Singapore medical journal最新文献

Introduction: Operating theatres significantly contribute to hospital expenditures. Traditional surgery scheduling, which is often based on manual methods or historical averages, lacks precision. This inefficiency impacts cost, timely care delivery and patient experience, particularly in high-volume surgeries. To address this, we aimed to create data-driven predictive models for cataract surgery durations, a largely unexplored area in local literature.

Methods: We utilised supervised machine learning models, including linear regression, random forest and extreme gradient boosting (XGBoost). Performance metrics were accuracy (within ± 10 min of actual surgery time) and mean squared error (MSE). The dataset, post-outlier removal, comprised 4242 cataract cases (80% training sets and 20% test sets).

Results: Compared to the embedded scheduling algorithm in EPIC (an electronic health records system) and surgeons' predictions, machine learning models displayed superior performance, achieving 40% and 20% greater accuracy compared to EPIC and surgeons, respectively, with a significantly lower MSE. Machine learning models' error margin primarily ranged from 0 to 5 min. Notably, underestimation beyond the ± 10-min threshold occurred in about 9% of cases.

Conclusion: In this study, machine learning models have been shown to be more effective in predicting cataract surgery durations compared to current methods, offering practical benefits for optimising operating theatre management. The use of machine learning significantly improves the accuracy of surgery duration estimates.

Introduction: The routine use of preoperative electrocardiograms (ECGs) in patients scheduled for cataract surgery is a deeply entrenched practice in Singapore, despite a lack of evidence supporting its role. Unnecessary ECGs and downstream referrals result in increased healthcare costs, strain on healthcare resources and poorer patient experience from multiple hospital visits, investigations and operation delays. International guidelines recommend against routine use of preoperative ECGs. We launched a quality improvement project to reduce the routine use of preoperative ECGs in low-risk patients undergoing cataract surgery, with the aim of aligning our practice with international guidelines and assessing the impact of this on the incidence of surgical cancellations, perioperative morbidity, and mortality.

Methods: One thousand patients scheduled for elective cataract surgery were assigned to either a control group, where routine ECG is performed (current practice) or an intervention group where the need for ECG was determined through standardised screening of relevant symptoms and vitals as per international guidelines. Adverse medical events and surgery postponement were recorded.

Results: There was no statistically significant difference in overall cancellation rates between the control and intervention groups (4% vs. 3.2%, P = 0.79). There were no significant differences in the rate of intraoperative events or unplanned admissions between the control and intervention arms.

Conclusion: The results of this project indicate no benefit from the current practice of routine preoperative ECG for cataract surgery in asymptomatic individuals. The study also provides local data to support international guidelines which recommend against this routine practice.

Introduction: Lumbar endoscopic discectomy (LED) is an increasingly common minimally invasive procedure used in treating lumbar disc herniation and decompressing spinal nerves. Various techniques have been described, each offering improved intraoperative visualisation and safety profile yet maintaining smaller incisions, resulting in better surgical outcomes and shorter hospital stay, as compared to minimally invasive microdiscectomy (MISD). This study aimed to investigate the cost-effectiveness of LED (uniportal and biportal approaches) against conventional MISD.

Methods: This is a single-centre, multi-surgeon, retrospective case cohort study of 24 and 18 patients who underwent elective single-level uniportal LED and biportal LED, respectively. In addition, an age-matched group of 42 patients who underwent single-level MISD was included. Patient demographics (age, gender, body mass index, Charlson Comorbidity Index and Functional Independence Measure), 6-month postoperative complications and inpatient hospitalisation costs were compared.

Results: Both uniportal and biportal endoscopic discectomy groups had significantly higher operation durations but maintained comparable hospital length of stay, and intra- and postoperative complication rates. The uniportal group had significantly higher overall inpatient hospitalisation bill compared to the biportal and MISD groups due to the rental fee for specialised endoscopic equipment.

Conclusion: The biportal endoscopic approach - due to its equipment versality - has lower equipment costs than uniportal endoscopic discectomy. For the biportal approach to potentially become a cost-effective and safe alternative to conventional MISD, a learning curve remains for surgeons and institutions to overcome in order to achieve shorter hospital stays and operative durations.

Introduction: Despite the exponential increase in microbiome research, knowledge and beliefs about the gut microbiome and faecal microbiota transplantation (FMT) remain unclear. The aim of this study was to identify the extent of knowledge, awareness and perception among the general public regarding the gut microbiome and FMT.

Methods: An online questionnaire on knowledge and beliefs about the gut microbiome and FMT was administered to 1831 participants. Data analysis software was used to generate descriptive statistics and explore associations between knowledge and sociodemographic variables.

Results: Even though only 33% of participants had heard of the gut microbiome, more than 92% had consumed probiotic drinks or supplements. While 85% had not heard of the FMT procedure, 72% of respondents would consider having FMT to treat Clostridioides difficile infection (CDI). Willingness to receive FMT depended mainly on recommendation from healthcare providers (77%). Knowledge and awareness regarding the gut microbiome and FMT were relatively low, despite most participants having prior gut health-related behaviours.

Conclusion: This study identified the public's perceptions of FMT and the potential barriers to its uptake. Insights from the study highlight the need for health education to enhance acceptance of FMT and the importance of using information supported by medical professionals to immunise the public against poorly validated science.

Introduction: Total knee arthroplasty (TKA) remains the gold standard treatment for end-stage knee osteoarthritis. With rising TKA numbers, effective resource management, such as reducing length of stay, is crucial. While prior studies have focused on patient characteristics, this study aimed to investigate the influence of demographics and pre- and immediate postoperative patient-reported outcome measures (PROMs) on successful 24-h discharge using Enhanced Recovery After Surgery (ERAS) protocols.

Methods: Patients who underwent TKA with ERAS from August 2020 to July 2021 were followed up. Successful protocol completion was defined as discharge within 24 hours of surgery. Baseline characteristics and PROMs were recorded. Outcomes measures were compared between patients who successfully completed or failed the ERAS protocol, and variables were imputed into a binary logistic regression.

Results: Of 342 patients, 315 (92.1%) completed the ERAS protocol for TKA. Logistic regression analysis showed that higher postoperative pain scores and American Society of Anesthesiology (ASA) class > 2 significantly reduced the likelihood of passing the ERAS protocol (postoperative visual analogue scale odds ratio 0.742, P = 0.004; ASA > 2 odds ratio 0.196, P = 0.02). The model demonstrated satisfactory goodness of fit and accurately classified 80.1% of patients at the optimal cut-off. Receiver operating characteristic curve analysis showed good probability of discriminating between patients (area under the curve = 0.741).

Conclusion: Immediate postoperative pain scores and ASA class may be useful adjuncts in predicting successful 24-h discharge after TKA using ERAS protocol.

Abstract: ChatGPT gained widespread attention for its capabilities in natural language processing, enabling machines to assess human language inputs and generate complex, yet evolving answers. As large language models (LLMs) continue to develop, clear guidelines are needed to help healthcare providers and educators maximise their benefits while mitigating potential risks. This review assessed the utility and accuracy of applying ChatGPT in healthcare assistance, specifically in understanding clinical knowledge and guiding clinical practice and research. A search on PubMed/MEDLINE for ChatGPT-related articles from 30 November 2022 (ChatGPT's release date) to 14 March 2024 yielded 2690 articles. After screening and reviewing, 2141 articles were deemed relevant to the clinical and research domains. Of the articles, 60.3% were supportive of ChatGPT, highlighting its immense potential for automating routine tasks, enhancing decision-making processes and addressing complex challenges in health care. However, 0.9% were not supportive of ChatGPT's utilisation in its current form, given the unresolved ethical implications and concerns regarding accuracy, bias, privacy and legal. Additionally, 38.8% had an equivocal stance, suggesting for further research to fully understand the rapidly evolving capabilities and potential impacts of ChatGPT in healthcare. This review presents a newly created conceptual framework, the 'ABCD model', to facilitate a systematic approach for researchers and healthcare practitioners to navigate ChatGPT's strengths and limitations. The model aims to align the development and deployment of ChatGPT by providing guiding principles, which ChatGPT and other emerging LLMs should incorporate into further developments to ensure their suitable application in health care.

Introduction: Self-administered screening questionnaires are one of the key strategies to shorten diagnostic delay among patients with autoimmune rheumatic diseases (ARDs). However, most existing screening questionnaires for ARDs were developed to screen for one or a limited number of ARDs, and thus have limited utility when the goal is to screen for common ARDs. We aimed to develop a list of ARDs for population screening, and based on this, a list of manifestations to be assessed in a screening questionnaire for ARDs.

Methods: This study comprised two phases: Phase 1 involved the development of a list of ARDs through a modified Delphi study with accredited rheumatologists and Phase 2 involved the development of a list of manifestations through a modified nominal group technique with accredited rheumatologists, other healthcare professionals caring for patients with ARDs, and patients with ARDs.

Results: In Phase 1, 14 candidate ARDs were identified using a multipronged approach, ten of which were deemed necessary to be screened for in the general population, through three rounds of Delphi exercise. In Phase 2, 80 candidate manifestations of these ten ARDs were identified from a literature review. Of these, 59 manifestations were deemed necessary to be assessed in a screening questionnaire through one round of prenominal group dialogue and two rounds of nominal group discussion.

Conclusion: Consensus-based lists of ARDs and their manifestations were developed in this study. They provide a basis for developing new ARD screening questionnaires to facilitate early diagnosis of ARDs in the general population.