PMC:2652658 / 3422-7677
Annnotations
{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/2652658","sourcedb":"PMC","sourceid":"2652658","source_url":"https://www.ncbi.nlm.nih.gov/pmc/2652658","text":"2 Methods\n\n2.1 Participants\nParticipants were 228 patients admitted with ACS to one of four London hospitals. Patients were recruited on 3 days per week rather than consecutively due to staffing constraints. ACS was diagnosed on the basis of chest pain verified by electrocardiographic criteria and/or troponin T measurement [14]. Other inclusion criteria included ability to recall the time symptoms started, time of calling for medical help and events prior to hospital admission, absence of comorbid conditions (renal failure, cancer, stroke, ongoing infection or inflammatory conditions such as inflammatory bowel disease) that might influence symptom presentation, mood or troponin positivity [15], and ability to complete an interview in English. The study was approved by the University College London/University College London Hospitals Ethics Committee and ethics committees of participating hospitals, and the investigation conforms with the principles outlined in the Declaration of Helsinki [16]. Data were collected between 2001 and 2004 in the context of a larger longitudinal observational cohort study of emotional and behavioral triggers of ACS [17]. A total of 375 patients were potentially eligible for this study; of these, 48 (12.8%) were discharged or transferred before the interview could take place, information regarding delay was incomplete for a further 67 (17.9%) due to initial admission to/transfer from non-participating hospitals, and 32 (8.5%) declined participation. The effective response rate was therefore 88%. All participants gave informed written consent.\n\n2.2 Measures\nInformation concerning sociodemographic and socioeconomic factors, cardiovascular history and risk factors, patient's attribution of symptoms, clinical and proximal factors, and time of admission, symptom onset and call for assistance was collected using medical records and semi-structured interviews 2.6 ± 1.5 days after hospital admission. Socioeconomic position was assessed using educational qualifications which were categorized into 3 groups; high school/university qualification, below high school, or no formal educational qualifications of any kind. Patients were asked whether they initially attributed the pain to a heart attack or to a non-cardiac cause (e.g. indigestion, muscle strain, flu). Clinical data included type of ACS, which was classified as ST elevation myocardial infarction (STEMI), non-ST elevation myocardial infarction (NSTEMI) or unstable angina (UA); intensity of chest pain, rated on a 10 point scale (0 = none to 10 = excruciating); number and type of pain symptoms reported in addition to chest pain (i.e. pain in arms, shoulders, jaw, back) and non-pain symptoms (i.e. breathlessness, nausea/vomiting, sweating, flu-like, dizziness/fainting); cardiac history and risk factors. Proximal factors included time/day of onset, presence of a bystander and location, and a record was made of whether they initially contacted the EMS or another source of help such as a physician, family or friends.\n\n2.3 Statistical analysis\nThe distribution of all time periods (total pre-hospital delay, decision time and home-to-hospital delay) was skewed, so analyses were based on binary divisions of each interval. The factors associated with total pre-hospital delay were analyzed by comparing the characteristics of patients with delays longer or shorter than the median of 120 min. Decision time was analyzed by comparing individuals with decision times ≤ 60 or \u003e 60 min. This criterion was selected because reperfusion therapy is most effective if initiated within the first hour [2]. Home-to-hospital delay was also analyzed by comparing individuals with delays ≤ 60 or \u003e 60 min since the target set by the UK National Service Framework for administration of thrombolysis to eligible patients is within 1 h of calling for help [18]. Other studies investigating pre-hospital delay have used similar time cut offs [11]. Groups were compared using χ2 tests, and significant effects were subsequently entered into multivariate analyses using logistic regression with age and gender as covariates. Results are presented as percentages and odds ratios (OR) adjusted for age and gender with 95% confidence intervals 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