The patient himself was an unlikely candidate for a cardiac scare. He had been a consistent, well-controlled CPAP user for thirteen years, treated for obstructive sleep apnea with a fixed pressure of 7.6 millibars delivered through a nasal mask. He was not obese, his weight was stable, and his only medication was aspirin. A recent medical evaluation had already given him a clean bill of health where it counted: a normal neurological assessment, a normal brain MRI, a normal cardiac echocardiogram and a normal ergospirometry test. So when he noticed residual respiratory events accumulating on his device across several consecutive mornings, and the downloaded SD-card data from his ResMed AirSense10 revealed a total apnea-hypopnea index of 8.7 events per hour with central apneas at 8.5 per hour and Cheyne–Stokes respiration flagged at 11 percent of the record, the finding landed as a genuine surprise. The machine’s leak data, at a median of 1.2 liters per minute and a 95th percentile of 8 liters per minute, ruled out the most common technical culprit: a leaky mask corrupting the flow signal.

With device-detected Cheyne–Stokes respiration on the table, the team followed the logical sequence laid out in sleep medicine practice. The gold standard for confirming the pattern is fully attended polysomnography under American Academy of Sleep Medicine criteria, because it captures brain activity and precise sleep staging. Respiratory polygraphy, which records airflow, respiratory effort and oxygen saturation without EEG, is accepted as a reasonable first screening step when a CPAP device raises the alarm, ideally with a microphone attached to help distinguish obstructive from central events. The physicians withdrew CPAP for five days and ran a 659-minute polygraphy recording. The result reframed everything. The study showed a clear obstructive sleep apnea pattern, with an obstructive apnea-hypopnea index of 21.8 per hour within a total index of 27.8 per hour, an oxygen desaturation index of 29.3 per hour, and prominent snoring. There were no Cheyne–Stokes episodes. The central apnea-hypopnea index of 6.5 per hour was driven largely by mixed apneas carrying an initial central component, and the overall tracings produced airflow patterns that could genuinely mimic the periodic breathing signature of Cheyne–Stokes respiration.

Why would a CPAP algorithm be so easily misled? The answer lies in how these machines measure breathing. The AirSense10 does not watch the chest or abdomen; it infers everything from airflow, using a forced oscillation technique in which small pressure pulses are injected into the circuit. When the measured flow falls, the device checks whether the oscillations dissipate. If they fade away, the upper airway is presumed open, and the event is classified as central. If the oscillations persist, the airway is presumed closed and the event is obstructive. To label Cheyne–Stokes respiration, the software additionally searches for a characteristic flow pattern: a specific crescendo-decrescendo cycle length, defined episode durations, and the presence of central events. The criteria and algorithms involved have never been standardized across manufacturers, and each company’s thresholds remain proprietary. The Belgian team points to earlier work from the AlertApnée study, in which researchers documented that apparent onset of Cheyne–Stokes respiration during CPAP telemonitoring was attributable to obstructive events occurring just before the flagged episodes, and that the AirSense10 software recurrently misclassified typical obstructive apneas as Cheyne–Stokes respiration.

Layered on top of the algorithmic blind spot is a physiological phenomenon that makes the mimicry genuinely convincing: ventilatory control instability. Obstructive sleep apnea emerges from an interplay of pathophysiological mechanisms, one of which is loop gain, a measure of how sensitive the breathing control system is to disturbance. Loop gain has three components, describing the control, the exchange and the connection elements of the ventilatory system. When loop gain exceeds one, the system becomes hypersensitive, overcorrecting every perturbation with an excessive ventilatory response that can manifest as periodic breathing or full-blown Cheyne–Stokes respiration. When loop gain stays below one, breathing remains stable. A high loop gain during non-rapid eye movement sleep in a patient with obstructive sleep apnea can therefore generate airflow patterns that look, to an algorithm reading only the flow channel, exactly like the real thing. The researchers hypothesized that this was precisely what happened in their patient: his recent nasal obstruction had destabilized his ventilatory control, and his CPAP device’s pattern-matching software read the resulting pseudo-periodic airflow as central disease.

The treatment course told the story in real time. First, the clinicians raised the fixed CPAP pressure progressively from 7.6 to 11 millibars and switched the patient from a nasal mask to a naso-buccal mask, deliberately bypassing the obstructed nasal passages. The change partially worked. The software stopped flagging Cheyne–Stokes respiration entirely, but residual events persisted, with the flow-based apnea-hypopnea index stuck at 11 per hour. Then came the decisive intervention, and it was almost mundane: nasal corticosteroids for the obstruction itself. One month later, with the CPAP settings completely unchanged, the flow-based index dropped below 5 per hour, the conventional threshold for well-controlled sleep apnea. The breathing instability had not been a new cardiac or neurological disease; it was a mechanical problem in the nose propagating upward into the control of breathing, and once the nose was treated, the entire pseudocentral picture dissolved.

The mechanism the authors propose is a chain of escalating instability. Nasal obstruction increases inspiratory effort, because the patient must pull harder against resistance to move the same volume of air. Greater effort makes arousals from sleep more frequent, and each arousal triggers a burst of hyperventilation. In a system primed with high loop gain, that post-arousal ventilation overshoots, blowing off carbon dioxide below the threshold needed to sustain breathing drive and setting up the next pause in an oscillating loop. Crucially, the authors emphasize, this is not a phenotypic conversion of obstructive sleep apnea into central sleep apnea. The patient’s underlying disease did not change character. Instead, the nasal blockage caused a secondary destabilization of ventilatory control, generating mixed apneas and unstable, pseudo-periodic airflow that the device’s flow-only analysis could not reliably untangle from true Cheyne–Stokes respiration.

The broader implication is a cautionary tale for the era of connected medical devices. CPAP telemonitoring has become a powerful surveillance tool, capable of flagging emergent central apnea and, by extension, serious cardiac disease years before symptoms demand attention. But that power depends on algorithms that, in this case at least, could not see respiratory effort and therefore could not reliably distinguish obstructive or unstable breathing from central periodicity. The authors argue that device-based algorithms relying solely on airflow are known to misclassify obstructive or unstable breathing as Cheyne–Stokes respiration in the absence of effort signals, and they call for two concrete improvements: better detection accuracy and standardized, manufacturer-independent criteria for what counts as device-detected Cheyne–Stokes respiration. Until then, the practical message for clinicians is that a CPAP report announcing new-onset central apnea in a stable, long-treated patient should trigger confirmatory testing rather than reflexive alarm, and that an apparently mundane complaint such as a stuffy nose deserves a place on the differential diagnosis list.

The case, documented with device downloads, polygraphy tracings and a straightforward pharmacological resolution, adds a human-scale illustration to a problem that will only grow as home-based sleep data multiplies. Millions of nightly records flow from CPAP machines into cloud dashboards, screened by software and reviewed by clinicians who may never hear the patient’s own observation that something changed, in this instance the recent onset of nasal obstruction, before the numbers did. The Belgian team’s conclusion is measured but pointed: physicians should be aware of the limits of CPAP data collection reliability. A blocked nose, it turns out, can speak fluent Cheyne–Stokes to an algorithm that listens only to airflow, and only a careful look at the whole patient can tell the difference between a cardiac warning and a treatable case of congestion.

Subject of Research: False detection of Cheyne–Stokes respiration by CPAP devices due to nasal obstruction-induced ventilatory instability

Article Title: False Detection of Cheyne–Stokes Respiration on Continuous Positive Airway Pressure Resolved After Treatment of Nasal Obstruction

Article References: Castermans, E., Impens, D., Libert, W., & Bruyneel, M. (2026). False Detection of Cheyne–Stokes Respiration on Continuous Positive Airway Pressure Resolved After Treatment of Nasal Obstruction. Respirology Case Reports, 14(9), Article e70745. https://doi.org/10.1002/rcr2.70745

Image Credits: AI Generated

DOI: 10.1002/rcr2.70745

Keywords: sleep apnea, CPAP, Cheyne–Stokes respiration, nasal obstruction, ventilatory instability, loop gain, respiratory polygraphy, polysomnography, central sleep apnea, telemonitoring, case report, False

The study, led by Azarbarzin and colleagues and published in the Journal of Clinical Sleep Medicine, drew on 7,530 participants from two well-established cohort studies, the Sleep Heart Health Study and the Osteoporotic Fractures in Men Study, known as MrOS. Over nearly nine years of follow-up, 2,258 major adverse cardiovascular events occurred in this population. The investigators computed an oxygen overshoot burden for each participant: the cumulative area under the oxygen saturation curve that lies above an individual’s stable-sleep baseline, normalized for total sleep time. This is a deliberately individualized measure. Rather than comparing every patient against a fixed cutoff, the analysis anchors the signal to each person’s own resting saturation during uneventful sleep, so that even small relative rises above the personal baseline accumulate into a meaningful summary of nightly physiological stress.

The headline result is striking. Among participants with central sleep apnea and high overshoot burden, 54.6 percent experienced a major adverse cardiovascular event during follow-up, compared with 25.6 percent of control participants, corresponding to an adjusted hazard ratio of 1.45. Crucially, central sleep apnea with low overshoot burden carried no elevated risk relative to controls, and no corresponding association appeared in obstructive sleep apnea. The relationship survived statistical adjustment for the apnea-hypopnea index, the central apnea index, hypoxic burden, and, in the MrOS cohort, an estimate of loop gain, the control-system parameter that describes how vigorously breathing responds to disturbances in blood gases. That specificity is intriguing: it suggests the overshoot signal is not merely a proxy for how often someone stops breathing, but may capture something distinct about the instability of their ventilatory control.

The authors and commentators have proposed an intuitive biological explanation rooted in oxidative stress. The cycle of desaturation and reoxygenation that characterizes sleep apnea resembles ischemia-reperfusion injury, and repeated swings are thought to generate reactive oxygen species, inflammation, and vascular damage. Hypoxic burden, which integrates the depth and duration of event-related desaturation, already predicts cardiovascular outcomes better than a simple count of respiratory events, lending weight to the idea that the shape of the oxygen trace carries mechanistic information. Extending that logic above the baseline line is tempting: if falling oxygen is harmful, perhaps overshooting oxygen is harmful too, and the cumulative area of overshoot might quantify a dose of oxidative injury delivered night after night.

Yet a careful reading of the physiology counsels caution before accepting that interpretation. Oxygen overshoot as measured here is a relative oximetry signal, not demonstrated hyperoxia. A rise in peripheral oxygen saturation above a person’s stable-sleep baseline does not establish an elevated arterial partial pressure of oxygen, nor does it demonstrate increased tissue oxygen exposure. The study provides no mechanistic pathway, no oxidative biomarker measurements, and no bench or animal evidence showing that this specific above-baseline signal causes oxidative injury. Evidence from the intermittent hypoxia and reoxygenation literature cannot simply be transferred to this different signal. Indeed, previous work in obstructive sleep apnea found that greater post-event saturation overshoot was associated with lower nocturnal glucose, a pattern that argues against harm and even hints at benefit. Treating the oxygen rise itself as the causal exposure is, for now, premature.

A more plausible reading is that the oximetric overshoot is the visible tail of a much larger ventilatory and autonomic response. When an apnea terminates, the accumulated carbon dioxide and chemoreflex drive produce a vigorous recovery breath; the resulting hypocapnia is a direct signature of unstable ventilatory control, which is precisely the physiology that generates central sleep apnea and Cheyne-Stokes respiration in the first place. Human studies of apnea have documented marked sympathetic nerve activation and blood pressure surges around the termination of each event, followed by vagal modulation tied to lung inflation during the recovery phase. These autonomic oscillations, repeated hundreds of times a night, offer a credible route to myocardial infarction, arrhythmia, and stroke that does not require a modest rise in saturation to be intrinsically toxic. On this view, overshoot burden is a marker of the force of each recovery, not a poison in its own right.

This interpretation also exposes an important analytical gap in the new study. Adjusting for event frequency and hypoxic burden does not establish that overshoot is independent of the severity of each respiratory event. A longer or more severe apnea accumulates more hypercapnia, more chemoreflex stimulation, more arousal-related and sympathetic activation, and a longer loss of the vagal restraint normally provided by lung inflation. Those stimuli can then generate a larger recovery breath and a larger oxygen overshoot, and desaturation depth alone does not fully represent them. Consistent with this, work in obstructive sleep apnea has shown that ventilatory burden, a measure of the effort expended against collapsed airways, predicts cardiovascular outcomes and explains much of the variation in hypoxic burden. Oxygen overshoot may play an analogous role in central sleep apnea, summarizing a hidden physiological load that conventional indices leave unmeasured, without being the injurious agent itself.

Residual cardiac confounding remains another live possibility. In older community cohorts, central sleep apnea and Cheyne-Stokes respiration often reflect underlying cardiac dysfunction, elevated left-sided filling pressures, and prolonged circulation time, rather than mediating the cardiovascular consequences of those conditions. Heart failure identified through self-report and clinical records may miss subclinical disease, so some of the apparent association between overshoot burden and events could reflect undiagnosed cardiac impairment that both destabilizes breathing control and drives outcomes. Adjustment for loop gain in one cohort helps address the ventilatory-instability pathway, but detailed cardiac phenotyping, with objective measures of structure and function, is still needed before the direction of the arrow can be declared with confidence.

Two further cautions temper clinical translation. The central sleep apnea subgroup comprised only 303 participants, so confidence intervals around the headline event proportions deserve as much attention as the proportions themselves, and the findings require replication in larger and more diverse samples. The demonstration that a subject-specific baseline outperformed a fixed threshold of saturation at or above 96 percent confirms that the result depends on small relative differences in the oximetry signal, which places a premium on signal quality and measurement precision. The cohorts were 88 percent White, and known differential pulse-oximeter error by skin pigmentation is relevant to any saturation-based metric, although its effect on an above-baseline area calculation is currently unknown and warrants direct study.

The path forward is clear enough. The next study should measure event duration, airflow, respiratory effort, carbon dioxide, arousals, and event-level autonomic responses alongside oximetry, with detailed cardiac phenotyping and representative recruitment, and then test whether oxygen overshoot adds prognostic information once those features are accounted for. Until that work is done, oxygen overshoot burden should be regarded as a promising risk marker, a way of reading the recovery half of the apnea cycle that standard metrics ignore, rather than a demonstrated oxidative mechanism or a validated treatment target. Even so, the study is a reminder that the familiar oximetry trace still holds unexploited information, and that the line above the dips may matter as much as the dips themselves.

Subject of Research: Oxygen overshoot burden measured on overnight oximetry traces in central sleep apnea and its association with major adverse cardiovascular events.

Article Title: Above the line: oxygen overshoot in the oximetry trace

Article References: Manuel, A. R. G. (2026). Above the line: oxygen overshoot in the oximetry trace. Journal of Clinical Sleep Medicine, 22(1), Article 169. https://doi.org/10.1007/s44470-026-00183-8

Image Credits: AI Generated

DOI: 10.1007/s44470-026-00183-8

Keywords: central sleep apnea, oxygen overshoot, pulse oximetry, Cheyne-Stokes respiration, cardiovascular risk, hypoxic burden, ventilatory control, autonomic surges, oxidative stress, Sleep Heart Health Study, loop gain, sleep apnea