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The comparison between apnoea-hypopnoea index in afternoon nap polysomnography and overnight polysomnography at a health establishment in KwaZulu-Natal

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Background: Sleep-disordered breathing (SDB) is a highly prevalent, though under-recognised, public health problem. The apnoea-hypopnoea index (AHI) is a standard measure used to assess the presence and severity of SDB. It is also a primary measure to assess the effectiveness of SDB treatment. This study aimed to compare the apnoea hypopnoea index (AHI) between the overnight polysomnography (OPSG) and the afternoon-nap polysomnography (ANPSG) tests through the variables measured. This was accomplished by comparing the AHI values and other variables of the ANPSG and OPSG in diagnosing SDB. Method: The study investigated the correlation of the AHI, by measuring the dependent variables using the afternoon nap polysomnography (ANPSG) and overnight polysomnography (OPSG) on the same patients at Inkosi Albert Luthuli Central Hospital (IALCH). A sample size of 25 was deemed adequate for analysis. Patients with the following symptoms and signs, highly suggestive of SDB, were recruited into the study: excessive sleepiness and tiredness during the day, snoring, nocturnal choking or gasping, and restlessness. A validated Epworth screening questionnaire was done at base hospital by the attending physician prior to booking the patient for sleep test. Afternoon nap PSG and overnight PSG data were compared using SPSS (Version 28®), where both descriptive and inferential statistics were used to analyse the data. Results: The majority of patients were females (56%) while males accounted for 44%. Most of the patients were older than 50 years of age (60%) with a mean age of 51.04 ± 10.65 years. The mean BMI was 37.6 ±10.9 (kg/m2), the mean neck circumference was 41.4 ±4.6 cm, the mean weight 103.1 ± 28.6 kg, and the mean height 1.66 ± 0.1m. Furthermore, the correlation coefficient revealed a strong linear association between ANPSG and OPSG. The paired sample test showed that there was a difference between afternoon and overnight polysomnography measured for RDI (p < 0.001), AHI (p = 0.002), NREM (RDI) (p < 0.001), NREM (AHI) (p = 0.001), REM (RDI) (p = 0.005), REM (AHI (p = 0.027), total sleeping time (p < 0.001), and initial REM latency (p < 0.001). The mean value measured for OPSG was higher when compared with the ANPSG for the following variables: RDI (72.85 ± 33.99), AHI (66.76 ± 33.73), NREM (RDI) (72.69 ± 36.48), NREM (AHI) (66.63 ± 36.18), REM (RDI) (76.72 ± 26.65), REM (AHI) (69.64 ± 28.97), total sleep time (421.96 ± 61.03), and initial REM latency (116.74 ± 71.46). ANPSG underestimates the severity parameters of sleep-disordered breathing (SDB). ANPSG may confirm the presence of AHS, however may not grade the true nocturnal severity, and when SDB is at a mild stage, ANPSG may not rule out that SDB will be or will not be present in the OPSG. ANPSG underestimates the value of AHI, RDI and other variables when compared to OPSG, see Annexure 26.
Durban University of Technology
Title: The comparison between apnoea-hypopnoea index in afternoon nap polysomnography and overnight polysomnography at a health establishment in KwaZulu-Natal
Description:
Background: Sleep-disordered breathing (SDB) is a highly prevalent, though under-recognised, public health problem.
The apnoea-hypopnoea index (AHI) is a standard measure used to assess the presence and severity of SDB.
It is also a primary measure to assess the effectiveness of SDB treatment.
This study aimed to compare the apnoea hypopnoea index (AHI) between the overnight polysomnography (OPSG) and the afternoon-nap polysomnography (ANPSG) tests through the variables measured.
This was accomplished by comparing the AHI values and other variables of the ANPSG and OPSG in diagnosing SDB.
Method: The study investigated the correlation of the AHI, by measuring the dependent variables using the afternoon nap polysomnography (ANPSG) and overnight polysomnography (OPSG) on the same patients at Inkosi Albert Luthuli Central Hospital (IALCH).
A sample size of 25 was deemed adequate for analysis.
Patients with the following symptoms and signs, highly suggestive of SDB, were recruited into the study: excessive sleepiness and tiredness during the day, snoring, nocturnal choking or gasping, and restlessness.
A validated Epworth screening questionnaire was done at base hospital by the attending physician prior to booking the patient for sleep test.
Afternoon nap PSG and overnight PSG data were compared using SPSS (Version 28®), where both descriptive and inferential statistics were used to analyse the data.
Results: The majority of patients were females (56%) while males accounted for 44%.
Most of the patients were older than 50 years of age (60%) with a mean age of 51.
04 ± 10.
65 years.
The mean BMI was 37.
6 ±10.
9 (kg/m2), the mean neck circumference was 41.
4 ±4.
6 cm, the mean weight 103.
1 ± 28.
6 kg, and the mean height 1.
66 ± 0.
1m.
Furthermore, the correlation coefficient revealed a strong linear association between ANPSG and OPSG.
The paired sample test showed that there was a difference between afternoon and overnight polysomnography measured for RDI (p < 0.
001), AHI (p = 0.
002), NREM (RDI) (p < 0.
001), NREM (AHI) (p = 0.
001), REM (RDI) (p = 0.
005), REM (AHI (p = 0.
027), total sleeping time (p < 0.
001), and initial REM latency (p < 0.
001).
The mean value measured for OPSG was higher when compared with the ANPSG for the following variables: RDI (72.
85 ± 33.
99), AHI (66.
76 ± 33.
73), NREM (RDI) (72.
69 ± 36.
48), NREM (AHI) (66.
63 ± 36.
18), REM (RDI) (76.
72 ± 26.
65), REM (AHI) (69.
64 ± 28.
97), total sleep time (421.
96 ± 61.
03), and initial REM latency (116.
74 ± 71.
46).
ANPSG underestimates the severity parameters of sleep-disordered breathing (SDB).
ANPSG may confirm the presence of AHS, however may not grade the true nocturnal severity, and when SDB is at a mild stage, ANPSG may not rule out that SDB will be or will not be present in the OPSG.
ANPSG underestimates the value of AHI, RDI and other variables when compared to OPSG, see Annexure 26.

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