Autore: ABC Study

Background: Microalbuminuria is associated with adverse outcomes in acute coronary syndrome (ACS) patients.
Methods: To evaluate the very long-term association between Microalbuminuria and the overall mortality and causes of death in this clinical setting, we prospectively studied 579 unselected ACS patients admitted to three hospitals. The baseline albumin-to-creatinine ratio (ACR) was measured on days 1, 3, and 7 in 24-h urine samples. Patients were followed for 22 years or until death.
Results: Virtually all patients completed follow-up; 449(78%) had died: 41% due to non-sudden cardiac death (non-SCD), 19% sudden cardiac death (SCD), 40% due to non-cardiac (non-CD) death. Using unadjusted Cox regression analysis, ACR was a significant predictor of all-cause mortality (hazard ratio [HR] 1.26;95%confidence interval [CI] 1.22–1.31; p˂0.0001) and the three causes of death (HR 1.40;95%CI 1.32–1.48; p˂0.0001), (HR 1.22;95%CI 1.12–1.32; p˂0.0001) and (HR 1.16;95%CI 1.09–1.23; p˂0.0001) for non-SCD, SCD and non-CD respectively.
Using a fully adjusted model, ACR was a significant independent predictor of all-cause mortality
(HR 1.12; 95% CI 1.08–1.16; p˂0.0001) and only non-SCD (HR 1.21; 95%CI 1.14–1.29; p˂0.0001). There was a positive interaction between ACR level and history of AMI (HR 1.15; 95%CI 1.03– 1.29; p = 0.01) and the presence of heart failure at admission (HR 1.11; 95%CI 1.01–1.24; p =0.04), and negative interaction with higher than median LVEF (HR 0.89; 95%CI 0.80–0.99; p =0.03) for all-cause mortality at the multivariable level.
Conclusion: Based on the present analysis, baseline urinary albumin excretion during ACS is a strong independent predictor of the very long-term mortality risk, chiefly due to non-sudden cardiac death.

Background: An increased risk of cancer death has been demonstrated for patients
diagnosed with acute coronary syndrome (ACS). We are investigating possible
geographic risk disparities.
Methods: This prospective study included 541 ACS patients who were admitted to
hospitals and discharged alive in three provinces of Italy’s Veneto region. The patients
were classified as residing in urban or rural areas in each province.
Results: With 3 exceptions, all patients completed the 22-year follow-up or were followed
until death. Urban (46%) and rural (54%) residents shared most of their baseline
demographic and clinical characteristics. Pre-existing malignancy was noted in 15
patients, whereas 106 patients developed cancer during the follow-up period, which
represented 6232 person-years. No difference in the cancer death risk was found
between the urban and rural areas or between southern and northern provinces
(hazard ratio [HR] 1.1; 95% confidence interval [CI] 0.7–1.7; p = 0.59 and HR 1.1; 95%
CI 0.9–1.4; p = 0.29, respectively) according to the unadjusted Cox regression analysis.
Geographic areas, however, showed a strong positive interaction, with risk increasing
from the urban to rural areas from southern to northern provinces (HR 1.9; 95% CI 1.1–
3.0; p = 0.01). The fully adjusted Cox regression and Fine-Gray competing risk regression
models provided similar results. Interestingly, these results persisted, and even
strengthened, after exclusion of the 22 patients who developed malignancy and
survived to the end of follow-up. We did not observe an urban/rural difference in nonneoplastic
death risk or a significant interaction between the geographic areas.
Conclusion: Our analysis reveals that the cancer death risk among unselected ACS
patients in Italy’s Veneto region significantly differs by geography. The northern rural area
has the highest risk. These results highlight the importance of implementing a preventive
policy based on area-specific knowledge.