Objective: The purpose of this study was to examine the effects of digital cervical examination on maternal and neonatal outcomes among women with preterm rupture of membranes.
Study Design: This analysis includes data from a previously reported trial of antibiotic treatment during expectant management of rupture of membranes at 24 to 32 weeks' gestation in singleton and twin gestations. Patients from both the randomized trial (n = 299 in the antibiotic group and n = 312 in the placebo group) and the observational component (n = 183) are included in this analysis. The groups were divided into those with one (n = 161) or two digital cervical examinations (n = 27) and those with no digital cervical examinations (n = 606).
Results: The gestational ages at enrollment were similar in the two groups (29 +/- 2 weeks' gestation for one or two examinations vs 29 +/- 2 weeks' gestation for no examinations; P =.85). There were no differences in chorioamnionitis (27% vs 29%; P =.69), endometritis (13% vs 11%; P =.5), or wound infection (0.5% vs 1%; P >.999) between the group with one or two examinations and the no-examination group. Infant outcomes were also similar in the two groups, including early sepsis (6% vs 5%; P =.68), respiratory distress syndrome (51% vs 45%; P =.18), intraventricular hemorrhage (7% vs 7%; P =.67), necrotizing enterocolitis (5% vs 3%; P =.19), and perinatal death (7% vs 5%; P =.45). A composite outcome made up of these neonatal outcomes was not different (56% vs 48%; P =.10) between the group with one or two examinations and the no-examination group. The time from rupture to delivery was shorter in the digital examination group (median value, 3 vs 5 days; P <. 009). Multivariable analysis to adjust for antibiotic study group, group B streptococcal culture status, race, and maternal transfer did not modify these results.
Conclusion: Performance of one or two digital cervical examinations during the course of expectant management of rupture of membranes between 24 and 32 weeks' gestation was associated with shorter latency but did not appear to worsen either maternal or neonatal outcome.
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http://dx.doi.org/10.1067/mob.2000.106765 | DOI Listing |
J Med Imaging (Bellingham)
January 2025
Okaya City Hospital, Division of Diagnostic Pathology, Okaya, Japan.
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October 2024
Department of Radiology, School of Medicine, Addis Ababa University, Addis Ababa, Ethiopia.
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November 2024
Family Medicine and Primary Care Department, King Abdulaziz Medical City Riyadh, Riyadh, SAU.
Background Computer vision syndrome (CVS) is a common condition affecting individuals who spend prolonged periods using electronic devices. It is characterized by symptoms such as eye strain, dryness, headaches, and neck pain. This study aims to assess the prevalence of CVS symptoms among healthcare professionals, their awareness of the condition, and the effectiveness of various preventative practices.
View Article and Find Full Text PDFZhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi
December 2024
Department of Otorhinolaryngology Head and Neck Surgery, Yuhuangding Hospital of Qingdao University, Yantai264000, China Shandong Provincial Clinical Research Center for Otorhinolaryngologic Diseases, Yantai264000, China Yantai Key Laboratory of Otorhinolaryngologic Diseases, Yantai264000, China.
To investigate the clinical characteristics, treatment, and efficacy of spontaneous cerebrospinal fluid rhinorrhea (CFR) combined with aspiration pneumonia. In this case series study, a total of 8 patients diagnosed with spontaneous CFR combined with aspiration pneumonia were admitted to the Department of Otorhinolaryngology Head and Neck Surgery at Yuhuangding Hospital Affiliated with Qingdao University from March 2020 to March 2022. There were 3 males and 5 females, with ages ranging from 45 to 57 years.
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December 2024
Department of Digital Medicine, School of Biomedical Engineering and Medical Imaging, Army Medical University, Chongqing 400038, China. Electronic address:
Background And Purpose: Accurate segmentation of the clinical target volume (CTV) is essential to deliver an effective radiation dose to tumor tissues in cervical cancer radiotherapy. Also, although automated CTV segmentation can reduce oncologists' workload, challenges persist due to the microscopic spread of tumor cells undetectable in CT imaging, low-intensity contrast between organs, and inter-observer variability. This study aims to develop and validate a multi-task feature fusion network (MTF-Net) that uses distance-based information to enhance CTV segmentation accuracy.
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