lab 9 PRELAB

SAINT XAVIER UNIVERSITYSchool of Nursing and Health Sciences EXSC 275, Exercise Physiology for Sport (4) Fall 2022, Lecture: TTh 12:30p – 1:50p Labs: M 9:00a – 11:00a W 9:00a – 11:00a Name: ___________________________________ Date: _______________ Lab #9, Myocardial Work Background Exercising muscles require greater blood flow than resting muscles. One of the important factors in bringing about greater blood flow is the increase in the arterial systolic pressure. Since diastolic pressure in the normal young individual changes very little with exercise, the change in mean arterial pressure during exercise depends primarily upon the systolic blood pressure which is influenced by the cardiac output and the decreased peripheral resistance caused by vasodilation of the micro-circulation (capillaries). In comparing both rhythmic and static work in the muscles, a greater perfusion (arterial) pressure is needed to provide blood flow in the muscle involved in a static contraction. This added pressure is somewhat proportional to the intensity of the contraction. It has also been shown that myocardial oxygen consumption (MVO 2) is highly correlated to the product of heart rate and systolic blood pressure. This number, called the rate-pressure product (RPP) or double product, can be used effectively in the evaluation of a cardiac patient's response to exercise since the magnitude of this value is also related to the onset of angina pectoris caused by myocardial ischemia (Robinson, 1967). Of added interest is the effect of static exercise on this index. It has been shown that static contractions can also increase the double product disproportionately and thereby increase the demands on the heart. The extent of this increase is dependent on the relative force of the contraction as well as the duration of the event, but not to the absolute tension produced or to the bulk (mass) of the muscle activated. Myocardial oxygen consumption is equal to coronary blood flow multiplied by the arterial-venous oxygen difference. During diastole, the ventricles are receiving blood before systolic contraction. This filling phase of the cardiac cycle allows the coronary arteries to provide maximum blood flow to the heart. Additionally, this is the only phase of the cardiac cycle that allows blood to arrive at the sub-endocardium which is the most distal portion. Myocardial oxygen consumption is the most important indicator of the load on the heart. Major determinants of myocardial oxygen demand are left ventricular systolic pressure, radius, and mass, contractility, and heart rate. Although myocardial oxygen consumption is difficult to measure directly, the rate-pressure product (heart 1 rate × systolic BP) is a strong correlate of myocardial oxygen consumption and is an easy parameter to measure in ambulatory patients. Objective The purpose of the myocardial lab is to: 1. Measure the heart rate and blood pressure response to static and dynamic exercise and relate these changes to the stress upon the heart as indicated by the rate-pressure product. 2. Interpret the results of the myocardial lab. Equipment • Cycle ergometer • Stethoscope and sphygmomanometer • Hand grip dynamometer Hand-Grip Dynamometer Procedure The participant holds the dynamometer in the hand to be tested, with the arm at right angles and the elbow by the side of the body. The handle of the dynamometer is adjusted if required - the base should rest on the first metacarpal (heel of palm), while the handle should rest on middle of the four fingers. When ready the subject squeezes the dynamometer with maximum isometric effort, which is maintained for about 5 seconds. No other body movement is allowed. The participant should be strongly encouraged to give a maximum effort. Procedure 1. Adjust the seat of the ergometer to the appropriate height. Determine 35% and 70% of maximal voluntary contraction (MVC) using the handgrip dynamometer. Attach the blood pressure (BP) cuff to the upper non-dominant arm. 2. Obtain resting heart rate (HR) and systolic/diastolic blood pressure. 3. Have the participant ride at a moderate workload (1-1.5 kp/min for females and 2-2.5 kp/min for males) at a rate of 50 rpm for a period of six (6) minutes. Record HR and BP (systolic only) on alternate minutes (i.e.: 2, 4, and 6 minutes). 4. Without interruption, at the beginning of the seventh minute have the participant remove the foot from the pedal on the same side as the blood pressure is being taken and rest it on the foot support so that he/she now pedals one-legged at the same workload. Record HR and BP each minute for two (2) minutes of one-legged pedaling. 5. Now, without interruption, have the participant return to two-legged pedaling for three (3) minutes. Record HR and BP for each minute. 2 6. Next, without interruption, have the participant hold a 35% maximal voluntary contraction (MVC) on dynamometer the handgrip with the dominant hand for one (1) minute. Record the HR and BP at 30 seconds and one minute of this stage. 7. Release the grip and continue to ride for another 4 minutes while maintaining the same workload. Record HR and BP at 2 and 4 minutes. 8. Next, repeat the static contraction of step #6 using the 70% MVC on the dominant hand for one (1) minute. Record the HR and BP at 30 seconds and one minute of this stage. 9. Finally, have the participant pedal at the same workload for six (6) additional minutes. Record HR and BP at 2, 4, & 6 minutes. Calculations Compute the RPP and MVO2 for each minute according to the following formulas: • Rate pressure product: http://www.scymed.com/en/smnxph/phgjr014.htm • Myocardial oxygen consumption (mL/100gLV/min) = (0.16 x RPP) – 6.0 Statistical Analysis Analysis of Variance (ANOVA) The ANOVA test checks if the difference between the averages of two or more groups is significant, using sample data. ANOVA is usually used when there are at least three groups since for two groups, the two-tailed pooled variance t-test and the right-tailed ANOVA test have the same result. The basic ANOVA test contains only one categorical value, one-way ANOVA. For example, if you compare the performance of three schools, the categorical variable is school, and the possible values of the categorical variable are School-A, School-B, School-C. There are more complex ANOVA tests that contain two categorical variables (Two-way ANOVA calculator ), or more. When performing a one-way ANOVA test, we try to determine if the difference between the averages reflects a real difference between the groups or is due to the random noise inside each group. The F statistic represents the ratio of the variance between the groups and the variance inside the groups. Unlike many other statistic tests, the smaller the F statistic the more likely the averages are equal. Assumptions • Independent samples • Normal distribution of the analyzed population • Equal standard deviation, σ1=σ2=...=σk (the assumption is more important when the groups' sizes not similar) 3 Interpreting results The three different options for t-tests have slightly different interpretations, but they all hinge on hypothesis testing and P values. You need to select a significance threshold for your P value (often 0.05) before doing the test. While P values can be easy to misinterpret, they are the most used method to evaluate whether there is evidence of a difference between the sample of data collected and the null hypothesis. Once you have run the correct t test, look at the resulting P value. If the test result is less than your threshold, you have enough evidence to conclude that the data are significantly different. If the test result is larger or equal to your threshold, you cannot conclude that there is a difference. However, you cannot conclude that there was definitively no difference either. It's possible that a dataset with more observations would have resulted in a different conclusion. Depending on the test you run, you may see other statistics that were used to calculate the P value, including the mean difference, t-statistic, degrees of freedom, and standard error. The confidence interval and a review of your dataset is given as well on the results page. Effect size Effect size is a quantitative measure of the magnitude of the experimental effect. The larger the effect size the stronger the relationship between two variables. You can look at the effect size when comparing any two groups to see how substantially different they are. For this analysis, choose medium effect size (0.5). Significance level or alpha level The significance level, also denoted as alpha or α, is the probability of rejecting the null hypothesis when it is true. For example, a significance level of 0.05 indicates a 5% risk of concluding that a difference exists when there is no actual difference. For this analysis, the significance level will be 0.05. Outliers An outlier is an observation that lies an abnormal distance from other values in a random sample from a population. In a sense, this definition leaves it up to the analyst (or a consensus process) to decide what will be considered abnormal. For this analysis, outliers will be included. The following website will help with the statistical analysis you must run for the data. You should report calculate and report the sample size (n), mean, standard deviation, variance, and range for all metrics. Additionally, you need to discuss the data regarding the null and alternative hypotheses, p-value, T-statistic, and effect size. Rename groups one and two, females and males, respectively. https://www.statskingdom.com/index.html 4 Applications 1. Using an ANOVA, check if the difference between the averages of post-exercise only myocardial oxygen consumption from females, males, Tuesday lab section, and Thursday lab section are significant. Include the statistics to support your interpretation of the data with respect to your stated hypotheses. 2. Using an ANOVA, check if the difference between the averages of post-exercise only rate-pressure product from females, males, Tuesday lab section, and Thursday lab section are significant. Include the statistics to support your interpretation of the data with respect to your stated hypotheses. 5 References Robinson BF. Relation of Heart Rate and Systolic Blood Pressure to the Onset of Pain in Angina Pectoris. Circulation 35: 1073-1083, 1967 DOI: doi:10.1161/01.CIR.35.6.1073. Hoffman JI and Buckberg GD. The myocardial oxygen supply:demand index revisited. J Am Heart Assoc 3: e000285, 2014 DOI: 10.1161/jaha.113.000285. Yu X, Konstantinov IE, Kantoch MJ, Rebeyka IM, and Li J. Dynamic changes of myocardial oxygen consumption at pacing increased heart rate – the first observation by the continuous measurement of systemic oxygen consumption. Scandinavian Cardiovascular Journal 45: 301306, 2011 DOI: 10.3109/14017431.2011.589470. Sembulingam P and Ilango S. Rate Pressure Product as a Determinant of Physical Fitness in Normal Young Adults. IOSR Journal of Dental and Medical Sciences 14: 8-12, 2015 DOI: 10.9790/0853-14420812. Roberts HC, Denison HJ, Martin HJ, Patel HP, Syddall H, Cooper C, and Sayer AA. A review of the measurement of grip strength in clinical and epidemiological studies: towards a standardised approach. Age Ageing 40: 423-429, 2011 DOI: 10.1093/ageing/afr051. Kim TK. T test as a parametric statistic. Korean journal of anesthesiology 68: 540-546, 2015 DOI: 10.4097/kjae.2015.68.6.540. Skaik Y. The bread and butter of statistical analysis "t-test": Uses and misuses. Pakistan journal of medical sciences 31: 1558-1559, 2015 DOI: 10.12669/pjms.316.8984. Peterson SJ and Foley S. Clinician's guide to understanding effect size, α level, power, and sample size. Nutr Clin Pract, 2021 DOI: 10.1002/ncp.10674. Hazra A and Gogtay N. Biostatistics Series Module 3: Comparing Groups: Numerical Variables. Indian journal of dermatology 61: 251-260, 2016 DOI: 10.4103/0019-5154.182416. Keselman HJ, Huberty CJ, Lix LM, Olejnik S, Cribbie RA, Donahue B, Kowalchuk RK, Lowman LL, Petoskey MD, Keselman JC, and Levin JR. Statistical Practices of Educational Researchers: An Analysis of their ANOVA, MANOVA, and ANCOVA Analyses. Review of Educational Research 68: 350-386, 1998 DOI: 10.3102/00346543068003350. 6 Data Table 1 Gender Height (m) Weight (kg) Hand Grip Strength 35% 70% Rest Heart rate (bpm) Systolic/diastolic blood pressure (mmHg) 7 Data Table 2 Two-Legged Heart rate (bpm) Systolic blood pressure (mmHg) Rate-pressure product (mmHg/bpm) Myocardial oxygen consumption (mL/100gLV/min) 2 minutes 4 minutes 6 minutes One-Legged 9 minutes Two-Legged 10 minutes 11 minutes 12 minutes 8 35% maximal volumetic contraction 13 minutes 13 minutes 30 seconds Release 16 minutes 18 minutes 70% maximal volumetric contraction 19 minutes 19 minutes 30 seconds Release 22 minutes 24 minutes 26 minutes 28 minutes 9 10 Group members name: Lab title: Null hypothesis (H0): states that a population parameter (such as the mean, the standard deviation, and so on) is equal to a hypothesized value. The null hypothesis is often an initial claim that is based on previous analyses or specialized knowledge. Alternative Hypothesis (H1): states that a population parameter is smaller, greater, or different than the hypothesized value in the null hypothesis. The alternative hypothesis is what you might believe to be true or hope to prove true. Ho: Rationale: H1: Rationale: References: