Browsing by Author "Pereira-Macedo, Juliana"
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- Contralateral carotid stenosis is a predictor of long-term adverse events in carotid endarterectomyPublication . Moreira, Rita; Duarte-Gamas, Luís; Pereira-Macedo, Juliana; Pereira-Neves, António; Domingues-Monteiro, Diogo; Jácome, Filipa; Andrade, José P.; Marreiros, Ana; Rocha-Neves, JoãoContralateral carotid stenosis (cICS) has been described as a perioperative predictor of mortality after carotid endarterectomy (CEA). However, its predictive value on long-term cardiovascular events remains controversial. The study aims to assess the potential role of cICS as a long-term predictor of major adverse cardiovascular events (MACE) in patients who underwent CEA. From January 2012 to July 2020, patients undergoing CEA under regional anesthesia for carotid stenosis in a tertiary care and referral center were eligible from a prospective database, and a post hoc analysis was performed. The primary outcome consisted in the occurrence of long-term MACE. Secondary outcomes included all-cause mortality, stroke, myocardial infarction, acute heart failure, and major adverse limb events. A total of 192 patients were enrolled. With a median 50 months follow-up, chronic kidney disease (CKD) (mean survival time (MST) 51.7 vs. 103.3, P < 0.010) and peripheral artery disease (PAD) (MST 75.1 vs. 90.3, P = 0.001) were associated with decreased survival time. After propensity score matching (PSM), CKD (MST 49.1 vs. 106.0, P = 0.001) and PAD (MST 75.7 vs. 94.0, P = 0.001) maintained this association. On multivariate Cox regression analysis, contralateral stenosis was associated with higher MACE (hazard ratio (HR) = 2.035; 95% CI: 1.113-3.722, P = 0.021 and all-cause mortality (HR = 2.564; 95% CI: 1.276-5,152 P = 0.008). After PSM, only all-cause mortality (HR 2.323; 95% CI: 0.993-5.431, P = 0.052) maintained a significant association with cICS. On multivariable analysis, cICS (aHR 2.367; 95% CI: 1.174-4.771, P = 0.016), age (aHR 1.039, 95% CI: 1.008-1.070), CKD (aHR 2.803; 95% CI: 1.409-5.575, P = 0.003) and PAD (aHR 3.225, 95% CI: 1.695-6.137, P < 0.001) were independently associated with increased all-cause mortality. Contrary to MACE, cICS is a strong predictor of long-term all-cause mortality after CEA. However, MACE risk may compromise CEA benefits by other competitive events. Therefore, further studies are needed to establish the role of cICS on postoperative events and on patients' specific assessments in order to determine the best medical treatment and easy access to surgical intervention.
- R2CHA2DS2-VA predictsthe cardiovascular risk after carotid endarterectomyPublication . Quesado, João; Dias, Lara; Pereira-Macedo, Juliana; Duarte-Gamas, Luís; Khairy, Ahmed; Pinheiro, Marina; Reis, Pedro; Andrade, José P.; Rocha-Neves, João; Marreiros, AnaBackground: R2CHA2DS2-VA score has been used to predict short and long-term outcomes in many cardiovascular diseases. This study aims to validate the R2CHA2DS2-VA score as a long-term major adverse cardiovascular events (MACE) predictor after carotid endarterectomy (CEA). Secondary outcomes were also assessed regarding the incidence of all-cause mortality, acute myocardial infarction (AMI), major adverse limb events (MALE), and acute heart failure (AHF).Methods: From January 2012 to December 2021, patients (n 1/4 205) from a Portuguese tertiary care and referral center that underwent CEA with regional anesthesia (RA) for carotid stenosis (CS) were selected from a previously collected prospective database, and a posthoc analysis was performed. Demographics and comorbidities were registered. Clinical adverse events were assessed 30 days after the procedure and in the subsequent long-term surveillance period. Statistical analysis was performed by the Kaplan-Meier method and Cox proportional hazards regression.Results: Of the patients enrolled, 78.5% were males with a mean age of 70.44 & PLUSMN; 8.9 years. Higher scores of R2CHA2DS2-VA were associated with long-term MACE (adjusted hazard ratio (aHR) 1.390; 95% confidence interval (CI) 1.173-1.647); and mortality (aHR 1.295; 95% CI 1.08-1.545). Conclusions: This study demonstrated the potential of the R2CHA2DS2-VA score to predict long-term outcomes, such as AMI, AHF, MACE, and all-cause mortality, in a population of pa-tients submitted to carotid endarterectomy.
- The Gupta perioperative risk for myocardial infarct or cardiac arrest (MICA) calculator as an intraoperative neurologic deficit predictor in carotid endarterectomyPublication . Pereira-Macedo, Juliana; Fernandes, Beatriz; Duarte-Gamas, Luís; Pereira-Neves, António; Mourão, Joana; Khairy, Ahmed; Andrade, José Paulo; Marreiros, Ana; Rocha-Neves, JoãoBackground: Patients undergoing carotid endarterectomy (CEA) may experiment intraoperative neurologic deficits (IND) during carotid cross-clamping. This work aimed to assess the impact of the Gupta Perioperative Myocardial Infarct or Cardiac Arrest (MICA) risk calculator in the IND. Methods: From January 2012 to April 2021, patients undergoing CEA with regional anaesthesia for carotid stenosis with IND and consecutively control operated patients without IND were selected. A regressive predictive model was created, and a receiver operating characteristic (ROC) curve was applied for comparison. A multivariable dependence analysis was conducted using a classification and regression tree (CRT) algorithm. Results: A total of 97 out of 194 included patients developed IND. Obesity showed aOR = 4.01 (95% CI: 1.66–9.67) and MICA score aOR = 1.21 (1.03–1.43). Higher contralateral stenosis showed aOR = 1.29 (1.08–1.53). The AUROC curve was 0.656. The CRT algorithm differentiated obese patients with a MICA score ≥ 8. Regarding non-obese patients, the model identified the presence of contralateral stenosis ≥ 55% with a MICA ≥ 10. Conclusion: MICA score might play an additional role in stratifying patients for IND in CEA. Obesity was determined as the best discrimination factor, followed by a score ≥ 8. A higher ipsilateral stenosis degree is suggested to have a part in avoiding procedure-related IND. Larger studies might validate the benefit of MICA score regarding the risk of IND.