The Association between Supraphysiologic Arterial Oxygen Levels and Mortality in Critically Ill Patients. A Multicenter Observational Cohort Study

Abstract

Rationale: There is conflicting evidence on harm related to exposure to supraphysiologic Pa_O2 (hyperoxemia) in critically ill patients.Objectives: To examine the association between longitudinal exposure to hyperoxemia and mortality in patients admitted to ICUs in five United Kingdom university hospitals.Methods: A retrospective cohort of ICU admissions between January 31, 2014, and December 31, 2018, from the National Institute of Health Research Critical Care Health Informatics Collaborative was studied. Multivariable logistic regression modeled death in ICU by exposure to hyperoxemia.Measurements and Main Results: Subsets with oxygen exposure windows of 0 to 1, 0 to 3, 0 to 5, and 0 to 7 days were evaluated, capturing 19,515, 10,525, 6,360, and 4,296 patients, respectively. Hyperoxemia dose was defined as the area between the Pa_O2 time curve and a boundary of 13.3 kPa (100 mm Hg) divided by the hours of potential exposure (24, 72, 120, or 168 h). An association was found between exposure to hyperoxemia and ICU mortality for exposure windows of 0 to 1 days (odds ratio [OR], 1.15; 95% compatibility interval [CI], 0.95-1.38; P = 0.15), 0 to 3 days (OR 1.35; 95% CI, 1.04-1.74; P = 0.02), 0 to 5 days (OR, 1.5; 95% CI, 1.07-2.13; P = 0.02), and 0 to 7 days (OR, 1.74; 95% CI, 1.11-2.72; P = 0.02). However, a dose-response relationship was not observed. There was no evidence to support a differential effect between hyperoxemia and either a respiratory diagnosis or mechanical ventilation.Conclusions: An association between hyperoxemia and mortality was observed in our large, unselected multicenter cohort. The absence of a dose-response relationship weakens causal interpretation. Further experimental research is warranted to elucidate this important question.

Keywords: critical care; hyperoxia; logistic models.

Figure 1.

Illustration of the calculation of hyperoxemia dose. The blue area defines hyperoxemia exposure for a real patient drawn from the Critical Care Health Informatics Collaborative database. Red points indicate actual observations. Black interrupted lines show the linear imputation strategy. Gaps exist in the imputation between observations greater than 12 hours apart. Hyperoxemia dose was calculated by summing the blue area and dividing by the hours of the potential exposure window for the given model (from top panel to bottom panel: 24, 72, 120, or 168 h). This yields the natural units originally used to measure Pa_O2 (shown in kilopascals). Vertical dashed lines indicate the point of censoring at the end of the exposure window.

Figure 2.

Point estimates of odds ratios and 95% compatibility intervals are presented for all linear model terms. Hyperoxemia has been assessed in two ways: as an indicator (any hyperoxemia exposure) and hyperoxemia dose variables. There was a progressively stronger association between any hyperoxemia exposure and ICU mortality from the Day 0 to Day 1 model up to the Day 0 to Day 7 model. There was a lack of evidence to support a relationship between hyperoxemia dose and ICU mortality. Odds ratios are not presented for age, weight, and the Acute Physiology and Chronic Health Evaluation II score because these were modeled nonlinearly.

Figure 3.

Counterfactual risk plot illustrating the change in predicted mortality by setting all hyperoxemia exposure to 0. The model-predicted risk of mortality with the observed hyperoxemia is shown on the y-axis. The model-predicted risk of mortality when setting hyperoxemia to 0 is shown on the x-axis. The Day 0 to Day 5 cohort is used as an example (other cohorts demonstrate a similar pattern). The 45° identity line is marked as a dashed diagonal line representing no change in risk. Several observations lie on the identity line, in keeping with the proportion of patients who had no exposure to hyperoxemia and so cannot see an adjustment to their mortality risk via this mechanism.