BMJ Surgery Interventions Health Technologies最新文献

{"title":"Systematic review of preoperative n-3 fatty acids in major gastrointestinal surgery.","authors":"Jason George,&nbsp;Daniel White,&nbsp;Barbara Fielding,&nbsp;Michael Scott,&nbsp;Timothy Rockall,&nbsp;Martin Brunel Whyte","doi":"10.1136/bmjsit-2022-000172","DOIUrl":"https://doi.org/10.1136/bmjsit-2022-000172","url":null,"abstract":"<p><strong>Objectives: </strong>Perioperative nutrition aims to replenish nutritional stores before surgery and reduce postoperative complications. 'Immunonutrition' (including omega-3 fatty acids) may modulate the immune system and attenuate the postoperative inflammatory response. Hitherto, immunonutrition has overwhelmingly been administered in the postoperative period-however, this may be too late to provide benefit.</p><p><strong>Design: </strong>A systematic literature search using MEDLINE and EMBASE for randomized controlled trials (RCTs).</p><p><strong>Setting: </strong>Perioperative major gastrointestinal surgery.</p><p><strong>Participants: </strong>Patients undergoing major gastrointestinal surgery.</p><p><strong>Interventions: </strong>Omega-3 fatty acid supplementation commenced in the preoperative period, with or without continuation into postoperative period.</p><p><strong>Main outcome measures: </strong>The effect of preoperative omega-3 fatty acids on inflammatory response and clinical outcomes.</p><p><strong>Results: </strong>833 studies were identified. After applying inclusion and exclusion criteria, 12 RCTs, involving 1456 randomized patients, were included. Ten articles exclusively enrolled patients with cancer. Seven studies used a combination of EPA (eicosapentaenoic acid) and DHA (docosahexaenoic acid) as the intervention and five studies used EPA alone. Eight out of 12 studies continued preoperative nutritional support into the postoperative period.Of the nine studies reporting mortality, no difference was seen. Duration of hospitalisation ranged from 4.5 to 18 days with intervention and 3.5 to 23.5 days with control. Omega-3 fatty acids had no effect on postoperative C-reactive protein and the effect on cytokines (including tumor necrosis factor-α, interleukin (IL)-6 and IL-10) was inconsistent. Ten of the 12 studies had low risk of bias, with one study having moderate bias from allocation and blinding.</p><p><strong>Conclusions: </strong>There is insufficient evidence to support routine preoperative omega-3 fatty acid supplementation for major gastrointestinal surgery, even when this is continued after surgery.</p><p><strong>Prospero registration number: </strong>CRD42018108333.</p>","PeriodicalId":33349,"journal":{"name":"BMJ Surgery Interventions Health Technologies","volume":"5 1","pages":"e000172"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/18/3d/bmjsit-2022-000172.PMC10314636.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9745798","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 total knee replacement at 2 and 5 years in osteoarthritis patients using machine learning.","authors":"Khadija Mahmoud,&nbsp;M Abdulhadi Alagha,&nbsp;Zuzanna Nowinka,&nbsp;Gareth Jones","doi":"10.1136/bmjsit-2022-000141","DOIUrl":"https://doi.org/10.1136/bmjsit-2022-000141","url":null,"abstract":"<p><strong>Objectives: </strong>Knee osteoarthritis is a major cause of physical disability and reduced quality of life, with end-stage disease often treated by total knee replacement (TKR). We set out to develop and externally validate a machine learning model capable of predicting the need for a TKR in 2 and 5 years time using routinely collected health data.</p><p><strong>Design: </strong>A prospective study using datasets Osteoarthritis Initiative (OAI) and the Multicentre Osteoarthritis Study (MOST). OAI data were used to train the models while MOST data formed the external test set. The data were preprocessed using feature selection to curate 45 candidate features including demographics, medical history, imaging assessments, history of intervention and outcome.</p><p><strong>Setting: </strong>The study was conducted using two multicentre USA-based datasets of participants with or at high risk of knee OA.</p><p><strong>Participants: </strong>The study excluded participants with at least one existing TKR. OAI dataset included participants aged 45-79 years of which 3234 were used for training and 809 for internal testing, while MOST involved participants aged 50-79 and 2248 were used for external testing.</p><p><strong>Main outcome measures: </strong>The primary outcome of this study was prediction of TKR onset at 2 and 5 years. Performance was evaluated using area under the curve (AUC) and F1-score and key predictors identified.</p><p><strong>Results: </strong>For the best performing model (gradient boosting machine), the AUC at 2 years was 0.913 (95% CI 0.876 to 0.951), and at 5 years 0.873 (95% CI 0.839 to 0.907). Radiographic-derived features, questionnaire-based assessments alongside the patient's educational attainment were key predictors for these models.</p><p><strong>Conclusions: </strong>Our approach suggests that routinely collected patient data are sufficient to drive a predictive model with a clinically acceptable level of accuracy (AUC>0.7) and is the first such tool to be externally validated. This level of accuracy is higher than previously published models utilising MRI data, which is not routinely collected.</p>","PeriodicalId":33349,"journal":{"name":"BMJ Surgery Interventions Health Technologies","volume":"5 1","pages":"e000141"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/18/4d/bmjsit-2022-000141.PMC9933661.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10772204","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":"Market competition among manufacturers of novel high-risk therapeutic devices receiving FDA premarket approval between 2001 and 2018.","authors":"Vinay K Rathi,&nbsp;James L Johnston,&nbsp;Sanket Dhruva,&nbsp;Joseph Ross","doi":"10.1136/bmjsit-2022-000152","DOIUrl":"https://doi.org/10.1136/bmjsit-2022-000152","url":null,"abstract":"© Author(s) (or their employer(s)) 2023. Reuse permitted under CC BYNC. No commercial reuse. See rights and permissions. Published by BMJ. INTRODUCTION The US Food and Drug Administration (FDA) regulates highrisk medical devices through the premarket approval (PMA) pathway, which requires clinical evidence assuring safety and effectiveness for approval. After approval, manufacturers may face barriers to successful commercialization, such as uncertainties about reimbursement or limited market exclusivity. 3 These clinical, financial and operational hurdles may discourage market entry by manufacturers, thereby limiting competitive innovation. We sought to evaluate the extent of market entry by manufacturers of firstinclass devices and subsequent competitors.","PeriodicalId":33349,"journal":{"name":"BMJ Surgery Interventions Health Technologies","volume":"5 1","pages":"e000152"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/75/ac/bmjsit-2022-000152.PMC9923248.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9522194","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":"Distinct phenotypes of kidney transplant recipients aged 80 years or older in the USA by machine learning consensus clustering.","authors":"Charat Thongprayoon,&nbsp;Caroline C Jadlowiec,&nbsp;Shennen A Mao,&nbsp;Michael A Mao,&nbsp;Napat Leeaphorn,&nbsp;Wisit Kaewput,&nbsp;Pattharawin Pattharanitima,&nbsp;Pitchaphon Nissaisorakarn,&nbsp;Matthew Cooper,&nbsp;Wisit Cheungpasitporn","doi":"10.1136/bmjsit-2022-000137","DOIUrl":"https://doi.org/10.1136/bmjsit-2022-000137","url":null,"abstract":"<p><strong>Objectives: </strong>This study aimed to identify distinct clusters of very elderly kidney transplant recipients aged ≥80 and assess clinical outcomes among these unique clusters.</p><p><strong>Design: </strong>Cohort study with machine learning (ML) consensus clustering approach.</p><p><strong>Setting and participants: </strong>All very elderly (age ≥80 at time of transplant) kidney transplant recipients in the Organ Procurement and Transplantation Network/United Network for Organ Sharing database database from 2010 to 2019.</p><p><strong>Main outcome measures: </strong>Distinct clusters of very elderly kidney transplant recipients and their post-transplant outcomes including death-censored graft failure, overall mortality and acute allograft rejection among the assigned clusters.</p><p><strong>Results: </strong>Consensus cluster analysis was performed in 419 very elderly kidney transplant and identified three distinct clusters that best represented the clinical characteristics of very elderly kidney transplant recipients. Recipients in cluster 1 received standard Kidney Donor Profile Index (KDPI) non-extended criteria donor (ECD) kidneys from deceased donors. Recipients in cluster 2 received kidneys from older, hypertensive ECD deceased donors with a KDPI score ≥85%. Kidneys for cluster 2 patients had longer cold ischaemia time and the highest use of machine perfusion. Recipients in clusters 1 and 2 were more likely to be on dialysis at the time of transplant (88.3%, 89.4%). Recipients in cluster 3 were more likely to be preemptive (39%) or had a dialysis duration less than 1 year (24%). These recipients received living donor kidney transplants. Cluster 3 had the most favourable post-transplant outcomes. Compared with cluster 3, cluster 1 had comparable survival but higher death-censored graft failure, while cluster 2 had lower patient survival, higher death-censored graft failure and more acute rejection.</p><p><strong>Conclusions: </strong>Our study used an unsupervised ML approach to cluster very elderly kidney transplant recipients into three clinically unique clusters with distinct post-transplant outcomes. These findings from an ML clustering approach provide additional understanding towards individualised medicine and opportunities to improve care for very elderly kidney transplant recipients.</p>","PeriodicalId":33349,"journal":{"name":"BMJ Surgery Interventions Health Technologies","volume":"5 1","pages":"e000137"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/85/b1/bmjsit-2022-000137.PMC9944353.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10792650","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":"Surgical device design: do instruments fit today's surgeons?","authors":"Andrea Mesiti,&nbsp;Heather Yeo","doi":"10.1136/bmjsit-2022-000159","DOIUrl":"https://doi.org/10.1136/bmjsit-2022-000159","url":null,"abstract":"© Author(s) (or their employer(s)) 2023. Reuse permitted under CC BYNC. No commercial reuse. See rights and permissions. Published by BMJ. Since introduction of laparoscopy in the 1980s, the field of surgery has rapidly transitioned toward minimal access techniques and procedures. Along with this shift, many new surgical devices and instruments have been developed. The design and implementation of these devices is complex and expensive, yet vital to advancing surgery. Medical device companies frequently employ human factors engineers and key opinion leaders to help guide the design of these devices and to understand how to make them useful for physicians. Unfortunately, because surgery has traditionally been a male dominated field, most instruments have been built and designed with the male user in mind. Biomechanics and anthropometry are integral, related components of device development. Biomechanics refers to the structure and function of mechanical aspects of individuals, such as joint function, while anthropometry refers to measurements of the human body. The design of these devices involves incorporating these inherently intertwined dimensions to make them effective for users. These measurements are highly variable among the differing demographics of surgeons. For example, females have less grip strength, grip span and different hand anthropometry compared with male counterparts and a recent commentary by Hallbeck and Lal underscores the fact these measures vary by ethnicity as well. A 2001 medical device ergonomics paper defined the goal of designing laparoscopic instruments: to design a handle that accommodates 95% of the defined user population. This begs the question, who comprises the aforementioned ‘user population’? The field surgery is continuing to diversify and recruit women. This has been a welcome change. But, as the change in the population of surgeons occurs, design of laparoscopic devices has not seen parallel change. An ergonomics paper by van Veelen et al defined the population of laparoscopic surgeons as 90% male and 10% female. While this may have been previously true, this is no longer the case and will continue to change and evolve. Data from the AAMC reports that 44.8% of current general surgery residents are female as of 2021. Further, an overwhelming 85.2% of obstetrics and gynecology residents, a subspecialty which frequently uses laparoscopy, are women. Since it is obvious that the population of people using laparoscopic instruments has changed and will continue to change, the design of these instruments must also start to adapt. These key points are summarized in box 1. While most women and smallhanded surgeons can probably agree that palming bowel graspers and Marylands during laparoscopic cases is feasible, where the ergonomic difference is particularly pronounced is with disposable laparoscopic instruments. These devices are made mostly of plastic and then disposed of as medical waste at the end of cases. In th","PeriodicalId":33349,"journal":{"name":"BMJ Surgery Interventions Health Technologies","volume":"5 1","pages":"e000159"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/aa/cf/bmjsit-2022-000159.PMC10351279.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10213595","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":"Integration of a personalised mobile health (mHealth) application into the care of patients with brain tumours: proof-of-concept study (IDEAL stage 1).","authors":"Andrew Gvozdanovic,&nbsp;Felix Jozsa,&nbsp;Naomi Fersht,&nbsp;Patrick James Grover,&nbsp;Georgina Kirby,&nbsp;Neil Kitchen,&nbsp;Riccardo Mangiapelo,&nbsp;Andrew McEvoy,&nbsp;Anna Miserocchi,&nbsp;Rayna Patel,&nbsp;Lewis Thorne,&nbsp;Norman Williams,&nbsp;Michael Kosmin,&nbsp;Hani J Marcus","doi":"10.1136/bmjsit-2021-000130","DOIUrl":"10.1136/bmjsit-2021-000130","url":null,"abstract":"<p><strong>Objectives: </strong>Brain tumours lead to significant morbidity including a neurocognitive, physical and psychological burden of disease. The extent to which they impact the multiple domains of health is difficult to capture leading to a significant degree of unmet needs. Mobile health tools such as Vinehealth have the potential to identify and address these needs through real-world data generation and delivery of personalised educational material and therapies. We aimed to establish the feasibility of Vinehealth integration into brain tumour care, its ability to collect real-world and (electronic) patient-recorded outcome (ePRO) data, and subjective improvement in care.</p><p><strong>Design: </strong>A mixed-methodology IDEAL stage 1 study.</p><p><strong>Setting: </strong>A single tertiary care centre.</p><p><strong>Participants: </strong>Six patients consented and four downloaded and engaged with the mHealth application throughout the 12 weeks of the study.</p><p><strong>Main outcome measures: </strong>Over a 12-week period, we collected real-world and ePRO data via Vinehealth. We assessed qualitative feedback from mixed-methodology surveys and semistructured interviews at recruitment and after 2 weeks.</p><p><strong>Results: </strong>565 data points were captured including, but not limited to: symptoms, activity, well-being and medication. EORTC QLQ-BN20 and EQ-5D-5L completion rates (54% and 46%) were impacted by technical issues; 100% completion rates were seen when ePROs were received. More brain cancer tumour-specific content was requested. All participants recommended the application and felt it improved care.</p><p><strong>Conclusions: </strong>Our findings indicate value in an application to holistically support patients living with brain cancer tumours and established the feasibility and safety of further studies to more rigorously assess this.</p>","PeriodicalId":33349,"journal":{"name":"BMJ Surgery Interventions Health Technologies","volume":"4 1","pages":"e000130"},"PeriodicalIF":0.0,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/62/76/bmjsit-2021-000130.PMC9791405.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10457903","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":"Building Blocks for the Long-acting and Permanent Contraceptives Coordinated Registry Network.","authors":"Courtney E Baird, Maryam Guiahi, Scott Chudnoff, Nilsa Loyo-Berrios, Stephanie Garcia, Mary Jung, Laura Elisabeth Gressler, Jialin Mao, Beth Hodshon, Art Sedrakyan, Sharon Andrews, Kelly Colden, Jason Roberts, Abby Anderson, Catherine Sewell, Danica Marinac-Dabic","doi":"10.1136/bmjsit-2020-000075","DOIUrl":"10.1136/bmjsit-2020-000075","url":null,"abstract":"<p><strong>Objectives: </strong>A multistakeholder expert group under the Women's Health Technology Coordinated Registry Network (WHT-CRN) was organized to develop the foundation for national infrastructure capturing the performance of long-acting and permanent contraceptives. The group, consisting of representatives from professional societies, the US Food and Drug Administration, academia, industry and the patient community, was assembled to discuss the role and feasibility of the CRN and to identify the core data elements needed to assess contraceptive medical product technologies.</p><p><strong>Design: </strong>We applied a Delphi survey method approach to achieve consensus on a core minimum data set for the future CRN. A series of surveys were sent to the panel and answered by each expert anonymously and individually. Results from the surveys were collected, collated and analyzed by a study design team from Weill Cornell Medicine. After the first survey, questions for subsequent surveys were based on the analysis process and conference call discussions with group members. This process was repeated two times over a 6-month time period until consensus was achieved.</p><p><strong>Results: </strong>Twenty-three experts participated in the Delphi process. Participation rates in the first and second round of the Delphi survey were 83% and 100%, respectively. The working group reached final consensus on 121 core data elements capturing reproductive/gynecological history, surgical history, general medical history, encounter information, long-acting/permanent contraceptive index procedures and follow-up, procedures performed in conjunction with the index procedure, product removal, medications, complications related to the long-acting and/or permanent contraceptive procedure, pregnancy and evaluation of safety and effectiveness outcomes.</p><p><strong>Conclusions: </strong>The WHT-CRN expert group produced a consensus-based core set of data elements that allow the study of current and future contraceptives. These data elements influence patient and provider decisions about treatments and include important outcomes related to safety and effectiveness of these medical devices, which may benefit other women's health stakeholders.</p>","PeriodicalId":33349,"journal":{"name":"BMJ Surgery Interventions Health Technologies","volume":"4 Suppl 1","pages":"e000075"},"PeriodicalIF":2.1,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/cb/18/bmjsit-2020-000075.PMC9660629.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9723702","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":"Maturity framework and select approaches for developing Coordinated Registry Networks (CRNs): Medical Device Epidemiology Network (MDEpiNet) supplement.","authors":"Art Sedrakyan, Suvekshya Aryal","doi":"10.1136/bmjsit-2022-000148","DOIUrl":"10.1136/bmjsit-2022-000148","url":null,"abstract":"","PeriodicalId":33349,"journal":{"name":"BMJ Surgery Interventions Health Technologies","volume":"4 Suppl 1","pages":"e000148"},"PeriodicalIF":2.1,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/24/08/bmjsit-2022-000148.PMC9660703.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9723698","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":"Orthopedic Coordinated Registry Network (Ortho-CRN): advanced infrastructure for real-world evidence generation.","authors":"Laura Elisabeth Gressler, Vincent Devlin, Mary Jung, Danica Marinac-Dabic, Art Sedrakyan, Elizabeth W Paxton, Patricia Franklin, Ronald Navarro, Said Ibrahim, Jonathan Forsberg, Paul E Voorhorst, Robbert Zusterzeel, Michael Vitale, Michelle C Marks, Peter O Newton, Raquel Peat","doi":"10.1136/bmjsit-2020-000073","DOIUrl":"10.1136/bmjsit-2020-000073","url":null,"abstract":"","PeriodicalId":33349,"journal":{"name":"BMJ Surgery Interventions Health Technologies","volume":"4 Suppl 1","pages":"e000073"},"PeriodicalIF":2.1,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/ab/11/bmjsit-2020-000073.PMC9660599.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9708575","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 coordinated registry network for pelvic organ prolapse technologies.","authors":"Courtney E Baird, Bilal Chughtai, Catherine S Bradley, Kathleen Kobashi, Mary Jung, Art Sedrakyan, Sharon Andrews, Ann Ferriter, Terri Cornelison, Danica Marinac-Dabic","doi":"10.1136/bmjsit-2020-000076","DOIUrl":"10.1136/bmjsit-2020-000076","url":null,"abstract":"<p><strong>Objectives: </strong>The accumulation of data through a prospective, multicenter Coordinated Registry Network (CRN) could be a robust and cost-effective way to gather real-world evidence on the performance of pelvic organ prolapse (POP) technologies for device-based and intervention-based studies. To develop the CRN, a group of POP experts consisting of representatives from professional societies, the Food and Drug Administration, academia, industry, and the patient community, was convened to discuss the role and feasibility of the CRN and to identify the core data elements important to assess POP technologies.</p><p><strong>Design: </strong>A Delphi method approach was employed to achieve consensus on a core minimum dataset for the CRN. A series of surveys were sent to the panel and answered by each expert anonymously and individually. Results from the surveys were collected, collated, and analyzed by the study design team from Weill Cornell Medicine. Questions for the next round were based on the analysis process and discussed with group members via conference call. This process was repeated twice over a 6-month time period during which consensus was achieved.</p><p><strong>Results: </strong>Twenty-one experts participated in the effort and proposed 120 data elements. Participation rates in the first and second round of the Delphi survey were 95.2% and 71.4%, respectively. The working group reached final consensus among responders on 90 data elements capturing relevant general medical and surgical history, procedure and discharge, short-term and long-term follow-up, device factors, and surgery and surgeon factors.</p><p><strong>Conclusions: </strong>The CRN successfully developed a set of core data elements to support the study of POP technologies through convening an expert panel on POP technologies and using the Delphi method. These standardized data elements have the potential to influence patient and provider decisions about treatments and include important outcomes related to efficacy and safety.</p>","PeriodicalId":33349,"journal":{"name":"BMJ Surgery Interventions Health Technologies","volume":"4 Suppl 1","pages":"e000076"},"PeriodicalIF":2.1,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/c7/1e/bmjsit-2020-000076.PMC9660621.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9708577","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}