Background/objective: Arthroscopic surgery in knee osteoarthritis is controversial with many studies refuting its efficacy in recent literature. This study aims to evaluate the mean duration to knee arthroplasty, and the effect of microfracture on the need for subsequent knee arthroplasty in patients above the age of 55 undergoing arthroscopic procedures for osteoarthritis. Methods: One hundred and nine consecutive patients with diagnosed osteoarthritis who underwent arthroscopic surgery performed from January 2000 to December 2012 on patients aged 55 years and above by a single surgeon were reviewed retrospectively. Demographic data, age at operation, comorbidities, perioperative details and information of subsequent total knee arthroplasty were collected and analysed. Results: There were 38 males and 71 females in our study group. The group was predominantly Chinese (51.38%), with hypertension and hyperlipidaemia being the most common comorbidities, each affecting 57.8% of our study cohort. All patients had a preoperative radiograph and a magnetic resonance imaging confirming the diagnosis of osteoarthritis associated with meniscal tears. Fifty-eight knees underwent microfracture along with arthroscopic meniscectomy. The mean follow-up duration was 127.5 months (10.5 years, range: 67-212 months). Twenty three patients (20.91%) underwent knee arthroplasties subsequently, with the mean duration to arthroplasty being 65.0 months (5.5 years, range: 7-166 months). The odds ratio of avoiding knee arthroplasty with microfracture was 1.03 (95% CI ¼ 0.410-2.581). Conclusion: Arthroscopic procedures could possibly delay the need for subsequent knee arthroplasty for approximately 65 months in older patients with osteoarthritis. However, microfracture does not affect the duration between therapeutic arthroscopy and subsequent arthroplasty. Our long-term retrospective study provides an additional step in the understanding of the impact of arthroscopic procedures and a prospective case-control study would be an ideal follow-up to fully justify the application of arthroscopic procedures to delay knee arthroplasty.
BACKGROUND During the Coronavirus Disease 2019 (COVID-19) outbreak, community care facilities (CCF) were set up as temporary out-of-hospital isolation facilities to contain the surge of cases in Singapore. Confined living spaces within CCFs posed an increased risk of communicable disease spread among residents. OBJECTIVE This inspired our healthcare team managing a CCF operation to design a low-cost communicable disease outbreak surveillance system (CDOSS). METHODS Our CDOSS was designed with the following considerations: (1) comprehensiveness, (2) efficiency through passive reconnoitering from electronic medical record (EMR) data, (3) ability to provide spatiotemporal insights, (4) low-cost and (5) ease of use. We used Python to develop a lightweight application – Python-based Communicable Disease Outbreak Surveillance System (PyDOSS) – that was able perform syndromic surveillance and fever monitoring. With minimal user actions, its data pipeline would generate daily control charts and geospatial heat maps of cases from raw EMR data and logged vital signs. PyDOSS was successfully implemented as part of our CCF workflow. We also simulated a gastroenteritis (GE) outbreak to test the effectiveness of the system. RESULTS PyDOSS was used throughout the entire duration of operation; the output was reviewed daily by senior management. No disease outbreaks were identified during our medical operation. In the simulated GE outbreak, PyDOSS was able to effectively detect an outbreak within 24 hours and provided information about cluster progression which could aid in contact tracing. The code for a stock version of PyDOSS has been made publicly available. CONCLUSIONS PyDOSS is an effective surveillance system which was successfully implemented in a real-life medical operation. With the system developed using open-source technology and the code made freely available, it significantly reduces the cost of developing and operating CDOSS and may be useful for similar temporary medical operations, or in resource-limited settings.
Introduction Urgent radiological studies obtained during on-call hours are often preliminarily read by on-call residents before consultant radiologists finalise the reports at a later time. Such provisional radiology reports provide important information to guide initial patient management. This study aims to determine discrepancy rates between provisional reports and final interpretations, and to assess the clinical significance of such discrepancies. Methods This retrospective quality assurance project reviewed a total of 1218 cross-sectional imaging studies of the body (thorax, abdomen and pelvis) done between July 2015 and May 2016 during on-call hours. The studies included 1201 Computed tomography (CT) scans and 17 Magnetic Resonance Imaging (MRI) scans. Studies with incomplete or unavailable reports were excluded. Conclusions of both the provisional and final reports of each study were reviewed for concordance, with reference to the full report if needed. Discrepancies were graded according to the ACR 2016 RADPEER scoring system. Results There were 1210 studies with complete reports. Discrepant reports were noted in 183 (15.1%) studies. Of these, 89 (7.3%) were assessed to be clinically significant and the majority of these (55) were due to interpretations which should be made most of the time. CT of the abdomen and pelvis were the most prone to discrepant reports, accounting for 148 cases (80.9%). Conclusion The majority of preliminary reports for on-call body scans were concordant with final interpretations. The discrepancy rates for provisional body scan reports provided by residents while on call were comparable to those previously reported in literature.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.