Inter-hospital trends of post-resuscitation interventions and outcomes of out-of-hospital cardiac arrest in Singapore

INTRODUCTION@#Hospital-based resuscitation interventions, such as therapeutic temperature management (TTM), emergency percutaneous coronary intervention (PCI) and extracorporeal membrane oxygenation (ECMO) can improve outcomes in out-of-hospital cardiac arrest (OHCA). We investigated post-resuscitation interventions and hospital characteristics on OHCA outcomes across public hospitals in Singapore over a 9-year period.@*METHODS@#This was a prospective cohort study of all OHCA cases that presented to 6 hospitals in Singapore from 2010 to 2018. Data were extracted from the Pan-Asian Resuscitation Outcomes Study Clinical Research Network (PAROS CRN) registry. We excluded patients younger than 18 years or were dead on arrival at the emergency department. The outcomes were 30-day survival post-arrest, survival to admission, and neurological outcome.@*RESULTS@#The study analysed 17,735 cases. There was an increasing rate of provision of TTM, emergency PCI and ECMO (P<0.001) in hospitals, and a positive trend of survival outcomes (P<0.001). Relative to hospital F, hospitals B and C had lower provision rates of TTM (≤5.2%). ECMO rate was consistently <1% in all hospitals except hospital F. Hospitals A, B, C, E had <6.5% rates of provision of emergency PCI. Relative to hospital F, OHCA cases from hospitals A, B and C had lower odds of 30-day survival (adjusted odds ratio [aOR]<1; P<0.05 for hospitals A-C) and lower odds of good neurological outcomes (aOR<1; P<0.05 for hospitals A-C). OHCA cases from academic hospitals had higher odds ratio (OR) of 30-day survival (OR 1.3, 95% CI 1.1-1.5) than cases from hospitals without an academic status.@*CONCLUSION@#Post-resuscitation interventions for OHCA increased across all hospitals in Singapore from 2010 to 2018, correlating with survival rates. The academic status of hospitals was associated with improved survival.

Determinants of emergency department utilisation by older adults in Singapore: A systematic review

INTRODUCTION@#Adults aged ≥60 years contribute to disproportionately higher visits to the emergency departments (ED). We performed a systematic review to examine the reasons why older persons visit the ED in Singapore.@*METHODS@#We searched Medline, Embase and Scopus from January 2000 to December 2021 for studies reporting on ED utilisation by older adults in Singapore, and included studies that investigated determinants of ED utilisation. Statistically significant determinants and their effect sizes were extracted. Determinants of ED utilisation were organised using Andersen and Newman's model. Quality of studies was evaluated using Newcastle Ottawa Scale and Critical Appraisal Skills Programme.@*RESULTS@#The search yielded 138 articles, of which 7 were used for analysis. Among the significant individual determinants were predisposing (staying in public rental housing, religiosity, loneliness, poorer coping), enabling (caregiver distress from behavioural and psychological symptoms of dementia) and health factors (multimorbidity in patients with dementia, frailty, primary care visit in last 6 months, better treatment adherence). The 7 included studies are of moderate quality and none of them employed conceptual frameworks to organise determinants of ED utilisation.@*CONCLUSION@#The major determinants of ED utilisation by older adults in Singapore were largely individual factors. Evaluation of societal determinants of ED utilisation was lacking in the included studies. There is a need for a more holistic examination of determinants of ED utilisation locally based on conceptual models of health seeking behaviours.

Artificial Intelligence Applications for COVID-19 in Intensive Care and Emergency Settings: A Systematic Review

BackgroundLittle is known about the role of artificial intelligence (AI) as a decisive technology in the clinical management of COVID-19 patients. We aimed to systematically review and critically appraise the current evidence on AI applications for COVID-19 in intensive care and emergency settings, focusing on methods, reporting standards, and clinical utility. MethodsWe systematically searched PubMed, Embase, Scopus, CINAHL, IEEE Xplore, and ACM Digital Library databases from inception to 1 October 2020, without language restrictions. We included peer-reviewed original studies that applied AI for COVID-19 patients, healthcare workers, or health systems in intensive care, emergency or prehospital settings. We assessed predictive modelling studies using PROBAST (prediction model risk of bias assessment tool) and a modified TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) statement for AI. We critically appraised the methodology and key findings of all other studies. ResultsOf fourteen eligible studies, eleven developed prognostic or diagnostic AI predictive models, all of which were assessed to be at high risk of bias. Common pitfalls included inadequate sample sizes, poor handling of missing data, failure to account for censored participants, and weak validation of models. Studies had low adherence to reporting guidelines, with particularly poor reporting on model calibration and blinding of outcome and predictor assessment. Of the remaining three studies, two evaluated the prognostic utility of deep learning-based lung segmentation software and one studied an AI-based system for resource optimisation in the ICU. These studies had similar issues in methodology, validation, and reporting. ConclusionsCurrent AI applications for COVID-19 are not ready for deployment in acute care settings, given their limited scope and poor quality. Our findings underscore the need for improvements to facilitate safe and effective clinical adoption of AI applications, for and beyond the COVID-19 pandemic.

Comparison of inhalational methoxyflurane (Penthrox®) and intramuscular tramadol for prehospital analgesia

INTRODUCTION@#Treatment of pain is an important component of prehospital care. Inhalational analgesia agents have attractive strengths, but there is a paucity of studies comparing these with more conventional agents. We aimed to compare inhalational methoxyflurane and intramuscular (IM) tramadol as first-contact analgesia in the Singapore national ambulance service.@*METHODS@#Ambulances were randomised to carry either methoxyflurane or IM tramadol for the first six months and crossed over to the other arm after six months. Patients aged ≥ 16 years, with acute pain arising from musculoskeletal trauma with Numerical Rating Scale (NRS) score ≥ 3 were enrolled. Variables included NRS reduction, time variables, adverse effects, Ramsay Sedation Scores, and patient and paramedic satisfaction scores on a Likert scale.@*RESULTS@#A total of 369 patients were enrolled into this study, but 26 patients were excluded due to missing data. The methoxyflurane arm had a shorter median time taken from arrival at the scene to drug administration (9.0 [interquartile range 6.0-14.0] minutes vs. 11.0 [interquartile range 8.0-15.0] minutes). For patients who achieved reduction in NRS ≥ 3 within 20 minutes, those in the methoxyflurane arm took a shorter time. However, the methoxyflurane (46.7%) arm experienced lower proportion of patients not achieving NRS reduction ≥ 3 when compared to the tramadol (71.6%) arm after over 20 minutes. The methoxyflurane arm had significantly higher paramedic and patient satisfaction scores.@*CONCLUSION@#For the doses of medication used in this implementation study, methoxyflurane was superior in efficacy, speed of onset and administration, but had more minor adverse effects when compared to IM tramadol.

Coronavirus Disease 2019 (COVID-19): An Evidence Map of Medical Literature

Since the beginning of the COVID-19 outbreak in December 2019, a substantial body of COVID-19 medical literature has been generated. As of May 2020, gaps in the existing literature remain unidentified and, hence, unaddressed. In this paper, we summarise the medical literature on COVID-19 between 1 January and 24 March 2020 using evidence maps and bibliometric analysis in order to systematically identify gaps and propose areas for valuable future research. The examined COVID-19 medical literature originated primarily from Asia and focussed mainly on clinical features and diagnosis of the disease. Many areas of potential research remain underexplored, such as mental health research, the use of novel technologies and artificial intelligence, research on the pathophysiology of COVID-19 within different body systems, and research on indirect effects of COVID-19 on the care of non-COVID-19 patients. Research collaboration at the international level was limited although improvements may aid global containment efforts.

Letter to the Editor: Compression Rate during Cardiopulmonary Resuscitation

No abstract available.

Prehospital system delay in patients with ST-segment elevation myocardial infarction in Singapore / 世界急诊医学杂志（英文）

@#BACKGROUND: Timely reperfusion in ST-segment elevation myocardial infarction (STEMI) improves outcomes. System delay is that between first medical contact and reperfusion therapy, comprising prehospital and hospital components. This study aimed to characterize prehospital system delay in Singapore. METHODS: A retrospective chart review was performed for 462 consecutive STEMI patients presenting to a tertiary hospital from December 2006 to April 2008. Patients with cardiac arrest secondarily presented were excluded. For those who received emergency medical services (EMS), ambulance records were reviewed. Time intervals in the hospital were collected prospectively. The patients were divided into two equal groups of high/low prehospital system delay using visual binning technique. RESULTS: Of 462 patients, 76 received EMS and 52 of the 76 patients were analyzed. The median system delay was 125.5 minutes and the median prehospital system delay was 33.5 minutes (interquartile range [IQR]=27.0, 42.0). Delay between call-received-by-ambulance and ambulance-dispatched was 2.48 minutes (IQR=1.47, 16.55); between ambulance-dispatch and arrival-at-patient-location was 8.07 minutes (IQR=1.30, 22.13); between arrival-at- and departure-from-patient-location was 13.12 minutes (IQR=3.12, 32.2); and between leaving-patient-location to ED-registration was 9.90 minutes (IQR=1.62, 32.92). Comparing patients with prehospital system delay of less than 35.5 minutes versus more showed that the median delay between ambulance-dispatch and arrival-at-patient-location was shorter (5.75 vs. 9.37 minutes, P<0.01). The median delay between arrival-at-patient-location and leaving-patient-location was also shorter (10.78 vs. 14.37 minutes, P<0.01). CONCLUSION: Prehospital system delay in our patients was suboptimal. This is the first attempt at characterizing prehospital system delay in Singapore and forms the basis for improving efficiency of STEMI care.