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Statistical Evaluation of Research Study

Part A

1. The research question of the study is to find out the acute impact of Electronic Storm. The study will also focus on identifying the factors associated with increased morality and virtuous treatments used for treating patients that suffered from Electrical storm (Prabhu et al., 2015).

2. In order to identify the acute impact of Electronic storm, the research design of an observational study was adopted. In this observational study, the patients of electric storm that were admitted at Sree Chitra Tirunal Institute for Medical Services between 1/1/2007 and 31/12/2013 were used as a sample to conduct the observational study.

3. The alternate study design can be adopted in the current study is Comparative Research Design. In this research design, the population can be divided into two groups in order to compare the impact of intervention on two groups. In the research design adopted in the study conducted by Prabhu et al.(2013), the researcher has excluded the patients within the one week of Electronic storm.

In the comparative research design, one group can consist of the patients within one week of Electronic storm suffering. The other group will be consisting the patients after the one week of Electronic storm suffering. In this way the effectiveness of treatment and judgement can be evaluated on the patients of electronic storm within the first week of suffering in comparison to the treatment that takes place after one week. Therefore, it can be evaluated that the adoption of comparative research design can further increase the usefulness of the study and quality of the findings of the research findings.

4. a) The primary outcome of research study is Acute Outcome of treatment of patients.

b) The Acute Outcome of treatment of patients is used as a dependent variable in the analysis in the current research study.

5. a) The exposure variable is Electronic Storm in the current research study.

b) The exposure variable is utilized as an independent variable in the current research study.

Part B

1. Acute outcome in terms of morality and survival ratio has been used as a measure of association between the exposure and primary variable in order to analyse the impact of Electronic shock.

2.

50% Higher morality

Reasonably acute

14.29%

Reasonable survival


3.

A sample of 36 patients was selected in order to conduct the analysis and find out the mortality indicators. Out of 36, it was found out that 14.63% of the patients were dealing with ACS. Therefore, it could be evaluated that the ACS was one of the common triggers of Electronic Storm.

presence of ACS and Hypokkaemia in the patients suffering from Electronic Storm

The above diagram depicts the presence of ACS and Hypokkaemia in the patients suffering from Electronic Storm indicating that both ACS and Hypokkaemia can be considered as common triggers of ES. While only 21.95% of the total patients had already implanted ICD.

Mean: People with ACS/ Total People

Total People with ACS: 14.63% of n

Total People with ACS: 14.63% of 36

Total People with ACS: 5.2

Mean: 6

Standard Deviaton:

Mean = 6, s= , n= 36

4. 95% Confidence interval

CI = mean +- z(a/2,n-1)*(sd/sqrt(n))

CI =

5. The aim of the study was to evaluate the acute outcome of the Electronic storm, treatment modalities used and the factors of morality. The association between Electronic storm and morality ratio has been depicted by the author in the research study. The findings also displayed the different triggers and differences in the morality rates among the patients on the basis of different health factors. I would have not presented the data results in this manner because there are various diseases that the individuals in sample selected are dealing with. Along with this, different therapeutic methods were used with the patients in the single sample. Therefore, it may become difficult to reject or accept the hypothesis because the heterogeneous nature of the sample.

Part C

  1.  

H0: There is significant relationship between Electronic Storm and increased morality.

HA:  There does not exist significant relationship between Electronic Storm and increased morality.

  1. In statistics, Type 1 error refers to a situation in which the researcher ends up accepting false null hypothesis. Type 2 error occurs when the researcher fails to reject the null hypothesis when it is false (Lando & Mungan, 2018).
  2. The 95% confidence interval indicates the range of values in which the true mean of the population will lie. The researcher can be 95% sure that the value of the population mean will lie in between this range.
  3. p value can be used a statistical measure for accepting or rejecting the null hypothesis. If the analysis has been conducted on 95% confidence interval, then the critical value of p is equivalent to 0.05. If the value of p is less than 0.05 then it depicts a strong evidence against the null hypothesis and if p is greater than 0.05 null hypothesis gets accepted.
  4. The p value in the entire analysis conducted in the study conducted by Prabhu et al. (2015), is greater than 0.05 which depicts that the null hypothesis will be rejected. However, the study depicts this measure as a trend towards clinical significance.
  5. The rationale of this conclusion was that the paper was identifying the morality factors associated with ES. The results of the analysis indicated that most of the patients that died from ES were dealing with ACS as compared to other aetiologies. Therefore, it can be evaluated that there was significant association between ACS and morality outcome of ES.
  6. No, this conclusion is not justified because the research question of the study did not included ACS or the names of any other aetiologies (Bradley & Brand, 2016).
  7. The researchers could have reduced the magnitude of the p value by taking homogeneous group data (King, 2019). The people with similar characteristics should be placed within one sample in order to further increase the quality of the research findings.

References for Evidence-Based Medicine Assignment 

Bradley, M. T., & Brand, A. (2016). Accuracy when inferential statistics are used as measurement tools. BMC research notes9(1), 241.

King, T. W. (2019). Statistics for Bench Research. In Success in Academic Surgery: Basic Science (pp. 43-52). Springer, Cham.

Lando, H., & Mungan, M. C. (2018). The effect of type-1 error on deterrence. International review of law and economics53, 1-8.

Prabhu, M. A., Namboodiri, N., BV, S. P., Abhilash, S. P., Thajudeen, A., & Ajith, K. V. (2015). Acute outcome of treating patients admitted with electrical storm in a tertiary care centre. indian pacing and electrophysiology journal15(6), 286-290.

Remember, at the center of any academic work, lies clarity and evidence. Should you need further assistance, do look up to our Nursing Assignment Help

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