Visual and different automatic scoring profiles of respiratory variables in the diagnosis of sleep apnoea-hypopnoea syndrome

Abstract

The purpose of our study was to explore the diagnostic accuracy of different methods of scoring night time recording of respiratory variables (NTRRV) for the diagnosis of the sleep apnoea-hypopnoea syndrome (SAHS).Within a 2 week period, we performed a partially attended night time recording of respiratory variables and a full polysomnography (PSG) for reference in patients with suspected SAHS. Night time recording of respiratory variables was carried out using equipment which records, and continuously displays on a monitor, oximetry, airflow, chest and abdominal motion and body position. Night time recording of respiratory variables was scored manually and automatically, according to different combinations of the parameters described previously. Full polysomnography was performed in the Sleep Laboratory following conventional standards.Thirty six patients were studied. Visual analysis and different automatic scoring profiles of night time recording of respiratory variables were compared to full polysomnography in terms of agreement, sensitivity and specificity. Visual scoring of night time recording of respiratory variables gave the finest agreement-sensitivity-specificity relationship. Automatic scoring of nighttime recording of respiratory variables showed a trend to underestimate the apnoea-hypopnoea index (AHI) with respect to full polysomnography due mainly to underrecognition of hypopnoeas. Agreement-sensitivity-specificity relationships of automatic night time recording of respiratory variables with respect to full polysomnography varied depending on the automatic profile used. Some had a good agreement and sensitivity whilst others had a good specificity.These findings show that visual scoring of night time recording of respiratory variables is the most accurate method of analysis when compared to full polysomnography. The usefulness of the automatic methods of scoring of respiratory variables depends on the end-point chosen and is not reliable enough to be used in all situations. Night time recording of respiratory variables represents a real complement to conventional full polysomnography in clinical practice.

Effectiveness of sequential automatic-manual home respiratory polygraphy scoring

“…As mentioned, a constant in previously published studies and the present study is the underestimation of AHI by automatic scoring in comparison with manual scorings [17,18,20,21], which can make it difficult to identify a cut-off point that rules out SAHS. This happens primarily with the hypopnoea number, indicating deficient algorithms for automatically identifying hypopnoeas.…”

“…Several studies have tested the agreement with simultaneous PSG in sleep labs [17][18][19][20][21]. The common finding has been that it underestimates the average AHI, and shows worse AHI agreement with PSG in Bland-Altman plot.…”

“…Several studies have assessed the agreement of automatic versus manual scoring [16] or PSG [17][18][19][20][21][22][23]. The studies which assessed the agreement of automatic scoring with PSG found good apnoea-hyopnoea index (AHI) cut-off points to confirm SAHS diagnosis in a substantial number of patients, but did not find good cut-off points for ruling out the condition [17,20]. Thus, one potential use of automatic scoring is to reduce the need for manual scoring, if automatic scoring is done first [18].…”

Misclassification of OSA Severity With Automated Scoring of Home Sleep Recordings

“…Similar to the current fi ndings, previously examined automated algorithms tend to underestimate the AHI compared with manual scoring. 11,12,14 Underestimation of the AHI could lead to misclassifi cation of patients with mild OSA as being normal and thus limit the utility of automated scoring algorithms in screening for OSA. In contrast to the AHI, higher concordance between manual and automated scoring was observed with the ODI.…”

“…OSA severity can also aff ect automated scoring accuracy, which improves with increasing disease severity. 10 Not surprisingly, visual (manual) scoring of portable monitoring data is superior to automated scoring and improves the reliability of automated scoring for both type 3 [11][12][13][14][15][16] and type 4 [17][18][19][20][21][22][23] portable monitors when AHI is used to identify and classify OSA. Similar to the current fi ndings, previously examined automated algorithms tend to underestimate the AHI compared with manual scoring.…”