Daytime Hypercapnia Impairs Working Memory in Young and Middle-Aged Patients with Obstructive Sleep Apnea Hypopnea Syndrome.

Purpose: Obstructive sleep apnea hypopnea syndrome (OSAHS) can lead to cognitive impairment, though few studies have so far examined hypercapnia as its causal mechanism, due to the invasive nature of conventional arterial CO2 measurement. The study aims to investigate the effects of daytime hypercapnia on working memory in young and middle-aged patients with OSAHS. Patients and Methods: This prospective study screened 218 patients and eventually recruited 131 patients (aged 25-60 years) with polysomnography (PSG)-diagnosed OSAHS. Using a cut-off of 45mmHg daytime transcutaneous partial pressure of carbon dioxide (PtcCO2), 86 patients were assigned into the normocapnic group and 45 patients into the hypercapnic group. Working memory was evaluated using the Digit Span Backward Test (DSB) and the Cambridge Neuropsychological Test Automated Battery. Results: Compared with the normocapnic group, the hypercapnic group performed worse in verbal, visual, and spatial working memory tasks. PtcCO2≥45mmHg was an independent predictor for lower DSB scores (OR=4.057), lower accuracy in the immediate Pattern Recognition Memory (OR=2.600), delayed Pattern Recognition Memory (OR=2.766) and Spatial Recognition Memory (OR=2.722) tasks, lower Spatial Span scores (OR=4.795), and more between errors in the Spatial Working Memory task (OR=2.734 and 2.558, respectively). Notably, PSG indicators of hypoxia and sleep fragmentation did not predict task performance. Conclusion: Hypercapnia may be plays an important role in working memory impairment in patients with OSAHS, perhaps more so than hypoxia and sleep fragmentation. Routine CO2 monitoring in these patients could prove of utility in clinical practices.

Generalized EEG Slowing Across Phasic REM Sleep, Not Subjective RBD Severity, Predicts Neurodegeneration in Idiopathic RBD.

Purpose: Idiopathic rapid eye movement sleep behavior disorder (iRBD) is the prodromal marker of α-synuclein degeneration with markedly high predictive value. We aim to evaluate the value of electroencephalography (EEG) data during rapid eye movement (REM) sleep and subjective RBD severity in predicting the conversion to neurodegenerative diseases in iRBD patients. Methods: At the baseline, iRBD patients underwent clinical assessment and video-polysomnography (PSG). Relative spectral power for nine frequency bands during phasic and tonic REM sleep in three regions of interest, slow-to-fast ratios, clinical and PSG variables were estimated and compared between iRBD patients who converted to neurodegenerative diseases (iRBD-C) and iRBD patients who remained disease-free (iRBD-NC). Receiver operating characteristic (ROC) curves evaluated the predictive performance of slow-to-fast ratios, and subjective RBD severity as assessed with RBD Questionnaire-Hong Kong. Results: Twenty-two (33.8%) patients eventually developed neurodegenerative diseases. The iRBD-C group showed shorter total sleep time (p < 0.001), lower stage 2 sleep percentage (p = 0.044), more periodic leg-movement-related arousal index (p = 0.004), increased tonic chin electromyelographic activity (p = 0.040) and higher REM density in the third REM episode (p = 0.034) than the iRBD-NC group. EEG spectral power analyses revealed that iRBD phenoconverters showed significantly higher delta and lower alpha power, especially in central and occipital regions during the phasic REM state compared to the iRBD-NC group. Significantly higher slow-to-fast ratios were observed in a more generalized way during the phasic state in the iRBD-C group compared to the iRBD-NC group. ROC analyses of the slowing ratio in occipital areas during phasic REM sleep yielded an area under the curve of 0.749 (p = 0.001), while no significant predictive value of subjective RBD severity was observed. Conclusion: Our study shows that EEG slowing, especially in a more generalized manner during the phasic period, may be a promising marker in predicting phenoconversion in iRBD, rather than subjective RBD severity.

Two effective clinical prediction models to screen for obstructive sleep apnoea based on body mass index and other parameters.

BACKGROUND AND OBJECTIVE: The diagnosis of obstructive sleep apnea (OSA) relies on polysomnography which is time-consuming and expensive. We therefore aimed to develop two simple, non-invasive models to screen adults for OSA. METHODS: The effectiveness of using body mass index (BMI) and a new visual prediction model to screen for OSA was evaluated using a development set (1769 participants) and confirmed using an independent validation set (642 participants). RESULTS: Based on the development set, the best BMI cut-off value for diagnosing OSA was 26.45 kg/m2, with an area under the curve (AUC) of 0.7213 (95% confidence interval (CI), 0.6861-0.7566), a sensitivity of 57% and a specificity of 78%. Through forward conditional logistic regression analysis using a stepwise selection model developed from observed data, seven clinical variables were evaluated as independent predictors of OSA: age, BMI, sex, Epworth Sleepiness Scale score, witnessed apnoeas, dry mouth and arrhythmias. With this new model, the AUC was 0.7991 (95% CI, 0.7668-0.8314) for diagnosing OSA (sensitivity, 75%; specificity, 71%). The results were confirmed using the validation set. A nomogram for predicting OSA was generated based on this new model using statistical software. CONCLUSIONS: BMI can be used as an indicator to screen for OSA in the community. We created an internally validated, highly distinguishable, visual and parsimonious prediction model comprising BMI and other parameters that can be used to identify patients with OSA among outpatients. Use of this prediction model may help to improve clinical decision-making.

Analysis of nocturnal hypokinesia and sleep quality in Parkinson's disease.

Nocturnal hypokinesia/akinesia and sleep disorder are believed to be common in Parkinson's disease (PD), but are often underestimated. To date, only a few studies have focused on nocturnal symptoms related to motor function and sleep quality in PD patients, and the assessments were based mainly on the subjective descriptions of the patients. In this study, we assessed the relationships between motor symptoms and sleep quality in 29 PD patients (17 PD patients reporting impaired bed mobility (IBM) and 12 patients without IBM). All the participants were monitored using multisite inertial sensors and polysomnography in sleep-monitoring rooms for whole night. Compared with PD-IBM patients, PD+IBM patients tended to have fewer turning-over episodes and smaller degree turns. Meanwhile, PD+IBM patients had worse Pittsburgh Sleep Quality Index (PSQI) and Parkinson's Disease Sleep Scale (PDSS) scores, and less total sleep time (TST) than PD-IBM patients. Spearman correlation analyses found that the number of turning-over events showed negative correlations with disease duration (r = -0.378, P < 0.05) and Unified Parkinson's Disease Rating Scale (UPDRS) axial scores (r = -0.370, P < 0.05). Moreover, TST (r = 0.505, p < 0.05) and sleep efficiency (SE) (r = 0.473, p < 0.05) positively correlated with the number of turns in bed. Multivariate linear regression analyses showed that UPDRS axial scores and the number of turns were significantly associated with TST (both p < 0.05). In conclusion, the number of turns in bed and UPDRS axial scores were two significant factors affecting sleep quality. Multisite inertial sensors can be used to quantitatively evaluate nocturnal motor functions in PD patients.

Determination of four fluoroquinolone antibiotics in tap water in Guangzhou and Macao.

Four fluoroquinolone antibiotics (norfloxacin, ciprofloxacin, lomefloxacin, and enrofloxacin) in tap water in Guangzhou and Macao were analyzed using high performance liquid chromatography fluorescence detection. The results showed that all target antibiotics were detected in high rate both in Guangzhou (77.5%) and Macao (100%), ranging from 1.0 to 679.7 ng/L (SD