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Intravenous Fluids 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

Identify the Treatment Variable

The treatment variable in a study is the factor or condition that researchers manipulate or alter to examine its effect on the response variable. It represents the 'cause' in a cause-and-effect relation. In this study, the treatment variable is the type of intravenous fluid given to patients: balanced crystalloids or saline solutions.

02

Check for Significant Difference in Response Variable

The response variable, or the 'effect', in this study is the occurrence of major adverse kidney events within 30 days. To establish whether there is a significant difference in the response variable between the two treatment groups, we compare the P-value (0.04) with the significance level (0.05). Since the P-value is less than the significance level, it indicates profound evidence against the null hypothesis. Thus, we can say there is a significant difference in the occurrence of major adverse kidney events between the two groups.

03

Interpret the Results

The results from this study show that the patients in the balanced-crystalloids group had a lower rate of major adverse kidney events (14.3%) as compared with those in the saline group (15.4%). With the P-value (0.04) less than the significance level (0.05), the difference is statistically significant and not due to random chance. Therefore, based on this study, balanced crystalloids may be a more preferable intravenous fluid than saline for critically ill patients.

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Key Concepts

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

Treatment Variable

In clinical studies, the treatment variable is the element that researchers change or control to observe its effects on a certain outcome. In other words, it is the "cause" in a cause-and-effect relationship. In the discussed study, the treatment variable was the type of intravenous fluid administered to patients. Researchers gave patients either balanced crystalloids or saline solutions. Changing this treatment allows researchers to compare the effects and determine which fluid might lead to better health outcomes for the patients. By focusing on the treatment variable, the study aimed to see if one type of fluid was more beneficial than the other.

Response Variable

The response variable in a study is typically the "effect" observed due to alterations in the treatment variable. It helps show the outcome impacted by the treatment administered. In this particular study, the response variable was the occurrence of major adverse kidney events within 30 days of treatment.

This variable is crucial as it reflects the real impact of the treatment and provides insight into its effectiveness. By measuring this variable, researchers could determine whether there was a noticeable difference between the two groups - those receiving balanced crystalloids and those receiving saline solutions. Observing such differences aids in understanding which treatment may lead to improved health outcomes.

Significance Testing

Significance testing is a statistical method used to decide if the observed differences between groups in a study are likely due to the treatment or merely random variation. It involves comparing a calculated p-value to a pre-determined significance level, often 0.05.

In this study, the main concern was whether there was a significant difference in the occurrence of adverse kidney events. With a p-value of 0.04, which is less than the significance level of 0.05, the study findings are statistically significant. It indicates strong evidence against the null hypothesis, suggesting the difference in kidney event rates between the balanced crystalloids and saline groups is not just by chance. This statistical validation reassures researchers that the observed effect is meaningful and warrants further consideration.

Clinical Outcomes

Clinical outcomes are the endpoints of a study, reflecting the direct effect of the treatment on patients' health. They are essential in determining whether a treatment provides real-world benefits. In this research, the clinical outcomes were based on the rate of major adverse kidney events.

The lower incidence of such events in the balanced crystalloids group (14.3%) compared to the saline group (15.4%) indicates better clinical outcomes for patients receiving balanced crystalloids. The statistically significant difference confirms that choosing balanced crystalloids may lead to improved health outcomes, offering a potentially preferable option for managing critically ill patients.