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Critically ill patients are often given intravenous fluids in hospital, either in the form of balanced crystalloids or saline solutions. In a 2018 study published in The New England Journal of Medicine, researchers investigated which of these approaches resulted in better clinical outcomes. Read this excerpt from the abstract that accompanies this study and answer the following questions (Semmler et al. 2018). Methods: In a pragmatic, cluster-randomized, multiple-crossover trial conducted in five intensive care units at an academic center, we assigned 15,802 adults to receive saline or balanced crystalloids. The primary outcome was a major adverse kidney event within 30 days \(-a\) composite of death from any cause, new renal-replacement therapy, or persistent renal dysfunction. Results: Among the 7942 patients in the balanced-crystalloids group, 1139 (14.3\%) had a major adverse kidney event, as compared with 1211 of 7860 patients \((15.4 \%)\) in the saline group \((P=0.04)\). a. Identify the treatment variable. b. The response variable in this study is major adverse kidney event within 30 days. Was there a significant difference in occurrence of major adverse kidney events between the two groups? Explain. Assume a significance level of \(0.05\). c. Based on this study, do you think one type of intravenous fluid may be preferable over the other? Explain.

Step by step solution

01

Identification of Treatment Variable

A treatment variable, in the context of an experiment or a study, is a variable that is manipulated or changed in order to gauge its effect on a certain outcome. From the study details, it is clear that the treatment variable is the type of intravenous fluid given to patients, which could be either saline or balanced crystalloids.

02

Significance Test

In statistics, a significance level, denoted by \( P \), is a measure of the strength of the evidence against the null hypothesis. Generally, if \( P < 0.05 \), it is considered significant. In this scenario, the \( P \) value is mentioned as \( P = 0.04 \) which is less than 0.05. Therefore, the difference in the occurrence of major adverse kidney events between the two groups (saline group and balanced-crystalloids group) is statistically significant.

03

Interpretation

Based on the study, it was found that a lower percentage of patients (14.3%) in the balanced-crystalloids group experienced a major adverse kidney event as compared to the saline group (15.4%) and the difference was statistically significant. Therefore, it could be argued that balanced crystalloids may be preferable to saline, considering the particular outcome being measured in this study.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Treatment Variable

The term 'treatment variable' refers to the element in a clinical trial that researchers manipulate to observe its effect on subjects. It is essentially the variable that 'treats' or changes something within the experiment, to help determine the efficacy or impact of that treatment on an outcome.

In the context of the clinical trial examining the effects of intravenous fluids on critically ill patients, the treatment variable is the type of intravenous fluid administered: either saline or balanced crystalloids. Deciphering the treatment variable is crucial as it forms the basis of comparison. Understanding how to identify and measure this variable is an essential skill in clinical research and has real implications for patient care, as evidenced by this study on major adverse kidney events.

Significance Test

A significance test in clinical trial statistics is used to determine if the differences observed in the data are likely due to the treatment or intervention being tested, rather than occurring by chance.

When you read that a result is 'statistically significant,' this usually means that the probability of the observed outcome happening by chance is low (typically less than 5% or a p-value < 0.05). The p-value helps researchers to either reject or fail to reject the null hypothesis—where the null hypothesis usually suggests that there is no effect or difference.

In the mentioned clinical trial, the p-value was 0.04 when comparing the rates of major adverse kidney events between the balanced crystalloids group and the saline group. This indicates a statistically significant difference, leading to the conclusion that the type of intravenous fluid given does affect the rate of these kidney events.

Major Adverse Kidney Events

Major adverse kidney events are critical outcomes used to measure kidney function and health following clinical procedures. This composite outcome typically includes factors such as death from any cause, new renal-replacement therapy, or persistent renal dysfunction.

In clinical trial statistics, these events are often used as a response variable to gauge the safety and efficacy of medical treatments, particularly those treatments that might impact kidney health. In the study between saline and balanced crystalloids, researchers used the occurrence of major adverse kidney events within 30 days to assess the outcomes for the two types of intravenous fluids.

A composite outcome, like major adverse kidney events, is considered because it provides a more comprehensive picture of the medical intervention's impact rather than looking at single outcomes. This broad view can be more informative for health professionals assessing the risks associated with medical treatments.