BMJ medicine最新文献

{"title":"Development and validation of a prognostic model to predict birth weight: individual participant data meta-analysis.","authors":"John Allotey, Lucinda Archer, Kym I E Snell, Dyuti Coomar, Jacques Massé, Line Sletner, Hans Wolf, George Daskalakis, Shigeru Saito, Wessel Ganzevoort, Akihide Ohkuchi, Hema Mistry, Diane Farrar, Fionnuala Mone, Jun Zhang, Paul T Seed, Helena Teede, Fabricio Da Silva Costa, Athena P Souka, Melanie Smuk, Sergio Ferrazzani, Silvia Salvi, Federico Prefumo, Rinat Gabbay-Benziv, Chie Nagata, Satoru Takeda, Evan Sequeira, Olav Lapaire, Jose Guilherme Cecatti, Rachel Katherine Morris, Ahmet A Baschat, Kjell Salvesen, Luc Smits, Dewi Anggraini, Alice Rumbold, Marleen van Gelder, Arri Coomarasamy, John Kingdom, Seppo Heinonen, Asma Khalil, François Goffinet, Sadia Haqnawaz, Javier Zamora, Richard D Riley, Shakila Thangaratinam, Alex Kwong, Ary I Savitri, Sohinee Bhattacharya, Cuno Spm Uiterwaal, Annetine C Staff, Louise Bjoerkholt Andersen, Elisa Llurba Olive, Christopher Redman, Maureen Macleod, Baskaran Thilaganathan, Javier Arenas Ramírez, Francois Audibert, Per Minor Magnus, Anne Karen Jenum, Fionnuala M McAuliffe, Jane West, Lisa M Askie, Peter A Zimmerman, Catherine Riddell, Joris van de Post, Sebastián E Illanes, Claudia Holzman, Sander M J van Kuijk, Lionel Carbillon, Pia M Villa, Anne Eskild, Lucy Chappell, Luxmi Velauthar, Miriam van Oostwaard, Stefan Verlohren, Lucilla Poston, Enrico Ferrazzi, Christina A Vinter, Mark Brown, Karlijn C Vollebregt, Josje Langenveld, Mariana Widmer, Camilla Haavaldsen, Guillermo Carroli, Jørn Olsen, Nelly Zavaleta, Inge Eisensee, Patrizia Vergani, Pisake Lumbiganon, Maria Makrides, Fabio Facchinetti, Marleen Temmerman, Robert Gibson, Tiziana Frusca, Jane E Norman, Ernesto A Figueiró-Filho, Hannele Laivuori, Jacob A Lykke, Agustin Conde-Agudelo, Alberto Galindo, Alfred Mbah, Ana Pilar Betran, Ignacio Herraiz, Lill Trogstad, Gordon G S Smith, Eric A P Steegers, Read Salim, Tianhua Huang, Annemarijne Adank, Wendy S Meschino, Joyce L Browne, Rebecca E Allen, Kerstin Klipstein-Grobusch, Caroline A Crowther, Jan Stener Jørgensen, Jean-Claude Forest, Ben W Mol, Yves Giguère, Louise C Kenny, Anthony O Odibo, Jenny Myers, SeonAe Yeo, Lesley McCowan, Eva Pajkrt, Bassam G Haddad, Gustaaf Dekker, Emily C Kleinrouweler, Édouard LeCarpentier, Claire T Roberts, Henk Groen, Ragnhild Bergene Skråstad, Kajantie Eero, Athanasios Pilalis, Renato T Souza, Lee Ann Hawkins, Francesc Figueras, Francesca Crovetto","doi":"10.1136/bmjmed-2023-000784","DOIUrl":"10.1136/bmjmed-2023-000784","url":null,"abstract":"<p><strong>Objective: </strong>To predict birth weight at various potential gestational ages of delivery based on data routinely available at the first antenatal visit.</p><p><strong>Design: </strong>Individual participant data meta-analysis.</p><p><strong>Data sources: </strong>Individual participant data of four cohorts (237 228 pregnancies) from the International Prediction of Pregnancy Complications (IPPIC) network dataset.</p><p><strong>Eligibility criteria for selecting studies: </strong>Studies in the IPPIC network were identified by searching major databases for studies reporting risk factors for adverse pregnancy outcomes, such as pre-eclampsia, fetal growth restriction, and stillbirth, from database inception to August 2019. Data of four IPPIC cohorts (237 228 pregnancies) from the US (National Institute of Child Health and Human Development, 2018; 233 483 pregnancies), UK (Allen et al, 2017; 1045 pregnancies), Norway (STORK Groruddalen research programme, 2010; 823 pregnancies), and Australia (Rumbold et al, 2006; 1877 pregnancies) were included in the development of the model.</p><p><strong>Results: </strong>The IPPIC birth weight model was developed with random intercept regression models with backward elimination for variable selection. Internal-external cross validation was performed to assess the study specific and pooled performance of the model, reported as calibration slope, calibration-in-the-large, and observed versus expected average birth weight ratio. Meta-analysis showed that the apparent performance of the model had good calibration (calibration slope 0.99, 95% confidence interval (CI) 0.88 to 1.10; calibration-in-the-large 44.5 g, -18.4 to 107.3) with an observed versus expected average birth weight ratio of 1.02 (95% CI 0.97 to 1.07). The proportion of variation in birth weight explained by the model (R²) was 46.9% (range 32.7-56.1% in each cohort). On internal-external cross validation, the model showed good calibration and predictive performance when validated in three cohorts with a calibration slope of 0.90 (Allen cohort), 1.04 (STORK Groruddalen cohort), and 1.07 (Rumbold cohort), calibration-in-the-large of -22.3 g (Allen cohort), -33.42 (Rumbold cohort), and 86.4 g (STORK Groruddalen cohort), and observed versus expected ratio of 0.99 (Rumbold cohort), 1.00 (Allen cohort), and 1.03 (STORK Groruddalen cohort); respective pooled estimates were 1.00 (95% CI 0.78 to 1.23; calibration slope), 9.7 g (-154.3 to 173.8; calibration-in-the-large), and 1.00 (0.94 to 1.07; observed <i>v</i> expected ratio). The model predictions were more accurate (smaller mean square error) in the lower end of predicted birth weight, which is important in informing clinical decision making.</p><p><strong>Conclusions: </strong>The IPPIC birth weight model allowed birth weight predictions for a range of possible gestational ages. The model explained about 50% of individual variation in birth weights, was well calibrated (especiall","PeriodicalId":72433,"journal":{"name":"BMJ medicine","volume":"3 1","pages":"e000784"},"PeriodicalIF":0.0,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11344865/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142057474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting birth weight at booking.","authors":"Emily Prior, Sabita Uthaya","doi":"10.1136/bmjmed-2024-001018","DOIUrl":"10.1136/bmjmed-2024-001018","url":null,"abstract":"","PeriodicalId":72433,"journal":{"name":"BMJ medicine","volume":"3 1","pages":"e001018"},"PeriodicalIF":10.0,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11340215/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142037902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Age and sex specific thresholds for risk stratification of cardiovascular disease and clinical decision making: prospective open cohort study.","authors":"Zhe Xu, Juliet Usher-Smith, Lisa Pennells, Ryan Chung, Matthew Arnold, Lois Kim, Stephen Kaptoge, Matthew Sperrin, Emanuele Di Angelantonio, Angela M Wood","doi":"10.1136/bmjmed-2023-000633","DOIUrl":"10.1136/bmjmed-2023-000633","url":null,"abstract":"<p><strong>Objective: </strong>To quantify the potential advantages of using 10 year risk prediction models for cardiovascular disease, in combination with risk thresholds specific to both age and sex, to identify individuals at high risk of cardiovascular disease for allocation of statin treatment.</p><p><strong>Design: </strong>Prospective open cohort study.</p><p><strong>Setting: </strong>Primary care data from the UK Clinical Practice Research Datalink GOLD, linked with hospital admissions from Hospital Episode Statistics and national mortality records from the Office for National Statistics in England, 1 January 2006 to 31 May 2019.</p><p><strong>Participants: </strong>1 046 736 individuals (aged 40-85 years) with no cardiovascular disease, diabetes, or a history of statin treatment at baseline using data from electronic health records.</p><p><strong>Main outcome measures: </strong>10 year risk of cardiovascular disease, calculated with version 2 of the QRISK cardiovascular disease risk algorithm (QRISK2), with two main strategies to identify individuals at high risk: in strategy A, estimated risk was a fixed cut-off value of ≥10% (ie, as per the UK National Institute for Health and Care Excellence guidelines); in strategy B, estimated risk was ≥10% or ≥90th centile of age and sex specific risk distributions.</p><p><strong>Results: </strong>Compared with strategy A, strategy B stratified 20 241 (149.8%) more women aged ≤53 years and 9832 (150.2%) more men aged ≤47 years as having a high risk of cardiovascular disease; for all other ages the strategies were the same. Assuming that treatment with statins would be initiated in those identified as high risk, differences in the estimated gain in cardiovascular disease-free life years from statin treatment for strategy B versus strategy A were 0.14 and 0.16 years for women and men aged 40 years, respectively; among individuals aged 40-49 years, the numbers needed to treat to prevent one cardiovascular disease event for strategy B versus strategy A were 39 versus 21 in women and 19 versus 15 in men, respectively.</p><p><strong>Conclusions: </strong>This study quantified the potential gains in cardiovascular disease-free life years when implementing prevention strategies based on age and sex specific risk thresholds instead of a fixed risk threshold for allocation of statin treatment. Such gains should be weighed against the costs of treating more younger people with statins for longer.</p>","PeriodicalId":72433,"journal":{"name":"BMJ medicine","volume":"3 1","pages":"e000633"},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11340247/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142037899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing policy to promote inclusive medical product evidence: development of a reference standard and structured audit of clinical trial diversity policies","authors":"Jennifer Miller, William Pelletiers, Sakinah C. Suttiratana, Michael Ofosu Mensah, Jason Schwartz, Reshma Ramachandran, Cary Gross, Joseph S. Ross","doi":"10.1136/bmjmed-2024-000920","DOIUrl":"https://doi.org/10.1136/bmjmed-2024-000920","url":null,"abstract":"To develop a reference standard based on US Food and Drug Administration and stakeholder guidance for pharmaceutical companies' policies on diversity in clinical trials and to assess these policies.Development of a reference standard and structured audit for clinical trial diversity policies.50 pharmaceutical companies selected from the top 500 by their market capitalizations in 2021 (the 25 largest companies and 25 non-large companies, randomly selected from the remaining 475 companies).Data from pharmaceutical company websites and annual reports. Policy guidance from the Pharmaceutical Research and Manufacturers of America, International Federation of Pharmaceutical Manufacturers and Associations, Biotechnology Industry Organization, International Committee of Medical Journal Editors, the US Food and Drug Administration, European Medicines Agency, and World Health Organization, up to 15 May 2023.Multicomponent measure based on distinct themes derived from FDA and stakeholder guidance.Reviewing FDA and stakeholder guidance identified 14 distinct themes recommended for improving diversity in clinical trials, which were built into a reference standard: (1) enrollment targets that reflect the prevalence of targeted conditions in populations, (2) broad eligibility criteria for trials, (3) diversity in the workforce, (4) identification and remedy of barriers to trial recruitment and retention, (5) incorporation of patient input into trial design, (6) health literacy, (7) multidimensional approaches to diversity, (8) sites with diverse providers and patient populations, (9) data collection after product approval, (10) diverse enrollment in every country where trials are conducted, (11) diverse enrollment should be a focus for all phases of clinical trials, not just later stage or pivotal trials, (12) varied trial design, (13) expanded access, and (14) public reporting of the personal characteristics of participants in trials. Applying this reference standard, 48% (24/50) of companies had no public policy on diversity in clinical trials; among those with policies, content varied widely. Large companies were more likely to have a public policy than non-large companies (21/25, 84%v5/25, 20%, P<0.001). Large companies most frequently committed to using epidemiological based trial enrollment targets representing the prevalence of indicated conditions in various populations (n=15, 71%), dealing with barriers to trial recruitment (n=15, 71%), and improving patient awareness of trial opportunities (n=14, 67%). The location of the company was not associated with having a public diversity policy (P=0.17). The average company policy had five of the 14 commitments (36%, range 0-8) recommended in FDA and stakeholder guidance.The findings of the study showed that many pharmaceutical companies did not have public policies on diversity in clinical trials, although policies were more common in large than non-large companies. Policies that were publicly available varie","PeriodicalId":72433,"journal":{"name":"BMJ medicine","volume":"51 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141716180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fostering diversity in clinical trials: need for evidence and implementation to improve representation","authors":"David Collister, Claire Song, S. Ruzycki","doi":"10.1136/bmjmed-2024-000984","DOIUrl":"https://doi.org/10.1136/bmjmed-2024-000984","url":null,"abstract":"","PeriodicalId":72433,"journal":{"name":"BMJ medicine","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141698393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the methodological quality and risk of bias of systematic reviews: primer for authors of overviews of systematic reviews.","authors":"Carole Lunny, Salmaan Kanji, Pierre Thabet, Anna-Bettina Haidich, Konstantinos I Bougioukas, Dawid Pieper","doi":"10.1136/bmjmed-2023-000604","DOIUrl":"10.1136/bmjmed-2023-000604","url":null,"abstract":"","PeriodicalId":72433,"journal":{"name":"BMJ medicine","volume":"3 1","pages":"e000604"},"PeriodicalIF":0.0,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11141200/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141201463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regular use of fish oil supplements and course of cardiovascular diseases: prospective cohort study.","authors":"Ge Chen, Zhengmin Min Qian, Junguo Zhang, Shiyu Zhang, Zilong Zhang, Michael G Vaughn, Hannah E Aaron, Chuangshi Wang, Gregory Yh Lip, Hualiang Lin","doi":"10.1136/bmjmed-2022-000451","DOIUrl":"10.1136/bmjmed-2022-000451","url":null,"abstract":"<p><strong>Objective: </strong>To examine the effects of fish oil supplements on the clinical course of cardiovascular disease, from a healthy state to atrial fibrillation, major adverse cardiovascular events, and subsequently death.</p><p><strong>Design: </strong>Prospective cohort study.</p><p><strong>Setting: </strong>UK Biobank study, 1 January 2006 to 31 December 2010, with follow-up to 31 March 2021 (median follow-up 11.9 years).</p><p><strong>Participants: </strong>415 737 participants, aged 40-69 years, enrolled in the UK Biobank study.</p><p><strong>Main outcome measures: </strong>Incident cases of atrial fibrillation, major adverse cardiovascular events, and death, identified by linkage to hospital inpatient records and death registries. Role of fish oil supplements in different progressive stages of cardiovascular diseases, from healthy status (primary stage), to atrial fibrillation (secondary stage), major adverse cardiovascular events (tertiary stage), and death (end stage).</p><p><strong>Results: </strong>Among 415 737 participants free of cardiovascular diseases, 18 367 patients with incident atrial fibrillation, 22 636 with major adverse cardiovascular events, and 22 140 deaths during follow-up were identified. Regular use of fish oil supplements had different roles in the transitions from healthy status to atrial fibrillation, to major adverse cardiovascular events, and then to death. For people without cardiovascular disease, hazard ratios were 1.13 (95% confidence interval 1.10 to 1.17) for the transition from healthy status to atrial fibrillation and 1.05 (1.00 to 1.11) from healthy status to stroke. For participants with a diagnosis of a known cardiovascular disease, regular use of fish oil supplements was beneficial for transitions from atrial fibrillation to major adverse cardiovascular events (hazard ratio 0.92, 0.87 to 0.98), atrial fibrillation to myocardial infarction (0.85, 0.76 to 0.96), and heart failure to death (0.91, 0.84 to 0.99).</p><p><strong>Conclusions: </strong>Regular use of fish oil supplements might be a risk factor for atrial fibrillation and stroke among the general population but could be beneficial for progression of cardiovascular disease from atrial fibrillation to major adverse cardiovascular events, and from atrial fibrillation to death. Further studies are needed to determine the precise mechanisms for the development and prognosis of cardiovascular disease events with regular use of fish oil supplements.</p>","PeriodicalId":72433,"journal":{"name":"BMJ medicine","volume":"3 1","pages":"e000451"},"PeriodicalIF":0.0,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11116879/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141154867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a national maternity early warning score: centile based score development and Delphi informed escalation pathways.","authors":"Stephen Gerry, Jonathan Bedford, Oliver C Redfern, Hannah Rutter, Mae Chester-Jones, Marian Knight, Tony Kelly, Peter J Watkinson","doi":"10.1136/bmjmed-2023-000748","DOIUrl":"https://doi.org/10.1136/bmjmed-2023-000748","url":null,"abstract":"<p><strong>Objective: </strong>To derive a new maternity early warning score (MEWS) from prospectively collected data on maternity vital signs and to design clinical response pathways with a Delphi consensus exercise.</p><p><strong>Design: </strong>Centile based score development and Delphi informed escalation pathways.</p><p><strong>Setting: </strong>Pregnancy Physiology Pattern Prediction (4P) prospective UK cohort study, 1 August 2012 to 28 December 2016.</p><p><strong>Participants: </strong>Pregnant people from the 4P study, recruited before 20 weeks' gestation at three UK maternity centres (Oxford, Newcastle, and London). 841, 998, and 889 women provided data in the early antenatal, antenatal, and postnatal periods.</p><p><strong>Main outcome measures: </strong>Development of a new national MEWS, assigning numerical weights to measurements in the lower and upper extremes of distributions of individual vital signs from the 4P prospective cohort study. Comparison of escalation rates of the new national MEWS with the Scottish and Irish MEWS systems from 18 to 40 weeks' gestation. Delphi consensus exercise to agree clinical responses to raised scores.</p><p><strong>Results: </strong>A new national MEWS was developed by assigning numerical weights to measurements in the lower and upper extremes (5%, 1%) of distributions of vital signs, except for oxygen saturation where lower centiles (10%, 2%) were used. For the new national MEWS, in a healthy population, 56% of observation sets resulted in a total score of 0 points, 26% a score of 1 point, 12% a score of 2 points, and 18% a score of ≥2 points (escalation of care is triggered at a total score of ≥2 points). Corresponding values for the Irish MEWS were 37%, 25%, 22%, and 38%, respectively; and for the Scottish MEWS, 50%, 18%, 21%, and 32%, respectively. All three MEWS were similar at the beginning of pregnancy, averaging 0.7-0.9 points. The new national MEWS had a lower mean score for the rest of pregnancy, with the mean score broadly constant (0.6-0.8 points). The new national MEWS had an even distribution of healthy population alerts across the antenatal period. In the postnatal period, heart rate threshold values were adjusted to align with postnatal changes. The centile based score derivation approach meant that each vital sign component in the new national MEWS had a similar alert rate. Suggested clinical responses to different MEWS values were agreed by consensus of an independent expert panel.</p><p><strong>Conclusions: </strong>The centile based MEWS alerted escalation of care evenly across the antenatal period in a healthy population, while reducing alerts in healthy women compared with other MEWS systems. How well the tool predicted adverse outcomes, however, was not assessed and therefore external validation studies in large datasets are needed. Unlike other MEWS systems, the new national MEWS was developed with prospectively collected data on vital signs and used a systematic, expert ","PeriodicalId":72433,"journal":{"name":"BMJ medicine","volume":"3 1","pages":"e000748"},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11097818/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140961331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Participant characteristics and exclusion from phase 3/4 industry funded trials of chronic medical conditions: meta-analysis of individual participant level data.","authors":"Jennifer Lees, Jamie Crowther, Peter Hanlon, Elaine W Butterly, Sarah H Wild, Frances Mair, Bruce Guthrie, Katie Gillies, Sofia Dias, Nicky J Welton, Srinivasa Vittal Katikireddi, David A McAllister","doi":"10.1136/bmjmed-2023-000732","DOIUrl":"10.1136/bmjmed-2023-000732","url":null,"abstract":"<p><strong>Objectives: </strong>To assess whether age, sex, comorbidity count, and race and ethnic group are associated with the likelihood of trial participants not being enrolled in a trial for any reason (ie, screen failure).</p><p><strong>Design: </strong>Bayesian meta-analysis of individual participant level data.</p><p><strong>Setting: </strong>Industry funded phase 3/4 trials of chronic medical conditions.</p><p><strong>Participants: </strong>Participants were identified using individual participant level data to be in either the enrolled group or screen failure group. Data were available for 52 trials involving 72 178 screened individuals of whom 24 733 (34%) were excluded from the trial at the screening stage.</p><p><strong>Main outcome measures: </strong>For each trial, logistic regression models were constructed to assess likelihood of screen failure in people who had been invited to screening, and were regressed on age (per 10 year increment), sex (male <i>v</i> female), comorbidity count (per one additional comorbidity), and race or ethnic group. Trial level analyses were combined in Bayesian hierarchical models with pooling across condition.</p><p><strong>Results: </strong>In age and sex adjusted models across all trials, neither age nor sex was associated with increased odds of screen failure, although weak associations were detected after additionally adjusting for comorbidity (odds ratio of age, per 10 year increment was 1.02 (95% credibility interval 1.01 to 1.04) and male sex (0.95 (0.91 to 1.00)). Comorbidity count was weakly associated with screen failure, but in an unexpected direction (0.97 per additional comorbidity (0.94 to 1.00), adjusted for age and sex). People who self-reported as black seemed to be slightly more likely to fail screening than people reporting as white (1.04 (0.99 to 1.09)); a weak effect that seemed to persist after adjustment for age, sex, and comorbidity count (1.05 (0.98 to 1.12)). The between-trial heterogeneity was generally low, evidence of heterogeneity by sex was noted across conditions (variation in odds ratios on log scale of 0.01-0.13).</p><p><strong>Conclusions: </strong>Although the conclusions are limited by uncertainty about the completeness or accuracy of data collection among participants who were not randomised, we identified mostly weak associations with an increased likelihood of screen failure for age, sex, comorbidity count, and black race or ethnic group. Proportionate increases in screening these underserved populations may improve representation in trials.</p><p><strong>Trial registration number: </strong>PROSPERO CRD42018048202.</p>","PeriodicalId":72433,"journal":{"name":"BMJ medicine","volume":"3 1","pages":"e000732"},"PeriodicalIF":0.0,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11085787/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140913562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a national maternity early warning score: centile based score development and Delphi informed escalation pathways","authors":"Stephen Gerry, Jonathan P. Bedford, O. Redfern, Hannah Rutter, Mae Chester-Jones, Marian Knight, Tony Kelly, Peter J Watkinson","doi":"10.1136/bmjmed-2023-000748","DOIUrl":"https://doi.org/10.1136/bmjmed-2023-000748","url":null,"abstract":"Objective To derive a new maternity early warning score (MEWS) from prospectively collected data on maternity vital signs and to design clinical response pathways with a Delphi consensus exercise. Design Centile based score development and Delphi informed escalation pathways. Setting Pregnancy Physiology Pattern Prediction (4P) prospective UK cohort study, 1 August 2012 to 28 December 2016. Participants Pregnant people from the 4P study, recruited before 20 weeks' gestation at three UK maternity centres (Oxford, Newcastle, and London). 841, 998, and 889 women provided data in the early antenatal, antenatal, and postnatal periods. Main outcome measures Development of a new national MEWS, assigning numerical weights to measurements in the lower and upper extremes of distributions of individual vital signs from the 4P prospective cohort study. Comparison of escalation rates of the new national MEWS with the Scottish and Irish MEWS systems from 18 to 40 weeks' gestation. Delphi consensus exercise to agree clinical responses to raised scores. Results A new national MEWS was developed by assigning numerical weights to measurements in the lower and upper extremes (5%, 1%) of distributions of vital signs, except for oxygen saturation where lower centiles (10%, 2%) were used. For the new national MEWS, in a healthy population, 56% of observation sets resulted in a total score of 0 points, 26% a score of 1 point, 12% a score of 2 points, and 18% a score of ≥2 points (escalation of care is triggered at a total score of ≥2 points). Corresponding values for the Irish MEWS were 37%, 25%, 22%, and 38%, respectively; and for the Scottish MEWS, 50%, 18%, 21%, and 32%, respectively. All three MEWS were similar at the beginning of pregnancy, averaging 0.7-0.9 points. The new national MEWS had a lower mean score for the rest of pregnancy, with the mean score broadly constant (0.6-0.8 points). The new national MEWS had an even distribution of healthy population alerts across the antenatal period. In the postnatal period, heart rate threshold values were adjusted to align with postnatal changes. The centile based score derivation approach meant that each vital sign component in the new national MEWS had a similar alert rate. Suggested clinical responses to different MEWS values were agreed by consensus of an independent expert panel. Conclusions The centile based MEWS alerted escalation of care evenly across the antenatal period in a healthy population, while reducing alerts in healthy women compared with other MEWS systems. How well the tool predicted adverse outcomes, however, was not assessed and therefore external validation studies in large datasets are needed. Unlike other MEWS systems, the new national MEWS was developed with prospectively collected data on vital signs and used a systematic, expert informed process to design an associated escalation protocol.","PeriodicalId":72433,"journal":{"name":"BMJ medicine","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141054089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}