BACKGROUND: Patients with obstructive sleep apnea are at risk for perioperative morbidity. The authors used a screening prediction model for obstructive sleep apnea to generate a sleep apnea clinical score (SACS) that identified patients at high or low risk for obstructive sleep apnea. This was combined with postanesthesia care unit (PACU) monitoring with the aim of identifying patients at high risk of postoperative oxygen desaturation and respiratory complications. METHODS: In this prospective cohort study, surgical patients with a hospital stay longer than 48 h who consented were enrolled. The SACS (high or low risk) was calculated; all patients were monitored in the PACU for recurrent episodes of bradypnea, apnea, desaturations, and pain-sedation mismatch. All patients underwent pulse oximetry postoperatively; complications were documented. Chi-square, two-sample t test, and logistic regression were used for analysis. The oxygen desaturation index (number of desaturations per hour) was calculated. Oxygen desaturation index and incidence of postoperative cardiorespiratory complications were primary endpoints. RESULTS: Six hundred ninety-three patients were enrolled. From multivariable logistic regression analysis, the likelihood of a postoperative oxygen desaturation index greater than 10 was increased with a high SACS (odds ratio = 1.9, P < 0.001) and recurrent PACU events (odds ratio = 1.5, P = 0.036). Postoperative respiratory events were also associated with a high SACS (odds ratio = 3.5, P < 0.001) and recurrent PACU events (odds ratio = 21.0, P < 0.001). CONCLUSIONS: Combination of an obstructive sleep apnea screening tool preoperatively (SACS) and recurrent PACU respiratory events was associated with a higher oxygen desaturation index and postoperative respiratory complications. A two-phase process to identify patients at higher risk for perioperative respiratory desaturations and complications may be useful to stratify and manage surgical patients postoperatively.
BACKGROUND:Patients with obstructive sleep apnea are at risk for perioperative morbidity. The authors used a screening prediction model for obstructive sleep apnea to generate a sleep apnea clinical score (SACS) that identified patients at high or low risk for obstructive sleep apnea. This was combined with postanesthesia care unit (PACU) monitoring with the aim of identifying patients at high risk of postoperative oxygen desaturation and respiratory complications. METHODS: In this prospective cohort study, surgical patients with a hospital stay longer than 48 h who consented were enrolled. The SACS (high or low risk) was calculated; all patients were monitored in the PACU for recurrent episodes of bradypnea, apnea, desaturations, and pain-sedation mismatch. All patients underwent pulse oximetry postoperatively; complications were documented. Chi-square, two-sample t test, and logistic regression were used for analysis. The oxygen desaturation index (number of desaturations per hour) was calculated. Oxygen desaturation index and incidence of postoperative cardiorespiratory complications were primary endpoints. RESULTS: Six hundred ninety-three patients were enrolled. From multivariable logistic regression analysis, the likelihood of a postoperative oxygen desaturation index greater than 10 was increased with a high SACS (odds ratio = 1.9, P < 0.001) and recurrent PACU events (odds ratio = 1.5, P = 0.036). Postoperative respiratory events were also associated with a high SACS (odds ratio = 3.5, P < 0.001) and recurrent PACU events (odds ratio = 21.0, P < 0.001). CONCLUSIONS: Combination of an obstructive sleep apnea screening tool preoperatively (SACS) and recurrent PACU respiratory events was associated with a higher oxygen desaturation index and postoperative respiratory complications. A two-phase process to identify patients at higher risk for perioperative respiratory desaturations and complications may be useful to stratify and manage surgical patients postoperatively.
Authors: Toby N Weingarten; Natasha M Hawkins; W Brian Beam; Heather A Brandt; Diana J Koepp; Todd A Kellogg; Juraj Sprung Journal: Obes Surg Date: 2015-06 Impact factor: 4.129
Authors: Alexandre N Cavalcante; Carmelina Gurrieri; Juraj Sprung; Darrell R Schroeder; Toby N Weingarten Journal: Bosn J Basic Med Sci Date: 2018-02-20 Impact factor: 3.363
Authors: Toby N Weingarten; Vitaly Herasevich; Maria C McGlinch; Nicole C Beatty; Erin D Christensen; Susan K Hannifan; Amy E Koenig; Justin Klanke; Xun Zhu; Bhargavi Gali; Darrell R Schroeder; Juraj Sprung Journal: Anesth Analg Date: 2015-08 Impact factor: 5.108
Authors: Lioudmila V Karnatovskaia; Augustine S Lee; S Patrick Bender; Daniel Talmor; Emir Festic Journal: J Clin Sleep Med Date: 2014-06-15 Impact factor: 4.062
Authors: Matthias Eikermann; Jaime Garzon-Serrano; Jean Kwo; Martina Grosse-Sundrup; Ulrich Schmidt; Luca Bigatello Journal: Open Respir Med J Date: 2010-06-25
Authors: Akram Khan; Wendy C King; Emma J Patterson; Jamie Laut; William Raum; Anita P Courcoulas; Charles Atwood; Bruce M Wolfe Journal: J Clin Sleep Med Date: 2013-01-15 Impact factor: 4.062