The relationship of tidal volume and driving pressure with mortality in hypoxic patients receiving mechanical ventilation.

PURPOSE: To determine whether tidal volume/predicted body weight (TV/PBW) or driving pressure (DP) are associated with mortality in a heterogeneous population of hypoxic mechanically ventilated patients. METHODS: A retrospective cohort study involving 18 intensive care units included consecutive patients ≥18 years old, receiving mechanical ventilation for ≥3 days, with a PaO2/FiO2 ratio ≤300 mmHg, whether or not they met full criteria for ARDS. The main outcome was hospital mortality. Multiple logistic regression (MLR) incorporated TV/PBW, DP, and potential confounders including age, APACHE IVa® predicted hospital mortality, respiratory system compliance (CRS), and PaO2/FiO2. Predetermined strata of TV/PBW were compared using MLR. RESULTS: Our cohort comprised 5,167 patients with mean age 61.9 years, APACHE IVa® score 79.3, PaO2/FiO2 166 mmHg and CRS 40.5 ml/cm H2O. Regression analysis revealed that patients receiving DP one standard deviation above the mean or higher (≥19 cmH20) had an adjusted odds ratio for mortality (ORmort) = 1.10 (95% CI: 1.06-1.13, p = 0.009). Regression analysis showed a U-shaped relationship between strata of TV/PBW and adjusted mortality. Using TV/PBW 4-6 ml/kg as the referent group, patients receiving >10 ml/kg had similar adjusted ORmort, but those receiving 6-7, 7-8 and 8-10 ml/kg had lower adjusted ORmort (95%CI) of 0.81 (0.65-1.00), 0.78 (0.63-0.97) and 0.80 0.67-1.01) respectively. The adjusted ORmort in patients receiving 4-6 ml/kg was 1.26 (95%CI: 1.04-1.52) compared to patients receiving 6-10 ml/kg. CONCLUSIONS: Driving pressures ≥19 cmH2O were associated with increased adjusted mortality. TV/PBW 4-6ml/kg were used in less than 15% of patients and associated with increased adjusted mortality compared to TV/PBW 6-10 ml/kg used in 82% of patients. Prospective clinical trials are needed to prove whether limiting DP or the use of TV/PBW 6-10 ml/kg versus 4-6 ml/kg benefits mortality.

A quality improvement project to improve the Medicare and Medicaid Services (CMS) sepsis bundle compliance rate in a large healthcare system.

Sepsis is a leading cause of mortality and morbidity in hospitalised patients. The Centers for Medicare and Medicaid Services (CMS) mandated that US hospitals report sepsis bundle compliance rate as a quality process measure in October 2015. The specific aim of our study was to improve the CMS sepsis bundle compliance rate from 30% to 40% across 20 acute care hospitals in our healthcare system within 1 year. The study included all adult inpatients with sepsis sampled according to CMS specifications from October 2015 to September 2016. The CMS sepsis bundle compliance rate was tracked monthly using statistical process control charting. A baseline rate of 28.5% with 99% control limits was established. We implemented multiple interventions including computerised decision support systems (CDSSs) to increase compliance with the most commonly missing bundle elements. Compliance reached 42% (99% statistical process control limits 18.4%-38.6%) as CDSS was implemented system-wide, but this improvement was not sustained after CMS changed specifications of the outcome measure. Difficulties encountered elucidate shortcomings of our study methodology and of the CMS sepsis bundle compliance rate as a quality process measure.

Real-Time Automated Sampling of Electronic Medical Records Predicts Hospital Mortality.

BACKGROUND: Real-time automated continuous sampling of electronic medical record data may expeditiously identify patients at risk for death and enable prompt life-saving interventions. We hypothesized that a real-time electronic medical record-based alert could identify hospitalized patients at risk for mortality. METHODS: An automated alert was developed and implemented to continuously sample electronic medical record data and trigger when at least 2 of 4 systemic inflammatory response syndrome criteria plus at least one of 14 acute organ dysfunction parameters was detected. The systemic inflammatory response syndrome and organ dysfunction alert was applied in real time to 312,214 patients in 24 hospitals and analyzed in 2 phases: training and validation datasets. RESULTS: In the training phase, 29,317 (18.8%) triggered the alert and 5.2% of such patients died, whereas only 0.2% without the alert died (unadjusted odds ratio 30.1; 95% confidence interval, 26.1-34.5; P < .0001). In the validation phase, the sensitivity, specificity, area under the curve, and positive and negative likelihood ratios for predicting mortality were 0.86, 0.82, 0.84, 4.9, and 0.16, respectively. Multivariate Cox-proportional hazard regression model revealed greater hospital mortality when the alert was triggered (adjusted hazards ratio 4.0; 95% confidence interval, 3.3-4.9; P < .0001). Triggering the alert was associated with additional hospitalization days (+3.0 days) and ventilator days (+1.6 days; P < .0001). CONCLUSION: An automated alert system that continuously samples electronic medical record data can be implemented, has excellent test characteristics, and can assist in the real-time identification of hospitalized patients at risk for death.