| Course | NUR-7630 Biostatistics and Clinical Epidemiology |
|---|---|
| Module | Module 3 |
| Paper type | Statistical inference |
| Length | About 1,022 words, 6 pages |
| Format | APA 7 student paper |
| School | Thomas Edison State University |
| Program | Doctor of Nursing Practice |
| Updated | October 2026 |
Free sample paper for NUR 7630 Module 3
What 0.75 With an Interval of 0.64 to 0.89 Means: Reading P-Values, Confidence Intervals and Clinical Significance in an Intensive Blood Pressure Trial
Student Name
Doctor of Nursing Practice, Thomas Edison State University
NUR-7630: Biostatistics and Clinical Epidemiology
Mentor Name
Month Day, Year
What 0.75 With an Interval of 0.64 to 0.89 Means: Reading P-Values, Confidence Intervals and Clinical Significance in an Intensive Blood Pressure Trial
The Claim on the Table
At our hypertension committee meeting, a member summarized a trial as showing that intensive blood pressure control "cut cardiovascular events and deaths by a quarter, with p less than 0.001," and proposed lowering the clinic's target for all hypertensive adults to a systolic pressure below 120 millimeters of mercury. The chair asked me, as the committee's doctoral student, to test the claim against the paper. Each part of that sentence needs interpretation: the relative reduction, the p-value and the population to whom it applies.
The Trial
In SPRINT, 9,361 adults over 50 with a top number of at least 130 and raised heart risk, none with diabetes or a past stroke, were assigned either a goal under 120 or the usual goal under 140 (SPRINT Research Group, 2015). At one year, mean systolic pressure was 121.4 in the intensive group and 136.2 in the standard group. The trial was stopped early after a median of 3.26 years. The combined outcome, covering heart attacks, other acute coronary events, strokes, heart failure and cardiovascular death, struck 1.65 percent of the intensive group each year and 2.19 percent of the standard group, giving the 0.75 hazard ratio, its 0.64 to 0.89 interval and a p-value under 0.001. Deaths from every cause fell by a similar proportion.
What the P-Value Says and Does Not Say
In 2016 the American Statistical Association, through Wasserstein and Lazar (2016), issued its first formal statement on p-values, built around six principles. First, the number reports how poorly the observed data sit with a chosen model, typically a model in which the treatment does nothing. Second, it cannot tell you how likely the hypothesis is, or how likely it is that the data were a fluke. Third, a decision should never hang on whether one number falls under 0.05. Fourth, honest inference means reporting every analysis, not the favorable one. Fifth, a tiny p-value can accompany a trivial effect. Sixth, on its own the number is a weak summary of what the study shows.
For SPRINT, a figure under 0.001 says that a gap at least this wide would almost never appear if the lower target were useless. It is not a 99.9 percent certainty that intensive treatment works, and it is silent on whether the gain is worth having.
What the Confidence Interval Adds
The confidence interval is more informative. A 95 percent interval of 0.64 to 0.89 describes the range of hazard ratios compatible with the data under the model: reductions in risk from about 11 percent to 36 percent. The interval excludes 1, so no effect is not compatible with the data, and its whole range lies on the side of benefit. Amrhein et al. (2019), with more than 800 signatories, urged researchers to stop dichotomizing results as significant or not and to describe what the whole interval implies, treating values inside it as compatible with the data rather than declaring an effect present or absent at an arbitrary cutoff.
The interval's width is information too. A narrow interval says the study measured the effect precisely; a wide one says the true effect could be small or large. SPRINT's interval is moderately wide, which is why the committee should picture both the 11 percent and the 36 percent reductions when weighing the decision, rather than fixing on the middle value of 25 percent.
Relative Versus Absolute
"Cut events by a quarter" is a relative statement. In absolute terms, the event rate fell from 2.19 to 1.65 percent a year, a difference of 0.54 percentage points a year. Over the trial's median of about 3.3 years, that is roughly 1.8 fewer events per 100 people, so about 56 people would need intensive treatment for that period to prevent one primary event. A relative reduction of 25 percent sounds dramatic; one prevented event for every 56 people treated for three years is a meaningful but more modest benefit.
The committee member's phrase "deaths by a quarter" also blurred two outcomes. The 25 percent figure belongs to the combined cardiovascular outcome; deaths from any cause fell by a similar relative amount, but deaths are rarer than the combined events, so the absolute number of deaths prevented is smaller still.
| Measure | Value |
|---|---|
| Event rate, intensive | 1.65 percent per year |
| Event rate, standard | 2.19 percent per year |
| Hazard ratio (95 percent CI) | 0.75 (0.64 to 0.89) |
| Absolute difference | 0.54 percentage points per year |
| Approximate number needed to treat over 3.3 years | About 56 |
Harms and Who the Trial Applies To
Statistical significance for benefit says nothing about harm. Serious adverse events of low blood pressure, fainting, electrolyte abnormalities and acute kidney injury were more frequent in the intensive group. Nobody with diabetes, a past stroke, heart failure with symptoms or a nursing home address was enrolled, so the results say nothing about them. SPRINT's readings came from an automated cuff after five minutes of rest, often with the patient alone, a method that runs lower than a nurse's quick check; aiming for 120 on our rushed office readings would push patients lower than the trial did.
Recommendation to the Committee
The trial supports offering the lower goal to patients who look like its volunteers, that is, older adults at raised heart risk who have neither diabetes nor a past stroke, once the benefit in absolute terms and the likely side effects have been discussed and readings are taken the trial's way. It does not support a clinic-wide target of 120 for all hypertensive adults.
Conclusion
The committee member's summary was accurate but incomplete. The p-value shows that the results are hard to explain if intensive control had no effect; the confidence interval shows a range of benefit from modest to substantial; the absolute difference shows about one prevented event per 56 people over three years; and the harms and exclusions show who should be offered the approach. Reading all four together, rather than relying on a single significant p-value, is the skill the decision requires.
References
Amrhein, V., Greenland, S., & McShane, B. (2019). Scientists rise up against statistical significance. Nature, 567(7748), 305-307. https://doi.org/10.1038/d41586-019-00857-9
SPRINT Research Group. (2015). A randomized trial of intensive versus standard blood-pressure control. New England Journal of Medicine, 373(22), 2103-2116. https://doi.org/10.1056/NEJMoa1511939
Wasserstein, R. L., & Lazar, N. A. (2016). The ASA's statement on p-values: Context, process, and purpose. The American Statistician, 70(2), 129-133. https://doi.org/10.1080/00031305.2016.1154108
What the NUR 7630 Module 3 instructions ask for
Statistical concepts used to critique research findings lead the NUR-7630 catalog description, and with the syllabus private, this third module puts p-values and confidence intervals under the lens of one practice decision. Expect to take a published result apart: its test statistic, its interval, how big the effect is in absolute terms, and for whom it holds. Some classrooms provide output from a statistics package to interpret instead of an article. Look for whether a specific statement on p-values must be cited. Interpret every number in a full sentence that a clinician could understand, and say what the interval's width implies. Show how you would explain the result to the committee in two sentences.
Inside the NUR 7630 Module 3 example
A committee member's summary of an intensive blood pressure trial opens the paper. The trial's population, achieved pressures and main results are reported. A section applies each of the American Statistical Association's six principles to the trial's p-value. The confidence interval is interpreted as a range of compatible effects, linked to the call to retire statistical significance. Relative results are converted to absolute ones and a number needed to treat in a five-row table. Harms, exclusions and the trial's measurement method follow, then a recommendation limited to similar patients and a conclusion. A separate paragraph reads the interval's two ends as two different futures for the clinic's patients.
Reading the NUR 7630 Module 3 grading rubric
An inference paper earns marks for reading the trial's numbers correctly, separating a reliable effect from an important one, restating results as absolute differences and checking harms and the population. Readers watch for one error above all: treating the p-value as the odds the finding is real. Calculations should be shown and tied to time periods. Recommendations should be restricted to populations the study represents. Current statistical guidance and APA references complete the grade. Discussing the width of the interval, and what its two ends would mean for patients, is usually what lifts a paper into the top band. A paper that explains the trial's blood pressure measurement method, and why office readings differ, shows the attention to detail that applicability requires.
NUR 7630 Module 3 help from the desk
Students most often turn a p-value into odds that the result is luck or odds the treatment works, and both readings are wrong. Use the formal meaning. Many drafts stop at the relative drop; put it in events per hundred people over the trial's years, and name the treated count needed for one benefit. Read the confidence interval, not just whether it crosses 1. Check the adverse events and the exclusion criteria, and be clear about which outcome a quoted percentage belongs to. Ask whether measurement methods in the trial match those in your setting. Send the article your NUR-7630 section assigned and receive a first interpretation draft without charge.
Write yours, or have the desk draft it
This paper is an original model document written by our desk, not a submitted student paper and not an official Thomas Edison State University document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.
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NUR 7630 Module 3 questions, answered
Where can I find a free NUR 7630 Module 3 sample paper?
The SPRINT interpretation paper is printed above, with the calculation table and margin notes.
What does a p-value mean?
In SPRINT's case, that results as strong as these would be surprising if a lower target did nothing; it is not the chance the target works and says nothing about the size of the gain.
How do you interpret a 95 percent confidence interval for a hazard ratio?
SPRINT's 0.64 to 0.89 says the data fit risk cuts anywhere from about 11 to 36 percent, and fit no effect poorly, so the decision should consider both ends.
What did the SPRINT trial show?
Targeting systolic pressure below 120 rather than 140 lowered the primary cardiovascular composite from 2.19 to 1.65 percent a year, with more adverse events such as low pressure and kidney injury.
What is the difference between statistical and clinical significance?
The first asks whether chance under a no-effect model explains the data; the second asks whether one fewer event in 56 people over three years is worth the pills, visits and side effects.