Revista Española de Cardiología (English Edition) Revista Española de Cardiología (English Edition)
Rev Esp Cardiol. 2014;67:545-51 - Vol. 67 Num.07 DOI: 10.1016/j.rec.2013.11.010

Cocaine Use Disorders and Acute Myocardial Infarction, Excess Length of Hospital Stay and Overexpenditure

Miguel Gili a,b,, Gloria Ramírez a,b, Luis Béjar b, Julio López a,b, Dolores Franco c,d, José Sala e

a Unidad de Gestión Clínica de Medicina Preventiva, Vigilancia y Promoción de la Salud, Hospital Universitario Virgen Macarena, Seville, Spain
b Departamento de Medicina Preventiva y Salud Pública, Universidad de Sevilla, Seville, Spain
c Unidad de Gestión Clínica de Salud Mental, Hospital Universitario Virgen Macarena, Seville, Spain
d Departamento de Psiquiatría, Universidad de Sevilla, Seville, Spain
e Servicio de Documentación Clínica, Hospital Universitario Virgen Macarena, Seville, Spain

Refers to

The Epidemiology of Clinical and Health Effects Associated With Cocaine
Clara Gironés-Bredy, Miguel Galicia, Alberto Domínguez-Rodríguez, Guillermo Burillo-Putze
Rev Esp Cardiol. 2014;67:966-7
Full text - PDF
Is Cocaine-associated Acute Myocardial Infarction the Same as Myocardial Infarction Associated With Recent Cocaine Consumption?
Xavier Carrillo, Eduard Fernandez-Nofrerias, Oriol Rodriguez-Leor, Antoni Bayes-Genis
Rev Esp Cardiol. 2014;67:964-5
Full text - PDF

Keywords

Cocaine. Myocardial infarction. Excess length of stay. Overexpenditure.

Abstract

Introduction and objectives

To investigate the relationship between the prevalence of cocaine use disorders and acute myocardial infarction in patients aged ≥ 18 years and to estimate the influence of cocaine use disorders on mortality, excess length of stay, and overexpenditure among hospitalized patients with acute myocardial infarction.

Methods

Retrospective study of the minimum basic data set of 87 Spanish hospitals from 2008 to 2010.

Results

Among 5 575 325 admissions reviewed, there were 24 126 patients with cocaine use disorders and 79 076 cases of acute myocardial infarction. The incidence of acute myocardial infarction among patients with cocaine use disorders increased with age and reached a peak at 55 years to 64 years (P < .0001). Multivariate analysis showed that cocaine use disorders were more prevalent among patients with acute myocardial infarction independently of age, sex, other addictive disorders, and 30 other comorbidities (odds ratio = 3.0). Among patients with acute myocardial infarction, those with cocaine use disorders did not show an increase of in-hospital death, but did show excess length of hospital stay (1.5 days) and overexpenditure (382 euros).

Conclusions

Cocaine use disorders are associated with acute myocardial infarction and increase the length of hospital stay and overexpenditure among acute myocardial infarction patients. Cessation of cocaine use among these patients should be one of the primary therapeutic goals after hospital discharge.

Article

INTRODUCTION

Cocaine use has increased in the last 10 years, and this substance is now the second most frequently consumed drug in Europe after cannabis.1, 2 After the United Kingdom, Spain is the country with the highest prevalence of cocaine use among persons aged 15 years to 64 years, with 8.3% having consumed the drug at some time. Consumption is particularly high among young men (15-34 years): 5.5% during the last year and 1.9% during the last month,2 which has been attributed to its wide availability, ease of administration, increasingly lower cost, and the mistaken belief that recreational cocaine use is not dangerous.

Cocaine is the most widely used illicit drug among patients attending hospital emergency departments and drug rehabilitation centers.2, 3, 4

While cocaine use has been increasing, there has been an extraordinary rise in the number of its cardiovascular complications, such as unstable angina pectoris, acute myocardial infarction (AMI), aortic dissection, infectious endocarditis, and other entities.5, 6 A topic that has been analyzed in the last few years is the impact of cocaine use disorders (cocaine abuse and dependence) on cardiovascular diseases in persons > 50 years, since, in many developed countries, there has been an increase in older cohorts with this addiction.7, 8

To analyze the association between the prevalence of cocaine use disorders and AMI, we studied this phenomenon in patients aged ≥ 18 years admitted to a sample of 87 Spanish hospitals from 2008 to 2010 and attempted to control for other confounding and interaction variables, such as age, sex, other addictions, and a considerable number of comorbidities. Another aim of this study was to evaluate the possible influence of these disorders on mortality, excess length of hospital stay, and overexpenditure among patients hospitalized for AMI.

METHODS Sample and Participants

Multistage sampling was performed, initially based on calculating the sample size of the study nationally and for autonomous communities, adjusted to their population weights. Problems related to alcohol, smoking and other drugs were analyzed with an alpha error of 5%, a 2-tailed test, a statistical power of 90%, a control:case ratio of at least 4:1, and a more unfavorable proportion of cases in which cases were exposed and controls were not exposed, based on the available scientific evidence. The hospital selection was adjusted to the distribution of hospital groups in each autonomous community, which resulted in 87 hospitals being selected from all the autonomous communities in Spain.

Based on the written or digitalized information in the medical record, each patient's diagnoses, the external causes and the procedures applied were codified, following the ICD-9 (ninth revision of the International Classification of Diseases and Causes of Death). Specialized personnel, with solid training and experience in data recording, codified the data and introduced the information in the databases. These databases contained information on demographic characteristics, admission and discharge dates, type of admission and discharge, diagnostic codes for the main and secondary diagnoses, and external causes and procedures, classified using ICD-9 codes. These databases also included diagnosis-related groups and each hospital was classified into a group, depending on its size and complexity.9 The analysis was restricted to patients ≥ 18 years of age at the time of hospital discharge.

Variables

Cases of AMI, first episode, were defined as those in which the code appeared in the main diagnosis (codes 410.01-410.91). Cases were excluded if the code appeared in one of the secondary diagnoses, but not the main diagnosis. The ICD-9 codes were used to define cocaine use disorders as cocaine dependence (304.20-304.23) and cocaine abuse (305.60-305.63). Disorders due to cannabis, opioid, amphetamine, sedative or hypnotic, alcohol use and smoking were defined in a similar manner.

Age was quantified in years. The following comorbidities were identified: obesity, uncomplicated hypertension, complicated hypertension, arrhythmias, pulmonary circulation disorders, valvular disease, deficiency anemia, posthemorrhagic anemia, electrolyte disorders, weight loss, hypothyroidism, coagulopathy, previous AMI, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, rheumatic disease, peptic ulcer, diabetes mellitus without chronic complications, diabetes mellitus with chronic complications, hemiplegia or paraplegia, kidney disease, moderate or severe liver disease, cancer, leukemia or lymphoma, metastatic cancer, AIDS, and depression. We used the ICD-9 codes proposed by Quan et al10 for these comorbidities. The Charlson comorbidity index was also calculated for each patient.11

Data Analysis

The main aim was to calculate the association between the incidence of AMI and cocaine use disorders in patients admitted to hospital. The secondary aims were to determine mortality, length of hospital stay, and hospital costs in patients with and without cocaine use disorders who had experienced an AMI. We calculated costs by using the specific hospital costs for each diagnosis-related group stratified by hospital group and using the estimates published by the Ministry of health for 2008 to 2010.9

A univariate analysis was performed to examine the association between AMI and addictive disorders, age, sex, and comorbidities. Then, multivariate models were constructed, using unconditional logistic regression analysis to determine the association between cocaine disorders and other addictions with AMI and in-hospital death due to AMI, and controlling for the remaining variables. A multivariate analysis of covariance was performed to determine the effect of cocaine use disorders on length of hospital stay in days and on costs in patients with AMI. The data were adjusted by age, sex, addictions, hospital group, and the above-mentioned comorbidities. The analysis was performed with the STATA statistical program, version MP 12.1.

RESULTS Patient Characteristics

The characteristics of patients with and without cocaine use disorders are shown in Table 1. We identified 5 475 325 patients, of which 24 126 (0.44%) had cocaine use disorders and 79 076 (1.4%) were admitted for AMI. A total of 538 (2.2%) patients with cocaine use disorders were admitted for AMI, while 78 538 (1.4%) without these disorders were admitted.

Table 1. Characteristics of Patients With and Without Cocaine Use Disorders

Variables With CUD (n = 24 126) Without CUD (n = 5 451 199) P
Acute myocardial infarction 538 (2.2) 78 538 (1.4) < .0001
Mean age (95%CI), years 37.3 (37.2-37.5) 57.7 (57.7-57.7) < .0001
Sex
Female 5 259 (21.8) 2 970 310 (54.5) < .0001
Male 18 867 (78.2) 2 480 889 (45.5) < .0001
Tobacco use disorder 14 218 (58.9) 1 096 327 (20.1) < .0001
Alcohol use disorder 12 137 (50.3) 332 292 (6.1) < .0001
Cannabis use disorder 8 608 (35.7) 21 223 (0.4) < .0001
Opioid use disorder 7 976 (33.1) 30 315 (0.6) < .0001
Amphetamine use disorder 1 082 (4.50) 1 894 (0.03) < .0001
Sedative or hypnotic use disorder 2 373 (9.8) 7052 (0.1) < .0001
Comorbidities
Obesity 624 (2.6) 238 191 (4.4) < .0001
Uncomplicated hypertension 1 379 (5.7) 1 413 874 (25.9) < .0001
Complicated hypertension 231 (1.0) 278 510 (5.1) < .0001
Cardiac arrhythmias 648 (2.7) 685 076 (12.6) < .0001
Pulmonary circulation disorders 206 (0.9) 113 765 (2.1) < .0001
Valvular disease 321 (1.3) 253 960 (4.7) < .0001
Deficiency anemia 330 (1.4) 109 905 (2.0) < .0001
Posthemorrhagic anemia 104 (0.4) 126 289 (2.3) < .0001
Electrolyte disorders 540 (2.2) 142 295 (2.6) .0002
Weight loss 546 (2.3) 64 139 (1.2) < .0001
Hypothyroidism 227 (0.9) 170 476 (3.1) < .0001
Coagulopathy 319 (1.3) 60 595 (1.1) .0019
Previous myocardial infarction 280 (1.2) 138 280 (2.5) < .0001
Congestive heart failure 479 (2) 329 014 (6) < .0001
Peripheral vascular disease 3 (0.01) 4893 (0.09) < .0001
Cerebrovascular disease 273 (1.1) 153 620 (2.8) < .0001
Dementia 8 (0.03) 118 961 (2.20) < .0001
Chronic pulmonary disease 2 203 (9.1) 653 091 (12.0) < .0001
Rheumatic diseases 54 (0.2) 63 053 (1.2) < .0001
Peptic ulcer 160 (0.7) 41 249 (0.8) .0944
Mild liver disease 1.245 (5.2) 145 520 (2.7) < .0001
Diabetes without chronic complications 961 (4.0) 693 215 (12.7) < .0001
Diabetes with chronic complications 283 (1.2) 151 940 (2.8) < .0001
Hemiplegia or paraplegia 205 (0.8) 47 133 (0.9) .8023
Kidney disease 287 (1.2) 106 420 (2.0) < .0001
Moderate or severe liver disease 633 (2.6) 76 678 (1.4) < .0001
Cancer, leukemia or lymphoma 276 (1.1) 289 449 (5.3) < .0001
Metastatic cancer 170 (0.7) 222 425 (4.1) < .0001
AIDS 1.467 (6.1) 19 847 (0.4) < .0001
Depression 1.570 (6.5) 208 433 (3.8) < .0001
Charlson comorbidity index, media (95%CI) 0.80 (0.77-0.82) 0.93 (0.93-0.93) < .0001

95%CI, 95% confidence interval; CUD, cocaine use disorder.
Unless otherwise indicated, the data are expressed as no. (%).

Patients with cocaine use disorders were younger (mean age, 37.3 years), were mainly male (78.2%) and showed a high prevalence of addiction to all drugs, mainly tobacco (58.9%) and alcohol (50.3%), but also cannabis (35.7%), opioids (33.1%), amphetamines (4.5%), and sedatives or hypnotics (9.8%).

The mean Charlson comorbidity index score was lower in patients with cocaine use disorders, which could be explained by their mean age; in addition, in most of these patients, their rates of specific comorbidities were significantly lower–or without statistically significant differences–than those of patients without these disorders. However, patients with cocaine use disorders had a higher prevalence of weight loss, coagulopathies, mild, moderate or severe liver disease, AIDS, and depression.

A more detailed analysis of the distribution of the prevalence of cocaine use disorders by age and sex is presented in Figure 1, which shows that, in both men and women, the group with the highest prevalence of these disorders was that aged 35 years to 44 years, followed by the group < 35 years, that aged 45 years to 54 years and, finally, that aged 55 years to 64 years.

Distribution by groups and age and sex of the prevalence of cocaine use disorders among patients admitted to a sample of 87 Spanish hospitals from 2008 to 2010.

Figure 1. Distribution by groups and age and sex of the prevalence of cocaine use disorders among patients admitted to a sample of 87 Spanish hospitals from 2008 to 2010.

Association Between Cocaine and Acute Myocardial Infarction

The characteristics of patients with and without AMI are shown in Table 2. Those admitted for AMI were older (mean age, 67.7 years), were mainly male (70.8%), and showed the two most prevalent addictions: tobacco (45.7%) and cocaine (0.7%).

Table 2. Characteristics of Patients With and Without Acute Myocardial Infarction

Variables With AMI (n = 79 076) Without AMI (n = 5 396 249) P
Cocaine use disorder 538 (0.7) 23 588 (0.4) < .0001
Tobacco use disorder 36 160 (45.7) 1 074 385 (19.9) < .0001
Alcohol use disorder 4 305 (5.4) 340 124 (6.3) < .0001
Cannabis use disorder 346 (0.4) 29 485 (0.5) < .0001
Opioid use disorder 164 (0.2) 38 127 (0.7) < .0001
Amphetamine use disorder 12 (0.01) 2 964 (0.05) < .0001
Sedative or hypnotic use disorder 19 (0.02) 9406 (0.2) < .0001
Mean age (95%CI), years 67.7 (67.6-67.8) 57.5 (57.4-57.5) < .0001
Sex
Female 23 121 (29.2) 2 952 448 (54.7) < .0001
Male 55 955 (70.8) 2 443 801 (45.3) < .0001
Comorbidities
Obesity 8641 (10.9) 230 174 (4.3) < .0001
Uncomplicated hypertension 38 529 (48.7) 1 376 724 (25.5) < .0001
Complicated hypertension 7061 (8.9) 271 680 (5.0) < .0001
Cardiac arrhythmias 22 025 (27.8) 663 699 (12.3) < .0001
Pulmonary circulation disorders 1973 (2.5) 111 998 (2.1) < .0001
Valvular disease 10 563 (13.4) 243 718 (4.5) < .0001
Deficiency anemia 1669 (2.1) 108 566 (2.0) .0497
Posthemorrhagic anemia 428 (0.5) 125 965 (2.3) < .0001
Electrolyte disorders 1428 (1.8) 141 407 (2.6) < .0001
Weight loss 286 (0.4) 64 399 (1.2) < .0001
Hypothyroidism 2202 (2.8) 168 501 (3.1) < .0001
Coagulopathy 787 (1.0) 60 127 (1.1) .0015
Prior myocardial infarction 8221 (10.4) 130 339 (2.4) < .0001
Congestive heart failure 16 408 (20.7) 313 085 (5.8) < .0001
Peripheral vascular disease 10 (0.01) 4886 (0.09) < .0001
Cerebrovascular disease 3042 (3.8) 150 851 (2.8) < .0001
Dementia 1218 (1.5) 117 751 (2.2) < .0001
Chronic pulmonary disease 9087 (11.5) 646 207 (12.0) < .0001
Rheumatic diseases 870 (1.1) 62 237 (1.1) .1647
Peptic ulcer 592 (0.7) 40 817 (0.7) .8028
Mild liver disease 588 (0.7) 146 177 (2.7) < .0001
Diabetes without chronic complications 20 559 (26.0) 673 617 (12.5) < .0001
Diabetes with chronic complications 3577 (4.5) 148 646 (2.8) < .0001
Hemiplegia or paraplegia 208 (0.3) 47 130 (0.9) < .0001
Kidney disease 1759 (2.2) 104 948 (1.9) < .0001
Moderate or severe liver disease 142 (0.2) 77 169 (1.4) < .0001
Cancer, leukemia or lymphoma 1950 (2.5) 287 775 (5.3) < .0001
Metastatic cancer 412 (0.5) 222 183 (4.1) < .0001
AIDS 167 (0.2) 21 147 (0.4) < .0001
Depression 2719 (3.4) 207 284 (3.8) < .0001
Charlson comorbidity index, mean (95%CI) 0.96 (0.95-0.97) 0.93 (0.93-0.93) < .0001

95%CI, 95% confidence interval; AMI, acute myocardial infarction.
Unless otherwise indicated, the data are expressed as no. (%).

The mean Charlson score was higher among patients with AMI, mainly due to the comorbidities associated with risk of AMI: obesity, hypertension, cardiac arrhythmias, pulmonary circulation disorders, valvular disease, prior AMI, congestive heart failure, cerebrovascular disease, diabetes mellitus without chronic complications, and diabetes mellitus with chronic complications.

A more detailed analysis of the distribution of cases of AMI by groups of age and sex is presented in Figure 2, which shows that the prevalence of AMI increased with age and reached a peak in the group aged 55 years to 64 years; however, the odds ratio was significantly higher among patients with cocaine use disorders, with a significant positive tendency: the prevalence of AMI doubled among the group aged 35 years to 44 years, tripled among that aged 45 years to 54 years and quadrupled among the group aged 55 years to 64 years when compared with the reference group aged < 35 years (P for tendency < 0.0001). These analyses were limited to the population aged 18 years to 64 years, because only 3 patients aged ≥ 65 years had a cocaine use disorder and AMI.

Frequency of myocardial infarction in patients with and without cocaine use disorders by age groups. The odds ratio of each age group is shown in comparison with that in the group aged 18 years to 34 years and the <i>P</i>-value for tendency (chi-squared). 95%CI, 95% confidence interval; OR, odds ratio.

Figure 2. Frequency of myocardial infarction in patients with and without cocaine use disorders by age groups. The odds ratio of each age group is shown in comparison with that in the group aged 18 years to 34 years and the P-value for tendency (chi-squared). 95%CI, 95% confidence interval; OR, odds ratio.

The results of the multivariate analysis are shown in Table 3, which reveals that the prevalence of AMI was 3-fold higher in patients with cocaine use disorders than in those without these disorders when the analysis was adjusted by age, sex, the remaining addictions, and the 30 comorbidities listed previously. The positive tendency between age and AMI was maintained in the multivariate analysis, but the differences between odds ratios were less marked than in the univariate analysis.

Table 3. Logistic Regression Model for Hospital Admissions for Acute Myocardial Infarction in Patients aged ≥ 18 Years, 2008-2010

Risk factor aOR (95%CI) P
Age 35-44 years (vs 18-34 years) 2.08 (2.05-2.12) < .0001
Age 45-54 years (vs 18-34 years) 2.47 (2.43-2.50) < .0001
Age 55-64 years (vs 18-34 years) 2.91 (2.88-2.95) < .0001
Male sex 2.02 (1.98-2.06) < .0001
Cocaine use disorder 3.03 (2.75-3.35) < .0001
Tobacco use disorder 3.01 (2.96-3.06) < .0001
Obesity 1.91 (1.86-1.96) < .0001
Uncomplicated hypertension 1.75 (1.73-1.78) < .0001
Complicated hypertension 1.21 (1.17-1.24) < .0001
Cardiac arrhythmia cardiaca 1.31 (1.29-1.34) < .0001
Valvular disease 1.83 (1.79-1.87) < .0001
History of myocardial infarction 1.98 (1.93-2.03) < .0001
Congestive heart failure 2.48 (2.43-2.53) < .0001
Diabetes without chronic complications 1.35 (1.33-1.38) < .0001
Diabetes with chronic complications 1.12 (1.08-1.16) < .0001

95%CI, 95% confidence interval; aOR, adjusted odds ratio.

Mortality, Excess Length of Hospital Stay, and Overexpenditure

The multivariate analysis showed no association between having a cocaine use disorder and mortality among patients with AMI.

The multivariate analysis of covariance, which included age, sex, hospital group, and all the above-mentioned addictions and comorbidities, showed that, among patients with an AMI, those with cocaine use disorders had a mean excess length of hospital stay of 1.5 days (95% confidence interval, 1.4-1.6 days). Overexpendure due to hospital stay among patients with an AMI and cocaine use disorder was 382 (95% confidence interval, 298-464) euros.

DISCUSSION

Our results indicate that cocaine use disorders significantly impact the incidence of AMI, independently of age, sex, smoking, other addictions, and the 30 comorbidities studied. When the adjusted odds ratio for AMI were considered in the multivariate model, the excess incidence of AMI in patients with cocaine use disorders was 203% in comparison with patients without these disorders (odds ratio = 3.0). Among patients with an AMI, those with cocaine use disorders had more prolonged hospital stays and higher hospital costs.

There is abundant evidence in the scientific literature indicating that cocaine use disorders are an independent risk factor for AMI and other cardiovascular diseases.5, 6 Cocaine use triggers coronary failure through several mechanisms,12 stimulates the sympathetic nervous system by inhibiting catecholamine reuptake in the nerve endings and increasing their sensitivity to noradrenaline,13 promotes endothelial release of endothelin-1–a potent vasoconstrictor14, and inhibits production of nitric acid, the main vasodilator produced by endothelial cells.15 Likewise, cocaine use promotes coronary thrombosis through platelet activation,16, 17 thus favoring platelet aggregation17, 18 and increasing the activity of plasminogen activator inhibitors19 and concentrations of fibrinogen and von Willebrand factor.20

The isolated impact of cocaine use is especially marked in the youngest users, among whom the cumulative effects of cocaine do not compete with those of other addictions and the comorbidities that increase with age. Our results showed a positive association of age with the incidence of AMI, which is higher among patients with cocaine use disorders. The group aged 55 years to 64 years had the highest odds ratio, which can easily be explained by the greater number of comorbidities with age and the cumulative effect of prolonged use of cocaine and other substances. Some estimates indicate that, in the United States, the number of patients ≥ 50 years who seek treatment for their addictions will increase from 1.7 million in the year 2000 to 4.4 million in 2020.7 Similar estimates have been made in Europe, where the number of older patients seeking treatment for their addictions will double from 2001 to 2020.21 These tendencies are the result of the demographic phenomenon of the aging population in developed countries, and particularly reflect aging of the “baby-boom” generation, consisting of persons born between 1946 and 1964.7

The high prevalence of smoking, alcohol use, and other addictions in patients with cocaine use disorders is worrisome. Multiple addictions are widespread among patients with drug disorders. Simultaneous tobacco and cocaine exposure increases the risk of AMI, because smoking produces vasoconstriction of the coronary arteries through alpha-adrenergic stimulation similar to that provoked by cocaine.22 The combination of tobacco and cocaine increases heart rate, the energy used for contraction, and systemic arterial pressure, all of which increases myocardial oxygen needs and, at the same time, reduces oxygen supply due to vasoconstriction.23 Simultaneous cocaine and alcohol use produces cocaethylene, which also blocks neurotransmitter reuptake in the nerve endings and enhances the toxic systemic effects of cocaine.24, 25

Limitations

Our study has several limitations. The data used were drawn exclusively from the Minimum Basic Data Set (MBSD) and were not completed by additional data from the patients. Throughout the study, we used the definitions of addictive disorders, AMI and comorbidities as assigned the physicians in each center, which were then codified and introduced in the databases by the codifiers. Another limitation is the potential under-registration of information due to the possibility that the medical record did not contain all the data required for the codifiers to assign codes or due to variation in the codifiers’ interpretations.

The prevalence of cocaine use disorders in the hospitalized population was markedly higher in men than in women, and the group with the highest rate (3.5%) consisted of men aged 35 years to 44 years. The real prevalence is probably underestimated in hospitalized patients, given the results of several studies comparing the reported addiction rate with other objective indicators such as the prevalence of cocaine metabolites in urine. In a study by Bosch et al,26 19% of the patients did not admit to having used cocaine, even though cocaine metabolites were detected in their urine. In other studies, the proportion of patients denying cocaine use varied: 28% of the patients in a study by Hollander et al27 and 48.2% of those in a study by Lee et al.28 All these factors indicate that the present study probably underestimated the number of cases of AMI concomitant to cocaine use and that the impact of cocaine is probably considerably greater.

Databases such as the MBSD also have considerable advantages.29 Registered data is usually complete in most hospital discharges and, because these databases include practically all cases, they allow fairly accurate estimates on incidence, prevalence, comorbidities, and mortality from diseases attended in the hospital setting.30 These data can be retrospectively analyzed, unlike other designs that require prospective data collection. Data from long periods and a large number of patients, as in the present study, can be collected relatively rapidly and easily. Because the data are systematically gathered, the cost reduction is considerable. Studies based on these databases may show fewer selection biases, such as those biases that lead patients or their legal representatives to refuse to sign informed consent and participate in the study.

The results of this study are supported by several factors. We used the 410.x1 codes of the ICD-9 for AMI, first episode as the main diagnosis (excluding those that appeared as a secondary diagnosis), following the inclusion and exclusion criteria of the United States’ AHRQ (Agency for Healthcare Research and Quality) in its health care quality indicator “in-hospital mortality from acute myocardial infarction”31 to obtain maximal validity of AMI diagnosis. A study carried out and published in Spain that used the MBSD and the AHRQ criteria found that mortality from AMI was highly similar to that of patients who were followed up in observational studies such as PRIMHO, PRIMHO II, RISCI, and ARIM.32 The latter study also found that other characteristics, such as distribution by sex, mean age, and the frequency of cardiovascular risk factors, were similar, indicating that the use of the MBSD led to adequate representation of the epidemiological profile of AMI.32 The results of another study on the validity of the comorbidities of AMI in Spain, calculated from MBSD data, which also used the AHRQ inclusion and exclusion criteria, suggest that the information obtained from the MBSD is reliable and valid.33 The latter study, which analyzed in-hospital mortality from AMI from 2003 to 2009, observed that mortality was decreasing, a finding that also coincides with the tendency noted in other observational studies carried out in Spain.34, 35

The overexpenditure incurred by patients with cocaine use disorders was due to 2 factors. First, the higher number of diagnostic and therapeutic procedures and the greater number of complications in these patients, which led to their inclusion in more expensive diagnosis-related groups. Second, the excess cost was attributable to longer hospital stay.

Because of the sample size and the diversity of hospitals, our data can be generalized and are not limited to patients admitted to one or a few hospital centers. Calculation of overexpenditure was facilitated by the availability of costs for each diagnosis-related group stratified by hospital groups and by each year. To our knowledge, this is the first study that calculates the excess hospital stay and overexpenditure attributable to cocaine use disorders in patients with AMI.

One of the main therapeutic objectives after hospital discharge is cessation of cocaine use. The incidence of chest pain, AMI, and death decrease in patients who cease using cocaine.36, 37 The remaining cardiac risk factors should be modified, especially cigarette smoking,12 as well as any other addictions. Activities with demonstrated effectiveness that could prevent AMI recurrence in these patients include a brief intervention on the risks of these substances and referral to specialized rehabilitation services. Given the current economic restrictions, decreasing the number of admissions and readmissions due to cocaine would help to reduce hospital costs and increase the availability of hospital beds. Each case of AMI and of other diseases avoided or of prevented admission would also reduce the burden of the multiple problems experienced by these patients in a particularly difficult and stressful era.

CONCLUSIONS

Among patients with AMI, cocaine use disorders are associated with the incidence of AMI, excess hospital stay, and overexpenditure. Cessation of consumption of cocaine and other addictive substances should be one of the main objectives in these patients after hospital discharge.

FUNDING

This study was funded by the Delegación del Gobierno para el Plan Nacional Sobre Drogas, Ministerio de Sanidad, Servicios Sociales e Igualdad (Grant No. 009I017, Project G41825811).

CONFLICTS OF INTEREST

None declared.

Received 1 July 2013
Accepted 6 November 2013

Corresponding author: Unidad de Gestión Clínica de Medicina Preventiva, Vigilancia y Promoción de la Salud, Hospital Universitario Virgen Macarena, Avda. Dr. Fedriani s/n, 41070 Seville, Spain. mgili@us.es

Bibliography

1. Delegación del Gobierno para el Plan Nacional sobre Drogas. Plan Nacional sobre Drogas: Memoria 2010. Madrid: Ministerio de Sanidad, Servicios Sociales e Igualdad [cited 2013 Mar 10]. Available at: http://www.pnsd.msps.es/Categoria2/publica/publicaciones/home.htm.
2. Observatorio Europeo de las Drogas y las Toxicomanías. Informe anual 2010: El problema de la drogodependencia en Europa [cited 2013 Mar 10]. Available at: http://www.emcdda.europa.eu/publications/annual-report/2010.
3. Barrio Anta G, Rodríguez Arenas MA, De la Fuente de Hoz L, Royuela Morales L, Grupo de Trabajo para el Estudio de Urgencias por Psicoestimulantes. Urgencias en consumidores de cocaína en varios hospitales españoles: primeras evidencias de complicaciones agudas por consumo de crack. Med Clin (Barc). 1998;111:49-55.
Medline
4. Sanjurjo E, Montori E, Nogué S, Sánchez M, Munné P. Urgencias por cocaína: un problema emergente. Med Clin (Barc). 2006;126:616-9.
Medline
5. Lange RA, Hillis LD. Cardiovascular complications of cocaine use. N Engl J Med. 2001;345:351-8.
Medline
6. Maraj S, Figueredo VM, Morris L. Cocaine and the heart. Clin Cardiol. 2010;33:264-9.
Medline
7. Gfroerer J, Penne M, Pemberton M, Folsom R. Substance abuse treatment need among older adults in 2020: the impact of the aging baby-boom cohort. Drug Alcohol Depend. 2003;69:127-35.
Medline
8. Beynon CM. Drug use and ageing: older people do take drugs! Age Ageing. 2009;38:8-10.
9. Registro de Altas de los Hospitales Generales del Sistema Nacional de Salud. CMBD. Norma Estatal. Madrid: Ministerio de Sanidad, Servicios Sociales e Igualdad;2011 [cited 2013 Mar 10]. Available at: http://www.msc.es/estadEstudios/estadisticas/cmbd.htm.
10. Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi JC, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005;43:1130-9.
Medline
11. Charlson ME, Pompei P, Ales KL, McKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373-83.
Medline
12. Schwartz BG, Rezkalla S, Kloner RA. Cardiovascular effects of cocaine. Circulation. 2010;122:2558-69.
Medline
13. Vongpatanasin W, Mansour Y, Chavoshan B, Arbique D, Victor RG. Cocaine stimulates the human cardiovascular system via a central mechanism of action. Circulation. 1999;100:497-502.
Medline
14. Wilbert-Lampen U, Seliger C, Zilker T, Arendt RM. Cocaine increases the endothelial release of immunoreactive endothelin and its concentrations in human plasma and urine: reversal by coincubation with sigma-receptor antagonists. Circulation. 1998;98:385-90.
Medline
15. Mo W, Singh AK, Arruda JA, Dunea G. Role of nitric oxide in cocaine-induced acute hypertension. Am J Hypertens. 1998;11:708-14.
Medline
16. Kugelmass AD, Oda A, Monahan K, Cabral C, Ware JA. Activation of human platelets by cocaine. Circulation. 1993;88:876-83.
Medline
17. Heesch CM, Wilhelm CR, Ristich J, Adnane J, Bontempo FA, Wagner WR. Cocaine activates platelets and increases the formation of circulating platelet containing microaggregates in humans. Heart. 2000;83:688-95.
Medline
18. Rezkalla SH, Mazza JJ, Kloner RA, Tillema V, Chang SH. Effects of cocaine on human platelets in healthy subjects. Am J Cardiol. 1993;72:243-6.
Medline
19. Moliterno DJ, Lange RA, Gerard RD, Willard JE, Lackner C, Hillis LD. Influence of intranasal cocaine on plasma constituents associated with endogenous thrombosis and thrombolysis. Am J Med. 1994;96:492-6.
Medline
20. Siegel AJ, Mendelson JH, Sholar MB, McDonald JC, Lewandrowski KB, Lewandrowski EL, et al. Effect of cocaine usage on C-reactive protein, von Willebrand factor, and fibrinogen. Am J Cardiol. 2002;89:1133-5.
Medline
21. Consumo de sustancias en adultos mayores: un problema olvidado. Lisboa: Observatorio Europeo de las Drogas y las Toxicomanías;2008 [cited 2013 Abr 11]. Available at: http://www.emcdda.europa.eu/attachements.cfm/att_50566_ES_TDAD08001ESC_web.pdf.
22. Winniford MD, Wheelan KR, Kremers MS, Ugolini V, Van der Berg E, Jansen DE, et al. Smoking-induced coronary vasoconstriction in patients with atherosclerotic coronary artery disease: evidence for adrenergically mediated alterations in coronary artery tone. Circulation. 1986;73:662-7.
Medline
23. Moliterno DJ, Willard JE, Lange RA, Negus BH, Boehrer JD, Glamman DB, et al. Coronary-artery vasoconstriction induced by cocaine, cigarette smoking, or both. N Engl J Med. 1994;330:454-9.
Medline
24. Hearn WL, Flynn DD, Hime GW, Rose S, Coffino JC, Mantero-Atienza E, et al. Cocaethylene: a unique cocaine metabolite displays high affinity for the dopamine transporter. J Neurochem. 1991;56:698-701.
Medline
25. Wilson LD, Jeromin J, Garvey L, Dorbandt A. Cocaine, ethanol, and cocaethylene cardiotoxity in an animal model of cocaine and ethanol abuse. Acad Emerg Med. 2001;8:211-22.
Medline
26. Bosch X, Loma-Osorio P, Guasch E, Nogué S, Ortiz JT, Sánchez M. Prevalencia, características clínicas y riesgo de infarto de miocardio en pacientes con dolor torácico y consumo de cocaína. Rev Esp Cardiol. 2010;63:1028-34.
Medline
27. Hollander JE, Todd KH, Green G, Heilpern KL, Karras DJ, Singer AJ, et al. Chest pain associated with cocaine: An assessment of prevalence in suburban and urban emergency departments. Ann Emerg Med. 1995;26:671-6.
Medline
28. Lee MO, Vivier PM, Diercks DB. Is the self-report of recent cocaine or metamphetamine use reliable in illicit stimulant drug users who present to the emergency department with chest pain?. J Emerg Med. 2009;37:237-41.
Medline
29. Powell AE, Davies HTO, Thomson RG. Using routine comparative data to assess the quality of healthcare: understanding and avoiding common pitfalls. Qual Saf Health Care. 2003;12:122-8.
Medline
30. Needham DM, Scales DC, Lapaucis A, Pronovost PJ. A systematic review of the Charlson comorbidity index using Canadian administrative databases: a perspective on risk adjustment in critical care research. J Crit Care. 2005;20:12-9.
Medline
31. AHRQ Quality Indicators. Inpatient Quality Indicators: Technical Specifications. Rockville: Department of Health and Human Services, Agency for Healthcare Research and Quality;2012 [cited 2013 Abr 12]. Available at: http://www.qualityindicators.ahrq.gov.
32. Sendra JM, Sarría-Santamera A, Íñigo J, Regidor E. Factores asociados a la mortalidad intrahospitalaria del infarto de miocardio. Resultados de un estudio observacional. Med Clin (Barc). 2005;125:641-6.
Medline
33. Gili M, Sala J, López J, Carrión A, Béjar L, Moreno J, et al. Impacto de las comorbilidades en la mortalidad hospitalaria por infarto agudo de miocardio durante el periodo 2003-2009. Rev Esp Cardiol. 2011;64:1130-7.
Medline
34. Orozco-Beltran D, Cooper RS, Gil-Guillen V, Bertomeu-Martinez V, Pita-Fernandez S, Durazo-Arvizu R, et al. Tendencias en mortalidad por infarto de miocardio. Estudio comparativo entre España y Estados Unidos: 1990-2006. Rev Esp Cardiol. 2012;65:1079-85.
Medline
35. Dégano IR, Elosua R, Marrugat J. Epidemiología del síndrome coronario agudo en España: estimación del número de casos y la tendencia de 2005 a 2049. Rev Esp Cardiol. 2013;66:472-81.
Medline
36. Hollander JE, Hoffman RS, Gennis P, Fairweather P, Feldman JA, Fish SS, et al. Cocaine-associated chest pain: one-year follow-up. Acad Emerg Med. 1995;2:179-84.
Medline
37. Weber JE, Shofer FS, Larkin GL, Kalaria AS, Hollander JE. Validation of a brief observation period for patients with cocaine-associated chest pain. N Engl J Med. 2003;348:510-7.
Medline

1885-5857/© 2014 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved

Cookies
x
To improve our services and products, we use cookies (own or third parties authorized) to show advertising related to client preferences through the analyses of navigation customer behavior. Continuing navigation will be considered as acceptance of this use. You can change the settings or obtain more information by clicking here.
Cookies policy
x
To improve our services and products, we use cookies (own or third parties authorized) to show advertising related to client preferences through the analyses of navigation customer behavior. Continuing navigation will be considered as acceptance of this use. You can change the settings or obtain more information by clicking here.