J Clin Monit Comput - Pulse oximetry saturation patterns detect repetitive reductions in airflow.

Tópicos

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Resumo

JECTIVE: Postoperative patients exhibiting signs or symptoms of obstructive sleep apnea (OSA) have been identified to be at increased risk for respiratory compromise. One of the key markers associated with OSA is repetitive reductions in airflow (RRiA). A real-time pulse oximeter saturation pattern recognition algorithm (OxiMax SPD? intended for adult in-hospital use only) designed to detect specific signatures in the SpO(2) trend associated with RRiA may provide caregivers early indication of its presence so they can treat the patient appropriately. The purpose of our study was to test the performance of saturation pattern detection (SPD) in a clinical study targeting subjects with a high prevalence of RRiA.METHODS: Overnight polysomnograph (PSG) recordings were collected on 104 sleep lab patients. RRiA was defined in terms of specific criteria from four PSG signals, evaluated in consecutive 10 min epochs. PSG scoring was conducted blind to calculation of SPD. Statistical measures of sensitivity, specificity and area under the receiver operating characteristic (ROC) curve were calculated for the detection of RRiA by SPD.RESULTS: Data were analyzed for 92 valid sets of patient recordings, encompassing 3,917 epochs. At the highest available SPD alert setting, the sensitivity was 80.2% (95% C.I. = 76.8-83.3%), the specificity was 88.3% (87.2-89.3). Area under the ROC curve was 0.87 (0.84-0.89).CONCLUSIONS: The real-time SPD algorithm was able to detect episodes of RRiA in sleep lab patients with a high degree of sensitivity and specificity.

Resumo Limpo

jectiv postop patient exhibit sign symptom obstruct sleep apnea osa identifi increas risk respiratori compromis one key marker associ osa repetit reduct airflow rria realtim puls oximet satur pattern recognit algorithm oximax spd intend adult inhospit use design detect specif signatur spo trend associ rria may provid caregiv earli indic presenc can treat patient appropri purpos studi test perform satur pattern detect spd clinic studi target subject high preval rriamethod overnight polysomnograph psg record collect sleep lab patient rria defin term specif criteria four psg signal evalu consecut min epoch psg score conduct blind calcul spd statist measur sensit specif area receiv oper characterist roc curv calcul detect rria spdresult data analyz valid set patient record encompass epoch highest avail spd alert set sensit ci specif area roc curv conclus realtim spd algorithm abl detect episod rria sleep lab patient high degre sensit specif

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