Send to

Choose Destination
Anesth Analg. 2015 Sep;121(3):632-41. doi: 10.1213/ANE.0000000000000860.

Balancing Model Performance and Simplicity to Predict Postoperative Primary Care Blood Pressure Elevation.

Author information

From the *Department of Anesthesiology, Yale School of Medicine, New Haven, Connecticut; †Yale Center for Analytical Sciences, Yale School of Public Health, New Haven, Connecticut; ‡VA Connecticut Healthcare System, West Haven, Connecticut; §Departments of Emergency Medicine and Anesthesiology, Yale School of Medicine, New Haven, Connecticut; and ∥Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.



Because of uncertainty regarding the reliability of perioperative blood pressures and traditional notions downplaying the role of anesthesiologists in longitudinal patient care, there is no consensus for anesthesiologists to recommend postoperative primary care blood pressure follow-up for patients presenting for surgery with an increased blood pressure. The decision of whom to refer should ideally be based on a predictive model that balances performance with ease-of-use. If an acceptable decision rule was developed, a new practice paradigm integrating the surgical encounter into broader public health efforts could be tested, with the goal of reducing long-term morbidity from hypertension among surgical patients.


Using national data from US veterans receiving surgical care, we determined the prevalence of poorly controlled outpatient clinic blood pressures ≥140/90 mm Hg, based on the mean of up to 4 readings in the year after surgery. Four increasingly complex logistic regression models were assessed to predict this outcome. The first included the mean of 2 preoperative blood pressure readings; other models progressively added a broad array of demographic and clinical data. After internal validation, the C-statistics and the Net Reclassification Index between the simplest and most complex models were assessed. The performance characteristics of several simple blood pressure referral thresholds were then calculated.


Among 215,621 patients, poorly controlled outpatient clinic blood pressure was present postoperatively in 25.7% (95% confidence interval [CI], 25.5%-25.9%) including 14.2% (95% CI, 13.9%-14.6%) of patients lacking a hypertension history. The most complex prediction model demonstrated statistically significant, but clinically marginal, improvement in discrimination over a model based on preoperative blood pressure alone (C-statistic, 0.736 [95% CI, 0.734-0.739] vs 0.721 [95% CI, 0.718-0.723]; P for difference <0.0001). The Net Reclassification Index was 0.088 (95% CI, 0.082-0.093); P < 0.0001. A preoperative blood pressure threshold ≥150/95 mm Hg, calculated as the mean of 2 readings, identified patients more likely than not to demonstrate outpatient clinic blood pressures in the hypertensive range. Four of 5 patients not meeting this criterion were indeed found to be normotensive during outpatient clinic follow-up (positive predictive value, 51.5%; 95% CI, 51.0-52.0; negative predictive value, 79.6%; 95% CI, 79.4-79.7).


In a national cohort of surgical patients, poorly controlled postoperative clinic blood pressure was present in >1 of 4 patients (95% CI, 25.5%-25.9%). Predictive modeling based on the mean of 2 preoperative blood pressure measurements performed nearly as well as more complicated models and may provide acceptable predictive performance to guide postoperative referral decisions. Future studies of the feasibility and efficacy of such referrals are needed to assess possible beneficial effects on long-term cardiovascular morbidity.

[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Wolters Kluwer Icon for PubMed Central
Loading ...
Support Center