990 resultados para PULSE PRESSURE
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Abstract Introduction Several studies have shown that maximizing stroke volume (or increasing it until a plateau is reached) by volume loading during high-risk surgery may improve post-operative outcome. This goal could be achieved simply by minimizing the variation in arterial pulse pressure (ΔPP) induced by mechanical ventilation. We tested this hypothesis in a prospective, randomized, single-centre study. The primary endpoint was the length of postoperative stay in hospital. Methods Thirty-three patients undergoing high-risk surgery were randomized either to a control group (group C, n = 16) or to an intervention group (group I, n = 17). In group I, ΔPP was continuously monitored during surgery by a multiparameter bedside monitor and minimized to 10% or less by volume loading. Results Both groups were comparable in terms of demographic data, American Society of Anesthesiology score, type, and duration of surgery. During surgery, group I received more fluid than group C (4,618 ± 1,557 versus 1,694 ± 705 ml (mean ± SD), P < 0.0001), and ΔPP decreased from 22 ± 75 to 9 ± 1% (P < 0.05) in group I. The median duration of postoperative stay in hospital (7 versus 17 days, P < 0.01) was lower in group I than in group C. The number of postoperative complications per patient (1.4 ± 2.1 versus 3.9 ± 2.8, P < 0.05), as well as the median duration of mechanical ventilation (1 versus 5 days, P < 0.05) and stay in the intensive care unit (3 versus 9 days, P < 0.01) was also lower in group I. Conclusion Monitoring and minimizing ΔPP by volume loading during high-risk surgery improves postoperative outcome and decreases the length of stay in hospital. Trial registration NCT00479011
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Pulse-pressure variation (PPV) due to increased right ventricular afterload and dysfunction may misleadingly suggest volume responsiveness. We aimed to assess prediction of volume responsiveness with PPV in patients with increased pulmonary artery pressure.
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We found that pulse pressure variation (PPV) did not predict volume responsiveness in patients with increased pulmonary artery pressure. This study tests the hypothesis that PPV does not predict fluid responsiveness during an endotoxin-induced acute increase in pulmonary artery pressure and right ventricular loading.
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We assessed changes in intravascular volume monitored by difference in pulse pressure (dPP%) after stepwise hemorrhage in an experimental pig model. Six pigs (23-25 kg) were anesthetized (isoflurane 1.5 vol%) and mechanically ventilated to keep end-tidal CO2 (etCO2) at 35 mmHg. A PA-catheter and an arterial catheter were placed via femoral access. During and after surgery, animals received lactated Ringer's solution as long as they were considered volume responders (dPP>13%). Then animals were allowed to stabilize from the induction of anesthesia and insertion of catheters for 30 min. After stabilization, baseline measurements were taken. Five percent of blood volume was withdrawn, followed by another 5%, and then in 10%-increments until death from exsanguination occurred. After withdrawal of 5% of blood volume, all pigs were considered volume responders (dPP>13%); dPP rose significantly from 6.1+/-3.3% to 19.4+/-4.2%. The regression analysis of stepwise hemorrhage revealed a linear relation between blood loss (hemorrhage in %) and dPP (y=0.99*x+14; R2=0.7764; P<.0001). In addition, dPP was the only parameter that changed significantly between baseline and a blood loss of 5% (P<0.01), whereas cardiac output, stroke volume, heart rate, MAP, central venous pressure, pulmonary artery occlusion pressure, and systemic vascular resistance, respectively, remained unchanged. We conclude that in an experimental hypovolemic pig model, dPP correlates well with blood loss.
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Objective. The information derived from central venous catheters is underused. We developed an EKG-R synchronization and averaging system to obtained distinct CVP waveforms and analyzed components of these. Methods. Twenty-five paralyzed surgical patients undergoing CVP monitoring under mechanical ventilation were studied. CVP and EKG signals were analyzed employing our system, the mean CVP and CVP at end-diastole during expiration were compared, and CVP waveform components were measured using this system. Results. CVP waveforms were clearly visualized in all patients. They showed the a peak to be 1.8+/- 0.7 mmHg, which was the highest of three peaks, and the x trough to be lower than the y trough (-1.6+/- 0.7mmHgand-0.9+/- 0.5mmHg, respectively), withameanpulsepressureof3.4mmHg.ThedifferencebetweenthemeanCVPandCVPatend-diastoleduringexpirationwas0.58+/- 0.81 mmHg. Conclusions. The mean CVP can be used as an index of right ventricular preload in patients under mechanical ventilation with regular sinus rhythm. Our newly developed system is useful for clinical monitoring and for education in circulatory physiology.
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BACKGROUND: Difference in pulse pressure (dPP) reliably predicts fluid responsiveness in patients. We have developed a respiratory variation (RV) monitoring device (RV monitor), which continuously records both airway pressure and arterial blood pressure (ABP). We compared the RV monitor measurements with manual dPP measurements. METHODS: ABP and airway pressure (PAW) from 24 patients were recorded. Data were fed to the RV monitor to calculate dPP and systolic pressure variation in two different ways: (a) considering both ABP and PAW (RV algorithm) and (b) ABP only (RV(slim) algorithm). Additionally, ABP and PAW were recorded intraoperatively in 10-min intervals for later calculation of dPP by manual assessment. Interobserver variability was determined. Manual dPP assessments were used for comparison with automated measurements. To estimate the importance of the PAW signal, RV(slim) measurements were compared with RV measurements. RESULTS: For the 24 patients, 174 measurements (6-10 per patient) were recorded. Six observers assessed dPP manually in the first 8 patients (10-min interval, 53 measurements); no interobserver variability occurred using a computer-assisted method. Bland-Altman analysis showed acceptable bias and limits of agreement of the 2 automated methods compared with the manual method (RV: -0.33% +/- 8.72% and RV(slim): -1.74% +/- 7.97%). The difference between RV measurements and RV(slim) measurements is small (bias -1.05%, limits of agreement 5.67%). CONCLUSIONS: Measurements of the automated device are comparable with measurements obtained by human observers, who use a computer-assisted method. The importance of the PAW signal is questionable.
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We investigated whether a physiological marker of cardiovascular health, pulse pressure (PP), and age magnified the effect of the functional COMT Val158Met (rs4680) polymorphism on 15-years cognitive trajectories [episodic memory (EM), visuospatial ability, and semantic memory] using data from 1585 non-demented adults from the Betula study. A multiple-group latent growth curve model was specified to gauge individual differences in change, and average trends therein. The allelic variants showed negligible differences across the cognitive markers in average trends. The older portion of the sample selectively age-magnified the effects of Val158Met on EM changes, resulting in greater decline in Val compared to homozygote Met carriers. This effect was attenuated by statistical control for PP. Further, PP moderated the effects of COMT on 15-years EM trajectories, resulting in greater decline in Val carriers, even after accounting for the confounding effects of sex, education, cardiovascular diseases (diabetes, stroke, and hypertension), and chronological age, controlled for practice gains. The effect was still present after excluding individuals with a history of cardiovascular diseases. The effects of cognitive change were not moderated by any other covariates. This report underscores the importance of addressing synergistic effects in normal cognitive aging, as the addition thereof may place healthy individuals at greater risk for memory decline.
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An increase in left ventricular mass (LVM) occurs in the presence of type 2 diabetes, apparently independent of hypertension (1), but the determinants of this process are unknown. Brachial blood pressure is not representative of that at the ascending aorta (2) because the pressure wave is amplified from central to peripheral arteries. Central blood pressure is probably more clinically important since local pulsatile pressure determines adverse arterial and myocardial remodeling (3,4). Thus, an inaccurate assessment of the contribution of arterial blood pressure to LVM may occur if only brachial blood pressure is taken into consideration. In this study we sought the contribution of central blood pressure (and other interactive factors known to affect wave reflection, e.g., glycemic control and total arterial compliance) to LVM in patients with type 2 diabetes.
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Background Diabetes is a global epidemic. Cardiovascular disease (CVD) is one of the most prevalent consequences of diabetes. Nutrition is considered a modifiable risk factor for CVD, particularly for individuals with diabetes; albeit, there is little consensus on the role of carbohydrates, proteins and fats for arterial health for persons with or without diabetes. In this study, we examined the association of macronutrients with arterial pulse pressure (APP), a surrogate measure of arterial health by diabetes status and race. Methods Participants were 892 Mexican Americans (MA), 1059 Black, non-Hispanics (BNH) and 2473 White, non-Hispanics (WNH) with and without diabetes of a weighted sample from the National Nutrition and Health Examination Survey (NHANES) 2007-2008. The cross-sectional analysis was performed with IBM-SPSS version 18 with the complex sample analysis module. The two-year sample weight for the sub-sample with laboratory values was applied to reduce bias and approximate a nationally, representative sample. Arterial stiffness was assessed by arterial pulse pressure (APP). Results APP was higher for MA [B = 0.063 (95% CI 0.015 to 0.111), p = 0.013] and BNH [B = 0.044 (95% CI 0.006 to 0.082), p = 0.018] than WNH, controlling for diabetes, age, gender, body mass index (BMI), fiber intake, energy intake (Kcal) and smoking. A two-way interaction of diabetes by carbohydrate intake (grams) was inversely associated with APP [B = -1.18 (95% CI -0.178 to -0.058), p = 0.001], controlling for race, age, gender, BMI, Kcal and smoking. BNH with diabetes who consumed more mono-unsaturated fatty acids (MUFA) than WNH with diabetes had lower APP [B = -0.112 (95%CI-0.179 to -0.045), p = 0.003] adjusting for saturated fatty acids, Kcal, age, gender, BMI and smoking. Conclusion Higher MUFA and carbohydrate intake for persons with diabetes reflecting lower APP may be due to replacement of saturated fats with CHO and MUFA. The associations of APP with diabetes, race and dietary intake need to be confirmed with intervention and prospective studies. Confirmation of these results would suggest that dietary interventions for minorities with diabetes may improve arterial health.
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Background: Arterial pulse pressure, the difference between systolic and diastolic blood pressure, has been used as an indicator (surrogate measure) of arterial stiffness. High arterial pulse pressure (> 40) has been associated with increased cardiovascular disease and mortality. Several clinical trials have reported that the proportion of calories from carbohydrate has an effect on blood pressure. The primary objective of this study was to assess arterial pulse pressure and its association with carbohydrate quantity and quality (glycemic load) with diabetes status for a Cuban American population. Methods: A single point analysis included 367 participants. There was complete data for 365 (190 with and 175 without type 2 diabetes). The study was conducted in the investigator’s laboratory located in Miami, Florida. Demographic, dietary, anthropometric and laboratory data were collected. Arterial pulse pressure was calculated by the formula systolic minus the diastolic blood pressure. Glycemic load, fructose, sucrose, percent of average daily calories from carbohydrate, fat and protein, grams of fiber and micronutrient intakes were calculated from a validated food frequency questionnaire. Results: The mean arterial pulse pressure was significantly higher in participants with (52.9 ± 12.4) than without (48.6 ± 13.4) type 2 diabetes. The odds of persons with diabetes having high arterial pulse pressure (>40) was 1.85 (95% CI =1.09, 3.13); p=0.023. For persons with type 2 diabetes higher glycemic load was associated with lower arterial pulse pressure. Conclusions: Arterial pulse pressure and diet are modifiable risk factors of cardiovascular disease. Arterial pulse pressure may be associated with carbohydrate intake differently considering diabetes status. Results may be due to individuals with diabetes following dietary recommendations. The findings of this study suggest clinicians take into consideration how medical condition, ethnicity and diet are associated with arterial pulse pressure before developing a medical nutrition therapy plan in collaboration with the client.