PREDICTORS OF PULSE OXIMETRY DATA FAILURE

Background: Pulse oximeters have been reported to fail to record data in 1.12-2.50% of cases in which anesthesia records were handwritten. T here is reason to believe that these may be underestimates. Computeriz ed anesthesia records may provide insight into the true incidence of p ulse oximetry data failures and factors that are associated with such failures. Methods: The current study reviewed case files of 9,203 comp uterized anesthesia records. Pulse oximetry data failure was defined a s the presence of at least one continuous gap in data greater than or equal to 10 min in duration in a case. A multivariate logistic regress ion model was used to identify predictors of pulse oximetry data failu re, and a modified case-control method was used to determine whether e xtremes of blood pressure and hypothermia during the procedure were as sociated with pulse oximetry data failure. Results: The overall incide nce of cases that had at least one continuous gap of greater than or e qual to 10 min in pulse oximetry data was 9.18%. The independent preop erative predictors of pulse oximetry data failure were ASA physical st atus 3, 4, or 5 and orthopedic, vascular, and cardiac surgery. Intraop erative hypothermia, hypotension, hyper-tension, and duration of proce dure were also independent risk factors for pulse oximetry data failur e. Conclusions: Pulse oximetry data failure rates based on review of c omputerized records were markedly greater than those previously report ed. Physical status, type of surgery, and intraoperative variables wer e risk factors for pulse oximetry data failure. Regulations and expect ations regarding pulse oximetry monitoring should reflect the limitati ons of the technology.