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About
The numeric rating scale (NRS) is one way to assess how much pain a patient is feeling after surgery, ranging from 0 (no pain) to 10 (the worst pain imaginable). The score getting lower can thus indicate pain relief. However, a small change in the score does not mean that the patient is actually satisfied with their pain relief treatment. The PASS (patient acceptable symptom state) is the score threshold beyond which a patient considers their treatment satisfactory.
The purpose of this observational study is to find out the PASS for the NRS in the first 48 hours after surgery. This will help guide future research on pain medicine, so that new techniques can deliver adequate patient satisfaction.
Full description
As healthcare delivery and research studies become more patient-centered, patient-reported outcome measures (PROMs) - instruments completed by a patient to capture their health status (e.g., pain, quality of life, function) - are increasingly used. However little attention has been paid to PROMs in the acute phase of postoperative recovery. Given that many patients experience moderate to severe pain in the first day following surgery (e.g., 50% for joint replacement surgery), and that acute postsurgical pain is associated with long-term outcomes, a focus on patient-reported acute pain following surgery is needed.
Both acute and chronic postoperative pain are commonly assessed using the 100 mm visual analogue scale (VAS, 0 mm = no pain to 100 mm = worst possible pain) or numeric rating scale (NRS, 0 = no pain to 10 = worst possible pain). While a reduction in the VAS or NRS pain score indicates some degree of pain relief, neither the raw numerical score nor the statistical significance of a score's change indicates whether the change is perceived by patients to be meaningful. Instead, the Patient Acceptable Symptom State (PASS), which represents the threshold beyond which patients consider themselves well or satisfied with a treatment, can be used to determine the proportion of patients that responded to treatment (i.e., the proportion of patients that achieved the PASS) and to calculate the number needed to treat. Little to no data has been found concerning the PASS for acute postsurgical pain. There has been somewhat more work quantifying the Minimum Clinically Important Difference (MCID; the smallest change that is important to patients), which is a related concept to the PASS that also determines the clinical significance of a change in pain score. The MCID varies widely across chronic pain disorders (from 8 mm for scleroderma to 82 mm for trigeminal neuralgia) and across non-surgical acute pain conditions (from 8 mm for patients presenting to the emergency department to 40 mm for rheumatic conditions). Therefore, the PASS for acute pain following surgeries is expected to vary based on the type of surgery, but this has not been determined. Similarly, there is no known study of the consistency in PASS throughout the postoperative period or across the patient and surgical factors that are known to be important for MCID (e.g., preoperative pain, pain expectations), or the opioid dose (measured in morphine milligram equivalents) needed to achieve the PASS.
The primary objective of this study is to determine the PASS for the NRS pain score in the first 48 hours after surgery in patients who received intravenous patient-controlled analgesia (PCA). The study includes patients who have undergone surgery at UHN between June 4, 2022, and December 31, 2023 (the study period). Patients will be identified using the Epic data management software. All required data for this study will be obtained from the Epic electronic medical record at UHN. For patients who are on intravenous PCA, the patient's pain score at rest and with activity is taken using the NRS multiple times per day and recorded in Epic. Each time the NRS is taken, the patient's satisfaction (yes/no) is also recorded along with the cumulative PCA opioid dose.
This study will include a descriptive analysis of the data collected. The descriptive analysis will be used to summarize the characteristics of the study population and to identify patterns and trends in the data. Measures of central tendency (e.g., mean, median, mode) and measures of variability (e.g., standard deviation, range) will be calculated for continuous variables. Frequency distributions and proportions will be used to describe categorical variables. Missing data will not be imputed but will be reported for every variable. Graphs and charts will be used to visualize the data. Histograms, bar charts, and pie charts will be used to describe the distribution of continuous and categorical variables.
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7,000 participants in 1 patient group
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Data sourced from clinicaltrials.gov
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