Pub Date : 2024-08-01DOI: 10.1016/j.ajog.2024.01.030
{"title":"Prenatal diagnosis of severe hydrocephalus caused by fetal intracranial pineal gland tumors","authors":"","doi":"10.1016/j.ajog.2024.01.030","DOIUrl":"10.1016/j.ajog.2024.01.030","url":null,"abstract":"","PeriodicalId":7574,"journal":{"name":"American journal of obstetrics and gynecology","volume":null,"pages":null},"PeriodicalIF":8.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139745843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1016/j.ajog.2024.04.045
Background
ChatGPT, a publicly available artificial intelligence large language model, has allowed for sophisticated artificial intelligence technology on demand. Indeed, use of ChatGPT has already begun to make its way into medical research. However, the medical community has yet to understand the capabilities and ethical considerations of artificial intelligence within this context, and unknowns exist regarding ChatGPT’s writing abilities, accuracy, and implications for authorship.
Objective
We hypothesize that human reviewers and artificial intelligence detection software differ in their ability to correctly identify original published abstracts and artificial intelligence-written abstracts in the subjects of Gynecology and Urogynecology. We also suspect that concrete differences in writing errors, readability, and perceived writing quality exist between original and artificial intelligence-generated text.
Study Design
Twenty-five articles published in high-impact medical journals and a collection of Gynecology and Urogynecology journals were selected. ChatGPT was prompted to write 25 corresponding artificial intelligence-generated abstracts, providing the abstract title, journal-dictated abstract requirements, and select original results. The original and artificial intelligence-generated abstracts were reviewed by blinded Gynecology and Urogynecology faculty and fellows to identify the writing as original or artificial intelligence-generated. All abstracts were analyzed by publicly available artificial intelligence detection software GPTZero, Originality, and Copyleaks, and were assessed for writing errors and quality by artificial intelligence writing assistant Grammarly.
Results
A total of 157 reviews of 25 original and 25 artificial intelligence-generated abstracts were conducted by 26 faculty and 4 fellows; 57% of original abstracts and 42.3% of artificial intelligence-generated abstracts were correctly identified, yielding an average accuracy of 49.7% across all abstracts. All 3 artificial intelligence detectors rated the original abstracts as less likely to be artificial intelligence-written than the ChatGPT-generated abstracts (GPTZero, 5.8% vs 73.3%; P<.001; Originality, 10.9% vs 98.1%; P<.001; Copyleaks, 18.6% vs 58.2%; P<.001). The performance of the 3 artificial intelligence detection software differed when analyzing all abstracts (P=.03), original abstracts (P<.001), and artificial intelligence-generated abstracts (P<.001). Grammarly text analysis identified more writing issues and correctness errors in original than in artificial intelligence abstracts, including lower Grammarly score reflective of poorer writing quality (82.3 vs 88.1; P=.006), more total writing issues (19.2 vs 12.8; P<.001), critical issues (5.4 vs 1.3; P<.001), confusin
{"title":"Human vs machine: identifying ChatGPT-generated abstracts in Gynecology and Urogynecology","authors":"","doi":"10.1016/j.ajog.2024.04.045","DOIUrl":"10.1016/j.ajog.2024.04.045","url":null,"abstract":"<div><h3>Background</h3><p>ChatGPT, a publicly available artificial intelligence large language model, has allowed for sophisticated artificial intelligence technology on demand. Indeed, use of ChatGPT has already begun to make its way into medical research. However, the medical community has yet to understand the capabilities and ethical considerations of artificial intelligence within this context, and unknowns exist regarding ChatGPT’s writing abilities, accuracy, and implications for authorship.</p></div><div><h3>Objective</h3><p>We hypothesize that human reviewers and artificial intelligence detection software differ in their ability to correctly identify original published abstracts and artificial intelligence-written abstracts in the subjects of Gynecology and Urogynecology. We also suspect that concrete differences in writing errors, readability, and perceived writing quality exist between original and artificial intelligence-generated text.</p></div><div><h3>Study Design</h3><p>Twenty-five articles published in high-impact medical journals and a collection of Gynecology and Urogynecology journals were selected. ChatGPT was prompted to write 25 corresponding artificial intelligence-generated abstracts, providing the abstract title, journal-dictated abstract requirements, and select original results. The original and artificial intelligence-generated abstracts were reviewed by blinded Gynecology and Urogynecology faculty and fellows to identify the writing as original or artificial intelligence-generated. All abstracts were analyzed by publicly available artificial intelligence detection software GPTZero, Originality, and Copyleaks, and were assessed for writing errors and quality by artificial intelligence writing assistant Grammarly.</p></div><div><h3>Results</h3><p>A total of 157 reviews of 25 original and 25 artificial intelligence-generated abstracts were conducted by 26 faculty and 4 fellows; 57% of original abstracts and 42.3% of artificial intelligence-generated abstracts were correctly identified, yielding an average accuracy of 49.7% across all abstracts. All 3 artificial intelligence detectors rated the original abstracts as less likely to be artificial intelligence-written than the ChatGPT-generated abstracts (GPTZero, 5.8% vs 73.3%; <em>P</em><.001; Originality, 10.9% vs 98.1%; <em>P</em><.001; Copyleaks, 18.6% vs 58.2%; <em>P</em><.001). The performance of the 3 artificial intelligence detection software differed when analyzing all abstracts (<em>P</em>=.03), original abstracts (<em>P</em><.001), and artificial intelligence-generated abstracts (<em>P</em><.001). Grammarly text analysis identified more writing issues and correctness errors in original than in artificial intelligence abstracts, including lower Grammarly score reflective of poorer writing quality (82.3 vs 88.1; <em>P</em>=.006), more total writing issues (19.2 vs 12.8; <em>P</em><.001), critical issues (5.4 vs 1.3; <em>P</em><.001), confusin","PeriodicalId":7574,"journal":{"name":"American journal of obstetrics and gynecology","volume":null,"pages":null},"PeriodicalIF":8.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140850599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1016/j.ajog.2024.04.043
Background
Many clinical trials use systematic methodology to monitor adverse events and determine grade (severity), expectedness, and relatedness to treatments as determined by clinicians. However, patient perspectives are often not included in this process.
Objective
This study aimed to compare clinician vs patient grading of adverse event severity in a urogynecologic surgical trial. Secondary objectives were to estimate the association of patient grading of adverse events with decision-making and quality of life outcomes and to determine if patient perspective changes over time.
Study Design
This was a planned supplementary study (Patient Perspectives in Adverse Event Reporting [PPAR]) to a randomized trial comparing 3 surgical approaches to vaginal apical prolapse. In the parent trial, adverse events experienced by patients were collected per a standardized protocol every 6 months during which clinicians graded adverse event severity (mild, moderate, severe/life-threatening). In this substudy, we obtained additional longitudinal patient perspectives for 19 predetermined “PPAR adverse events.” Patients provided their own severity grading (mild, moderate, severe/very severe/life-threatening) at initial assessment and at 12 and 36 months postoperatively. Clinicians and patients were masked to each other’s reporting. The primary outcome was the interrater agreement (kappa statistic) for adverse event severity between the initial clinician and patient assessment, combining patient grades of mild and moderate. The association between adverse event severity and the Decision Regret Scale, Satisfaction with Decision Scale, the 12-Item Short-Form Health Survey, and Patient Global Impression of Improvement scores was assessed using the Spearman correlation coefficient () for continuous scales, the Mantel–Haenszel chi-square test for Patient Global Impression of Improvement, and t tests or chi-square tests comparing the assessments of patients who rated their adverse events or symptoms as severe with those who gave other ratings. To describe patient perspective changes over time, the intraobserver agreement was estimated for adverse event severity grade over time using weighted kappa coefficients.
Results
Of the 360 randomly assigned patients, 219 (61%) experienced a total of 527 PPAR adverse events (91% moderate and 9% severe/life-threatening by clinician grading). Mean patient age was 67 years; 87% were White and 12% Hispanic. Among the patients reporting any PPAR event, the most common were urinary tract infection (61%), de novo urgency urinary incontinence (35%), stress urinary incontinence (22%), and fecal incontinence (13%). Overall agreement between clinician and participant grading of severity was poor (kappa=0.24 [95% confidence int
{"title":"Patient perspectives in adverse event reporting after vaginal apical prolapse surgery","authors":"","doi":"10.1016/j.ajog.2024.04.043","DOIUrl":"10.1016/j.ajog.2024.04.043","url":null,"abstract":"<div><h3>Background</h3><p>Many clinical trials use systematic methodology to monitor adverse events and determine grade (severity), expectedness, and relatedness to treatments as determined by clinicians. However, patient perspectives are often not included in this process.</p></div><div><h3>Objective</h3><p>This study aimed to compare clinician vs patient grading of adverse event severity in a urogynecologic surgical trial. Secondary objectives were to estimate the association of patient grading of adverse events with decision-making and quality of life outcomes and to determine if patient perspective changes over time.</p></div><div><h3>Study Design</h3><p>This was a planned supplementary study (<strong>P</strong>atient <strong>P</strong>erspectives in <strong>A</strong>dverse Event <strong>R</strong>eporting [PPAR]) to a randomized trial comparing 3 surgical approaches to vaginal apical prolapse. In the parent trial, adverse events experienced by patients were collected per a standardized protocol every 6 months during which clinicians graded adverse event severity (mild, moderate, severe/life-threatening). In this substudy, we obtained additional longitudinal patient perspectives for 19 predetermined “PPAR adverse events.” Patients provided their own severity grading (mild, moderate, severe/very severe/life-threatening) at initial assessment and at 12 and 36 months postoperatively. Clinicians and patients were masked to each other’s reporting. The primary outcome was the interrater agreement (kappa statistic) for adverse event severity between the initial clinician and patient assessment, combining patient grades of mild and moderate. The association between adverse event severity and the Decision Regret Scale, Satisfaction with Decision Scale, the 12-Item Short-Form Health Survey, and Patient Global Impression of Improvement scores was assessed using the Spearman correlation coefficient (<span><math><mrow><mi>ρ</mi></mrow></math></span>) for continuous scales, the Mantel–Haenszel chi-square test for Patient Global Impression of Improvement, and <em>t</em> tests or chi-square tests comparing the assessments of patients who rated their adverse events or symptoms as severe with those who gave other ratings. To describe patient perspective changes over time, the intraobserver agreement was estimated for adverse event severity grade over time using weighted kappa coefficients.</p></div><div><h3>Results</h3><p>Of the 360 randomly assigned patients, 219 (61%) experienced a total of 527 PPAR adverse events (91% moderate and 9% severe/life-threatening by clinician grading). Mean patient age was 67 years; 87% were White and 12% Hispanic. Among the patients reporting any PPAR event, the most common were urinary tract infection (61%), de novo urgency urinary incontinence (35%), stress urinary incontinence (22%), and fecal incontinence (13%). Overall agreement between clinician and participant grading of severity was poor (kappa=0.24 [95% confidence int","PeriodicalId":7574,"journal":{"name":"American journal of obstetrics and gynecology","volume":null,"pages":null},"PeriodicalIF":8.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140850878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1016/j.ajog.2024.04.055
{"title":"Maternal mortality in the United States: finally some good news","authors":"","doi":"10.1016/j.ajog.2024.04.055","DOIUrl":"10.1016/j.ajog.2024.04.055","url":null,"abstract":"","PeriodicalId":7574,"journal":{"name":"American journal of obstetrics and gynecology","volume":null,"pages":null},"PeriodicalIF":8.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140955375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1016/j.ajog.2024.05.023
Position: The Society for Maternal-Fetal Medicine strongly supports paid family leave and medical leave to optimize the health of pregnant people and their families and to improve health equity. All types of leave should include full wages and benefits and job protection to ensure that parents can care for themselves and their children. The Society for Maternal-Fetal Medicine endorses the implementation of a national policy that would provide fully-paid sick leave in addition to a minimum of 12 weeks of universal paid family and medical leave with job protection to optimize health and well-being across generations.
{"title":"Society for Maternal-Fetal Medicine Position Statement: Paid family and medical leave","authors":"","doi":"10.1016/j.ajog.2024.05.023","DOIUrl":"10.1016/j.ajog.2024.05.023","url":null,"abstract":"<div><p><strong>Position:</strong> The Society for Maternal-Fetal Medicine strongly supports paid family leave and medical leave to optimize the health of pregnant people and their families and to improve health equity. All types of leave should include full wages and benefits and job protection to ensure that parents can care for themselves and their children. The Society for Maternal-Fetal Medicine endorses the implementation of a national policy that would provide fully-paid sick leave in addition to a minimum of 12 weeks of universal paid family and medical leave with job protection to optimize health and well-being across generations.</p></div>","PeriodicalId":7574,"journal":{"name":"American journal of obstetrics and gynecology","volume":null,"pages":null},"PeriodicalIF":8.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0002937824006057/pdfft?md5=901880648a6d64be84018fc31bafa5c0&pid=1-s2.0-S0002937824006057-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141079463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1016/S0002-9378(24)00700-2
{"title":"AJOG MFM Table of Contents","authors":"","doi":"10.1016/S0002-9378(24)00700-2","DOIUrl":"10.1016/S0002-9378(24)00700-2","url":null,"abstract":"","PeriodicalId":7574,"journal":{"name":"American journal of obstetrics and gynecology","volume":null,"pages":null},"PeriodicalIF":8.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0002937824007002/pdfft?md5=e9c9768ea76aed17496f558cb9e7e034&pid=1-s2.0-S0002937824007002-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141954276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1016/j.ajog.2024.03.028
{"title":"Magnesium sulfate prophylaxis for late-postpartum severe hypertension","authors":"","doi":"10.1016/j.ajog.2024.03.028","DOIUrl":"10.1016/j.ajog.2024.03.028","url":null,"abstract":"","PeriodicalId":7574,"journal":{"name":"American journal of obstetrics and gynecology","volume":null,"pages":null},"PeriodicalIF":8.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140206232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1016/j.ajog.2024.03.021
{"title":"The value of maternal echocardiography after delivery in patients with severe preeclampsia","authors":"","doi":"10.1016/j.ajog.2024.03.021","DOIUrl":"10.1016/j.ajog.2024.03.021","url":null,"abstract":"","PeriodicalId":7574,"journal":{"name":"American journal of obstetrics and gynecology","volume":null,"pages":null},"PeriodicalIF":8.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140206235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1016/j.ajog.2024.03.030
{"title":"Cardiovascular protection by normotensive placental extracellular vesicles","authors":"","doi":"10.1016/j.ajog.2024.03.030","DOIUrl":"10.1016/j.ajog.2024.03.030","url":null,"abstract":"","PeriodicalId":7574,"journal":{"name":"American journal of obstetrics and gynecology","volume":null,"pages":null},"PeriodicalIF":8.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140206168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1016/j.ajog.2024.03.024
{"title":"Enduring safety concerns for out-of-hospital births in the United States","authors":"","doi":"10.1016/j.ajog.2024.03.024","DOIUrl":"10.1016/j.ajog.2024.03.024","url":null,"abstract":"","PeriodicalId":7574,"journal":{"name":"American journal of obstetrics and gynecology","volume":null,"pages":null},"PeriodicalIF":8.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140304402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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