Resuscitation is the medical process of reviving a patient in cardiac arrest or impending cardiac arrest. In this paper, we describe some of the resuscitation research conducted by our group. The discussion will include: using Geographic Information Systems (GIS) technology to describe the geographic epidemiology of pre-hospital cardiac arrest in Singapore, therapeutic post resuscitation hypothermia, and automated cardio-pulmonary resuscitation (CPR) using a load-distributing band (LDB) device.
Cardiopulmonary Resuscitation - Education

BACKGROUND: This study was undertaken to validate the use of the modified early warning score (MEWS) as a predictor of patient mortality and intensive care unit (ICU)/ high dependency (HD) admission in an Asian population. METHODS: The MEWS was applied to a retrospective cohort of 1024 critically ill patients presenting to a large Asian tertiary emergency department (ED) between November 2006 and December 2007. Individual MEWS was calculated based on vital signs parameters on arrival at ED. Outcomes of mortality and ICU/HD admission were obtained from hospital records. The ability of the composite MEWS and its individual components to predict mortality within 30 days from ED visit was assessed. Sensitivity, specificity, positive and negative predictive values were derived and compared with values from other cohorts. A MEWS of ≥4 was chosen as the cut-off value for poor prognosis based on previous studies. RESULTS: A total of 311 (30.4%) critically ill patients were presented with a MEWS ≥4. Their mean age was 61.4 years (SD 18.1) with a male to female ratio of 1.10. Of the 311 patients, 53 (17%) died within 30 days, 64 (20.6%) were admitted to ICU and 86 (27.7%) were admitted to HD. The area under the receiver operating characteristic curve was 0.71 with a sensitivity of 53.0% and a specificity of 72.1% in addition to a positive predictive value (PPV) of 17.0% and a negative predictive value (NPV) of 93.4% (MEWS cut-off of ≥4) for predicting mortality. CONCLUSION: The composite MEWS did not perform wel in predicting poor patient outcomes for critical y il patients presenting to an ED.

No abstract available.
Cardiopulmonary Resuscitation*

PURPOSE: We evaluated the influence of time-related input, throughput, and output factors on ambulance diversions in an urban emergency department (ED). METHODS: Data was prospectively collected in an urban ED for one year. We measured daily input factors (daily number of visit, etc), throughput factors (ED length of stay), and output factors (occupancy rate of adult ward, etc). The duty emergency physician had the authority to declare an ambulance diversion. There was no written protocol for ambulance diversion, and each diversion lasted 4 hours if not extended. We estimated the effect of the potential factors of the same day and the previous day on ambulance diversion with a multivariates logistic regression analysis excluding variables with collinearity RESULTS: The total annual number of visits was 40,863. The number of patients delivered by ambulance was 4,059 (9.9%). Ambulance diversion occurred 29 times during 365 twenty-four hour observation intervals (7.9%). The multivariates logistic regression analyses revealed three significant independent factors of ambulance diversion: the ward occupancy rate of the previous day (odds ratio [OR], 1.278; 95% confidence interval [CI], 1.039-1.573), the elderly proportion for the day (OR, 1.106; 95% CI, 1.005-1.217), the total number of visits of the day (OR, 1.079; 95% CI, 1.039-1.120). CONCLUSION: Daily number of visits, proportion of elderly, and ward occupancy rate of the previous day were found to be factors related with ambulance diversion, with the hospital occupancy rate of the previous day showing the highest OR.
Adult ; Aged ; Ambulances ; Crowding ; Emergencies ; Emergency Service, Hospital ; Humans ; Logistic Models ; Prospective Studies ; Time Factors

BACKGROUND:To determine if elderly frequent attenders are associated with increased 30-day mortality, assess resource utilization by the elderly frequent attenders and identify associated characteristics that contribute to mortality. METHODS:Retrospective observational study of electronic clinical records of all emergency department (ED) visits over a 10-year period to an urban tertiary general hospital in Singapore. Patients aged 65 years and older, with 3 or more visits within a calendar year were identified. Outcomes measured include 30-day mortality, admission rate, admission diagnosis and duration spent at ED. Chi-square-tests were used to assess categorical factors and Student t-test was used to assess continuous variables on their association with being a frequent attender. Univariate and multivariate logistic regressions were conducted on all significant independent factors on to the outcome variable (30-day mortality), to determine factor independent odds ratios of being a frequent attender. RESULTS:1.381 million attendance records were analyzed. Elderly patients accounted for 25.5％ of all attendances, of which 31.3％ are frequent attenders. Their 30-day mortality rate increased from 4.0％ in the first visit, to 8.8％ in the third visit, peaking at 10.2％ in the sixth visit. Factors associated with mortality include patients with neoplasms, ambulance utilization, male gender and having attended the ED the previous year. CONCLUSION:Elderly attenders have a higher 30-day mortality risk compared to the overall ED population, with mortality risk more marked for frequent attenders. This study illustrates the importance and need for interventions to address frequent ED visits by the elderly, especially in an aging society.

Humans ; Child ; Triage ; Magnetic Resonance Imaging ; Head ; Brain/diagnostic imaging* ; Artificial Intelligence

We aimed to know the risk-stratification-based prevalence of bacterial contamination of ambulance vehicle surfaces, equipment, and materials. This study was performed in a metropolitan area with fire-based single-tiered Basic Life Support ambulances. Total 13 out of 117 ambulances (11.1%) were sampled and 33 sites per each ambulance were sampled using a soft rayon swab and aseptic containers. These samples were then plated onto a screening media of blood agar and MacConkey agar. Specific identification with antibiotic susceptibility was performed. We categorized sampling sites into risk stratification-based groups (Critical, Semi-critical, and Non-critical equipment) related to the likelihood of direct contact with patients' mucosa. Total 214 of 429 samples showed positive results (49.9%) for any bacteria. Four of these were pathogenic (0.9%) (MRSA, MRCoNS, and K. pneumoniae), and 210 of these were environmental flora (49.0%). However, the prevalence (positive/number of sample) of bacterial contamination in critical, semi-critical airway, semi-critical breathing apparatus group was as high as 15.4% (4/26), 30.7% (16/52), and 46.2% (48/104), respectively. Despite current formal guidelines, critical and semi-critical equipments were contaminated with pathogens and normal flora. This study suggests the need for strict infection control and prevention for ambulance services.
Adult ; Aged ; *Ambulances ; Bacteria/growth & development/*isolation & purification ; Bacterial Infections/diagnosis ; Emergency Medical Services ; *Equipment Contamination ; Equipment and Supplies/*microbiology ; Female ; Humans ; Infection Control ; Male ; Microbial Sensitivity Tests ; Middle Aged ; Risk Factors

The role of the dispatch centre has increasingly become a focus of attention in cardiac arrest resuscitation. The dispatch centre is part of the first link in the chain of survival because without the initiation of early access, the rest of the chain is irrelevant. The influence of dispatch can also extend to the initiation of bystander cardiopulmonary resuscitation, early defibrillation and the rapid dispatch of emergency ambulances. The new International Liaison Committee on Resuscitation, the American Heart Association and, especially, the European Resuscitation Council 2015 guidelines have been increasing their emphasis on dispatch as the key to improving out-of-hospital cardiac arrest survival.

INTRODUCTION: Bystander cardiopulmonary resuscitation (B-CPR) is associated with improved out-of hospital cardiac arrest survival. Community-level interventions including dispatcher-assisted CPR (DA-CPR) and myResponder were implemented to increase B-CPR. We sought to assess whether these interventions increased B-CPR. METHODS: The Singapore out-of-hospital cardiac arrest registry captured cases that occurred between 2010 and 2017. Outcomes occurring in 3 time periods (Baseline, DA-CPR, and DA-CPR plus myResponder) were compared. Segmented regression of time-series data was conducted to investigate our intervention impact on the temporal changes in B-CPR. RESULTS: A total of 13,829 out-of-hospital cardiac arrest cases were included from April 2010 to December 2017. Higher B-CPR rates (24.8% versus 50.8% vs 64.4%) were observed across the 3 time periods. B-CPR rates showed an increasing but plateauing trend. DA-CPR implementation was significantly associated with an increased B-CPR (level odds ratio [OR] 2.26, 95% confidence interval [CI] 1.79-2.88; trend OR 1.03, 95% CI 1.01-1.04), while no positive change was detected with myResponder (level OR 0.95, 95% CI 0.82-1.11; trend OR 0.99, 95% CI 0.98-1.00). CONCLUSION B-CPR rates in Singapore have been increasing alongside the implementation of community-level interventions such as DA-CPR and myResponder. DA-CPR was associated with improved odds of receiving B-CPR over time while the impact of myResponder was less clear.

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.