Kidney disease (KD) in patients with acute myocardial infarction (AMI) is associated with major cardiovascular events (MACE). We sought to compare the long-term variation in KD in patients with AMI versus controls and its value as a risk factor for MACE in patients with AMI. A cohort of 300 outpatients with AMI, recruited between 2014 and 2016 in Barcelona, Spain, were compared with a control cohort matched 1:1 based on age and several risk factors for developing KD. Annual estimated glomerular filtration rate (eGFR) using MDRD-4 formula and albuminuria were collected and patients were followed up for the occurrence of MACE (death, heart failure hospitalization, AMI, or stroke). After a median follow-up of 5.3 years, the decline in eGFR was more pronounced in patients with AMI (−1.15 ml/min/1.73 m 2 / per year in patients with AMI vs −0.81 ml/min/1.73 m 2 per year in controls, p = 0.018 between the ß coefficients of both regression slopes). In patients with AMI, those with the greatest eGFR decline during follow-up had more MACE (hazard ratio [HR] for first vs fourth quartiles = 3.33, p <0.001). In multivariate analysis, after excluding patients with baseline KD, a newly diagnosed eGFR <60 ml/min/1.73 m 2 during follow-up was associated with MACE (HR = 3.21, p <0.001), as well as new onset albuminuria >30 mg/g (HR = 6.93, p <0.001) and the combination of both (HR 5.63, p <0.001). In conclusion, the decline in eGFR after AMI is more pronounced than in the general population. A longitudinal drop in eGFR and newly diagnosed albuminuria during follow-up are associated with MACE and can be useful tools to reclassify the risk profile after AMI.
Chronic kidney disease (CKD) is a known risk factor for major cardiovascular events (MACE) in the general population. In the setting of an acute myocardial infarction (AMI), it is known that baseline estimated glomerular filtration rate (eGFR), albuminuria, and in-hospital worsening renal function are all associated with worse short and long-term outcomes. The individual trend in long-term kidney function in this population has been poorly evaluated and only a few studies address the evolution of kidney function after the acute event in patients with AMI. A longitudinal assessment of 500 patients after AMI using 2 transversal cut points (1995 and 1998) in which eGFR was measured, showed that eGFR decreased over time and patients with a steeper decline in eGFR were exposed to a higher risk of MACE at 8 years, but the lack of a control group did not allow the authors to distinguish if the decline in eGFR was due to known cardiovascular risk factors or cardiorenal interaction. This study sought to compare the longitudinal trends in kidney function after AMI to a non-AMI population and to explore the association between eGFR and albuminuria with outcomes in the cohort of patients with previous AMI.
We recruited all adult outpatients who attended any of the primary cardiology clinics in Northern Barcelona from June 1, 2014 to July 31, 2016. From 5,508 patients, 484 were followed-up because of a first AMI in the previous 5 years. These patients were matched 1:1 with controls from the same cohort without ischemic heart disease based on the exact age (± 0.5 years), gender, the presence of hypertension and diabetes, and body mass index categories (<18, 18 to 25, 25 to 30, >30 kg/m 2 ), as all of them are known risk factors for CKD and may influence kidney function. Follow-up started on the day of the AMI for cases and on the same day as their matched pair for controls. Demographic variables, co-morbidities, and medication were collected retrospectively from clinical records. All patients were followed-up from digitalized clinical history until July 31, 2020, for the occurrence of AMI, heart failure hospitalization, stroke, or death, and MACE was defined as a combination of these. The individual components were assigned as considered by the treating physician at the time of admission. Follow-up was reviewed independently by 2 different general practitioners or cardiologists and then reviewed by a third physician to minimize the chances of missing events, although none of them were blinded to the patient’s CKD status.
Analytical values were retrospectively collected from electronical records. Annual values for hemoglobin, creatinine, albuminuria, and glycosylated hemoglobin were collected when available. Baseline analytical values were obtained from the first available blood sample immediately before the AMI. The samples from the acute episode were excluded. MDRD-4 formula was used to determine eGFR (ml/min/1.73 m 2 ). Kidney disease was dichotomized as present if eGFR was <60 ml/min/1.73 m 2 or albuminuria was >30 mg/g, corresponding to stages G3a or A2 according to the 2012 Kidney Disease: Improving Global Outcomes guidelines, both cutoffs defining the moderately increased risk categories. The variation between initial eGFR and its value at the end of follow-up was calculated as ∆eGFR (ml/min/1.73 m 2 ) = final eGFR − initial eGFR.
Baseline characteristics are shown as absolute numbers and frequencies for categorical variables and as a mean ± SD or median and interquartile range for continuous variables, according to normality. Normality was assessed using the Shapiro-Wilk W test, and a t test for independent samples or 2-sided Wilcoxon sign rank-sum test were used accordingly for continuous variables. For categorical variables, chi-square or Fisher’s exact test were used, as appropriate. ∆eGFR was represented graphically in a scatter plot, and to test the equality of regression coefficients (corresponding to the slopes of the linear regression models elaborated for each group), we conducted a Hausman-like test. The standardized ß coefficients for the independent predictors of ∆eGFR are shown. The analysis of the outcomes was only conducted in patients with AMI because the aim was to assess the impact of kidney function variation on outcomes in this group. To test the association between kidney disease and MACE during follow-up in patients with AMI, a backward stepwise multivariate Cox proportional hazards model including significant variables in univariate models (p values <0.10) was used, and hazard ratios (HRs) with their 95% confidence intervals (CIs) were reported. The Kaplan-Meier display with the log-rank p values was used to graphically show this association. The same analysis was conducted after excluding patients with kidney disease at baseline, to assess the impact on outcomes of newly developed kidney disease, and baseline characteristics were tested within a multivariate logistic regression as predictors for the appearance of kidney disease during follow-up. A two-tailed p value <0.05 was significant for all comparisons. All analyses were performed using Stata 15.1.
After 1:1 matching, 300 patients per group were compared and analyzed. As expected, no differences between groups were seen regarding age, sex, prevalence of hypertension or diabetes ( Table 1 ). Patients in the AMI group had less atrial fibrillation and were more frequently exposed to tobacco, received more angiotensin-converting enzyme inhibitors (ACEI) or angiotensin II receptor blockers (ARB) and insulin. No differences were observed in baseline eGFR (89.8 vs 87.8 ml/min/1.73 m 2 , p = 0.34) but patients with AMI had higher albuminuria at baseline (4.3 vs 0 mg/g, p <0.01).
| Previous AMI (n = 300) | Controls (n = 300) | p Value | |
|---|---|---|---|
| Age (years) | 63.7 ± 12.3 | 63.5 ± 12.2 | 0.88 |
| Men | 223 (74.3%) | 223 (74.3%) | 1.00 |
| BMI (kg/m 2 ) | 28.6 ± 4.2 | 29.5 ± 4.6 | 0.03 |
| Hypertension | 178 (59.3%) | 177 (59.0%) | 0.93 |
| Dyslipidemia | 156 (52.0%) | 133 (44.3%) | 0.06 |
| Diabetes mellitus | 62 (20.7%) | 58 (19.4%) | 0.70 |
| Atrial fibrillation | 7 (2.3%) | 22 (7.3%) | <0.01 |
| eGFR (ml/min/1.73 m 2 ) | 89.8 ± 24.9 | 87.8 ± 25.6 | 0.34 |
| Hemoglobin (g/100 ml) | 14.6 ± 1.6 | 14.4 ± 1.7 | 0.18 |
| LDLc (mg/100 ml) | 114 ± 44 | 120 ± 35 | 0.13 |
| HbA1c (%) | 6.5 ± 1.3 | 6.6 ± 1.5 | 0.74 |
| Albuminuria (mg/g) | 4.3 (1.9 – 9.6) | 0 (0 – 3.1) | <0.01 |
| CRP (mg/100 ml) | 1.5 ± 2.9 | 0.7 ± 0.8 | 0.03 |
| Systolic blood pressure | 133 ± 18 | 133 ± 16 | 0.76 |
| Aspirin | 275 (91.7%) | 49 (16.4%) | <0.01 |
| Second antiplatelet | 243 (81%) | 9 (3.0%) | <0.01 |
| Anticoagulation | 13 (4.3%) | 23 (7.7%) | 0.08 |
| ACEI or ARB | 224 (74.7%) | 126 (42.3%) | <0.01 |
| β-blockers | 239 (79.7%) | 60 (20.1%) | <0.01 |
| Statins | 275 (91.7%) | 91 (30.9%) | <0.01 |
| Insulin | 29 (9.7%) | 10 (3.4%) | <0.01 |
| Number of antidiabetics | 1.4 ± 0.9 | 1.1 ± 0.8 | 0.09 |
| Number of antihypertensives | 2.0 ± 0.8 | 1.7 ± 1.1 | 0.01 |
Stay updated, free articles. Join our Telegram channel
Full access? Get Clinical Tree
