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OBJECTIVE: We sought to determine real-world accuracy of inpatient continuous glucose monitoring (CGM) at multiple levels of acuity in a large safety-net hospital. RESEARCH DESIGN AND METHODS: We analyzed records from hospitalized patients on Dexcom G6 CGM, including clinical, point of care (POC), and laboratory (Lab) glucose, and CGM data. POC/Lab values were matched to the closest timed CGM value. Encounters were divided into not critically ill (NCI) versus critically ill (CI). CGM accuracy was evaluated. RESULTS: Paired readings (2,744 POC-CGM; 3,705 Lab-CGM) were analyzed for 233 patients with 239 encounters (83 NCI, 156 CI). POC-CGM aggregated and average mean absolute relative differences (MARD) were 15.1% and 17.1%. Lab-CGM aggregated and average MARDs were 11.4% and 12.2%. Accuracy for POC-CGM and Lab-CGM was 96.5% and 99.1% in Clarke Error Grid zones A/B. CONCLUSIONS: Real-world accuracy of inpatient CGM is acceptable for NCI and CI patients. Further exploration of conditions associated with lower CGM accuracy in real-world settings is warranted.

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OBJECTIVES: To define healthcare trajectories after tracheostomy to inform shared decision-making efforts for critically ill patients. DESIGN: Retrospective epidemiologic cohort study. SETTING: California Patient Discharge Database 2018-2019. PATIENTS: Patients who received a tracheostomy. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We tracked 1-year outcomes after tracheostomy, including survival and time alive in and out of a healthcare facility (HCF. Patients were stratified based on surgical status (did the patient require a major operating room procedure or not), age (65 yr old or older and less than 65 yr), pre-ICU comorbid states (frailty, chronic organ dysfunction, cancer, and robustness), and the need for dialysis during the tracheostomy admission. We identified 4,274 nonsurgical adults who received a tracheostomy during the study period with 50.9% being 65 years old or older. Among adults 65 years old or older, median survival after tracheostomy was less than 3 months for individuals with frailty, chronic organ dysfunction, cancer, or dialysis. Median survival was 3 months for adults younger than 65 years with cancer or dialysis. Most patients spent the majority of days alive after a tracheostomy in an HCF in the first 3 months. Older adults had very few days alive and out of an HCF in the first 3 months after tracheostomy. Most patients who ultimately died in the first year after tracheostomy spent almost all days alive in an HCF. CONCLUSIONS: Cumulative mortality and median survival after a tracheostomy were very poor across most ages and groups. Older adults and several subgroups of younger adults experienced high rates of prolonged hospitalization with few days alive and out of an HCF. This information may aid some patients, surrogates, and providers in decision-making.

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OBJECTIVES: Availability of long-term acute care hospitals has been associated with hospital discharge practices. It is unclear if long-term acute care hospital availability can influence patient care decisions. We sought to determine the association of long-term acute care hospital availability at different hospitals with the likelihood of tracheostomy. DESIGN: Retrospective cohort study. SETTING: California Patient Discharge Database, 2016-2018. PATIENTS: Adult patients receiving mechanical ventilation for respiratory failure. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Using the California Patient Discharge Database 2016-2018, we identified all mechanically ventilated patients and those who received tracheostomy. We determine the association between tracheostomy and the distance between each hospital and the nearest long-term acute care hospital and the number of long-term acute care hospital beds within 20 miles of each hospital. Among 281,502 hospitalizations where a patient received mechanical ventilation, 22,899 (8.1%) received a tracheostomy. Patients admitted to a hospital closer to a long-term acute care hospital compared with those furthest from a long-term acute care hospital had 38.9% (95% CI, 33.3-44.6%) higher odds of tracheostomy (closest hospitals 8.7% vs furthest hospitals 6.3%, adjusted odds ratio = 1.65; 95% CI, 1.40-1.95). Patients had a 32.4% (95% CI, 27.6-37.3%) higher risk of tracheostomy when admitted to a hospital with more long-term acute care hospital beds in the immediate vicinity (most long-term acute care hospital beds within 20 miles 8.9% vs fewest long-term acute care hospital beds 6.7%, adjusted odds ratio = 1.54; 95% CI, 1.31-1.80). Distance to the nearest long-term acute care hospital was inversely correlated with hospital risk-adjusted tracheostomy rates (ρ = -0.25; p < 0.0001). The number of long-term acute care hospital beds within 20 miles was positively correlated with hospital risk-adjusted tracheostomy rates (ρ = 0.22; p < 0.0001). CONCLUSIONS: Proximity and availability of long-term acute care hospital beds were associated with patient odds of tracheostomy and hospital tracheostomy practices. These findings suggest a hospital effect on tracheostomy decision-making over and above patient case-mix. Future studies focusing on shared decision-making for tracheostomy are needed to ensure goal-concordant care for prolonged mechanical ventilation.

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OBJECTIVES: Prone position ventilation is a potentially life-saving ancillary intervention but is not widely adopted for coronavirus disease 2019 or acute respiratory distress syndrome from other causes. Implementation of lung-protective ventilation including prone positioning for coronavirus disease 2019 acute respiratory distress syndrome is limited by isolation precautions and personal protective equipment scarcity. We sought to determine the safety and associated clinical outcomes for coronavirus disease 2019 acute respiratory distress syndrome treated with prolonged prone position ventilation without daily repositioning. DESIGN: Retrospective single-center study. SETTING: Community academic medical ICU. PATIENTS: Sequential mechanically ventilated patients with coronavirus disease 2019 acute respiratory distress syndrome. INTERVENTIONS: Lung-protective ventilation and prolonged protocolized prone position ventilation without daily supine repositioning. Supine repositioning was performed only when Fio2 less than 60% with positive end-expiratory pressure less than 10 cm H2O for greater than or equal to 4 hours. MEASUREMENTS AND MAIN RESULTS: Primary safety outcome: proportion with pressure wounds by Grades (0-4). Secondary outcomes: hospital survival, length of stay, rates of facial and limb edema, hospital-acquired infections, device displacement, and measures of lung mechanics and oxygenation. Eighty-seven coronavirus disease 2019 patients were mechanically ventilated. Sixty-one were treated with prone position ventilation, whereas 26 did not meet criteria. Forty-two survived (68.9%). Median (interquartile range) time from intubation to prone position ventilation was 0.28 d (0.11-0.80 d). Total prone position ventilation duration was 4.87 d (2.08-9.97 d). Prone position ventilation was applied for 30.3% (18.2-42.2%) of the first 28 days. Pao2:Fio2 diverged significantly by day 3 between survivors 147 (108-164) and nonsurvivors 107 (85-146), mean difference -9.632 (95% CI, -48.3 to 0.0; p = 0·05). Age, driving pressure, day 1, and day 3 Pao2:Fio2 were predictive of time to death. Thirty-eight (71.7%) developed ventral pressure wounds that were associated with prone position ventilation duration and day 3 Sequential Organ Failure Assessment. Limb weakness occurred in 58 (95.1%) with brachial plexus palsies in five (8.2%). Hospital-acquired infections other than central line-associated blood stream infections were infrequent. CONCLUSIONS: Prolonged prone position ventilation was feasible and relatively safe with implications for wider adoption in treating critically ill coronavirus disease 2019 patients and acute respiratory distress syndrome of other etiologies.

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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.

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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.

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STUDY OBJECTIVE: Bag-valve-mask ventilation remains an essential component of airway management. Rescuers continue to use both traditional 1- or 2-handed mask-face sealing techniques, as well as a newer modified 2-handed technique. We compare the efficacy of 1-handed, 2-handed, and modified 2-handed bag-valve-mask technique. METHODS: In this prospective, crossover study, health care providers performed 1-handed, 2-handed, and modified 2-handed bag-valve-mask ventilation on a standardized ventilation model. Subjects performed each technique for 5 minutes, with 3 minutes' rest between techniques. The primary outcome was expired tidal volume, defined as percentage of total possible expired tidal volume during a 5-minute bout. A specialized inline monitor measured expired tidal volume. We compared 2-handed versus modified 2-handed and 2-handed versus 1-handed techniques. RESULTS: We enrolled 52 subjects: 28 (54%) men, 32 (62%) with greater than or equal to 5 actual emergency bag-valve-mask situations. Median expired tidal volume percentage for 1-handed technique was 31% (95% confidence interval [CI] 17% to 51%); for 2-handed technique, 85% (95% CI 78% to 91%); and for modified 2-handed technique, 85% (95% CI 82% to 90%). Both 2-handed (median difference 47%; 95% CI 34% to 62%) and modified 2-handed technique (median difference 56%; 95% CI 29% to 65%) resulted in significantly higher median expired tidal volume percentages compared with 1-handed technique. The median expired tidal volume percentages between 2-handed and modified 2-handed techniques did not significantly differ from each other (median difference 0; 95% CI -2% to 2%). CONCLUSION: In a simulated model, both 2-handed mask-face sealing techniques resulted in higher ventilatory tidal volumes than 1-handed technique. Tidal volumes from 2-handed and modified 2-handed techniques did not differ. Rescuers should perform bag-valve-mask ventilation with 2-handed techniques.

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All forms of pulmonary hypertension are characterized by structural changes in pulmonary arteries. Increased numbers of cells expressing alpha-smooth muscle (alpha-SM) actin is a nearly universal finding in the remodeled artery. Traditionally, it was assumed that resident smooth muscle cells were the exclusive source of these newly appearing alpha-SM actin-expressing cells. However, rapidly emerging experimental evidence suggests other, alternative cellular sources of these cells. One possibility is that endothelial cells can transition into mesenchymal cells expressing alpha-SM actin and that this process contributes to the accumulation of SM-like cells in vascular pathologies. We review the evidence that endothelial-mesenchymal transition is an important contributor to cardiac and vascular development as well as to pathophysiological vascular remodeling. Recent work has provided evidence for the role of transforming growth factor-beta, Wnt, and Notch signaling in this process. The potential roles of matrix metalloproteinases and serine proteases are also discussed. Importantly, endothelial-mesenchymal transition may be reversible. Thus insights into the mechanisms controlling endothelial-mesenchymal transition are relevant to vascular remodeling and are important as we consider new therapies aimed at reversing pulmonary vascular remodeling.

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