6 resultados para Multivariate wavelet analysis
Resumo:
BACKGROUND: In ST-segment elevation myocardial infarction (STEMI) patients treated with primary angioplasty, neutrophil response and its prognostic significance are not entirely understood. METHODS: We retrospectively studied 305 consecutive and non-selected STEMI patients. They were divided into three groups according to the maximum neutrophil percentage in the first 48 hours. We compared baseline demographic characteristics, coronary disease risk factors, cardiac history, clinical presentation, therapeutics administered and clinical evolution. We then assessed survival in the three groups and determined predictors of 30-day mortality. Group 1 (G1) had a mean age of 57 +/- 14 years and showed mean neutrophilia of 73.3%, Group 2 (G2) 61 +/- 13 years and 79.9%, and Group 3 (G3) 66 +/- 13 years and 84.2%. We compared outcomes and 30-day mortality between the groups. RESULTS: Mean age rose with increased neutrophil response. There were no statistically significant baseline differences between the groups except for more smokers in Groups 1 and 2, and more patients presenting with Killip class > or = 2 and fewer with uncomplicated evolution in Group 3. During 30-day follow-up there were 19 deaths (G1=1, G2=3 and G3=15). In univariate analysis mortality predictors were age > or = 75 years, anterior STEMI, maximum creatinine kinase > or = 2500 UI/L, culprit lesion in proximal anterior descending artery, incomplete revascularization, Killip > or = 2 at presentation, and being in G3. After multivariate regression analysis independent predictors were age > or = 75 years, incomplete revascularization and being in G3. CONCLUSION: In myocardial infarction patients undergoing mechanical revascularization, an intense neutrophil response (routinely, easily and inexpensively assessed) is related to worse short-term prognosis.
Resumo:
The autonomic nervous system (ANS) is known to be an important modulator in the pathogenesis of paroxysmal atrial fibrillation (PAF). Changes in ANS control of heart rate variability (HRV) occur during orthostatism to maintain cardiovascular homeostasis. Wavelet transform has emerged as a useful tool that provides time-frequency decomposition of the signal under investigation, enabling intermittent components of transient phenomena to be analyzed. AIM: To study HRV during head-up tilt (HUT) with wavelet transform analysis in PAF patients and healthy individuals (normals). METHODS: Twenty-one patients with PAF (8 men; age 58 +/- 14 yrs) were examined and compared with 21 normals (7 men, age 48 +/- 12 yrs). After a supine resting period, all subjects underwent passive HUT (60 degrees) while in sinus rhythm. Continuous monitoring of ECG and blood pressure was carried out (Task Force Monitor, CNSystems). Acute changes in RR-intervals were assessed by wavelet analysis and low-frequency power (LF: 0.04-0.15 Hz), high-frequency power (HF: 0.15-0.60 Hz) and LF/HF (sympathovagal) were calculated for 1) the last 2 min of the supine period; 2) the 15 sec of tilting movement (TM); and 3) the 1st (TT1) and 2nd (TT2) min of HUT. Data are expressed as means +/- SEM. RESULTS: Baseline and HUT RR-intervals were similar for the two groups. Supine basal blood pressure was also similar for the two groups, with a sustained increase in PAF patients, and a decrease followed by an increase and then recovery in normals. Basal LF, HF and LF/ HF values in PAF patients were 632 +/- 162 ms2, 534 +/- 231 ms2 and 1.95 +/- 0.39 respectively, and 1058 +/- 223 ms2, 789 +/- 244 ms2 and 2.4 +/- 0.36 respectively in normals (p = NS). During TM, LF, HF and LF/HF values for PAF patients were 747 +/- 277 ms2, 387 +/- 94 ms2 and 2.9 +/- 0.6 respectively, and 1316 +/- 315 ms2, 698 +/- 148 ms2 and 2.8 +/- 0.6 respectively in normals (p < 0.05 for LF and HF). During TF1, LF, HF and LF/ HF values for PAF patients were 1243 +/- 432 ms2, 302 +/- 88 ms2 and 7.7 +/- 2.4 respectively, and 1992 +/- 398 ms2, 333 +/- 76 ms2 and 7.8 +/- 0.98 respectively for normals (p < 0.05 for LF). During TF2, LF, HF and LF/HF values for PAF patients were 871 +/- 256 ms2, 242 +/- 51 ms2 and 4.7 +/- 0.9 respectively, and 1263 +/- 335 ms2, 317 +/- 108 ms2 and 8.6 +/- 0.68 respectively for normals (p < 0.05 for LF/HF). The dynamic profile of HRV showed that LF and HF values in PAF patients did not change significantly during TM or TT2, and LF/HF did not change during TM but increased in TT1 and TT2. CONCLUSION: Patients with PAF present alterations in HRV during orthostatism, with decreased LF and HF power during TM, without significant variations during the first minutes of HUT. These findings suggest that wavelet transform analysis may provide new insights when assessing autonomic heart regulation and highlight the presence of ANS disturbances in PAF.
Resumo:
The impact of atrial dispersion of refractoriness (Disp_A) in the inducibility and maintenance of atrial fibrillation (AF) has not been fully resolved. AIM: To study the Disp_A and the vulnerability (A_Vuln) for the induction of self-limited (<60 s) and sustained episodes of AF. METHODS AND RESULTS: Forty-seven patients with paroxysmal AF (PAF): 29 patients without structural heart disease and 18 with hypertensive heart disease. Atrial effective refractory period (ERP) was assessed at five sites--right atrial appendage and low lateral right atrium, high interatrial septum, proximal and distal coronary sinus. We compared three groups: group A - AF not inducible (n=13); group B - AF inducible, self-limited (n=18); group C - AF inducible, sustained (n=16). Age, lone AF, hypertension, left atrial and left ventricular (LV) dimensions, LV systolic function, duration of AF history, atrial flutter/tachycardia, previous antiarrhythmics, and Disp_A were analysed with logistic regression to determine association with A_Vuln for AF inducibility. The ERP at different sites showed no differences among the groups. Group A had a lower Disp_A compared to group B (47+/-20 ms vs 82+/-65 ms; p=0.002), and when compared to group C (47+/-20 ms vs 80+/-55 ms; p=0.008). There was no significant difference in Disp_A between groups B and C. By means of multivariate regression analysis, the only predictor of A_Vuln was Disp_A (p=0.04). Conclusion: In patients with PAF, increased Disp_A represents an electrophysiological marker of A_Vuln. Inducibility of both self-limited and sustained episodes of AF is associated with similar values of Disp_A. These findings suggest that the maintenance of AF is influenced by additional factors.
Resumo:
OBJECTIVE:Endograft mural thrombus has been associated with stent graft or limb thrombosis after endovascular aneurysm repair (EVAR). This study aimed to identify clinical and morphologic determinants of endograft mural thrombus accumulation and its influence on thromboembolic events after EVAR. METHODS: A prospectively maintained database of patients treated by EVAR at a tertiary institution from 2000 to 2012 was analyzed. Patients treated for degenerative infrarenal abdominal aortic aneurysms and with available imaging for thrombus analysis were considered. All measurements were performed on three-dimensional center-lumen line computed tomography angiography (CTA) reconstructions. Patients with thrombus accumulation within the endograft's main body with a thickness >2 mm and an extension >25% of the main body's circumference were included in the study group and compared with a control group that included all remaining patients. Clinical and morphologic variables were assessed for association with significant thrombus accumulation within the endograft's main body by multivariate regression analysis. Estimates for freedom from thromboembolic events were obtained by Kaplan-Meier plots. RESULTS: Sixty-eight patients (16.4%) presented with endograft mural thrombus. Median follow-up time was 3.54 years (interquartile range, 1.99-5.47 years). In-graft mural thrombus was identified on 30-day CTA in 22 patients (32.4% of the study group), on 6-month CTA in 8 patients (11.8%), and on 1-year CTA in 17 patients (25%). Intraprosthetic thrombus progressively accumulated during the study period in 40 patients of the study group (55.8%). Overall, 17 patients (4.1%) presented with endograft or limb occlusions, 3 (4.4%) in the thrombus group and 14 (4.1%) in the control group (P = .89). Thirty-one patients (7.5%) received an aortouni-iliac (AUI) endograft. Two endograft occlusions were identified among AUI devices (6.5%; overall, 0.5%). None of these patients showed thrombotic deposits in the main body, nor were any outflow abnormalities identified on the immediately preceding CTA. Estimated freedom from thromboembolic events at 5 years was 95% in both groups (P = .97). Endograft thrombus accumulation was associated with >25% proximal aneurysm neck thrombus coverage at baseline (odds ratio [OR], 1.9; 95% confidence interval [CI], 1.1-3.3), neck length ≤ 15 mm (OR, 2.4; 95% CI, 1.3-4.2), proximal neck diameter ≥ 30 mm (OR, 2.4; 95% CI, 1.3-4.6), AUI (OR, 2.2; 95% CI, 1.8-5.5), or polyester-covered stent grafts (OR, 4.0; 95% CI, 2.2-7.3) and with main component "barrel-like" configuration (OR, 6.9; 95% CI, 1.7-28.3). CONCLUSIONS: Mural thrombus formation within the main body of the endograft is related to different endograft configurations, main body geometry, and device fabric but appears to have no association with the occurrence of thromboembolic events over time.
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AIMS: Device-based remote monitoring (RM) has been linked to improved clinical outcomes at short to medium-term follow-up. Whether this benefit extends to long-term follow-up is unknown. We sought to assess the effect of device-based RM on long-term clinical outcomes in recipients of implantable cardioverter-defibrillators (ICD). METHODS: We performed a retrospective cohort study of consecutive patients who underwent ICD implantation for primary prevention. RM was initiated with patient consent according to availability of RM hardware at implantation. Patients with concomitant cardiac resynchronization therapy were excluded. Data on hospitalizations, mortality and cause of death were systematically assessed using a nationwide healthcare platform. A Cox proportional hazards model was employed to estimate the effect of RM on mortality and a composite endpoint of cardiovascular mortality and hospital admission due to heart failure (HF). RESULTS: 312 patients were included with a median follow-up of 37.7months (range 1 to 146). 121 patients (38.2%) were under RM since the first outpatient visit post-ICD and 191 were in conventional follow-up. No differences were found regarding age, left ventricular ejection fraction, heart failure etiology or NYHA class at implantation. Patients under RM had higher long-term survival (hazard ratio [HR] 0.50, CI 0.27-0.93, p=0.029) and lower incidence of the composite outcome (HR 0.47, CI 0.27-0.82, p=0.008). After multivariate survival analysis, overall survival was independently associated with younger age, higher LVEF, NYHA class lower than 3 and RM. CONCLUSION: RM was independently associated with increased long-term survival and a lower incidence of a composite endpoint of hospitalization for HF or cardiovascular mortality.
Resumo:
BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.