The introduction of the article talks about accurate measurements for determining cardiac indices (CI) usually obtained while patients are in bed, in supine position. The authors suggest that accurate measurement for determining the cardiac index while patients are seated in a chair are not possible as this position caused a change in the direction and pattern of blood flow (Rader et al., 2011). The authors go on to say that no investigators have compared the calculated cardiac index values obtained while patients sit in a chair and those measurements taken while in supine position. The authors also confirm that currently no data presents accurate measurement obtained with patients seated in bedside chairs. They say that clinicians must put the patient back in bed before any measurements can be obtained because taking the measurements with the patients seated results. The introduction of this article does give a message of the importance of the problem.
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Statement of Problem
According to the authors, the purpose of this study “ is to determine if CI values based on measurements obtained in a bedside chair are similar to those based on measurements obtained in bed in cardiac surgical patients in stable condition,” ( Rader et al., 2011) The problem is clearly stated in the article and is feasible for research. The problem has a significant impact in nursing and its solution may lead to improved patient care. While the authors do a good job of stating the importance of the problem, it would be necessary for the authors to provide mention of the fact that a number of patients are affected by delay in obtained measurements while conducting the assessment with them seated in a chair.
The research question is clear and its aim is to compare CI values obtained on two different positions that is, supine in bed and sitting in a bedside chair. The authors indicate the target population as patients who undergo cardiac surgery and in an 18 bed cardiovascular intensive care unit at a 546-bed community-based hospital (Rader et al., 2011). The study design is clearly stated in the article. The patients are allotted computer-generated numbers and the researchers were not informed of the patient group allocation until the patients confirmed enrollment in the project. The type of research design is a method-comparison design and was clearly stated in the article.
Review of Literature
The literature review that is done by the authors is brief but comprehensive. The researchers in the article point out the limitations of previous studies on the same topic. According to the article, previous studies only addressed the effect of accuracy of CI values between head of the bed elevation and side lying position. The results illustrate that the variation in CI values is statistically significant especially in regards to the mixed results in different studies (Rader et al., 2011). Therefore, the investigators recommended that the side-lying position should not be used when picking measurements for determination of CI (Rader et al., 2011). The authors explain why their research is important since their study is the first to address the accuracy of measurements for determining CI values obtained with patient in supine position and sitting in a bedside chair, and how it can be used to positively grow the nursing practice. The reference list itself is adequate. However some of the articles used are outdated. This study was published in 2011 and several of the articles were dated as far back as 1984.
The research is carried out in an 18-bed cardiovascular intensive care unit at an American community medical facility. There is no clear hypothesis stated in the article. However, there are statements made by authors that could be regarded as the hypothesis. A good example is, “one could hypothesize that measurements of cardiac output for calculation of CI obtained with patients sitting in beside chairs could be inaccurate” (Rader et al., 2011). It would have been easier to know what the hypothesis early is in order to understand the methodology.
The investigations utilized the method comparison design to provide a comparison of CI values measurements obtained in different positions (Rader et al., 2011). These positions are supine in bed and sitting in a chair. This is a self-control clinical trial as the subjects served as their own controls and compare at different points in time. The authors do not state the hypothesis for guiding the study. However, the authors did mention that the dependent variable was the CI value. Patient treatment order was done by using a computer to generate random number sequences (Rader et al., 2011). The researchers do not know the group assignments until the patients were registered in the study (Rader et al., 2011). Patients are selected to either go in the chair first then in bed or in bed first then in chair in order to obtain measurements for CI value and calculation. This type of study design is very common for non-probability sampling.
The authors selected individuals that are currently in-patient in an 18 bed cardiovascular intensive care unit. The type of sampling was non-probability. The sample was not randomized which made it non-probability. The authors do not state why they chose the specific facility, and therefore I am speculating that it could also be a form of convenience sampling. Convenience sampling entails using the most conveniently available people as study participants; in this case they used one facility to sample. The study includes patients who had had coronary artery bypass surgery, valve surgery, repair of thoracic aortic repair and ventricular septal defect repair,” (Rader et al., 2011). The inclusion criteria are clearly stated in the article. The subjects are able to transfer to a chair with pulmonary artery catheter in correct position and have no active titration of vasoactive drugs within 10 minutes before and during data collection,” (Rader et al., 2011). There is an identified exclusion criterion. It appears the exclusion criteria includes medical contraindication to getting out of bed, mechanical ventilation; unstable hemodynamic status which the authors did explain what that mean.
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The authors do not explain what medical contraindication to getting out of bed entails. Twenty seven patients participated in the study. Since this is not a pilot study the sample size do not meet the central-limit theorem (Rader et al., 2011). The authors did provide justification for the sample size. This was reflected in the statement that, “the sample size was based on a priori power analysis for the F test and calculation were based on data from a previous study on the CI values”. However they do not state that a larger study sample would be needed to verify the findings in a future study. The operational definitions of the variables in-bed position, chair position and cardiac index are stated clearly in the article and are adequate enough to permit a replication in all important respects by another researcher.
The study procedure is adequate and the data gathering procedures are explained. The measurement has been described in detail and appeared adequate.
The authors use descriptive statistics to summarized data. They utilize a study of variance to determine whether the dependent variable (CI) values change according to position and/or order of positioning (Rader et al., 2011). Analysis of variance is a procedure that determines whether any differences exist among variable in two or more groups and the F test is usually used in analysis of variable. Using the estimation of variance to identify the CI value for different positions was appropriate for this particular study (Rader et al., 2011).
The article includesone table and one figure. The table shows the demographic data for 27 postoperative cardiac surgery patient of with cardiac index determined with subject in two positions. The patient characteristic was similar during data collection. The table is easy to read and appears to be accurate. The authors presented a figure using the Bland-Altaman illustration which shows the different scores CI measurements in the two different positions and the average of the different scores (Rader et al., 2011). The figure shows 95% of the CI measurement lie between the mean and + 2 standard deviation. The study shows only one of twenty seven patients had an absolute difference of 0.50 or more. The CI values did not show significant differences in the results obtained in the two different positions (that is, p=.51 and in different treatment orders with p=.29).
The authors state that their research proves that there is statistically insignificant between CI values measurement obtained in chair and in bed. The authors also state putting cardiac surgical patient back in bed to obtained measurement for CI values is not required when the patient condition is stable. They do say their work does not support previous research studies because their results show statistically insignificant between CI values in two different positions. The clinical significance of this study suggests that postoperative cardiac surgical patient in stable condition does not required going back in bed to obtain measurement of cardiac output in determine of CI if they were up in a chair.
The authors listed several weaknesses in their study. These include only using thermodilution technique and not using continuous cardiac output method for determining CI values, the study only limits the investigations to postoperative cardiac surgical with stable hemodynamic. The authors also point out that all the CI values in the study were normal values and not able to compare patients with abnormal low or high CI states. The authors say that their results need to be confirmed with different populations of patients. The authors do list recommendations for future research of the chair position with patient on mechanical ventilation and also patient on continuous cardiac output method for determining CI values.
The conclusions that the authors draw are appropriate for the study that was conducted. The authors recommend using a larger sample size in the conclusions. According to the evidence presented, the smaller sample size decreases the power analysis of the study. Smaller sample sizes can give slightly inaccurate conclusions in comparison to larger sample sizes (Rader et al., 2011). The study is not randomized which allows for possible selection bias. Overall, the study provides me with valuable information and I may be able to use it for creating a larger study.
Rader, C., Nelson, M., Sobek, C., Smith, M., Garcia, R., Wright, S…., & Richards, N. M. (2011). Cardiac index based on measurements obtained in a bedside chair and in bed [Entire issue]. American Journal of Critical Care, 20(3). Web.