Stability of Do-Not-Resuscitate Orders in Hospitalized Adults: A Population-Based Cohort Study.

OBJECTIVES: Prior work has shown substantial between-hospital variation in do-not-resuscitate orders, but stability of do-not-resuscitate preferences between hospitalizations and the institutional influence on do-not-resuscitate reversals are unclear. We determined the extent of do-not-resuscitate reversals between hospitalizations and the association of the readmission hospital with do-not-resuscitate reversal. DESIGN: Retrospective cohort study. SETTING: California Patient Discharge Database, 2016-2018. PATIENTS: Nonsurgical patients admitted to an acute care hospital with an early do-not-resuscitate order (within 24 hr of admission). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We identified nonsurgical adult patients who survived an initial hospitalization with an early-do-not-resuscitate order and were readmitted within 30 days. The primary outcome was the association of do-not-resuscitate reversal with readmission to the same or different hospital from the initial hospital. Secondary outcomes included association of readmission to a low versus high do-not-resuscitate-rate hospital with do-not-resuscitate reversal. Among 49,336 patients readmitted within 30 days following a first do-not-resuscitate hospitalization, 22,251 (45.1%) experienced do-not-resuscitate reversal upon readmission. Patients readmitted to a different hospital versus the same hospital were at higher risk of do-not-resuscitate reversal (59.5% vs 38.5%; p < 0.001; adjusted odds ratio = 2.4; 95% CI, 2.3-2.5). Patients readmitted to low versus high do-not-resuscitate-rate hospitals were more likely to have do-not-resuscitate reversals (do-not-resuscitate-rate quartile 1 77.0% vs quartile 4 27.2%; p < 0.001; adjusted odds ratio = 11.9; 95% CI, 10.7-13.2). When readmitted to a different versus the same hospital, patients with do-not-resuscitate reversal had higher rates of mechanical ventilation (adjusted odds ratio = 1.9; 95% CI, 1.6-2.1) and hospital death (adjusted odds ratio = 1.2; 95% CI, 1.1-1.3). CONCLUSIONS: Do-not-resuscitate reversals at the time of readmission are more common than previously reported. Although changes in patient preferences may partially explain between-hospital differences, we observed a strong hospital effect contributing to high do-not-resuscitate-reversal rates with significant implications for patient outcomes and resource.

Assessing the Course of Organ Dysfunction Using Joint Longitudinal and Time-to-Event Modeling in the Vasopressin and Septic Shock Trial.

Non-mortality septic shock outcomes (e.g., Sequential Organ Failure Assessment score) are important clinical endpoints in pivotal sepsis trials. However, comparisons of observed longitudinal non-mortality outcomes between study groups can be biased if death is unequal between study groups or is associated with an intervention (i.e., informative censoring). We compared the effects of vasopressin versus norepinephrine on the Sequential Organ Failure Assessment score in the Vasopressin and Septic Shock Trial to illustrate the use of joint modeling to help minimize potential bias from informative censoring. DESIGN: Secondary analysis of the Vasopressin and Septic Shock Trial data. SETTING: Twenty-seven ICUs in Canada, Australia, and United States. SUBJECTS: Seven hundred sixty-three participants with septic shock who received blinded vasopressin (n = 389) or norepinephrine infusions (n = 374). MEASUREMENTS AND MAIN RESULTS: Sequential Organ Failure Assessment scores were calculated daily until discharge, death, or day 28 after randomization. Mortality was numerically higher in the norepinephrine arm (28 d mortality of 39% vs 35%; p = 0.25), and there was a positive association between higher Sequential Organ Failure Assessment scores and patient mortality, characteristics that suggest a potential for bias from informative censoring of Sequential Organ Failure Assessment scores by death. The best-fitting joint longitudinal (i.e., linear mixed-effects model) and survival (i.e., Cox proportional hazards model for the time-to-death) model showed that norepinephrine was associated with a more rapid improvement in the total Sequential Organ Failure Assessment score through day 4, and then the daily Sequential Organ Failure Assessment scores converged and overlapped for the remainder of the study period. CONCLUSIONS: Short-term reversal of organ dysfunction occurred more rapidly with norepinephrine compared with vasopressin, although differences between study arms did not persist after day 4. Joint models are an accessible methodology that could be used in critical care trials to assess the effects of interventions on the longitudinal progression of key outcomes (e.g., organ dysfunction, biomarkers, or quality of life) that may be informatively truncated by death or other censoring events.

Hospital Mechanical Ventilation Volume and Patient Outcomes: Too Much of a Good Thing?

OBJECTIVES: Prior studies investigating hospital mechanical ventilation volume-outcome associations have had conflicting findings. Volume-outcome relationships within contemporary mechanical ventilation practices are unclear. We sought to determine associations between hospital mechanical ventilation volume and patient outcomes. DESIGN: Retrospective cohort study. SETTING: The California Patient Discharge Database 2016. PATIENTS: Adult nonsurgical patients receiving mechanical ventilation. INTERVENTIONS: The primary outcome was hospital death with secondary outcomes of tracheostomy and 30-day readmission. We used multivariable generalized estimating equations to determine the association between patient outcomes and hospital mechanical ventilation volume quartile. MEASUREMENTS AND MAIN RESULTS: We identified 51,689 patients across 274 hospitals who required mechanical ventilation in California in 2016. 38.2% of patients died in the hospital with 4.4% receiving a tracheostomy. Among survivors, 29.5% required readmission within 30 days of discharge. Patients admitted to high versus low volume hospitals had higher odds of death (quartile 4 vs quartile 1 adjusted odds ratio, 1.40; 95% CI, 1.17-1.68) and tracheostomy (quartile 4 vs quartile 1 adjusted odds ratio, 1.58; 95% CI, 1.21-2.06). However, odds of 30-day readmission among survivors was lower at high versus low volume hospitals (quartile 4 vs quartile 1 adjusted odds ratio, 0.77; 95% CI, 0.67-0.89). Higher hospital mechanical ventilation volume was weakly correlated with higher hospital risk-adjusted mortality rates (ρ = 0.16; p = 0.008). These moderately strong observations were supported by multiple sensitivity analyses. CONCLUSIONS: Contrary to previous studies, we observed worse patient outcomes at higher mechanical ventilation volume hospitals. In the setting of increasing use of mechanical ventilation and changes in mechanical ventilation practices, multiple mechanisms of worse outcomes including resource strain are possible. Future studies investigating differences in processes of care between high and low volume hospitals are necessary.