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Observational Modeling of Strict vs Conventional Blood Pressure Control in Patients With Chronic Kidney Disease

Abstract

Importance

The effect of strict blood pressure control on clinical outcomes in patients with chronic kidney disease (CKD) is unclear.

Objective

To compare the outcomes associated with a treated systolic blood pressure (SBP) of less than 120 mm Hg vs those associated with the currently recommended SBP of less than 140 mm Hg in a national CKD database of US veterans.

Design, setting, and participants

Historical cohort study using a nationwide cohort of US veterans with prevalent CKD, estimated glomerular filtration rate less than 60 mL/min/1.73 m(2), and uncontrolled hypertension, who then received 1 or more additional blood pressure medications with evidence of a decrease in SBP. Propensity scores were calculated to reflect each individual's probability for future SBP less than 120 vs 120 to 139 mm Hg.

Main outcomes and measures

The effect of SBP on all-cause mortality was evaluated by the log-rank test, and in Cox models adjusted for propensity scores.

Results

Using a database of 651,749 patients with CKD, we identified 77,765 individuals meeting the inclusion criteria. A total of 5760 patients experienced follow-up treated SBP of less than 120 mm Hg and 72,005 patients had SBP of 120 to 139 mm Hg. During a median follow-up of 6.0 years, 19,517 patients died, with 2380 deaths in the SBP less than 120 mm Hg group (death rate, 80.9/1000 patient-years [95% CI, 77.7-84.2/1000 patient-years]) and 17,137 deaths in the SBP 120 to 139 mm Hg group (death rate, 41.8/1000 patient-years [95% CI, 41.2-42.4/1000 patient-years]; P < .001). The mortality hazard ratio (95% CI) associated with follow-up SBP less than 120 vs 120 to 139 mm Hg was 1.70 (1.63-1.78) after adjustment for propensity scores.

Conclusions and relevance

Our results suggest that stricter SBP control is associated with higher all-cause mortality in patients with CKD. Confirmation of these findings by ongoing clinical trials would suggest that modeling of therapeutic interventions in observational cohorts may offer useful guidance for the treatment of conditions that lack clinical trial data.

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