Daily Anesthesiology Research Analysis

OBJECTIVE: Current methods for estimating inspiratory muscle pressure (Pmus) during mechanical ventilation are either invasive or dependent on occlusion maneuvers. A noninvasive artificial intelligence (AI) algorithm estimating in real-time the amplitude and timing of Pmus, enabling continuous monitoring of patient effort, driving pressure, and synchrony with the ventilator was designed, and its performance was evaluated against the gold standard obtained with esophageal manometry (Pmus,es). DESIGN: A prospective diagnostic accuracy study. SETTING: Two ICUs from the University of São Paulo, Brazil. PATIENTS: Adult patients under pressure support ventilation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Pmus estimated using AI (Pmus,AI) was compared with Pmus,es and to values derived from occlusion maneuvers, the pressure muscle index and the occlusion pressure (Pocc). Automatic detection of dyssynchronies based on Pmus,AI was compared with experts' classification. A total of 48 participants with 4918 cycles were analyzed. Pmus,es varied from 1.0 to 28.4 cm H2O. Pmus,AI showed a bias of 0.9 cm H2O, 95% limits of agreement -5.1, 6.9 cm H2O and detected extreme values of both Pmus,es and dynamic driving pressure with area under the receiver operating characteristic curve greater than 0.8. Pmus,AI accuracy was comparable to occlusion-based techniques. Sensitivity and specificity to detect ineffective effort, autotriggering or reverse triggering were 86.5% and 77.4%, respectively. CONCLUSIONS: AI presented good performance in detecting high and low Pmus, and allowed the automatic detection of specific types of dyssynchronies. This novel noninvasive method was comparable to intermittent techniques requiring occlusion maneuvers.

BACKGROUND: Unnecessary opioid prescribing following surgery is wasteful and expands the reservoir for non-medical use, thereby contributing to preventable morbidity and mortality. We used an interrupted time series design to evaluate whether implementing a system-wide clinical decision support (CDS) intervention reduced opioid prescribing at discharge. METHODS: We included adult surgical patients hospitalized for at least 24 hours who had not received any opioids in the 24 hours prior to discharge, as prescriptions in this cohort are more likely to represent unnecessary opioid prescribing. The pre- and post-intervention two-year periods were 2/13/21-2/12/23 and 2/13/23-2/12/25, respectively. Our primary outcome was discharge oxycodone in morphine milligram equivalents (MME). Secondary outcomes included whether any opioids were prescribed, and if so, how much. Segmented regression models adjusted for confounders were used to assess the immediate and trend-level effects of the intervention. RESULTS: Analyzed data included 10,422 pre- and 11,795 post-intervention discharges. Total oxycodone prescribed per discharge was 27.4 MME pre-intervention and 16.5 MME post-intervention. Oxycodone MME prescribed at discharge was significantly lower post-intervention, with a ratio of geometric means of 0.83 (95% CI: 0.76, 0.90; 1-tailed superiority P <0.001) for the level change but no difference in slopes (P=0.919). For secondary outcomes, 21% of discharges were prescribed any oxycodone pre-intervention versus 18% post-intervention, with a relative risk of 0.87 (95% CI: 0.79, 0.96) assessing the level change. For the discharges with a prescription, median MME [Q1, Q3] was lower after intervention than before (75 [38, 112] vs 112 [75, 150]), with a ratio of geometric means of 0.70 (95% CI: 0.65, 0.75). CONCLUSIONS: An automated real-time clinical decision support tool resulted in clinically significant reductions in oxycodone prescribed at discharge. Incorporation of similarly simple decision support tools in electronic health record systems may significantly reduce unnecessary opioid prescriptions at scale and better align with guideline-concordant care.

STUDY OBJECTIVE: Consensus statements recommend pre-induction arterial catheterization to reduce hypotension during anesthetic induction. However, insertion is often deferred to reduce procedural delays and patient discomfort. We evaluated whether oscillometric monitoring at 1-min interval is noninferior to continuous arterial pressure monitoring on induction hypotension. DESIGN: Bi-center randomized trial. SETTING: Two tertiary university hospitals. PATIENTS: Adults scheduled for noncardiac surgery requiring arterial catheterization. INTERVENTION: Patients were randomized to unblinded continuous arterial pressure monitoring or to 1-min interval oscillometric monitoring with blinded intra-arterial pressures during induction. MEASUREMENTS: The primary outcome was the area of mean arterial pressure (MAP) <65 mmHg during the initial 15 min of induction. Noninferiority was defined as a 10 mmHg∙min absolute increase in the observed median of the primary outcome compared with continuous monitoring, analyzed as a geometric mean ratio. MAIN RESULTS: Among 253 analyzed patients (127 in the continuous monitoring group, 126 in the 1-min oscillometry group; 71% ASA physical status I or II), the median (interquartile range) area of MAP <65 mmHg was 3.0 (0 to 20) mmHg∙min in the continuous monitoring group and 3.3 (0 to 20) mmHg∙min in 1-min oscillometry group. The upper 97.5% confidence limit for the geometric mean ratio was 1.63, meeting the noninferiority margin of 3.50 (P < 0.001 for noninferiority). Vasopressor use was significantly greater in the continuous monitoring group (61% vs. 41%; P = 0.003), primarily driven by more frequent phenylephrine administration (24% vs. 7%; P = 0.001). CONCLUSIONS: Induction hypotension was rare, and the area of MAP <65 mmHg was noninferior with oscillometric monitoring at 1-min interval versus continuous arterial pressure monitoring in relatively healthy patients. High-frequency oscillometric monitoring may be a safe and pragmatic alternative to pre-induction arterial catheterization.