Analysis of obstructive sleep apnea patients with "sawtooth sign" on the flow-volume curve

Clinical analysis of the "small plateau" sign on the flow-volume curve followed by deep learning automated recognition

BACKGROUND

Small plateau (SP) on the flow-volume curve was found in parts of patients with suspected asthma or upper airway abnormalities, but it lacks clear scientific proof. Therefore, we aimed to characterize its clinical features.

METHODS

We involved patients by reviewing the bronchoprovocation test (BPT) and bronchodilator test (BDT) completed between October 2017 and October 2020 to assess the characteristics of the sign. Patients who underwent laryngoscopy were assigned to perform spirometry to analyze the relationship of the sign and upper airway abnormalities. SP-Network was developed to recognition of the sign using flow-volume curves.

RESULTS

Of 13,661 BPTs and 8,168 BDTs completed, we labeled 2,123 (15.5%) and 219 (2.7%) patients with the sign, respectively. Among them, there were 1,782 (83.9%) with the negative-BPT and 194 (88.6%) with the negative-BDT. Patients with SP sign had higher median FVC and FEV₁% predicted (both P < .0001). Of 48 patients (16 with and 32 without the sign) who performed laryngoscopy and spirometry, the rate of laryngoscopy-diagnosis upper airway abnormalities in patients with the sign (63%) was higher than those without the sign (31%) (P = 0.038). SP-Network achieved an accuracy of 95.2% in the task of automatic recognition of the sign.

CONCLUSIONS

SP sign is featured on the flow-volume curve and recognized by the SP-Network model. Patients with the sign are less likely to have airway hyperresponsiveness, automatic visualizing of this sign is helpful for primary care centers where BPT cannot available.

Spirometric abnormalities in patients with sleep-related breathing disorders

Introduction:

Patients with sleep-related breathing disorders (SRBD) have various structural and functional abnormalities of the upper airway during sleep which may get reflected on their pulmonary function tests. The aim of the study was to find the correlation between the spirometric indices and snoring, grades of apnea–hypoapnea index (AHI), and STOPBANG. There is scarcity of literature showing correlation of STOP BANG with spirometric variables.

Material and Methods:

Patient with SRBD fulfilling the inclusion and exclusion criteria were enrolled. The pretest probability sleep score STOPBANG and polysomnography (PSG) were calculated for all the patients. Spirometric indices like forced expiratory volume in one sec (FEV1), forced vital capacity (FVC), postbronchodilator ratio FEVI/FVC (PBDR), and peak expiratory flow rate (PEFR) were studied. Their association with snoring, different grades of obstructive sleep apnea (OSA), and STOPBANG were evaluated using statistical analysis.

Results:

A total of 70 patients were enrolled. Abnormalities of spirometric indices were found to be common in patients with SRBD but their association with snoring, grades of OSA, and STOPBANG were not statistically significant. There is no statistically significant correlation between body mass index (BMI) and grades of AHI.

Conclusion:

This study found no statistically significant correlation between spirometric parameters and STOPBANG and degree of AHI. Primary care physicians should be aware that obstructive lung disease does coexist with the sleep disordered breathing but as per this study, their statistically significant association needs further validation.

The sawtooth sign is predictive of obstructive sleep apnea

BACKGROUND

The sawtooth sign in spirometry is associated with redundant upper airway tissue and snoring, but its predictive value for identifying obstructive sleep apnea (OSA) is disputed. We retrospectively assessed the predictive value of the spirometric sawtooth sign in terms of the odds ratio (OR) of association with a diagnosis of OSA compared to those without the sign.

METHODS

Consecutive spirometry reports showing a sawtooth sign were identified from our laboratory. We identified 50 subjects with sawtooth sign and 100 control subjects without sawtooth sign, matched for age, BMI, and gender. The electronic medical record of each patient was queried for a diagnosis of OSA based on physician-reported diagnoses.

RESULTS

Of the 50 subjects with sawtooth sign, 22 were found to have a current diagnosis of OSA (44%). Twenty-seven of the 100 controls (27%) also had OSA. From logistic regression analysis, sawtooth sign was associated with an increased likelihood of OSA (OR = 2.12, 95% C.I. 1.04 to 4.35). Similar results were obtained after adjustment for age, gender, pack years, and BMI (OR = 2.61, 95% C.I. 1.13 to 6.21).

CONCLUSIONS

Patients with the sawtooth sign have greater odds of having a diagnosis of OSA compared with those without the sign. If prospectively evaluated, as a result of improved identification, we hypothesize that the sawtooth sign may show an even stronger association with OSA. This relatively common finding, which adds no cost to routine spirometry, may serve as an indicator for OSA workup for some individuals not already identified as having OSA.