detailed instructions on how to interact with data-recorder automatic signaling. Patient compliance with data-recorder instructions, CCE excretion, and detection rates were prospectively assessed. RESULTS: The study enrolled 41 patients (29 men) with a mean age of 57 years. According to data recorder DR3-registered alerts, 14 patients (34 %) required a single booster only, 27 patients (66 %) required two boosters, and 13 patients (32 %) required a suppository. Comparison of the DR3 alerts with the returned vials showed that patient compliance to DR3 alerts was 100 %. During the procedure, 16 patients (39 %) called the physician/clinic from home. In 85 % of the cases, the CCE was excreted within the battery operating time. Lesions size 6 mm or larger were detected in 10 (24 %) of the 41 patients. CONCLUSIONS: As an out-of-clinic procedure, CCE is feasible and easily performed. A home-based procedure may be associated with better acceptability and potentially with increased adherence to Colorectal cancer screening.

Accuracy of automatic detection of small-bowel mucosa by second-generation colon capsule endoscopy.

BACKGROUND: Colon capsule endoscopy (CCE) is a noninvasive technique for the detection of colorectal lesions. However, for CCE to be offered as an out-of-clinic procedure, the system needs to automatically alert the patient when to ingest the laxative (booster). OBJECTIVE: We tested the reliability of the automatic detection of the small-bowel (SB) mucosa and the subsequent alert for booster ingestion by the Data Recorder 3 (DR3) of the second-generation CCE (CCE-2). DESIGN AND SETTING: Retrospective analysis. PATIENTS AND INTERVENTION: Data from 120 consecutive cases of CCE-2 were analyzed for proper DR3 automatic detection of the capsule entering the SB to prompt the patient to ingest the laxative booster. MAIN OUTCOME MEASUREMENTS: Accuracy of the DR3 for detecting the SB mucosa. RESULTS: The DR3 correctly identified the proper time for ingestion of the laxative (booster) in 118 of 120 cases, corresponding to a sensitivity of 98.3% (95% CI, 97%-100%). The median time difference between DR3 automatic SB detection to the observed entrance of the capsule into the SB was 3 minutes 30 seconds (interquartile range 2 minutes 35 seconds to 5 minutes 57 seconds). LIMITATION: Retrospective analysis. CONCLUSIONS: The 98.3% sensitivity of the DR3 for automatic identification of the SB mucosa and subsequent alert for the first laxative (booster) ingestion paves the way for CCE-2 to be offered as an out-of-clinic procedure.