Central sleep apnea is a fundamentally different beast from the far better-known obstructive form. In obstructive sleep apnea, the airway physically collapses even though the brain keeps issuing breathing commands; in the central form, the brain itself fails to send stable signals to the respiratory muscles, so the diaphragm simply stops contracting for stretches of ten, twenty, sometimes thirty seconds. The condition is especially common in patients with systolic heart failure, where unstable blood gases and heightened chemosensitivity make the respiratory control system oscillate like a poorly damped pendulum. Each apnea drains oxygen from the blood, jolts the sympathetic nervous system, and fragments sleep, and in heart failure populations this nocturnal burden is associated with worse outcomes.

Transvenous phrenic nerve stimulation, embodied commercially by the remedē System, was developed as an alternative to positive airway pressure therapy, which many central sleep apnea patients tolerate poorly or cannot use at all. The device is implanted much like a cardiac pacemaker: a lead is threaded into a vein and positioned adjacent to the phrenic nerve, and a pulse generator sewn beneath the skin in the upper chest delivers electrical bursts synchronized to inspiration. By recruiting the diaphragm directly, the stimulator stabilizes ventilation during sleep without requiring a mask, hose, or machine at the bedside. The pivotal randomized controlled trial published in The Lancet in 2016 by Costanzo, Ponikowski, Javaheri, and colleagues demonstrated significant reductions in the apnea-hypopnea index compared with a control group, and subsequent reports have extended safety and efficacy observations to five years.

The critique that provoked the reply, however, zeroes in on a subtle but important methodological point: the difference between how often patients use a therapy and whether the therapy actually changes the outcomes that matter. In drug research this distinction is familiar, since a prescription filled is not a prescription taken, and a pill taken is not necessarily a life prolonged. The commentators applied the same logic to neurostimulation, suggesting that high nightly usage figures, while impressive as measures of tolerability and adherence, do not by themselves establish that the device improves survival, cardiac function, or quality of life. Usage, in their framing, is a necessary but insufficient condition for efficacy, and conflating the two risks overstating what the evidence shows.

The reply authors counter that usage data in their studies were never offered as a substitute for efficacy endpoints but as a complement to them, and they point to the broader evidentiary record assembled over nearly a decade. That record includes the original randomized trial, long-term follow-up published in the journal Sleep by Fox, Oldenburg, Javaheri, and colleagues, the five-year safety and efficacy analysis in Nature and Science of Sleep, and, most recently, a win ratio analysis published in ESC Heart Failure by Abraham, Oldenburg, Lainscak, and colleagues that evaluated transvenous phrenic nerve stimulation against a composite hierarchy of clinical outcomes in heart failure patients. The win ratio method, increasingly popular in cardiology, ranks patients by a cascade of endpoints from death through worsening heart failure to symptom change, allowing a trial to detect clinically meaningful benefit even when individual components are individually underpowered.

The stakes of this statistical and conceptual argument are amplified by the checkered history of central sleep apnea treatment. Adaptive servo-ventilation, a sophisticated bilevel pressure machine that was once the dominant therapy for central apnea in heart failure, was dealt a devastating blow by the SERVE-HF trial published in the New England Journal of Medicine in 2015, in which Cowie, Woehrle, Wegscheider, and colleagues found that the therapy was associated with increased mortality in patients with predominant central apnea and systolic heart failure. That result transformed the field overnight: a device that measurably reduced apneas on paper turned out to harm the very patients it was meant to help. Ever since, the sleep medicine community has been rightly skeptical of surrogate endpoints, and any argument that leans on apnea index reductions or adherence statistics rather than hard clinical outcomes invites intense scrutiny.

It is against that backdrop that the American Academy of Sleep Medicine convened a clinical practice guideline, published in 2025 with Badr, Khayat, Allam, and colleagues as authors, to formalize recommendations for treating central sleep apnea in adults. Guideline panels must weigh exactly the tension at issue in this journal exchange: how much weight to give device usage and physiological endpoints, how much to randomized outcome data, and how to handle therapies whose evidence base is still maturing. The reply’s authors, several of whom participated in that guideline process, argue that the totality of evidence, including high nightly usage rates documented in their automatic activation study published earlier in 2026, supports a favorable risk-benefit profile for appropriately selected patients.

The automatic activation study itself deserves attention because it speaks directly to the usage question. Published in the Journal of Clinical Sleep Medicine with Khayat as first author, it examined a feature that allows the stimulator to activate itself when the patient falls asleep, removing the burden of remembering to turn the device on each night. The result was high nightly usage, which the investigators interpreted as evidence that the therapy integrates smoothly into patients’ lives, a prerequisite for any chronic implanted therapy to deliver benefit. Critics respond that usage, however high, remains an intermediate variable; defenders respond that no therapy, however efficacious in principle, can work if it is not actually running during the hours when central apneas occur.

Both positions contain legitimate technical truth, and the exchange illustrates a broader dilemma in device medicine that drug regulation solved decades ago with adherence-adjusted analyses and per-protocol versus intention-to-treat frameworks. An implanted stimulator is unusual among therapies in that usage can be logged objectively, second by second, by the device itself, producing adherence data of a fidelity that pill counts and self-report can never match. That transparency is a scientific asset, but it also creates a temptation, conscious or not, to foreground the numbers that look best. The commentators’ warning is essentially a caution against letting beautiful adherence dashboards substitute for the harder question of whether the therapy changes the trajectory of heart failure and survival.

The reply, received in April 2026 and published on 28 July 2026 as volume 22, article 126 of the journal, does not resolve the debate, and it was not designed to. What it does is clarify where the disagreement actually lies: not over the raw data, which both sides acknowledge, but over the inferential weight each category of evidence should carry. Readers should also note the declared interests shaping the discussion, since the remedē System Pivotal Trial was sponsored by ZOLL Respicardia, two of the reply’s authors are company employees, and two others serve as consultants, while Costanzo and Khan report no conflicts. For patients with central sleep apnea and failing hearts, the practical takeaway is that phrenic nerve stimulation remains a real option with a growing evidence base, but that the scientific community is still actively negotiating what its evidence means, and that negotiation, conducted in letters and replies like this one, is precisely how the field earns the right to call a therapy effective rather than merely used.

Subject of Research: Debate over usage versus efficacy evidence for transvenous phrenic nerve stimulation in central sleep apnea

Article Title: Reply to “Usage is not efficacy in transvenous phrenic nerve stimulation for central sleep apnea”

Article References: Khayat, R. N., Khan, M., Morgenthaler, T. I., McKane, S., Germany, R., & Costanzo, M. R. (2026). Reply to “Usage is not efficacy in transvenous phrenic nerve stimulation for central sleep apnea”. Journal of Clinical Sleep Medicine, 22(1), Article 126. https://doi.org/10.1007/s44470-026-00099-3

Image Credits: AI Generated

DOI: 10.1007/s44470-026-00099-3

Keywords: central sleep apnea, phrenic nerve stimulation, neurostimulation, heart failure, sleep medicine, remedē System, adaptive servo-ventilation, clinical trial evidence, device adherence, Journal of Clinical Sleep Medicine, win ratio analysis, AASM guideline

The distinction is not academic hair-splitting; it reflects two fundamentally different failures of the respiratory system. In obstructive sleep apnea, the sleeper’s airway physically collapses even as the brain keeps driving the breathing muscles—the effort continues, but airflow falters against a blocked conduit. In central sleep apnea, the problem lies upstream: neural output from the brainstem’s respiratory centers wanes, and airflow falls because the drive to breathe itself has been withdrawn. Central events arise from instability in the ventilatory control system, often quantified by an engineering concept known as loop gain. A system with high loop gain overreacts to fluctuations in carbon dioxide, overshooting corrections and oscillating into periodic breathing, whereas low loop gain indicates a stable control system resistant to such instability. Both obstructive and central apnea patients can exhibit elevated loop gain, and the degree of abnormality may predict how a given patient responds to different treatments.

While scoring rules for frank apneas—complete pauses in breathing—are well agreed upon, the AASM scoring manual treats classification of hypopneas as optional, and most sleep centers simply do not perform it. The panel argues this default has real consequences. In a large French cohort of more than 2,000 people with sleep apnea, the prevalence of central sleep apnea jumped from 5 percent to nearly 20 percent once hypopneas, in addition to apneas, were manually classified. That fourfold increase suggests a substantial population of patients whose underlying central ventilatory instability has been invisible to their diagnoses because their shallow breaths were assumed to be obstructive.

How, then, can a scorer tell the two event types apart on a routine polysomnogram? The current AASM criteria list snoring, flattening of the nasal pressure waveform, and thoracoabdominal desynchrony—out-of-phase motion of the chest and abdominal belts—as hallmarks of obstruction; when none of these features is present, the event should be scored as central. Winfried Randerath and colleagues developed a more elaborate algorithm, validated against esophageal manometry, the gold standard for measuring respiratory effort. Their stepwise approach adds the shape of the recovery breaths that follow an event, the position of the arousal relative to the recovery breaths, and the sleep stage in which the event occurs. Against esophageal pressure measurements, the algorithm correctly identified 60.5 percent of obstructive hypopneas and 76.9 percent of central hypopneas, for an overall accuracy of 68 percent. The two most informative signals in both frameworks are inspiratory flow flattening and respiratory paradox, with published sensitivities and specificities of 0.65 and 0.67 for flow flattening and 0.81 and 0.46 for paradox, underscoring that no single channel suffices and careful integration of multiple signals is essential.

Further physiological markers have been proposed by Javaheri and colleagues. Synchronous changes in airflow and effort, snoring during the recovery breaths rather than during the event itself, and a symmetric desaturation-resaturation pattern on the oximetry trace point toward central disease, whereas snoring during the event, arousals at event termination, and progressive prolongation of the inspiratory duty cycle—the fraction of the breath devoted to inspiration—characterize obstruction. That last feature has been confirmed experimentally in studies using inspiratory resistive loading, which mimics airway obstruction and reliably lengthens inspiratory time. A head-to-head comparison by Dupuy-McCauley and colleagues found the AASM and Randerath methods performed similarly, at 67 to 69 percent accuracy, but with only fair interrater reliability, a kappa of 0.30—meaning two trained scorers often disagree. Signal quality, particularly the notoriously variable nasal pressure signal, is a likely culprit.

To move the field forward, the panel proposes an operational definition: a central hypopnea shows no snoring during the event, waxing-and-waning airflow during recovery breaths, waxing-and-waning effort in the belts, and an arousal occurring in the middle of the recovery breaths rather than at their end. Just as importantly, it proposes a new category, the unclassified or indeterminate hypopnea, for events that meet no strict criteria, rather than forcing them into the obstructive bucket. Under this framework, a sleep report would include the overall apnea-hypopnea index along with separate obstructive, central, and unclassified indices that sum to the total. The panel stresses this is a provisional construct, not a guideline, and requires prospective validation.

Why does this matter now? Because sleep medicine is entering an era of mechanistically targeted therapies, and each therapy aims at a different piece of the physiology. Transvenous phrenic nerve stimulation, which paces the diaphragm to stabilize breathing, works on central ventilatory instability; hypoglossal nerve stimulation, which protrudes the tongue to hold the airway open, works on obstruction. In the pivotal trial of phrenic nerve stimulation, the likelihood of achieving at least a 50 percent reduction in the apnea-hypopnea index rose steadily with the baseline proportion of central events—from 37.5 percent when fewer than half of events were central to 76.5 percent when 90 percent or more were central. When hypopneas were classified retrospectively in this cohort, most residual events after implantation were found to be obstructive, and intriguingly, the proportion of central apneas did not correlate with the proportion of central hypopneas, meaning the two event types must be characterized independently rather than assumed to travel together. The same logic applies in reverse for hypoglossal nerve stimulation: a patient with a heavy load of unrecognized central hypopneas is a candidate for a disappointing result.

The stakes extend to routine positive airway pressure care. The AASM’s recent clinical practice guideline recommends adaptive servo-ventilation for central sleep apnea in patients with normal heart function when CPAP fails; if central events have been correctly enumerated from the outset, prolonged, fruitless trials of CPAP could potentially be avoided. The panel also draws attention to treatment-emergent central sleep apnea, which arises in roughly 4 to 19 percent of obstructive sleep apnea patients during CPAP initiation and persists in about one-third of those affected after months of therapy. Distinguishing pre-existing, treatment-resistant central disease from events that genuinely emerge after CPAP initiation matters for prognosis and management: emergent events are often transient and warrant re-evaluation after a few weeks, whereas persistent disease may respond to adaptive servo-ventilation, supplemental oxygen, or the carbonic anhydrase inhibitor acetazolamide. Longitudinal vigilance is essential, since central apnea can develop years into CPAP therapy with the onset of atrial fibrillation or left ventricular dysfunction, or with the use of opioids, baclofen, or ticagrelor—exposures that should prompt a fresh look at the pattern of breathing disturbances.

The panel is candid about the obstacles. Manual classification adds time and training demands for sleep technologists, and visual assessment suffers from inconsistent interrater reliability across centers. Overclassifying central hypopneas risks inappropriate therapy escalation and added cost; underclassifying them risks residual symptoms and missed combination therapy. The solution, many panelists believe, lies in automation. Several developmental pathways were outlined: event-level analysis extracting features from airflow, effort belts, diaphragmatic EMG, snoring, EEG, and heart rate signals; subject-level metrics such as central and obstructive indices that exploit the characteristic low cycle-length variability and sinusoidal airflow of central apnea, using tools like wavelet decomposition, cardiopulmonary coupling, and machine learning; multimodal models incorporating medications, comorbidities, and demographics; counterfactual prediction to resolve ambiguous events; and approaches that directly model therapeutic response. All of these depend on a prerequisite the panel emphasizes: harmonized, minimum signal-quality standards across laboratories, because algorithms trained on noisy, inconsistent signals will not generalize. With validation studies and human oversight, the panel concludes, routine hypopnea classification could become the foundation of a genuinely precision-based approach to sleep-disordered breathing, matching each patient’s endophenotype to the therapy most likely to quiet their nights and restore their days.

Subject of Research: Classification of obstructive versus central hypopneas in sleep-disordered breathing diagnosis and therapy selection

Article Title: The importance of classifying central hypopneas: a call to action

Article References: Ahn, A. P., Azarbarzin, A., Badr, M. S., Berry, R., DeYoung, P., Dupuy-McCauley, K., Morgenthaler, T. I., Pépin, J. L., Randerath, W., Sands, S., Tallavajhula, S., & Malhotra, A. (2026). The importance of classifying central hypopneas: a call to action. Journal of Clinical Sleep Medicine, 22(1), Article 149. https://doi.org/10.1007/s44470-026-00177-6

Image Credits: AI Generated

DOI: 10.1007/s44470-026-00177-6

Keywords: central sleep apnea, obstructive sleep apnea, hypopnea classification, polysomnography, loop gain, phrenic nerve stimulation, hypoglossal nerve stimulation, adaptive servo-ventilation, CPAP, treatment-emergent central sleep apnea, machine learning, sleep medicine

The finding comes from a team led by Ali Azarbarzin of Brigham and Women’s Hospital and Harvard Medical School, working with colleagues at several institutions, including Atul Malhotra of the University of California, San Diego. The researchers pooled data from two of the most extensively characterized sleep cohorts in the world: the Sleep Heart Health Study, which enrolled community-dwelling adults with an average age of 64, and the Osteoporotic Fractures in Men Study, known as MrOS, which followed older men with an average age of 76. Together the analysis included 7,530 participants, roughly 47 percent of whom were men in the combined framing of the two cohorts, each of whom had undergone overnight polysomnography with continuous pulse oximetry.

The technical concept at the heart of the study is deceptively simple. Every apnea episode, whether central or obstructive, produces a fall in oxygen saturation followed by a recovery. Conventional metrics such as the apnea-hypopnea index count how often these events occur, and more recent work has quantified the hypoxic burden, meaning the cumulative depth and duration of the desaturations themselves. Oxygen overshoot burden flips the perspective: it measures the area under the curve of oxygen saturation above baseline, capturing how far and how long the blood oxygen climbs back — and sometimes beyond — after each event. The researchers computed this overshoot against two reference points, a stable baseline recorded during sleep and, in secondary analyses, a baseline recorded during quiet wakefulness, to confirm that the signal was not an artifact of how the baseline was chosen.

Over a median follow-up of nearly nine years — 8.92 years — the cohorts recorded 2,258 major adverse cardiovascular events, a composite that captures the kind of outcomes that matter most to patients: heart attacks, heart failure episodes, strokes, and cardiovascular death. When the team modeled oxygen overshoot burden as a continuous variable, they found that higher burden was associated with increased cardiovascular risk across the population, but the association was markedly stronger among individuals who exhibited any central apneas during their sleep studies. The interaction was statistically significant for both the sleep baseline and the wakefulness baseline calculations, with p values of 0.003 and 0.02 respectively, suggesting the finding is robust to how the reference point is defined.

The most striking results emerged when the researchers stratified participants by diagnosis and by overshoot burden. People with central sleep apnea whose oxygen overshoot burden was at or above the cohort median experienced a dramatically elevated rate of cardiovascular events: 54.6 percent of them suffered a major adverse cardiovascular event during follow-up, compared with 25.6 percent of controls. After adjustment for a comprehensive set of covariates, the hazard ratio was 1.45, with a 95 percent confidence interval of 1.16 to 1.82 and a p value of 0.001. In contrast, three other groups showed cardiovascular risk that was statistically comparable to the controls: patients with central sleep apnea but low overshoot burden, and patients with obstructive sleep apnea whether their overshoot burden was high or low.

That last contrast is what makes the study potentially paradigm-shifting. Obstructive sleep apnea, caused by the physical collapse of the upper airway, and central sleep apnea, in which the brain temporarily stops sending the signals that drive breathing, have long been lumped together in clinical scoring systems that count respiratory events without much regard to their mechanism. Yet the new data suggest that the cardiovascular consequences of the two disorders may travel along different physiological paths, and that the overshoot of oxygen after each pause in breathing may be a signature of the central form that carries particular danger. The result held up even after the researchers adjusted for the apnea-hypopnea index, the central apnea index, loop gain — a measure of the instability of the respiratory control system — and the hypoxic burden, indicating that oxygen overshoot captures risk information that these established metrics do not.

The biological rationale for the finding lies in oxidative stress. Repeated cycles of deoxygenation and reoxygenation, known as intermittent hypoxia followed by reoxygenation, are thought to generate reactive oxygen species in much the same way that reperfusion injury damages tissue after a blocked artery is reopened. Animal studies dating back to the early 1990s have shown that episodic hypoxia elevates blood pressure and drives inflammation and atherosclerosis, and human studies have documented oxidative stress, endothelial dysfunction, and vascular inflammation in sleep apnea patients. The overshoot may be the moment when this chemistry is most active: as oxygen floods back into blood that has just been depleted, the surge could catalyze the oxidative bursts that injure the vessel wall. Central sleep apnea, which is especially prevalent in patients with heart failure and is associated with unstable respiratory control and high loop gain, may produce particularly pronounced or repetitive overshoots, creating a vicious cycle in which the breathing disorder and the heart disease feed each other.

The clinical implications are substantial. Central sleep apnea has been a stubborn therapeutic problem: large randomized trials of adaptive servo-ventilation and continuous positive airway pressure in heart failure patients have produced mixed or sobering results, and the field has increasingly recognized that not all patients with the same diagnosis carry the same risk. By identifying a high-risk phenotype — central apnea with high oxygen overshoot — the study offers a potential tool for stratifying patients in future trials, and it raises the possibility that therapies aimed specifically at blunting the overshoot, whether through oxygen titration, ventilatory support, or phrenic nerve stimulation, could be tested in the patients most likely to benefit. Recent trials of nocturnal oxygen therapy and transvenous phrenic nerve stimulation are already probing this territory, and overshoot burden could become an endpoint or an enrollment criterion in the next generation of studies.

The authors are careful to note the limitations. The two cohorts are older and, in the case of MrOS, exclusively male, so the findings need validation in larger and more diverse populations. Pulse oximetry itself carries a known bias across skin pigmentation, a concern highlighted by prior research showing that oximeters can overestimate oxygen saturation in people with darker skin, which could affect the precision of overshoot measurements. The study is observational, so it demonstrates association rather than causation, and residual confounding cannot be fully excluded. Still, the size of the cohorts, the length of follow-up, the consistency of the signal across baseline definitions, and the specificity of the effect to central apnea make the result one of the most compelling pieces of evidence yet that the aftermath of each apnea — not just the event itself — shapes cardiovascular fate.

For patients and clinicians, the message is that the texture of sleep-disordered breathing matters, not merely its frequency. A night of breathing pauses that end in modest, controlled recoveries of oxygen appears very different from one in which each pause is followed by a dramatic rebound, and the difference may separate a benign pattern from a dangerous one. As the field moves toward physiological phenotyping of sleep apnea, oxygen overshoot burden joins hypoxic burden and loop gain in a growing toolkit of quantitative measures that promise to replace blunt event counts with a more precise picture of what is actually happening in the blood, the brainstem, and the heart. The next step, the researchers say, is validation — and, ultimately, interventional trials that test whether taming the overshoot can tame the risk.

Subject of Research: Oxygen overshoot burden in central sleep apnea and its association with major adverse cardiovascular events

Article Title: Oxygen overshoot burden of central sleep apnea and its association with cardiovascular outcomes

Article References: Azarbarzin, A., McKane, S., Stone, K. L., Germany, R., Redline, S., & Malhotra, A. (2026). Oxygen overshoot burden of central sleep apnea and its association with cardiovascular outcomes. Journal of Clinical Sleep Medicine, 22(1), Article 153. https://doi.org/10.1007/s44470-026-00161-0

Image Credits: AI Generated

DOI: 10.1007/s44470-026-00161-0

Keywords: central sleep apnea, oxygen overshoot burden, cardiovascular outcomes, sleep-disordered breathing, oxidative stress, hypoxic burden, polysomnography, pulse oximetry, heart failure, intermittent hypoxia, risk stratification, Sleep Heart Health Study

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