The B-APNEIC score: distilling the STOP-Bang questionnaire to identify patients at high risk for severe obstructive sleep apnoea

Age- and sex-specific associations between obstructive sleep apnea risk and cognitive decline in middle-aged and older adults: A 3-year longitudinal analysis of the Canadian longitudinal study on aging

BACKGROUND

Whether obstructive sleep apnea (OSA) increases the risk of cognitive decline and how sex and age influence this association is not clear. Here, we characterized the sex- and age-specific associations between OSA risk and 3-year cognitive change in middle-aged and older adults.

METHODS

We included 24,819 participants aged 45-85 (52% women) from the Canadian Longitudinal Study on Aging. OSA risk was measured at baseline using the STOP combined to body mass index (STOP-B). Neuropsychological tests assessed memory, executive functioning, and psychomotor speed at baseline and at 3-year follow-up. We conducted age- and sex-specific linear mixed models to estimate the predictive role of baseline STOP-B score on 3-year cognitive change.

RESULTS

Men at high-risk for OSA aged 45-59 years showed a steeper decline in psychomotor speed (+13.2 [95% CI: -1.6, 27.9]) compared to men at low-risk. Men at high-risk for OSA aged 60-69 showed a steeper decline in mental flexibility (-1.2 [-1.9, -0.5]) and processing speed (+0.6 [0.3, 0.9]) than those at low-risk. Women at high-risk for OSA aged 45-59 showed a steeper decline in processing speed (+0.1 [-0.2, 0.4]) than women at low-risk, while women at high-risk ≥70 years had a steeper decline in memory (-0.2 [-0.6, 0.1]) and processing speed (+1.0 [0.4, 1.5]).

CONCLUSIONS

Associations between OSA risk and cognitive decline over 3 years depend on age and sex. Being at high-risk for OSA is associated with a generalized cognitive decline in attention and processing speed, while a memory decline is specific to older women (≥70 years).

Perioperative management of Obstructive Sleep Apnoea: Present themes and future directions

PURPOSE OF REVIEW

Obstructive sleep apnoea (OSA) is an increasingly common pathology that all those involved in perioperative care will come across. Patients with the condition present a challenge at many stages along the perioperative journey, not least because many patients living with OSA are unaware of their diagnosis.Key interventions can be made pre, intra-, and postoperatively to improve outcomes. Knowledge of screening tools, diagnostic tests, and the raft of treatment options are important for anyone caring for these patients.

RECENT FINDINGS

Recent literature has highlighted the increasing complexity of surgical patients and significant underdiagnosis of OSA in this patient population. Work has demonstrated how and why patients with OSA are at a higher perioperative risk and that effective positive airways pressure (PAP) therapy can reduce these risks, alongside evidencing how best to optimise adherence to therapy, a key issue in OSA.

SUMMARY

OSA, and particularly undiagnosed OSA, presents a huge problem in the perioperative period. Perioperative PAP reduces the risk of postoperative complications but adherence remains an issue. Bespoke perioperative pathways should be developed to identify and optimise high risk patients, although at present evidence on how best to achieve this is lacking.

A risk-predictive model for obstructive sleep apnea in patients with chronic obstructive pulmonary disease

Background

Obstructive sleep apnea syndrome (OSA) is increasingly reported in patients with chronic obstructive pulmonary disease (COPD). Our research aimed to analyze the clinical characteristics of patients with overlap syndrome (OS) and develop a nomogram for predicting OSA in patients with COPD.

Methods

We retroactively collected data on 330 patients with COPD treated at Wuhan Union Hospital (Wuhan, China) from March 2017 to March 2022. Multivariate logistic regression was used to select predictors applied to develop a simple nomogram. The area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA) were used to assess the value of the model.

Results

A total of 330 consecutive patients with COPD were enrolled in this study, with 96 patients (29.1%) confirmed with OSA. Patients were randomly divided into the training group (70%, n = 230) and the validation group (30%, n = 100). Age [odds ratio (OR): 1.062, 1.003–1.124], type 2 diabetes (OR: 3.166, 1.263–7.939), neck circumference (NC) (OR: 1.370, 1.098–1,709), modified Medical Research Council (mMRC) dyspnea scale (OR: 0.503, 0.325–0.777), Sleep Apnea Clinical Score (SACS) (OR: 1.083, 1.004–1.168), and C-reactive protein (CRP) (OR: 0.977, 0.962–0.993) were identified as valuable predictors used for developing a nomogram. The prediction model performed good discrimination [AUC: 0.928, 95% confidence interval (CI): 0.873–0.984] and calibration in the validation group. The DCA showed excellent clinical practicability.

Conclusion

We established a concise and practical nomogram that will benefit the advanced diagnosis of OSA in patients with COPD.

Accuracy and modification of the STOP ‐bang questionnaire for screening patients with obstructive sleep apnea in China

Despite the high sensitivity of the STOP-Bang questionnaire [snoring, tiredness, observed apneas, high blood pressure, body mass index, age, neck size, gender] questionnaire (SBQ), which is widely used to screen individuals at high risk of obstructive sleep apnea (OSA), few studies have evaluated the discrimination related to sex in the SBQ. Therefore, our study aimed to assess whether SBQ performance is gender-related and modified by changing body mass index (BMI) and neck circumference (NC) cut-off values. A total of 470 patients attended the sleep centres. They were divided into moderate-to-severe OSA and non-moderate-to-severe OSA groups based on the apnea-hypopnea index (AHI) and the results of the SBQ screening. The predictive performance of the SBQ screening instrument was evaluated by 2 × 2 contingency tables and discriminatory ability, which was estimated from the area under the curve (AUC) obtained from receiver operating characteristic curve. Our results suggest that when screening for moderate-to-severe OSA, the original SBQ has higher sensitivity and lower specificity for men; however, women have higher specificity and lower sensitivity. The SBQ achieved the maximum AUC of 0.783 for men and 0.634 for women when the BMI cut-off value was established at 30 kg/m² and the NC cut-off value was established at 38 cm in men, and the BMI cut-off value was established at 25 kg/m² and the NC cut-off value at 36 cm in women. Balancing the optimal sensitivity and specificity, the cut-off value of the optimal modified SBQ total scores for men was determined to be ≥4 and ≥3 for women.

Incorporating neck circumference or neck-to-height ratio into the GOAL questionnaire to better detect and describe obstructive sleep apnea with application to clinical decisions

Objective

Although neck circumference (NC) and neck-to-height ratio (NHR) have been recognized as effective predictors of the clinical diagnosis of adult obstructive sleep apnea (OSA), they have not been included in the widely used GOAL questionnaire. Not coincidentally, the NHR has not been adequately considered in the development and validation of the STOP-Bang questionnaire, No-Apnea score and the NoSAS score. The motivation for the study was (1) to combine the GOAL questionnaire with the NC and NHR, respectively, to evaluate its predictive performance and (2) to compare it with the STOP-Bang questionnaire, the No-Apnea score, the NOSAS score, and the GOAL questionnaire.

Materials and methods

This retrospectively allocated cross-sectional study was conducted from November 2017 to March 2022 in adults who underwent nocturnal polysomnography (PSG) or home sleep apnea testing (HSAT). In this paper, the GOAL questionnaire was combined with the NC and NHR, respectively, using logistic regression. The performance of the six screening tools was assessed by discriminatory ability [area under the curve (AUC) obtained from receiver operating characteristic (ROC) curves] and a 2 × 2 league table [including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), and negative likelihood ratio (LR−)] and compared under AHI ≥5/h, AHI ≥15/h, and AHI ≥30/h conditions.

Results

A total of 288 patients were enrolled in the study. For all severity OSA levels, the sensitivity of GOAL+NC ranged from 70.12 to 70.80%, and specificity ranged from 86.49 to 76.16%. The sensitivity of GOAL+NHR ranged from 73.31 to 81.75%, while specificity ranged from 83.78 to 70.86%. As for area under the curve (AUC) value under ROC curve, when AHI ≥5/h, compared with GOAL (0.806), No-Apnea (0.823), NoSAS (0.817), and GOAL+NC (0.815), GOAL+NHR (0.831) obtained the highest AUC value, but lower than STOP-Bang (0.837).

Conclusion

The predictive power of incorporating NC or NHR into the GOAL questionnaire was significantly better than that of the GOAL itself. Furthermore, GOAL+NHR was superior to GOAL+NC in predicting OSA severity and better than the No-Apnea score and the NoSAS score.