Jack I. Williams

Trauma outcome improves following the advanced trauma life support program in a developing country.

Trauma outcome variables before and after the institution of the Advanced Trauma Life Support (ATLS) program were compared for the largest hospital in Trinidad and Tobago from July 1981 through December 1985 (pre-ATLS) and from January 1986 to June 1990 (post-ATLS). A total of 199 physicians were ATLS trained by June 1990. Outcome data were analyzed for all dead or severely injured patients (ISS > or = 16; n = 413 pre-ATLS and n = 400 post-ATLS). Trauma mortality decreased post-ATLS (134 of 400 vs. 279 of 413) throughout the hospital, including the ICU (13.6% post-ATLS ICU mortality vs. 55.2% pre-ATLS). The odds of dying from trauma increased with age (1.02 for each year), ISS score (1.24 for each ISS increment), and blunt injury, both pre-ATLS and post-ATLS. Post-ATLS mortality was associated with a higher ISS (31.6 vs. 28.8). Although there was a higher percentage of blunt injury pre-ATLS (84.0%) versus post-ATLS (68.3%), the mortality rates for both blunt and penetrating injuries were higher in the pre-ATLS group (19.7% pre-ATLS vs. 6.3% post-ATLS for penetrating and 76.6% pre-ATLS versus 46.2% post-ATLS for blunt). For each ISS category, mortality was greater in the pre-ATLS group (ISS > or = 24 pre-ATLS mortality 47.9% vs. 16.7% post-ATLS; ISS 25-40 pre-ATLS mortality 91.0% vs. 71.0% post-ATLS). The overall ratio of observed to expected mortality based on the MTOS data base was lower for the post-ATLS period (pre-ATLS ratio 3.16; post-ATLS ratio 1.94).(ABSTRACT TRUNCATED AT 250 WORDS)

Impact of on-site care, prehospital time, and level of in-hospital care on survival in severely injured patients

A sample of 360 severely injured patients was selected from a cohort of 8007 trauma victims followed prospectively from the time of injury to death or discharge. A case referent study was used to test the association between on-site care, total prehospital time, and level of care at the receiving hospital with short-term survival. Multiple logistic regression analyses showed that use of Advanced Life Support (ALS) at the scene was not associated with survival, whereas treatment at a level I compatible hospital was associated with a 38% reduction in the odds of dying, which approached statistical significance. Total prehospital time over 60 minutes was associated with a statistically significant adjusted relative odds of dying (OR = 3.0). The results of this study support the need for regionalization of trauma care and fail to show a benefit associated with ALS.

Socioeconomic Status and Mortality after Acute Myocardial Infarction

Context Many studies show worse cardiovascular outcomes among poor persons than among affluent persons, but the factors that mediate this relationship are unknown. Contribution In this prospective study of 3407 Canadians who were hospitalized for myocardial infarction, 7.1% of the patients in the high-income group died within 2 years compared with 15.3% of the patients in the low-income group. Adjustment for age, preexisting cardiovascular disease, and risk factors greatly attenuated the relationship between mortality rates and income. Adjustment for other factors had little effect. Implications A history of 1 or more cardiovascular events and worse cardiovascular risk factors may explain why poor people have worse outcomes than affluent people after myocardial infarction. The Editors For many decades (1, 2) and across multiple nations (3-6), differences in socioeconomic status have been consistently associated with variations in cardiovascular disease and mortality rates (6, 7). This wealthhealth gradient (8) is independent of the socioeconomic indicator used (9), persists even after such cardiovascular events as acute myocardial infarction (MI) (10), and has been observed in countries with publicly funded universal health care (10-13). The causes of these incomeoutcome gradients are debatable (14-17). Poorer patients are more likely to smoke or have diabetes and hypertension, all of which lead to accelerated atherosclerosis and higher subsequent mortality rates (18, 19). However, incomeoutcome gradients persist after adjustment for cardiovascular events and traditional cardiac risk factors. These residual effects of income or education have led to speculation about differences in behaviors after MI, psychosocial stressors, and variations in access to medical care (10, 20-24). Although the mechanisms whereby psychosocial factors affect cardiovascular health are still incompletely delineated, ordinary risk factors (such as cigarette use) and health service intensity are potentially modifiable among the poor and those with less education. Therefore, our study focused on delineating the extent to which the association between socioeconomic factors and increased mortality rates can be explained by traditional risk factors and variations in service use. We hypothesized that cardiovascular risk factors remain the central intermediary pathway by which socioeconomic status is linked to increased mortality rates. We tested this hypothesis by using a cohort of patients who were hospitalized after an acute MI. By evaluating medium- term all-cause mortality in this sample, we increased the likelihood that death would be the result of a vascular event and reduced the risk for confounding by other causes of death (25). We aggregated traditional risk factors with previous vascular disease to obtain a powerful proxy for cumulative atherosclerotic burden, thereby enabling us to focus on assessing the incremental prognostic effect of socioeconomic status. Methods Data Source We obtained data from the Socio-Economic and Acute Myocardial Infarction (SESAMI) study, a prospective observational study of patients who were hospitalized because of acute MI throughout Ontario, Canada (19, 24). Of these data, we included a 13-item patient-completed questionnaire that addressed risk factors for atherosclerosis and socioeconomic status. By using encrypted health card numbers, we linked survey data to administrative databases for additional clinical information. We tracked each patients hospitalization history by using computerized abstracts that were assembled by the Canadian Institute for Health Information from 1 April 1988 to the date of the patients admission for the index event. We ascertained the number and types of cardiac procedures performed during and following the index admission by using the institutes data and physician billing claims from the Ontario Health Insurance Plan databases (10, 24). Procedure use reported in administrative databases was compared with patient self-reports; agreement levels ranged from 74% (coronary angiography) to 98% (coronary artery bypass surgery) and were similar across socioeconomic strata (24). We calculated patient deaths by acquiring data from the Ontario Registered Persons Data Base. Study Sample The SESAMI investigators recruited English-speaking patients who were admitted through the emergency departments in 53 of 57 large-volume (defined as having 100 or more patient admissions for MI per year) Ontario hospitals between 1 December 1999 and 26 February 2003. Trained nurses identified eligible patients through chart surveillance while patients were hospitalized in coronary or intensive care units. The diagnosis of MI was confirmed if at least 2 of 3 criteria were met: presence of symptoms, abnormal electrocardiographic findings, or elevated serum levels of cardiac enzymes. Of all eligible patients, 96% had acute MI confirmed by chart audits (19). We excluded patients younger than 19 years of age or older than 101 years of age, those lacking a valid health card number issued by the province of Ontario, and those who were transferred to the recruiting hospital. To be eligible, patients were required to complete a self-administered baseline survey at study entry. This requirement rendered ineligible those dying within 24 hours, those who had very severe illness (for example, patients receiving mechanical ventilation), those who had language barriers, or those undergoing early discharge or transfer (19, 24). Among 4668 consecutive eligible patients approached for consent, 3504 agreed to participate in baseline surveys and subsequent data linkage. For purposes of this study, 97 patients could not be linked to administrative data because of invalid or inaccurately documented health card numbers; 3407 patients remained available for participation. Socioeconomic Status, Ethnicity, and Demographic Factors We assessed self-reported household annual income (from all sources) as a 7-level categorical variable ranging from less than

A population-based nested case-control study of the costs of hip and knee replacement surgery.

15000 to greater than

Cognitive And Attitudinal Impact Of The Advanced Trauma Life Support Program In A Developing Country

80000 Canadian. Self-reported educational attainment was analyzed as a 5-level categorical variable ranging from an incomplete high school education to a university degree. Income and education levels were self-reported by 92% and 98% of participants, respectively. To mitigate the confounding effect of retirement from the labor force, the cohort was stratified into persons younger than 65 years of age and those 65 years of age and older (12, 26). To ensure similar sample sizes across socioeconomic subgroups, we reaggregated income categories into a 3-level ordinal variable for each age group. For the younger age group, income categories were less than

Differential thermal effects on the energy distribution between photosystem II and photosystem I in thylakoid membranes of a psychrophilic and a mesophilic alga.

30000,

Is attrition of advanced trauma life support acquired skills affected by trauma patient volume

30000 to

Determinants of on-scene time in injured patients treated by physicians at the site.

59999, and at least

A prospective population-based study of the predictors of undergoing total joint arthroplasty

60000 Canadian; for the older age group, the categories were less than

An Early Labor Assessment Program: A Randomized, Controlled Trial

20000,