Postoperative residual neuromuscular blockade after reversal based on a qualitative peripheral nerve stimulator response: A randomised controlled trial.

BACKGROUND: Incomplete recovery of neuromuscular blockade is a common postoperative adverse event in the postanaesthesia care unit. OBJECTIVE: We examined and compared the incidence of residual neuromuscular blockade when the recommended dose of neostigmine or sugammadex was administered according to a qualitative nerve stimulator response. DESIGN: A randomised controlled trial. SETTING: A tertiary care hospital in South Korea from September 2017 to November 2017. PATIENTS: Eighty patients aged between 18 and 69 years were included in this study. All were patients scheduled to undergo elective laparoscopic cholecystectomy and who had an American Society of Anaesthesiologists physical status of one or two were eligible. INTERVENTIONS: Patients were allocated randomly to receive neostigmine or sugammadex at the end of surgery. The doses of the reversal agents were based on the response to peripheral nerve stimulation, which was discontinued after administration of the reversal agent. MAIN OUTCOME MEASURES: The primary outcome was the incidence of postoperative residual neuromuscular blockade. The secondary outcomes were the incidences of symptoms or signs of residual neuromuscular blockade such as hypoxaemia, inability to maintain head-lift for 5 s and diplopia. RESULTS: The incidence of residual neuromuscular blockade on arrival in the recovery room was 44.4% in the neostigmine group and 0% in the sugammadex group (P < 0.0001, relative risk = 1.80, 95% confidence interval 1.36 to 2.41). The incidences of adverse events in the recovery room were low and comparable between the groups. CONCLUSION: The incidence of residual neuromuscular blockade on arrival in the recovery room was significantly higher in the neostigmine group than that in the sugammadex group. However, the incidence of adverse events was similar in the neostigmine and sugammadex groups. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03292965.

Development and validation of automated microscale walkability audit method.

Measuring microscale factors of walkability has been labor-intensive and expensive. To reduce the cost, various efforts have been made including virtual audits (i.e., manual audits using street view images) and the introduction of computer vision techniques. Although studies have shown that virtual audits (i.e., manual audits using street view images) can reliably replicate in-person audits, they are still prohibitively expensive to be applied to a large geographic area. Past studies used computer vision techniques to help automate the audit process, but off-the-shelf models cannot detect some of the important microscale walkability characteristics, falling short of fully capturing the multi-facetted concept of walkability. This study is one of the earliest attempts to use the combination of custom-trained computer vision models, geographic information systems, and street view images to automatically audit a complete set of items of a validated microscale walkability audit tool. This study validates the reliability of the automated audit with virtual audit results. The automated audit results show high reliability, indicating automated audit can be a highly scalable and reliable replacement of virtual audit.