J Clin Monit Comput - Effect of concurrent oxygen therapy on accuracy of forecasting imminent postoperative desaturation.

Tópicos

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Resumo

Episodic postoperative desaturation occurs predominantly from respiratory depression or airway obstruction. Monitor display of desaturation is typically delayed by over 30 s after these dynamic inciting events, due to perfusion delays, signal capture and averaging. Prediction of imminent critical desaturation could aid development of dynamic high-fidelity response systems that reduce or prevent the inciting event from occurring. Oxygen therapy is known to influence the depth and duration of desaturation epochs, thereby potentially influencing the accuracy of forecasting of desaturation. In this study, postoperative pulse oximetry data were retrospectively modeled using autoregressive methods to create prediction models for [Formula: see text] and imminent critical desaturation in the postoperative period. The accuracy of these models in predicting near future [Formula: see text] values was tested using root mean square error. The model accuracy for prediction of critical desaturation ([Formula: see text] [Formula: see text]) was evaluated using meta-analytical methods (sensitivity, specificity, likelihood ratios, diagnostic odds ratios and area under summary receiver operating characteristic curves). Between-study heterogeneity was used as a measure of reliability of the model across different patients and evaluated using the tau-squared statistic. Model performance was evaluated in [Formula: see text] patients who received postoperative oxygen supplementation and [Formula: see text] patients who did not receive oxygen. Our results show that model accuracy was high with root mean square errors between 0.2 and 2.8%. Prediction accuracy as defined by area under the curve for critical desaturation events was observed to be greater in patients receiving oxygen in the 60-s horizon ([Formula: see text] vs. [Formula: see text]). This was likely related to the higher frequency of events in this group (median [IQR] [Formula: see text] [Formula: see text]) than patients who were not treated with oxygen ([Formula: see text] [Formula: see text]; [Formula: see text]). Model reliability was reflected by the homogeneity of the prediction models which were homogenous across both prediction horizons and oxygen treatment groups. In conclusion, we report the use of autoregressive models to predict [Formula: see text] and forecast imminent critical desaturation events in the postoperative period with high degree of accuracy. These models reliably predict critical desaturation in patients receiving supplemental oxygen therapy. While high-fidelity prophylactic interventions that could modify these inciting events are in development, our current study offers proof of concept that the afferent limb of such a system can be modeled with a high degree of accuracy.

Resumo Limpo

episod postop desatur occur predomin respiratori depress airway obstruct monitor display desatur typic delay s dynam incit event due perfus delay signal captur averag predict immin critic desatur aid develop dynam highfidel respons system reduc prevent incit event occur oxygen therapi known influenc depth durat desatur epoch therebi potenti influenc accuraci forecast desatur studi postop puls oximetri data retrospect model use autoregress method creat predict model formula see text immin critic desatur postop period accuraci model predict near futur formula see text valu test use root mean squar error model accuraci predict critic desatur formula see text formula see text evalu use metaanalyt method sensit specif likelihood ratio diagnost odd ratio area summari receiv oper characterist curv betweenstudi heterogen use measur reliabl model across differ patient evalu use tausquar statist model perform evalu formula see text patient receiv postop oxygen supplement formula see text patient receiv oxygen result show model accuraci high root mean squar error predict accuraci defin area curv critic desatur event observ greater patient receiv oxygen s horizon formula see text vs formula see text like relat higher frequenc event group median iqr formula see text formula see text patient treat oxygen formula see text formula see text formula see text model reliabl reflect homogen predict model homogen across predict horizon oxygen treatment group conclus report use autoregress model predict formula see text forecast immin critic desatur event postop period high degre accuraci model reliabl predict critic desatur patient receiv supplement oxygen therapi highfidel prophylact intervent modifi incit event develop current studi offer proof concept affer limb system can model high degre accuraci

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