Nursing Case Study

Further, the relationship between $PaO_{2}$ and survival to ICU discharge was investigated. A dataset spanning 10 years (March 2004 - December 2014) was utilised for this analysis.\\

Most of the literature is made up of low quality retrospective non-randomised cohort studies with small sample sizes. Ultimately, large multi-centred, adequately powered, well-designed randomised trials are needed to establish clearer guidelines for the management of these patients.

For the present study with the same power of 80% and confidence interval of 95%, 43 patients in each group were needed to be included.

Based on National Institute of health and Clinical Excellence methodologies, early management of DFU can reduce complication, for example, preventable amputation and mortality, and can improve quality of life. The management of DFU can be improved by utilizing a multidisciplinary team,

The research methodology includes the detailed analysis of the risk of bias evaluation. In an effort to reduce this risk the authors of the research used such criteria as “method of randomization; concealed treatment allocation; blinding during pre-, peri-, and post-operative care; blinded data collection and analysis; blinded adjudication of study endpoints; and completeness of (follow-up) data” (Svircevic et al., 2011, p. 273). It should be stated that the metaregression did not show any associations “between the study outcome and factors varying over the years of execution of the individual studies or risk of bias items for any of the outcomes” (Svircevic et al., 2011, p. 276). Although, the meta-analysis does point out that there is an elevated risk for

The author’s readily acknowledge the limitations of the study, but do not seem to factor these limitations into their interpretations. In spite of the numerous limitations and failures of process, as well as the repetitive lack of statistical significance, they still conclude that the results are clinically significant, but do not provide a foundation for this conclusion.

At the end of the study the results showed some interesting results. By looking at the questionnaire mean all the patients quality of life increased from the original of 31.8 to 36.4 at the end of the treatment. Even though the scores were higher at the end of the treatment there was no significant difference in any of the groups that were studied

The limitations of this study may be limited to inaccuracies, because all responses were self-reported. A recommendation for further studies could collect data directly from the patients chart. Obtaining information directly from a patient’s chart eliminates the subjective data, and makes the information obtain more reliable and

The authors followed the intention to treat protocol very well. It was centrally randomization, allocation was concealed, and all parties were blinded at all stages. There was excellent adherence in both arms. The treatment of both groups were very similar after randomization; no follow-up visits were planned, and information about outcomes came from registers known to account for all deaths and hospital admissions. In addition, outcome measures were well defined and obtained from reliable public registers. The evaluation of these outcomes was also well conducted, using pre-specified flow charts to search for outcomes, followed by the assessment of these outcomes conducted by

The measurement of quality of life provides objective evaluations of how and how much the disease influences patients’ life and how patients cope with it. These evaluations may be used as a baseline of outcome measures and should provide framework to determine the impact of any change on patients’ quality of life after surgery.

The likelihood of implementing SDD in high-risk patients was lower according to the number of SCAI risk factors per patient, and was significantly lower in patients with 3 risk factors or greater (SCAI ≥ 3 vs, SCAI 1-2; OR [0.45. 95% IC, 0.29-0.71] p = 0.001). (Figure 3)- The reasons for hospitalization were secondary to comorbidities in 30.4% of the patients and related with the intervention in 20.3%. The other half was hospitalized because of the hour the procedure ended (25.9%) and for social causes in 23.4%.

(tal 2011) In a prospective study over five years, Cappello et al (2016), found an adjusted odds ratio of in-hospital mortality of 2.20 (95% CI 1.56-3.08, p (-- removed HTML --) 1000pg/mL. (cappello 2016)

Outcome measure is one of the three components of clinical evaluation. The use of outcome measures provides objectivity to anyone interested in the evidence of effectiveness of intervention (Corr and Siddons. 2005). Indeed, it has

In our study we found that; out of 81 patients enrolled in the study 34 patients

Because most of the studies were comparison studies with exception of one Cross-sectional one-way study to analyze their data, the researchers used two sample t-test for comparison, Linear regression test to see the relation between hemoglobin and hematocrit, Chi square test for the predicted data results, Mann–Whitney U test to compare the difference of the dependent variable, Kruskal–Wallis-one way analysis of variance, Pearson Correlation test, fisher exact test and covariance analysis (ANCOVA) (Mukhopadhyay et al., 2010; Oto et al., 2012; Peruzzi et al., 1993; Rezende et al., 2010; Riessen et al., 2015; Thomas et al., 2009; Ullman et al., 2015). For inclusion criteria, the researcher’s chose critically ill patients admitted to ICU with or without arterial or central venous catheter line, and intubated patients for more than 24 hours. However, their limitation as well as their exclusion criteria was actively bleeding patients, hemoglobin less than 7g/dl on admission, patients with cancer, chronic kidney disease, chronic anemia, or hematological disorders as these would have been confounding variables (Mukhopadhyay et al., 2010; Peruzzi et al., 1993; Rezende et al., 2010; Riessen et al., 2015).