[Gender differences in early reperfusion treatment after myocardial infarction]. / Diferencias de género en el tratamiento de revascularización precoz del infarto agudo de miocardio.

BACKGROUND AND OBJECTIVE: Clinical variability in myocardial infarction (MI) regarding age, comorbidities and atypical symptoms could determine gender differences in inhospital care. This study analyzes the magnitude and determinants of differences between men and women in early reperfusion therapy in people hospitalized after MI. PATIENTS AND METHOD: 2,836 patients who arrived to hospital with MI were studied (IBERICA-Basque Country study). The relative risk (RR) of receiving early reperfusion for men versus women, adjusted by age, clinical characteristics, risk factors, and pre-hospital delay was estimated. The effect decomposition methodology and the log binomial regression were applied. RESULTS: 29% of patients were women with a median age of 77 years. The RR of revascularization in men compared to women was different according to age. When factors such as hypertension diabetes, Killip III-IV at admission and atypical symptoms were taken into account, statistically significant differences between sexes were not detected at 45 years old (RR=0.91; 95% CI=0.77-1.07). However, for 64 years old and over, the RR of reperfusion was 1.24 (95% CI=1.05-1.47). Both the differences by sex and the sex-age interaction were no longer statistically significant after adjusting by pre-hospital delay. CONCLUSIONS: The delay to receive medical care in elderly women is responsible of gender differences in early reperfusion. It is necessary to analyze the reasons for treatment-seeking delay.

[Analysis with the propensity score of the association between likelihood of treatment and event of interest in observational studies. An example with myocardial reperfusion]. / Análisis de la asociación entre un tratamiento y un acontecimiento de interés en estudios observacionales utilizando la probabilidad de recibir el tratamiento (Propensity Score). Un ejemplo con la reperfusión miocárdica.

INTRODUCTION AND OBJECTIVES: Analysis of the effect of treatment in observational studies is complex due to differences between treated and nontreated patients. Calculating the probability of receiving treatment conditioned on relevant covariates (propensity score [PS]) has been proposed as a method to control for these differences. We report an application of PS to assess the association between reperfusion treatment and 28-day case fatality in patients with acute myocardial infarction (AMI). METHOD: We describe the procedure used to calculate PS for receiving reperfusion treatment, and different strategies to analyze the association between PS and case fatality with regression modeling and matching. Data were from a population-based registry of 6307 patients with AMI in Spain during 1997-98. RESULTS: The PS for reperfusion was calculated in 5622 patients. In the multivariate analysis, reperfusion was associated with lower case fatality (OR = 0.59; 95% confidence interval [95% CI]: 0.46-0.77). When PS was included as a covariate, this association became non- significant (OR = 0.76; 95% CI: 0.57-1.01). In the subgroup of matched patients with a similar PS (n = 3138), treatment was not associated with case fatality (OR = 0.95; 95% CI: 0.72-1.26). When the influence of cases with missing data on PS was controlled for, reperfusion treatment was associated with lower fatality (OR = 0.66; 95% CI: 0.55-0.80). CONCLUSIONS: Calculating propensity score is a method that controls for differences between treated and nontreated patients. This score has limitations when matching is incomplete and when data are missing. Results of the present example suggest that reperfusion treatment reduces AMI case fatality.

Análisis de la asociación entre un tratamiento y un acontecimiento de interés en estudios observacionales utilizando la probabilidad de recibir el tratamiento (Propensity Score). Un ejemplo con la reperfusión miocárdica / Analysis with the propensity score of the association between likelihood of treatment and event of interest in observational studies. An example with myocardial reperfusion

Introducción y objetivos. Determinar el efecto de un tratamiento en estudios observacionales es problemático por las diferencias existentes entre tratados y no tratados. Un método propuesto para controlar estas diferenciases calcular la probabilidad condicionada por covariables de recibir el tratamiento, Propensity Score (PS).Presentamos una aplicación de este método analizándola asociación entre reperfusión y letalidad a 28 días en pacientes con infarto agudo de miocardio (IAM).Método. Se presenta cómo calcular la PS de recibir reperfusión y las diferentes estrategias para analizar posteriormente su asociación con la letalidad mediante modelos de regresión y apareamiento. Utilizamos datos de un registro poblacional de IAM realizado en España entre1997 y 1998 que incluyó 6.307 IAM. Resultados. Se calculó la PS de reperfusión en 5.622pacientes. En el análisis multivariado la reperfusión se asoció con menor letalidad (odds ratio [OR] = 0,59; intervalo de confianza [IC] del 95%, 0,46-0,77); al ajustara demás por la PS de reperfusión esta asociación no fue significativa (OR = 0,76; IC del 95%, 0,57-1,01). En el subgrupo de pacientes apareados, tratados y no tratados con PS de reperfusión similar (n = 3.138), este tratamiento no se asoció con letalidad (OR = 0,95; IC del95%, 0,72-1,26). Controlando el impacto de los casos con datos insuficientes en la PS de reperfusión, ésta se asoció con menor letalidad (OR = 0,66; IC del 95%,0,55-0,80).Conclusiones. El cálculo de la PS es un método para controlar las diferencias entre los grupos tratado y no tratado. Tiene limitaciones cuando el apareamiento es incompleto o hay datos insuficientes en la PS calculada. Los resultados del ejemplo presentado indican que la reperfusión reduce la letalidad del IAM

Introduction and objectives. Analysis of the effect of treatment in observational studies is complex due to differences between treated and non-treated patients. Calculating the probability of receiving treatment conditioned on relevant covariates (propensity score [PS]) has been proposed as a method to control for these differences. Were port an application of PS to assess the association between reperfusion treatment and 28-day case fatality in patients with acute myocardial infarction (AMI).Method. We describe the procedure used to calculate PS for receiving reperfusion treatment, and different strategies to analyze the association between PS and case fatality with regression modeling and matching. Data were from a population-based registry of 6307 patients with AMI in Spain during 1997-98.Results. The PS for reperfusion was calculated in 5622patients. In the multivariate analysis, reperfusion was associated with lower case fatality (OR = 0.59; 95% confidence interval [95% CI]: 0.46-0.77). When PS was included as a covariate, this association became non-significant (OR = 0.76; 95% CI: 0.57-1.01). In the subgroup of matched patients with a similar PS (n = 3138),treatment was not associated with case fatality (OR =0.95; 95% CI: 0.72-1.26). When the influence of cases with missing data on PS was controlled for, reperfusion treatment was associated with lower fatality (OR = 0.66;95% CI: 0.55-0.80).Conclusions. Calculating propensity score is a method that controls for differences between treated and non-treated patients. This score has limitations when matching is incomplete and when data are missing. Results of the present example suggest that reperfusion treatment reduces AMI case fatality

Regional variability in population acute myocardial infarction cumulative incidence and mortality rates in Spain 1997 and 1998.

BACKGROUND: Myocardial infarction (MI) incidence and mortality display a high geographic variation. AIMS: The objective of the present study was to analyze MI mortality, cumulative incidence rate variability in seven regions of Spain from 1997 to 1998. METHODS AND RESULTS: Standardized methods were used to identify, find, register, and classify MI cases that were classified as definite, possible, insufficient-data MI, and non-MI. The total population of the seven monitored regions was 7,364,682 inhabitants. Of the 11,256 cases fulfilling eligibility criteria to investigate, 10,660 were selected to calculate MI rates: 6554 (61.5%) non-fatal definite MI, 1179 (11.1%) fatal definite MI, 1859 (17.4%) fatal possible MI, 1068 (10.0%) fatal cases with insufficient data. The IBERICA 25-74 years age-standardized cumulative incidence rates for men and women, were 207 (range: 175-252) and 45 (range: 36-65) per 100,000, respectively. The age-standardized mortality rates for men and women, were 73 (range: 62-94) and 20 (range: 13-29) per 100,000, respectively. Age-standardized case-fatality was 31.4 and 24.2% in men aged 25-74 and 35-64 years, respectively, and 32.7 and 27.0%, respectively, in women. CONCLUSIONS: MI cumulative incidence and mortality rates are low compared with other industrialized countries but, vary considerably among regions in a Mediterranean country like Spain.

[Hospital resources and myocardial infarction case fatality. The IBERICA study]. / Recursos hospitalarios y letalidad por infarto de miocardio. Estudio IBERICA.

INTRODUCTION AND OBJECTIVES: To determine the proportion of patients with myocardial infarction (MI) not admitted to a coronary care unit (CCU), the variables associated with admission into a CCU, and whether admission to a CCU, and the availability of coronary angiography in the same hospital, were associated with 28-day case fatality. PATIENTS AND METHOD: Population-based registry of MI in patients 25 to 74 years of age, admitted during 1996-1998. Demographic and clinical characteristics were recorded, as well as management, clinical course and survival after 28 days. Hospitals were classified according to the availability of a CCU and catheterization laboratory (advanced hospital), CCU only (intermediate hospital) or neither (basic hospital). Admission to the CCU was also recorded. RESULTS: In all, 9046 cases of MI were recorded; in 11.3% the patient was not admitted to a CCU. Age, smoking (OR=1.33; 95% CI, 1.08-1.64), non-Q MI (OR=0.62; 95% CI, 0.49-0.78) or undetermined location of MI (OR=0.34; 95% CI, 0.23-0.50), Killip 4 score on admission (OR=0.63; 95% CI, 0.40-1.00) and delay in arrival at the hospital >6 h were associated with CCU admission. Patients admitted to a CCU showed a lower case fatality in the first 24 h (4.2% vs 23.5%), which was independent of comorbidity, severity and treatment. The 24-hour survivors admitted to a basic hospital had higher case fatality (17.3% vs 7.8%) than other groups, which was related to differences in treatment. CONCLUSIONS: CCU admission is associated with a lower case fatality in the first 24 h. Admission to a basic hospital is associated with a higher 28-day case fatality even in patients who survive 24 h.