  Purpose: To explore the issue of counterintuitive data via analysis of a
representative case and further discussion of those situations in which the
data appear to be inconsistent with current knowledge. Case: 844 postoperative
CABG patients, who were extubated within 24 hours of surgery were identified in
a critical care database (MIMIC-III). Nurse elicited pain scores were
documented throughout their hospital stay on a scale of 0 to 10. Levels were
tracked as mean, median, and maximum values, and categorized as no (0/10), mild
(1-3), moderate (4-6) and severe pain (7-10). Regression analysis was employed
to analyze the relationship between pain scores and outcomes of interest
(mortality and hospital LOS). After covariate adjustment, increased levels of
pain were found to be associated with lower mortality rates and reduced
hospital LOS. Conclusion: These counterintuitive results for post-CABG pain
related outcomes have not been previously reported. While not representing
strong enough evidence to alter clinical practice, confirmed and reliable
results such as these should serve as a research trigger and prompt further
studies into unexpected associations between pain and patient outcomes. With
the advent of frequent secondary analysis of electronic health records, such
counterintuitive data results are likely to become more frequent. We discuss
the issue of counterintuitive data in extended fashion, including possible
reasons for, and approaches to, this phenomenon.
