Clinical utility of inappropriate positron emission tomography myocardial perfusion imaging: test results and cardiovascular events.

BACKGROUND: Appropriate use criteria for myocardial perfusion imaging (MPI) were developed to categorize scenarios where MPI might be beneficial (appropriate) or not (inappropriate). Few investigations have evaluated the clinical utility of this categorization strategy, particularly with positron emission tomography (PET) MPI. METHODS AND RESULTS: We conducted this retrospective cohort investigation in a Veterans Affairs (VA) medical center, on predominantly male subjects who underwent PET-MPI. We correlated appropriateness to test result and cardiovascular events. Of 521 subjects, 414 (79.5%) were appropriate, 54 (10.4%) were uncertain, and 53 (10.2%) were inappropriate. PET-MPI was abnormal more often when appropriate or uncertain (28% and 34.6%, respectively, vs 7.7% for inappropriate, P = .003). Among abnormal inappropriate tests, none detected occult ischemia. By Cox regression, summed difference score ≥5 (HR 5.06, 95% CI 2.72-9.44) and an abnormal test result (HR 4.48, 95% CI 2.19-9.14) were associated with higher likelihood of catheterization. Log-rank analysis demonstrated similar likelihood of catheterization when comparing abnormal vs normal test result (P < .0001) and between appropriate, uncertain, and inappropriate tests (P = .024). CONCLUSIONS: Inappropriate PET-MPI was rarely abnormal, associated with low catheterization rates, and failed to detect occult ischemia for any subjects. The clinical utility of inappropriate PET-MPI is negligible.

Photoplethysmography-new applications for an old technology: a sleep technology review.

Education is integral to the American Academy of Sleep Medicine (AASM) mission. The AASM Emerging Technology Committee identified an important and evolving piece of technology that is present in many of the consumer and clinical technologies that we review on the AASM #SleepTechnology (https://aasm.org/consumer-clinical-sleep-technology/) resource-photoplethysmography. As more patients with sleep tracking devices ask clinicians to view their data, it is important for sleep providers to have a general understanding of the technology, its sensors, how it works, targeted users, evidence for the claimed uses, and its strengths and weaknesses. The focus in this review is photoplethysmography-a sensor type used in the familiar pulse oximeter that is being developed for additional utilities and data outputs in both consumer and clinical sleep technologies. CITATION: Ryals S, Chang A, Schutte-Rodin S, et al. Photoplethysmography-new applications for an old technology: a sleep technology review. J Clin Sleep Med. 2023;19(1):189-195.

Knuckle cracking at night associated with sodium oxybate treatment.

NONE: During upward titration of a dose of sodium oxybate therapy for narcolepsy with cataplexy, a 25-year-old woman was observed by her husband to have new onset of knuckle-cracking and moaning behaviors during sleep ≥1 nights each week. The patient did previously occasionally crack her knuckles during the day (but never at night). These behaviors had not been evaluated by polysomnography. After transition of care, polysomnography with video monitoring was ordered and revealed 2 knuckle-cracking episodes that developed out of stage N2 sleep and were likely a non-rapid eye movement sleep parasomnia associated with sodium oxybate treatment.

Use of a Transformed ECG Signal to Detect Respiratory Effort During Apnea.

STUDY OBJECTIVES: To evaluate the ability of a transformed electrocardiography (ECG) signal recorded using standard electrode placement to detect inspiratory bursts from underlying surface chest wall electromyography (EMG) activity and the utility of the transformed signal for apnea classification compared to uncalibrated respiratory inductance plethysmography (RIP). METHODS: Part 1: 250 consecutive adult studies without regard to respiratory events were retrospectively reviewed. The ECG signal was transformed with high pass filtering and viewed with increased sensitivity and channel clipping to determine the fraction of studies with inspiratory burst visualization as compared to chest wall EMG (right thorax). Part 2: 445 consecutive studies were reviewed to select 40 with ≥ 10 obstructive and ≥ 10 mixed or central apneas (clinical scoring). Five obstructive and 5 central or mixed apneas were randomly selected from each study. A blinded scorer classified the apneas using either RIP or a transformed ECG signal using high pass filtering and QRS blanking. The agreement between the two classifications was determined by kappa analysis. RESULTS: Part 1: Inspiratory burst visualization was noted in the transformed ECG signals and chest wall EMG signals in 83% and 71% of the studies (P < .001). Part 2: The percentage agreement between RIP and transformed ECG signal classification was 88.5%, the kappa statistic was 0.81 (95% CI 0.76 to 0.86) and interclass correlation was 0.84, showing good agreement. CONCLUSIONS: A transformed ECG signal can exhibit inspiratory bursts in a high proportion of patients and is potentially useful for detecting respiratory effort and apnea classification.

Use of Chest Wall EMG to Classify Hypopneas as Obstructive or Central.

STUDY OBJECTIVES: To compare classification of hypopneas as obstructive or central based on an effort signal derived from surface chest wall electromyography (CW-EMG-EF) coupled with airflow amplitude versus classification using The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications (AASM Scoring Manual) criteria; and to characterize hypopneas classified as obstructive versus central using a resistance surrogate. METHODS: CW-EMG was recorded in the eighth intercostal space at the right midaxillary line. Five hypopneas were randomly selected from 65 consecutive adult clinical positive airway pressure titration studies meeting study criteria. A blinded scorer classified the hypopneas based on two groups of signals: Group 1: positive airway pressure flow (PAP flow), chest and abdominal effort, and snoring; or Group 2: smoothed PAP flow (for blinding amplitude but not flattening visible) and effort (CW-EMG-EF). A resistance surrogate (CW-EMG-EF / PAP flow) normalized to a pre-event breath was compared between obstructive and central hypopneas classified by AASM Scoring Manual criteria. RESULTS: The percentage agreement (Group 1 versus Group 2) was 92% and the kappa was 0.75 (95% confidence interval 0.65 to 0.85). The resistance surrogate was significantly higher in obstructive hypopneas versus central hypopneas during the first and second half of hypopneas. The resistance surrogate (mean ± standard deviation) for the second half of hypopnea was obstructive: 7.59 ± 7.24 versus central: 1.27 ± 0.56, P < .001). The resistance surrogate increased from the first to second half of hypopnea only for obstructive hypopneas. CONCLUSIONS: CW-EMG provides a useful complementary signal for hypopnea classification and a resistance surrogate based on CW-EMG is much higher in hypopneas classified as obstructive by AASM Scoring Manual criteria.

Use of Chest Wall Electromyography to Detect Respiratory Effort during Polysomnography.

STUDY OBJECTIVES: To evaluate the ability of chest wall EMG (CW-EMG) using surface electrodes to classify apneas as obstructive, mixed, or central compared to classification using dual channel uncalibrated respiratory inductance plethysmography (RIP). METHODS: CW-EMG was recorded from electrodes in the eighth intercostal space at the right mid-axillary line. Consecutive adult clinical sleep studies were retrospectively reviewed, and the first 60 studies with at least 10 obstructive and 10 mixed or central apneas and technically adequate tracings were selected. Four obstructive and six central or mixed apneas (as classified by previous clinical scoring) were randomly selected. A blinded experienced scorer classified the apneas on the basis of tracings showing either RIP channels or the CW-EMG channel. The agreement using the two classification methods was determined by kappa analysis and intraclass correlation. RESULTS: The percentage agreement was 89.5%, the kappa statistic was 0.83 (95% confidence interval 0.79 to 0.87), and the intraclass correlation was 0.83, showing good agreement. Of the 249 apneas classified as central by RIP, 26 were classified as obstructive (10.4%) and 7 as mixed (2.8%) by CW-EMG. Of the 229 events classified as central by CW-EMG, 7 (3.1%) were classified as obstructive and 6 (2.6%) as mixed by RIP. CONCLUSIONS: Monitoring CW-EMG may provide a clinically useful method of detection of respiratory effort when used with RIP and can prevent false classification of apneas as central. RIP can rarely detect respiratory effort not easily discernible by CW-EMG and the combination of the two methods is more likely to avoid apnea misclassification.