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Pharmacologically Induced Ventilatory Depression in the Postoperative Patient: A Sleep-Wake State-Dependent Perspective

Doufas, Anthony G. MD, PhD*; Weingarten, Toby N. MD

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doi: 10.1213/ANE.0000000000005370
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Abstract

Severe postoperative ventilatory depression, potentially leading to death or neurological damage, seems to be the result of the interaction between patient-related factors and drug effects (ie, pharmacologically induced ventilatory depression [PIVD]). It almost ubiquitously occurs in the context of decreased or completely withdrawn wakefulness drive to breath.1–3 To the extent that certain anatomical, behavioral, and/or physiological phenotypes can influence patient’s response to drug-induced hypoventilation, these phenotypes might be considered as risk markers or potential precursors for such events.4,5 Herein, we review the incidence, clinical risk factors, and potential mechanisms for postoperative PIVD.

INCIDENCE OF POSTOPERATIVE PIVD

The incidence of PIVD is difficult to precisely determine due to its wide spectrum of severity, ranging from mild hypoventilation to ventilatory failure, potentially leading to anoxic brain injury and death. Furthermore, identification of PIVD victims, using standard monitoring practices, can be problematic, especially in those patients with less severe ventilatory depression. The diverse methods and measurements used in the clinical trials, as well as the wide variety of criteria-specific employed definitions for ventilatory depression, can also influence the reported incidence of PIVD.6

In current practice, the majority of postoperative patients are admitted to standard postoperative wards, where they are monitored using manual, intermittent vital signs assessment, performed every few hours. However, the accuracy of this monitoring method in detecting ventilatory depression has been questioned7 and such concerns have been also illustrated by Taenzer et al,8 where 16 patients, who were monitored by both intermittent and continuous oxyhemoglobin saturation by pulse oximetry (Spo2) assessments, experienced episodes of sustained hypoxemia (Spo2 <90% for >15 minutes), which were detected only by the latter. The manually recorded Spo2 was at least 4% greater (mean 6.5%, 95% confidence interval [CI], 4.0-9.0) than the values obtained by continuous Spo2 monitoring. Interestingly, a “wake-up effect” (ie, the rise in Spo2 as a result of the measurement procedure itself) was not observed in that study, because no difference was observed during the continuous Spo2 monitoring before and after the manual Spo2 assessments.

Evidence that manual vital signs assessments do not reliably detect ventilatory depression was demonstrated by the American Society of Anesthesiologists closed claim analysis of postoperative opioid-induced ventilatory depression (OIVD) events, where several of the victims of such critical events had been assessed shortly before they decompensated.3 Interestingly, a recent analysis of cases submitted to the Obstructive Sleep Apnea (OSA) Death and Near Miss Registry Committee of the Society for Anesthesia and Sleep Medicine (SASM) found that among the 43 patients who died or sustained brain damage, only a third had respiratory monitoring in place at the time of the event, and only 3 (7%) of them had continuous central monitoring.9

Two major studies examined the incidence of hypoxemia/ventilatory depression in large cohorts of patients undergoing continuous monitoring of vital signs in regular postoperative wards.10,11 Evidence from these studies suggests alarming rates of postoperative ventilatory depression. Among 833 postoperative patients, who underwent continuous Spo2 monitoring up to 48 hours after surgery, hypoxemia was common and prolonged with 37% of patients experiencing Spo2 <90% for at least an hour.11 Importantly, however, nursing records missed 90% of these hypoxemic episodes. In another large prospective, observational study, the PRediction of Opioid-induced respiratory Depression In patients monitored by capnoGraphY (PRODIGY), 1335 patients underwent blinded continuous capnography and oximetry while receiving opioid analgesia on regular care wards.10 The PRODIGY trial detected similarly high rates of ventilatory depression with 614 (46%) of patients experiencing at least 1 such respiratory depressive event.

The vast majority of patients who experienced episodes of hypoxemia or ventilatory depression in those trials10,11 survived these episodes without lasting sequelae. Even though PRODIGY patients with at least 1 episode of ventilatory depression experienced an average increase in their hospital length of stay of 3 days,10 the majority of these episodes were “self-limited” (ie, were resolved without intervention). A more clinically relevant measure of severe PIVD would be those episodes that required an intervention to prevent possible harm. Naloxone administration, an intervention to reverse PIVD or associated somnolence, has thus been proposed as a reasonable marker for such severe events.12

Table 1. - Studies Reporting the Rate of Naloxone Administration to Reverse Overnarcotizationa in Postoperative Patients
Study/year Measure Clinical setting Number administration/total number of patients Cases/10,000 patients
Deljou et al (2018)13 Naloxone Academic medical center standard ward 48 postoperative hours 128/110,019 11.6
Rosenfeld et al (2016)16 Naloxone Academic medical center ward and ICU entire hospitalization 108/28,151 38.4
Weingarten et al (2015)1 Naloxone Academic medical center standard ward 48 postoperative hours 134/84,553 15.8
Khelemsky et al (2015)14 Naloxone Academic medical center after PACU discharge 72 postoperative hours 433/442,699 9.8
Ramachandran et al (2011)15 Naloxone, cardiac arrest Academic medical center standard wards entire hospitalization 32/87,650 3.7
Gordon and Pellino (2005)12 Naloxone Academic medical center postoperative 5 postoperative days 56/10,511 53.3
Abbreviations: ICU, intensive care unit; PACU, postanesthesia care unit.
aDefined as severe sedation or ventilatory depression attributed to opioid medication.

There have been 6 large retrospective studies that have utilized naloxone administration as a meaningful index of PIVD.1,12–16 These studies, similar in design, reviewed the medical records of 763,583 surgical patients and identified 891 patients who received naloxone to treat overnarcotization, defined as severe sedation or ventilatory depression attributed to opioid medications. The rate of naloxone administration ranged from 3.615 to 53.312 per 10,000 patients (Table 1). Importantly, the majority of cases occurred within the first 24 postoperative hours.1,12,13,15,16 This rate of naloxone administration presents an important challenge toward establishing safety using prospective randomized trials of different analgesic techniques (eg, perioperative gabapentin), because such studies would require a prohibitive sample size to establish risk. For example, with a rate of naloxone administration of approximately 10 per 10,000 cases to detect a doubling of the incidence from a drug (a relative risk of 2), with 80% power, would require a cohort of approximately 23,000 subjects per treatment arm, while a tripling of the incidence would require 7500 subjects per arm.

CLINICAL RISK FACTORS FOR POSTOPERATIVE PIVD

Incompletely understood, complex interactions among patients, perioperative, and pharmacologic factors contribute to the development of PIVD. Better appreciation of these factors will undoubtedly help to reduce the incidence and mitigate the effects of severe postoperative ventilatory depression.

Until recently most relevant large clinical studies have examined the more general outcome of postoperative pulmonary complications, leaving ventilatory depression out of intense focus.17,18 Only recently, the PRODIGY trial10 used continuously recorded capnography and pulse oximetry signals to identify patients experiencing OIVD, and developed a risk prediction model with an area under the curve of 0.74. The PRODIGY score is derived from age, male sex, history of opioid naivety, sleep-disordered breathing, and congestive heart failure, and ranks patients in comparison to low risk (odds ratio [OR]: 1.0), as intermediate (OR: 2.34, 95% CI, 1.72-3.19; P < .001), or high (OR: 6.07, 95% CI, 4.44-8.30; P < .001) risk for OIVD (Table 2).10 Evidence supports that patients with OSA may have increased pain perception19 associated with an enhanced sensitivity to the analgesic effect of opioids,20,21 which could potentially increase the risk for PIVD in this patient population.22–24

Table 2. - PRODIGY Tool to Assess Risk for OIVD
Risk factor Score
Age (y)
 <60 0
 60–69 8
 70–79 12
 ≥80 16
Male sex 8
Opioid naive 3
Sleep-disordered breathing 5
Chronic heart failure 7
PRODIGY risk level
 Low risk <8
 Intermediate risk 8–14
 High risk ≥15
Adapted with permission from Khanna et al.10
Abbreviations: OIVD, opioid-induced ventilatory depression; PRODIGY, PRediction of Opioid-induced respiratory Depression In patients monitored by capnoGraphY.

Besides patient-related factors, procedural factors also influence the risk for postoperative PIVD. Postoperative ventilatory depression is more common after general than after regional anesthetics. For example, use of general anesthesia for lower extremity joint arthroplasty was associated with a 2-fold increase in the incidence of ventilatory depression in the postanesthesia care unit (PACU), compared to a spinal anesthetic.25 Also general, orthopedic, and cardiothoracic surgeries have higher rates of PIVD than less invasive procedures, such as otolaryngologic and urologic procedures.16

Episodes of PIVD commonly observed in the PACU26 may provide valuable information for the PIVD risk later on during the postoperative patient care. Mayo Clinic has a practice where postoperative patients in the PACU are continuously monitored for signs of ventilatory depression (eg, apnea).27,28 Patients who experience an episode of ventilatory depression have their PACU stay prolonged, and for those with repeated episodes and/or concurrent untreated (or high risk for) sleep-disordered breathing, the protocol includes the application of continuous Spo2 monitoring on the ward, use of noninvasive positive pressure ventilation, and/or the escalation of postoperative care.27,28 Despite these added safety measures, 2 separate studies from Mayo Clinic found that patients who experienced episodes of PIVD in the PACU had a 5-fold increase in the risk for severe ventilatory depression, requiring treatment with naloxone, in the postoperative wards.1,13 Though the association between PIVD occurring during immediate recovery from anesthesia and ventilatory compromise that emerges later, on postoperative wards, has not been studied at other institutions, these observations are consistent with the concept that severe ventilatory complications are often preceded by early signs of vulnerability.29 This temporal relationship between PACU events of PIVD and severe ventilatory depression at a later time is supported by numerous studies, showing that several critical ventilatory adverse events occur within the first 6–12 hours of discharge from the PACU.1,3,13

While the ventilatory depressant effects of opioids, as sole agents, or combined with benzodiazepines30 or propofol,31,32 are well known, emerging evidence suggests important interactions between opioids and gabapentinoids, another class of commonly used medications during surgery and pain management. Gabapentin and pregabalin are nonopioid analgesics that are frequently used in “enhanced recovery after surgery” (ERAS) protocols.33 While they are devoid of ventilatory depressant actions when administered in isolation, gabapentinoids possess well-documented sedative effects,34,35 and can potentiate OIVD. Two animal studies found that coadministration of gabapentinoids and opioids augmented ventilatory depressant effects,36,37 and a human trial has shown that pregabalin enhances remifentanil-induced ventilatory depression.38 Evidence from Mayo Clinic supports an association between preoperative gabapentin (ERAS protocol) and postoperative PIVD in the postanesthesia care unit. In that setting, gabapentin increased the risk for PIVD both following general (OR: 1.47, 95% CI, 1.26-1.70) and spinal (OR: 1.60, 95% CI, 1.27-2.02) anesthesia for joint arthroplasty,25 as well as after laparoscopic surgery (OR: 1.26, 95% CI, 1.02-1.58).39 In addition, ERAS gabapentin increased the risk for activation of the postoperative rapid response team (OR: 1.60, 95% CI, 1.17-2.20), especially for pulmonary indications (OR: 2.81, 95% CI, 1.20-6.60),40 while surgical patients on chronic gabapentinoids had a 6-fold increase in the risk for receiving naloxone on postoperative wards.13

Based, in part, on these data, the Federal Drug Administration issued a warning regarding “serious breathing problems” that can occur in patients using gabapentin or pregabalin, especially in those with underlying lung problems or those using other central nervous system depressants.41 The exact mechanism for the association between gabapentinoids and PIVD when these drugs are coadministered with opioids and/or anesthetic agents is not fully understood. The subsequent section discusses the complex neural processes that drive and coordinate ventilatory processes during wakefulness and natural sleep, and how these could be affected by pharmacologically induced sedation.

SLEEP AND DRUG-INDUCED STATE-DEPENDENT VENTILATORY COMPROMISE

Ventilation is driven and coordinated by distinct sets of brainstem neurons42,43 that are responsible for generating the inspiratory rhythm of breathing (pre-Bötzinger complex [pre-BötC]), organizing the distribution of ventilatory drive to different actuating outputs44 (central pattern generator [CPG]), and transferring the signal to ventilatory muscles, via cranial (ie, hypoglossal and trigeminal motor nuclei) and spinal (ie, phrenic nerve nuclei) nerves. These central ventilatory circuits receive multiple cortical and subcortical inputs (wakefulness ventilatory drive), as well as peripheral autonomic (ie, chemosensory, airway, and lung stretch receptors) information, that, through various feedback loops, tailor the final breathing output to body’s metabolic needs.42

Ventilatory function is physiologically embedded to the state-dependent chemical environment of the brain. Sleep-wake state changes not only exert a centrally mediated, global effect on breathing, but also directly influence the upper airway (UA) and chemoreflex drives.

Sleep-Wake State-Dependent Ventilatory and UA Control

Impaired function of UA is an important mediator of sleep-induced hypoventilation. Ventilatory muscles with dual, ventilatory (ie, phasic), and nonventilatory (tonic) drive, like pharyngeal dilators (innervated by hypoglossal neurons), are more vulnerable to the suppressing effect of sleep, compared to exclusively ventilatory (inspiratory pump) muscles like diaphragm. In fact, according to Orem’s principle,45,46 the effect of sleep on a ventilatory neuron is proportional to the amount of nonventilatory (tonic) input determining the activity of that neuron. This tonic nonventilatory drive to hypoglossal motoneurons mainly consists of noradrenergic and glutamatergic excitatory inputs, which reflect an essential component of the wakefulness drive to breath.47,48

Following the concept of “sleep switch,”49 where the state stability of wakefulness or sleep is reinforced by interconnected and mutually inhibited arousal- and sleep-promoting mechanisms, the activity of hypoglossal motoneurons is determined by a balance between excitatory and inhibitory tonic drives, the latter being mediated by glycinergic and gamma-aminobutyric acid (GABA)ergic inputs.47 During wakefulness, the excitatory drives prevail over the inhibitory ones, thus preserving airway patency, whereas at sleep, loss of the wakefulness (tonic) drive leaves the inhibitory inputs to hypoglossal and trigeminal motoneurons unopposed, thus predisposing to UA collapse and hypoventilation.50,51

Ventilatory, as well as arousal, responses to hypercapnic and hypoxic stimuli are also modulated by state-dependent brain mechanisms. Stimulation of central and peripheral chemoreceptors increases ventilation, leading in parallel to a similar degree of genioglossus (GG) muscle and diaphragm activation in awake humans.52,53 At sleep, however, a selective, disproportionate inhibition of the hypoglossal versus phrenic motoneurons predisposes UA to collapse in response to the negative pressure that is generated in its airspace by the inspiratory pump muscles.54,55 In the setting of depressed ventilatory chemoreflexes,56,57 and rather insensitive GG,58,59 CO2- or hypoxia-induced arousals,60–65 remain the last line of defense against sleep-induced UA obstruction, by reactivating GG and reestablishing UA patency.

Figure 1.
Figure 1.:
A simplified, schematic description of the sleep-wake state-dependent ventilatory control system and the potential effects of commonly used perianesthesia drugs. Brainstem pre-BötC and BötC neurons set the rhythm and, through pre-motoneurons (PM; eg, to phrenic, HMN, and V), and the CPG, organize the pattern of distribution of ventilatory drive between the main ventilatory (inspiratory pump) muscles (eg, the diaphragm, innervated by the phrenic nerve) and the primary supporting muscles of breathing (eg, intercostals, GG, and TP, innervated by the intercostal nerves, HMN and V, respectively). An important input to the central ventilatory network, as well as to PM and motor neuron pools, is the wakefulness drive to breath, which is essentially expressed by the tonic drive emanating from cortical (not shown) and subcortical (eg, lateral RF) structures, directly influenced by arousal and sleep-promoting centers. During wakefulness (a state depicted in general as red), activation of the arousal mechanisms is associated with mutual inhibition of the sleep-promoting activities. During sleep (a state depicted in general as blue), the reverse process leads to a selective and disproportionate suppression in the activity of supporting ventilatory muscles, leaving the UA vulnerable to the suction, inspiratory, forces of the diaphragm (the walls of the collapsible segment of UA at inspiration during wakefulness and sleep, are depicted as dashed red and blue lines, respectively). Pathways and structures that are predominantly affected by loss of the wakefulness drive to breath are indicated by blue dots or blue-colored frames. In this physiological context, anesthetics and opioids affect breathing by central ventilatory depressant and sedative actions, and/or suppression of chemoreflex and UA reflex drives (see text for details; interested readers are encouraged to check important detailed reviews47 , 50 , 66 , 67 on the subject). BötC indicates Bötzinger complex; CB, carotid body; CC, central chemoreceptors; CPG, central pattern generator; GABA, gamma aminobutyric acid; GG, genioglossus; HMN, hypoglossal motor neurons; N, nerve; NMB, neuromuscular blockers; NPR, negative pressure reflex; PM, pre-motoneurons; pre-BötC, pre-Bötzinger complex; RF, reticular formation; TP, tensor palatini; UA, upper airway; V, trigeminal motor neurons.

A schematic depiction of central ventilatory control and how the involved circuits might be affected by sleep-wake state-dependent mechanisms and anesthetics is shown in Figure 1.

Ventilatory Instability During Sleep: The “Loop Gain”

The eupneic level of Paco2 at a fixed metabolic CO2 production rate is determined by the hyperbolic relationship of alveolar ventilation to arterial Pco2; it reflects the point on the isometabolic curve where the ventilatory response to Paco2 intersects the change in Paco2 resulting from a change in ventilation (Figure 2).75 In the control theory jargon, this point represents the continuous interaction between the plant (ie, the volume of gases stored in the body, including lungs’ functional residual capacity [FRC]) and the system’s controller (ie, all the chemosensory, neural, and anatomical devices that orchestrate the ventilatory response to changes in Paco2 or Pao2).76

Figure 2.
Figure 2.:
Eupneic Paco 2 is the point on the isometabolic ventilation-Paco 2 hyperbola, where CO2 responsiveness curve intersects the change in Paco 2 resulting from a change in ventilation. This point represents the continuous interaction between the plant and the ventilatory system’s controller. A, The plant of ventilatory control is the volume of CO2 stored in the body, including the lungs; plant gain is the change in Paco 2 (ΔPaco 2) per unit of change in alveolar ventilation (ΔPaco 2/ΔV˙ A; unit: mm Hg/L/min). Increased plant gain shifts the CO2 responsiveness curve to the right along the isometabolic hyperbola, leading to a smaller CO2 reserve (ie, the distance between eupneic Paco 2 and Paco 2 at the apneic threshold) and increased instability. Decreased plant gain shifts the CO2 responsiveness curve to the left, leading to a larger CO2 reserve and potentially more stable breathing. B, The controller consists of all the chemosensory, neural, and anatomical devices that orchestrate the ventilatory response to changes in Paco 2; controller gain is the change in minute ventilation (ΔV˙ E) per unit of change in Paco 2 (ΔV˙ E/ΔPaco 2; unit: L/min/mm Hg). Increased controller gain increases the slope of CO2 responsiveness curve, leading to a narrower CO2 reserve and increased instability. Decreased controller gain decreases the slope of CO2 responsiveness curve, leading to a narrower CO2 reserve and potentially more stable breathing. C, Sleep onset at eupneic Paco 2 in point (a) will result in a downward and rightward displacement of the isometabolic hyperbola and a lower ventilatory output, which will shift the CO2 responsiveness curve to the right, potentially “unmasking” an apneic threshold that lingers in the range of Paco 2 values consistent with awake eupneic levels, as in point (b). Reduced ventilation, and eventually apnea or hypopnea, between (b) and (d) will continue until a new sleeping eupneic Paco 2 equilibrium is established at point (d). Conversely, arousal from sleep at (d) would expose the ventilatory controller to relative hypercapnia, compared to wakefulness, thus prompting ventilatory overshoot to bring Paco 2 back to awake eupneic level at (a). With all other factors optimized, attainment of ventilatory stability, or not, will depend on the magnitude of Paco 2 level at (d),68 as well as the slope of CO2 responsiveness curve (ie, controller gain).69 D, Hypothetical scenario of opioid administration during sleep, in a subject with OSA and intermittent hypoxia, and a normal subject. In OSA, the CO2 responsiveness curve is shifted to the left (ie, decreased plant gain), while its slope is also steeper (ie, increased controller gain), compared to the normal subject, due to hypoxia-induced ventilatory long-term facilitation.70 , 71 This may result in a narrower CO2 reserve and increased likelihood for apnea/hypopnea with opioids in OSA. The breadth of CO2 reserve is indicated by the length of arrows (colored in red and blue from the respective colors for the OSA and normal condition) initiating at the eupneic Paco 2 level on the isometabolic curve and ending where the CO2 responsiveness line crosses the x-axis (ie, where V˙ E = 0). Graphs were modified from Horner and Malhotra57 (see text for details; interested readers are encouraged to check important detailed reviews57 , 67 , 72–74 on the subject). ΔV˙ A indicates change in alveolar ventilation; ΔV˙ E, change in minute ventilation; non-REM, nonrapid eye movement sleep; OSA, obstructive sleep apnea.

Instability in this setting is quantified by the loop gain (LG) of ventilatory control; that is, the ratio of a ventilatory response to the ventilatory disturbance that triggered this response (LG = V˙ E-response/V˙ E-disturbance; eg, if a decrease in V˙ E of 2 L/min results, via a rise in Paco2, in an increase of V˙ E by 2 L/min, that will indicate a LG = 1).76–78 According to theory, the total ventilatory LG is the product of 2 distinct components: (a) the plant gain (Figure 2A), which is the change in Paco2 (ΔPaco2) per unit of change in alveolar ventilation (ΔPaco2/ΔV˙ A; unit: mm Hg/L/min) and (b) the controller gain (Figure 2B), which is the change in minute ventilation (ΔV˙ E) per unit of change in Paco2 (ΔV˙ E/ΔPaco2; unit: L/min/mm Hg) and primarily reflects the chemoreceptor sensitivity to CO2 (ie, the slope of the ventilatory response to CO2 above and below eupnea). In a stable system (LG ≤ 1), a ventilatory response with magnitude equal to, or lower than, the magnitude of the original disturbance, promptly restores eupneic Paco2. In contrast, if either the controller or plant gain is too high (LG > 1) that will lead to an excessive ventilatory response (overshoot), potentially resulting in apneic levels of Paco2 and unstable breathing, demonstrated by cycles of apnea/hypopnea and hyperventilation.72,78–81

Loss of the wakefulness drive to breath leaves chemical drives (primarily Paco2) as the main inputs to ventilatory control. At sleep, a lower ventilatory drive is associated with rightward shift (rise) of eupneic Paco2 along the isometabolic hyperbola. Although sleep might suppress CO2 responsiveness (ie, decrease controller gain),82 the total LG increases due to the prevailing increase in plant gain, caused by the sleep-induced decrease in ventilatory drive.83 As a consequence, the CO2 reserve (ie, the distance between eupneic Paco2 and Paco2 at the apneic threshold) narrows, uncovering a highly sensitive, easy-to-cross, apneic threshold (2–5 mm Hg below eupneic sleeping Paco2 and within 1–2 mm Hg of eupneic waking Paco2) and thus promoting the likelihood for apnea and ventilatory instability.73,78

Arousal from sleep due to chemical and/or physical (eg, increased resistive ventilatory load) stimuli may also be an important promoter of ventilatory instability; others being the decreased FRC (via increased plant gain), a hypoxic environment (via increased controller gain),84 and the increased magnitude, as well as the rapidity, of the wakefulness drive withdrawal.69 It is important to emphasize that the probability for apnea/hypopnea and unstable breathing is determined by the net effect of the 2, potentially competing, components of LG.73,81

State-Dependent Control of Breathing During Recovery From Anesthesia

Commonly used hypnotics, sedatives, opioids, and muscle relaxants, at concentrations comparable to those encountered during recovery from anesthesia, are potent ventilatory depressants, by promoting and intensifying the effects of sleep on the chemical (central ventilatory and chemoreflex drives) and behavioral (loss of wakefulness drive to breath) control of breathing.66,85,86 Furthermore, like in sleep, the majority of anesthetics87,88 and nondepolarizing muscle relaxants89–91 show a differential pattern of action, with a predominant suppression of UA musculature, over the ventilatory pump muscles, thus predisposing to significant UA obstruction.66,92

At subanesthetic concentrations, volatile anesthetics92 and nondepolarizing muscle relaxants94,95 suppress the peripheral (fast) component of hypoxic ventilatory response (HVR) by >40%, having no effect on hypercapnic ventilatory response (HCVR).86,96,97 On the contrary, propofol98 and dexmedetomidine equipotently reduce the central (slow) component of HVR99 by 47% and 41%, and HCVR100 by 14% and 18%, respectively,101 and increase pharyngeal collapsibility,102–104 thus predisposing to UA obstruction at concentrations much lower than those associated with loss of consciousness. The observed decrease in the slope of HCVR suggests a centrally mediated arousal-suppressing (eg, inhibition of noradrenergic input to locus coeruleus)105,106 and/or sleep-promoting (GABAergic)47 effect on the ventilatory network in the brainstem, although a direct inhibitory effect of these drugs on the hypoglossal and trigeminal motoneurons cannot be excluded.48

Opioids, when administered as sole agents or through their potent interactions with other sedatives,32,38,86 can precipitate severe ventilatory depression, acting at several sites of ventilatory control integration, including central drive, chemoreflex and UA function, as well as the arousal centers of the brain.50 The pre-BötC in the medulla is an essential mediator for the observed opioid-induced decrease in ventilatory rate.107,108 Opioids decrease resting ventilation and increase Paco2 (ie, increase the plant gain); however, a sex-specific effect on HCVR and HVR has also been demonstrated, with both responses being differentially, if not predominantly, impaired in women.109,110

Overall, the evidence supports that sedation and/or pharmacologically promoted sleep clearly contribute to the physiology of PIVD.1,3,39 Due to the complex interactions between networks that are involved in endogenous sleep mechanisms and those that are responsible to generate and express the effects of anesthetics,111,112 it is impossible to pharmacologically separate the effect of reduced wakefulness drive to breath from other, more direct, actions on ventilation.51,113–115 Evidence for the presence of gamma aminobutyric acid alpha (GABAA) receptors in the pre-BötC neurons116 supports a state-dependent sensitivity of those neurons to opioids.108,117,118 On the other hand, a distinct sedative effect of opioids119 seems contributory to their ventilatory depressant actions,120,121 while an independent inhibitory effect on the hypoglossal motoneurons, associated with suppression of GG activity, has also been demonstrated.122

Opioids can severely suppress ventilation even in the midst of severe pain.123 Audiovisual and painful stimuli, like those frequently encountered in the postoperative period, do not seem to influence the effects of volatile anesthetics93,96,97,124,125 or opioids126 on the ventilatory responses to hypoxia or hypercapnia. However, a mere increase in resting ventilatory drive (ie, decrease in the plant gain) by painful or other stimuli might partially counteract opioid- or anesthetic-induced ventilatory depression.125,127 On the other hand, light sleep128 and increased sleep fragmentation (with multiple sleep-wake transitions), or short-term sleep deprivation,129 due to pain may promote ventilatory instability, especially in the setting of carotid body malfunction,130 rendering ventilatory control more vulnerable to apnea/hypopnea events.

Both sleep131 and pharmacological sedation32 augment the opioid-induced shift of the CO2 responsiveness curve to the right along the isometabolic hyperbola (ie, increasing plant gain), while further decreasing its slope (ie, decreasing controller gain). As shown in Figure 2D, the net effect of these 2 opposite influences, leads to an opioid-induced increase in total LG and a corresponding narrowing of CO2 reserve, thus increasing the probability for apnea with only mild hyperventilation (eg, arousal-related ventilatory overshoot). As stated above, the concomitant postoperative decrease in FRC and/or acute hypoxia could further destabilize breathing in that setting.

Recent evidence suggests that sleep-disordered breathing and chronic heart failure, 2 conditions that are characterized by periodic breathing and ventilatory instability during sleep,70,74,132–135 are associated with an increased risk for OIVD in the postoperative period.10 This evidence is in support of previous experimental and physiological data showing that intermittent hypoxia augments CO2 responsiveness (controller gain) above and below eupnea in awake and sleeping OSA subjects70,71,80,84,136,137 and these patients, depending on the involved OSA phenotype,138 might be at higher risk for OIVD during sleep or sedation,138–143 rather than when awake.144–146 In Figure 2D, a hypothetical scenario is schematically depicted, where opioids are administered in a sleeping OSA subject with enhanced controller gain (associated with decreased eupneic Paco2), compared to a normal subject, due to hypoxia-induced ventilatory long-term facilitation.70,71 As a consequence, although opioids tend to decrease controller gain for both the OSA and the normal subject, they may lead to a more pronounced narrowing of the CO2 reserve in the former than the latter, thus conferring a higher probability of crossing the apnea threshold to the OSA patient (see also the legend of Figure 2).

PHYSIOLOGY-ORIENTED MITIGATION OF POSTOPERATIVE PIVD

Ventilatory instability during sleep compromises both the UA function and central ventilatory drive, thus promoting PIVD, apnea, and obstructed breathing.128,147 Any measures to mitigate PIVD should aim at minimizing ventilatory instability by hastening full recovery of wakefulness,148 while simultaneously supporting UA patency with mechanical141 and/or other LG-targeted treatments.

When feasible, the use of regional rather than general anesthesia, as well as the careful intraoperative titration of the latter, may allow, to some extent, more rapid recovery of stable wakefulness. Moreover, decreasing the analgesic need for opioids, and exploring the use of opioids with a better profile for ventilatory depressants effects,149,150 or developing novel ventilatory-specific opioid reversal agents,151 could also be of fundamental importance in an effort to reduce the incidence of postoperative PIVD.152

Re-establishment of wakefulness drive to breath could facilitate maintenance of the UA by increasing ventilatory drive and motor output to pharyngeal dilator muscles.148 Changes in the body posture can promote pharyngeal patency by ameliorating the gravitational effects of tissues on UA in the lateral153 or increasing end-expiratory lung volume (FRC) and oxygenation in the sitting154 position.66 Increased lung volumes (FRC) apply a longitudinal traction on the UA and thus might render pharyngeal lumen less prone to collapse. Moreover, both the increased FRC73,74,78 and oxygen supplementation155,156 tend to promote ventilatory stability during sleep due to reduction in the total ventilatory gain by their respective decreasing effects on plant and controller LGs.

Although several non-OSA patients demonstrate clinical features of sleep-disordered breathing while recovering from anesthesia,157 this could potentially justify the use of continuous positive airway pressure (CPAP), which, despite the well-known ventilatory- and airway-stabilizing effects,74 has not been shown to reduce postoperative pulmonary complications in patients with OSA.158 Furthermore, although postoperative O2 supplementation has been shown to improve oxygenation and reduce obstructed breathing in patients with OSA, in approximately 11% of them, it also resulted in CO2 retention.159 Interestingly, in that study, supplemental O2 decreased rather than increased the duration of apnea/hypopnea episodes, whereas the opposite effect has been observed in nonsurgical OSA patient populations.160

Recognizing the complex anatomical-functional relationships characterizing sleep-wake state-dependent ventilatory control and the further destabilizing insults of perianesthesia period, it is fair to suggest that efficient and effective means to mitigate PIVD should take into account the developing dynamics and the involved physiologies on an individual patient basis. More sensitive and specific tests are required to determine the different phenotypes161–163 involved in the response to drug-induced sedation and ventilatory depression in both healthy and OSA patients, and thus to accurately quantify the risk for postoperative PIVD.

DISCLOSURES

Name: Anthony G. Doufas, MD, PhD.

Contribution: This author helped write the manuscript and created the figures.

Conflicts of Interest: None.

Name: Toby N. Weingarten, MD.

Contribution: This author helped write the manuscript.

Conflicts of Interest: T. N. Weingarten currently serves as a consultant to Medtronic in the role as chairman of the Clinical Endpoint Committee for the PRediction of Opioid-induced respiratory Depression In patients monitored by capnoGraphY (PRODIGY) trial and has received research support from Respiratory Motion (study equipment) and unrestricted investigator-initiated grants from Merck (active) and Baxter (completed).

This manuscript was handled by: Jean-Francois Pittet, MD.

    REFERENCES

    1. Weingarten TN, Herasevich V, McGlinch MC, et al. Predictors of delayed postoperative respiratory depression assessed from naloxone administration. Anesth Analg. 2015;121:422–429.
    2. Overdyk FJ, Dowling O, Marino J, et al. Association of opioids and sedatives with increased risk of in-hospital cardiopulmonary arrest from an administrative database. PLoS One. 2016;11:e0150214.
    3. Lee LA, Caplan RA, Stephens LS, et al. Postoperative opioid-induced respiratory depression: a closed claims analysis. Anesthesiology. 2015;122:659–665.
    4. Doufas AG. Obstructive sleep apnea, pain, and opioid analgesia in the postoperative patient. Curr Anesthesiol Rep. 2014;4:1–9.
    5. Doufas AG. Opioids and sleep-disordered breathing. ASA Monitor. 2017;81:24–26.
    6. Cashman JN, Dolin SJ. Respiratory and haemodynamic effects of acute postoperative pain management: evidence from published data. Br J Anaesth. 2004;93:212–223.
    7. Weinger MB, Lee LA. No patient shall be harmed by opioid-induced respiratory depression. APSF Newsletter. 2011;26:21–40.
    8. Taenzer AH, Pyke J, Herrick MD, Dodds TM, McGrath SP. A comparison of oxygen saturation data in inpatients with low oxygen saturation using automated continuous monitoring and intermittent manual data charting. Anesth Analg. 2014;118:326–331.
    9. Bolden N, Posner KL, Domino KB, et al. Postoperative critical events associated with obstructive sleep apnea: results from the society of anesthesia and sleep medicine obstructive sleep apnea registry. Anesth Analg. 2020;131:1032–1041.
    10. Khanna AK, Bergese SD, Jungquist CR, et al.; PRediction of Opioid-induced respiratory Depression In patients monitored by capnoGraphY (PRODIGY) Group Collaborators; PRediction of Opioid-induced respiratory Depression In patients monitored by capnoGraphY (PRODIGY) Group Collaborators. Prediction of opioid-induced respiratory depression on inpatient wards using continuous capnography and oximetry: an international prospective, observational trial. Anesth Analg. 2020;131:1012–1024.
    11. Sun Z, Sessler DI, Dalton JE, et al. Postoperative hypoxemia is common and persistent: a prospective blinded observational study. Anesth Analg. 2015;121:709–715.
    12. Gordon DB, Pellino TA. Incidence and characteristics of naloxone use in postoperative pain management: a critical examination of naloxone use as a potential quality measure. Pain Manag Nurs. 2005;6:30–36.
    13. Deljou A, Hedrick SJ, Portner ER, et al. Pattern of perioperative gabapentinoid use and risk for postoperative naloxone administration. Br J Anaesth. 2018;120:798–806.
    14. Khelemsky Y, Kothari R, Campbell N, Farnad S. Incidence and demographics of post-operative naloxone administration: a 13-year experience at a major tertiary teaching institution. Pain Physician. 2015;18:E827–E829.
    15. Ramachandran SK, Haider N, Saran KA, et al. Life-threatening critical respiratory events: a retrospective study of postoperative patients found unresponsive during analgesic therapy. J Clin Anesth. 2011;23:207–213.
    16. Rosenfeld DM, Betcher JA, Shah RA, et al. Findings of a naloxone database and its utilization to improve safety and education in a tertiary care medical center. Pain Pract. 2016;16:327–333.
    17. Canet J, Gallart L, Gomar C, et al.; ARISCAT Group. Prediction of postoperative pulmonary complications in a population-based surgical cohort. Anesthesiology. 2010;113:1338–1350.
    18. Neto AS, da Costa LGV, Hemmes SNT, et al.; LAS VEGAS. The LAS VEGAS risk score for prediction of postoperative pulmonary complications: an observational study. Eur J Anaesthesiol. 2018;35:691–701.
    19. Doufas AG, Tian L, Davies MF, Warby SC. Nocturnal intermittent hypoxia is independently associated with pain in subjects suffering from sleep-disordered breathing. Anesthesiology. 2013;119:1149–1162.
    20. Brown KA, Laferrière A, Lakheeram I, Moss IR. Recurrent hypoxemia in children is associated with increased analgesic sensitivity to opiates. Anesthesiology. 2006;105:665–669.
    21. Doufas AG, Tian L, Padrez KA, et al. Experimental pain and opioid analgesia in volunteers at high risk for obstructive sleep apnea. PLoS One. 2013;8:e54807.
    22. Cozowicz C, Chung F, Doufas AG, Nagappa M, Memtsoudis SG. Opioids for acute pain management in patients with obstructive sleep apnea: a systematic review. Anesth Analg. 2018;127:988–1001.
    23. Memtsoudis SG, Cozowicz C, Nagappa M, et al. Society of anesthesia and sleep medicine guideline on intraoperative management of adult patients with obstructive sleep apnea. Anesth Analg. 2018;127:967–987.
    24. Brackley AD, Andrade MA, Toney GM. Intermittent hypercapnic hypoxia induces respiratory hypersensitivity to fentanyl accompanied by tonic respiratory depression by endogenous opioids. J Physiol. 2020;598:3239–3257.
    25. Weingarten TN, Jacob AK, Njathi CW, Wilson GA, Sprung J. Multimodal analgesic protocol and postanesthesia respiratory depression during phase I recovery after total joint arthroplasty. Reg Anesth Pain Med. 2015;40:330–336.
    26. Gupta K, Nagappa M, Prasad A, et al. Risk factors for opioid-induced respiratory depression in surgical patients: a systematic review and meta-analyses. BMJ Open. 2018;8:e024086.
    27. Gali B, Whalen FX Jr, Gay PC, et al. Management plan to reduce risks in perioperative care of patients with presumed obstructive sleep apnea syndrome. J Clin Sleep Med. 2007;3:582–588.
    28. Gali B, Whalen FX, Schroeder DR, Gay PC, Plevak DJ. Identification of patients at risk for postoperative respiratory complications using a preoperative obstructive sleep apnea screening tool and postanesthesia care assessment. Anesthesiology. 2009;110:869–877.
    29. Taenzer AH, Pyke JB, McGrath SP. A review of current and emerging approaches to address failure-to-rescue. Anesthesiology. 2011;115:421–431.
    30. Bailey PL, Pace NL, Ashburn MA, Moll JW, East KA, Stanley TH. Frequent hypoxemia and apnea after sedation with midazolam and fentanyl. Anesthesiology. 1990;73:826–830.
    31. Bouillon TW, Bruhn J, Radulescu L, et al. Pharmacodynamic interaction between propofol and remifentanil regarding hypnosis, tolerance of laryngoscopy, bispectral index, and electroencephalographic approximate entropy. Anesthesiology. 2004;100:1353–1372.
    32. Nieuwenhuijs DJ, Olofsen E, Romberg RR, et al. Response surface modeling of remifentanil-propofol interaction on cardiorespiratory control and bispectral index. Anesthesiology. 2003;98:312–322.
    33. Verret M, Lauzier F, Zarychanski R, et al.; Canadian Perioperative Anesthesia Clinical Trials (PACT) Group. Perioperative use of gabapentinoids for the management of postoperative acute pain: a systematic review and meta-analysis. Anesthesiology. 2020;133:265–279.
    34. Doleman B, Heinink TP, Read DJ, Faleiro RJ, Lund JN, Williams JP. A systematic review and meta-regression analysis of prophylactic gabapentin for postoperative pain. Anaesthesia. 2015;70:1186–1204.
    35. Mishriky BM, Waldron NH, Habib AS. Impact of pregabalin on acute and persistent postoperative pain: a systematic review and meta-analysis. Br J Anaesth. 2015;114:10–31.
    36. Kozer E, Levichek Z, Hoshino N, et al. The effect of amitriptyline, gabapentin, and carbamazepine on morphine-induced hypercarbia in rabbits. Anesth Analg. 2008;107:1216–1222.
    37. Lyndon A, Audrey S, Wells C, et al. Risk to heroin users of polydrug use of pregabalin or gabapentin. Addiction. 2017;112:1580–1589.
    38. Myhre M, Diep LM, Stubhaug A. Pregabalin has analgesic, ventilatory, and cognitive effects in combination with remifentanil. Anesthesiology. 2016;124:141–149.
    39. Cavalcante AN, Sprung J, Schroeder DR, Weingarten TN. Multimodal analgesic therapy with gabapentin and its association with postoperative respiratory depression. Anesth Analg. 2017;125:141–146.
    40. Hardman MI, Kruthiventi SC, Schmugge MR, et al. Risk factors and outcomes of postoperative emergency response team activation: a matched case-control study. Crit Care Resusc. 2020;22:6–14.
    41. www.fda.gov/drugs/drug-safety-and-availability/fda-warns-about-serious-breathing-problems-seizure-and-nerve-pain-medicines-gabapentin-neurontin. Accessed on September 23, 2020.
    42. Feldman JL, Del Negro CA, Gray PA. Understanding the rhythm of breathing: so near, yet so far. Annu Rev Physiol. 2013;75:423–452.
    43. Kam K, Worrell JW, Janczewski WA, Cui Y, Feldman JL. Distinct inspiratory rhythm and pattern generating mechanisms in the preBötzinger complex. J Neurosci. 2013;33:9235–9245.
    44. Remmers JE. Altose MD, kawakami Y, eds. Central neural control of breathing. In: Control of Breathing in Health and Disease. 1999:Marcel Dekker, Inc; 1–40.
    45. Orem J, Lovering AT, Dunin-Barkowski W, Vidruk EH. Tonic activity in the respiratory system in wakefulness, NREM and REM sleep. Sleep. 2002;25:488–496.
    46. Orem J, Lydic R. Upper airway function during sleep and wakefulness: experimental studies on normal and anesthetized cats. Sleep. 1978;1:49–68.
    47. Horner RL. Emerging principles and neural substrates underlying tonic sleep-state-dependent influences on respiratory motor activity. Philos Trans R Soc Lond B Biol Sci. 2009;364:2553–2564.
    48. Horner RL, Hughes SW, Malhotra A. State-dependent and reflex drives to the upper airway: basic physiology with clinical implications. J Appl Physiol (1985). 2014;116:325–336.
    49. Saper CB, Scammell TE, Lu J. Hypothalamic regulation of sleep and circadian rhythms. Nature. 2005;437:1257–1263.
    50. Horner RL. Neural control of the upper airway: integrative physiological mechanisms and relevance for sleep disordered breathing. Compr Physiol. 2012;2:479–535.
    51. Horner RL. Kryger MH, Roth T, Dement WC, eds. Respiratory physiology: central neural control of respiratory neurons and motoneurons during sleep. In: Principles and Practice of Sleep Medicine. 2016:Elsevier; 155–166.
    52. Onal E, Lopata M, O’Connor TD. Diaphragmatic and genioglossal electromyogram responses to isocapnic hypoxia in humans. Am Rev Respir Dis. 1981;124:215–217.
    53. Onal E, Lopata M, O’Connor TD. Diaphragmatic and genioglossal electromyogram responses to CO2 rebreathing in humans. J Appl Physiol Respir Environ Exerc Physiol. 1981;50:1052–1055.
    54. Parisi RA, Neubauer JA, Frank MM, Edelman NH, Santiago TV. Correlation between genioglossal and diaphragmatic responses to hypercapnia during sleep. Am Rev Respir Dis. 1987;135:378–382.
    55. Parisi RA, Santiago TV, Edelman NH. Genioglossal and diaphragmatic EMG responses to hypoxia during sleep. Am Rev Respir Dis. 1988;138:610–616.
    56. Horner RL, Liu X, Gill H, Nolan P, Liu H, Sood S. Effects of sleep-wake state on the genioglossus vs. diaphragm muscle response to CO(2) in rats. J Appl Physiol (1985). 2002;92:878–887.
    57. Horner R, Malhotra A. Broaddus VC, ed. Control of breathing and upper airways during sleep. In: Murray and Nadel’s Textbook of Respiratory Medicine. 2016:6th ed. Elsevier; 1511–1526.
    58. Pillar G, Malhotra A, Fogel RB, et al. Upper airway muscle responsiveness to rising PCO(2) during NREM sleep. J Appl Physiol (1985). 2000;89:1275–1282.
    59. Stanchina ML, Malhotra A, Fogel RB, et al. Genioglossus muscle responsiveness to chemical and mechanical stimuli during non-rapid eye movement sleep. Am J Respir Crit Care Med. 2002;165:945–949.
    60. Ayas NT, Brown R, Shea SA. Hypercapnia can induce arousal from sleep in the absence of altered respiratory mechanoreception. Am J Respir Crit Care Med. 2000;162:1004–1008.
    61. Souza GMPR, Stornetta RL, Stornetta DS, Abbott SBG, Guyenet PG. Contribution of the retrotrapezoid nucleus and carotid bodies to hypercapnia- and hypoxia-induced arousal from sleep. J Neurosci. 2019;39:9725–9737.
    62. Kaur S, Pedersen NP, Yokota S, et al. Glutamatergic signaling from the parabrachial nucleus plays a critical role in hypercapnic arousal. J Neurosci. 2013;33:7627–7640.
    63. Guyenet PG, Bayliss DA. Neural control of breathing and CO2 homeostasis. Neuron. 2015;87:946–961.
    64. Berthon-Jones M, Sullivan CE. Ventilation and arousal responses to hypercapnia in normal sleeping humans. J Appl Physiol Respir Environ Exerc Physiol. 1984;57:59–67.
    65. Berthon-Jones M, Sullivan CE. Ventilatory and arousal responses to hypoxia in sleeping humans. Am Rev Respir Dis. 1982;125:632–639.
    66. Isono S. Yamaguchi K, ed. Instability of upper airway during anesthesia and sedation: how is upper airway unstable during anesthesia and sedation? In: Structure-Function Relationships in Various Respiratory Systems: Connecting to the Next Generation. 2020:Springer; 67–91.
    67. Dempsey JA, Veasey SC, Morgan BJ, O’Donnell CP. Pathophysiology of sleep apnea. Physiol Rev. 2010;90:47–112.
    68. Bulow K. Respiration and wakefulness in man. Acta Physiol Scand Suppl. 1963;209:1–110.
    69. Khoo MC. Altose MD, Kawakami Y, eds. Periodic breathing and central apnea. In: Control of Breathing in Health and Disease. 1999Marcel Dekker; 203–250.
    70. Salloum A, Rowley JA, Mateika JH, Chowdhuri S, Omran Q, Badr MS. Increased propensity for central apnea in patients with obstructive sleep apnea: effect of nasal continuous positive airway pressure. Am J Respir Crit Care Med. 2010;181:189–193.
    71. Chowdhuri S, Shanidze I, Pierchala L, Belen D, Mateika JH, Badr MS. Effect of episodic hypoxia on the susceptibility to hypocapnic central apnea during NREM sleep. J Appl Physiol (1985). 2010;108:369–377.
    72. White DP, Younes MK. Obstructive sleep apnea. Compr Physiol. 2012;2:2541–2594.
    73. Dempsey JA. Crossing the apnoeic threshold: causes and consequences. Exp Physiol. 2005;90:13–24.
    74. Younes M, Ostrowski M, Thompson W, Leslie C, Shewchuk W. Chemical control stability in patients with obstructive sleep apnea. Am J Respir Crit Care Med. 2001;163:1181–1190.
    75. Berger AJ, Mitchell RA, Severinghaus JW. Regulation of respiration (third of three parts). N Engl J Med. 1977;297:194–201.
    76. Cherniack NS, Longobardo GS. Cheyne-Stokes breathing: an instability in physiologic control. N Engl J Med. 1973;288:952–957.
    77. Khoo MC, Kronauer RE, Strohl KP, Slutsky AS. Factors inducing periodic breathing in humans: a general model. J Appl Physiol Respir Environ Exerc Physiol. 1982;53:644–659.
    78. Dempsey JA, Smith CA, Przybylowski T, et al. The ventilatory responsiveness to CO(2) below eupnoea as a determinant of ventilatory stability in sleep. J Physiol. 2004;560:1–11.
    79. Khoo MC. Determinants of ventilatory instability and variability. Respir Physiol. 2000;122:167–182.
    80. Deacon-Diaz N, Malhotra A. Inherent vs. induced loop gain abnormalities in obstructive sleep apnea. Front Neurol. 2018;9:896.
    81. Dempsey JA. Central sleep apnea: misunderstood and mistreated! F1000Res 2019;8:F1000 Faculty Rev-981.
    82. Cherniack NS. Respiratory dysrhythmias during sleep. N Engl J Med. 1981;305:325–330.
    83. Nakayama H, Smith CA, Rodman JR, Skatrud JB, Dempsey JA. Effect of ventilatory drive on carbon dioxide sensitivity below eupnea during sleep. Am J Respir Crit Care Med. 2002;165:1251–1260.
    84. Xie A, Skatrud JB, Dempsey JA. Effect of hypoxia on the hypopnoeic and apnoeic threshold for CO(2) in sleeping humans. J Physiol. 2001;535:269–278.
    85. Gross JB, Cerza DA. Ward DS, Dahan A, Teppema LJ, eds. Ventilatory effects of medications used for moderate and deep sedation. In: Pharmacology and Pathophysiology of the Control of Breathing. 2005:Taylor & Francis Group; 513–570.
    86. Dahan A, Teppema LJ. Influence of anaesthesia and analgesia on the control of breathing. Br J Anaesth. 2003;91:40–49.
    87. Hwang JC, StJohn WM, Bartlett D Jr. Afferent pathways for hypoglossal and phrenic responses to changes in upper airway pressure. Respir Physiol. 1984;55:341–354.
    88. Nishino T, Shirahata M, Yonezawa T, Honda Y. Comparison of changes in the hypoglossal and the phrenic nerve activity in response to increasing depth of anesthesia in cats. Anesthesiology. 1984;60:19–24.
    89. D’Honneur G, Lofaso F, Drummond GB, et al. Susceptibility to upper airway obstruction during partial neuromuscular block. Anesthesiology. 1998;88:371–378.
    90. Eikermann M, Vogt FM, Herbstreit F, et al. The predisposition to inspiratory upper airway collapse during partial neuromuscular blockade. Am J Respir Crit Care Med. 2007;175:9–15.
    91. Isono S, Kochi T, Ide T, Sugimori K, Mizuguchi T, Nishino T. Differential effects of vecuronium on diaphragm and geniohyoid muscle in anaesthetized dogs. Br J Anaesth. 1992;68:239–243.
    92. Hillman DR, Platt PR, Eastwood PR. The upper airway during anaesthesia. Br J Anaesth. 2003;91:31–39.
    93. Pandit JJ. The variable effect of low-dose volatile anaesthetics on the acute ventilatory response to hypoxia in humans: a quantitative review. Anaesthesia. 2002;57:632–643.
    94. Broens SJL, Boon M, Martini CH, et al. Reversal of partial neuromuscular block and the ventilatory response to hypoxia: a randomized controlled trial in healthy volunteers. Anesthesiology. 2019;131:467–476.
    95. Eriksson LI, Sato M, Severinghaus JW. Effect of a vecuronium-induced partial neuromuscular block on hypoxic ventilatory response. Anesthesiology. 1993;78:693–699.
    96. Pandit JJ. Effect of low dose inhaled anaesthetic agents on the ventilatory response to carbon dioxide in humans: a quantitative review. Anaesthesia. 2005;60:461–469.
    97. Dahan A, Teppema L. Influence of low-dose anaesthetic agents on ventilatory control: where do we stand? Br J Anaesth. 1999;83:199–201.
    98. Dahan A, Nieuwenhuijs DJ, Olofsen E. Influence of propofol on the control of breathing. Adv Exp Med Biol. 2003;523:81–92.
    99. Nieuwenhuijs D, Sarton E, Teppema L, Dahan A. Propofol for monitored anesthesia care: implications on hypoxic control of cardiorespiratory responses. Anesthesiology. 2000;92:46–54.
    100. Nieuwenhuijs D, Sarton E, Teppema LJ, et al. Respiratory sites of action of propofol: absence of depression of peripheral chemoreflex loop by low-dose propofol. Anesthesiology. 2001;95:889–895.
    101. Lodenius Å, Ebberyd A, Hårdemark Cedborg A, et al. Sedation with dexmedetomidine or propofol impairs hypoxic control of breathing in healthy male volunteers: a nonblinded, randomized crossover study. Anesthesiology. 2016;125:700–715.
    102. Lodenius Å, Maddison KJ, Lawther BK, et al. Upper airwaycollapsibility during dexmedetomidine and propofol sedation in healthy volunteers: a nonblinded randomized crossover study. Anesthesiology. 2019;131:962–973.
    103. Eastwood PR, Platt PR, Shepherd K, Maddison K, Hillman DR. Collapsibility of the upper airway at different concentrations of propofol anesthesia. Anesthesiology. 2005;103:470–477.
    104. Hillman DR, Walsh JH, Maddison KJ, et al. Evolution of changes in upper airway collapsibility during slow induction of anesthesia with propofol. Anesthesiology. 2009;111:63–71.
    105. Nelson LE, Guo TZ, Lu J, Saper CB, Franks NP, Maze M. The sedative component of anesthesia is mediated by GABA(A) receptors in an endogenous sleep pathway. Nat Neurosci. 2002;5:979–984.
    106. Nelson LE, Lu J, Guo T, Saper CB, Franks NP, Maze M. The alpha2-adrenoceptor agonist dexmedetomidine converges on an endogenous sleep-promoting pathway to exert its sedative effects. Anesthesiology. 2003;98:428–436.
    107. Montandon G, Horner R. CrossTalk proposal: the preBotzinger complex is essential for the respiratory depression following systemic administration of opioid analgesics. J Physiol. 2014;592:1159–1162.
    108. Montandon G, Qin W, Liu H, Ren J, Greer JJ, Horner RL. PreBotzinger complex neurokinin-1 receptor-expressing neurons mediate opioid-induced respiratory depression. J Neurosci. 2011;31:1292–1301.
    109. Dahan A, Sarton E, Teppema L, Olievier C. Sex-related differences in the influence of morphine on ventilatory control in humans. Anesthesiology. 1998;88:903–913.
    110. Sarton E, Teppema L, Dahan A. Sex differences in morphine-induced ventilatory depression reside within the peripheral chemoreflex loop. Anesthesiology. 1999;90:1329–1338.
    111. Lydic R, Baghdoyan HA. Sleep, anesthesiology, and the neurobiology of arousal state control. Anesthesiology. 2005;103:1268–1295.
    112. Van Dort CJ, Baghdoyan HA, Lydic R. Neurochemical modulators of sleep and anesthetic states. Int Anesthesiol Clin. 2008;46:75–104.
    113. Brown EN, Purdon PL, Van Dort CJ. General anesthesia and altered states of arousal: a systems neuroscience analysis. Annu Rev Neurosci. 2011;34:601–628.
    114. Maddison KJ, Walsh JH, Shepherd KL, et al. Comparison of collapsibility of the human upper airway during anesthesia and during sleep. Anesth Analg. 2020;130:1008–1017.
    115. Vecchio LM, Grace KP, Liu H, Harding S, Lê AD, Horner RL. State-dependent vs. central motor effects of ethanol on breathing. J Appl Physiol (1985). 2010;108:387–400.
    116. Montandon G, Wu H, Liu H, Vu MT, Orser BA, Horner RL. δ-Subunit containing GABAA receptors modulate respiratory networks. Sci Rep. 2017;7:18105.
    117. McKay LC, Janczewski WA, Feldman JL. Sleep-disordered breathing after targeted ablation of preBötzinger complex neurons. Nat Neurosci. 2005;8:1142–1144.
    118. Gray PA, Rekling JC, Bocchiaro CM, Feldman JL. Modulation of respiratory frequency by peptidergic input to rhythmogenic neurons in the preBötzinger complex. Science. 1999;286:1566–1568.
    119. Mortazavi S, Thompson J, Baghdoyan HA, Lydic R. Fentanyl and morphine, but not remifentanil, inhibit acetylcholine release in pontine regions modulating arousal. Anesthesiology. 1999;90:1070–1077.
    120. Montandon G, Cushing SL, Campbell F, Propst EJ, Horner RL, Narang I. Distinct cortical signatures associated with sedation and respiratory rate depression by morphine in a pediatric population. Anesthesiology. 2016;125:889–903.
    121. Montandon G, Horner RL. Electrocortical changes associating sedation and respiratory depression by the opioid analgesic fentanyl. Sci Rep. 2019;9:14122.
    122. Hajiha M, DuBord MA, Liu H, Horner RL. Opioid receptor mechanisms at the hypoglossal motor pool and effects on tongue muscle activity in vivo. J Physiol. 2009;587:2677–2692.
    123. Dahan A, Romberg R, Teppema L, Sarton E, Bijl H, Olofsen E. Simultaneous measurement and integrated analysis of analgesia and respiration after an intravenous morphine infusion. Anesthesiology. 2004;101:1201–1209.
    124. Sarton E, Dahan A, Teppema L, et al. Acute pain and central nervous system arousal do not restore impaired hypoxic ventilatory response during sevoflurane sedation. Anesthesiology. 1996;85:295–303.
    125. Pandit JJ, Moreau B, Donoghue S, Robbins PA. Effect of pain and audiovisual stimulation on the depression of acute hypoxic ventilatory response by low-dose halothane in humans. Anesthesiology. 2004;101:1409–1416.
    126. Karan S, Voter W, Palmer L, Ward DS. Effects of pain and audiovisual stimulation on the opioid-induced depression of the hypoxic ventilatory response. Anesthesiology. 2005;103:384–390.
    127. Karan SB, Norton JR, Voter W, Palmer L, Ward DS. Effects of pain and audiovisual stimulation on the hypoxic ventilatory response. Adv Exp Med Biol. 2004;551:275–279.
    128. Dempsey JA, Smith CA, Harms CA, Chow C, Saupe KW. Sleep-induced breathing instability: University of Wisconsin-Madison Sleep and Respiration Research Group. Sleep. 1996;19:236–247.
    129. White DP, Douglas NJ, Pickett CK, Zwillich CW, Weil JV. Sleep deprivation and the control of ventilation. Am Rev Respir Dis. 1983;128:984–986.
    130. Chenuel BJ, Smith CA, Henderson KS, Dempsey JA. Ventilatory instability induced by selective carotid body inhibition in the sleeping dog. Adv Exp Med Biol. 2004;551:197–201.
    131. Forrest WH Jr, Bellville JW. The effect of sleep plus morphine on the respiratory response to carbon dioxide. Anesthesiology. 1964;25:137–141.
    132. Chua TP, Ponikowski P, Webb-Peploe K, et al. Clinical characteristics of chronic heart failure patients with an augmented peripheral chemoreflex. Eur Heart J. 1997;18:480–486.
    133. Gottlieb DJ, Yenokyan G, Newman AB, et al. Prospective study of obstructive sleep apnea and incident coronary heart disease and heart failure: the sleep heart health study. Circulation. 2010;122:352–360.
    134. Javaheri S. A mechanism of central sleep apnea in patients with heart failure. N Engl J Med. 1999;341:949–954.
    135. Xie A, Skatrud JB, Puleo DS, Rahko PS, Dempsey JA. Apnea-hypopnea threshold for CO2 in patients with congestive heart failure. Am J Respir Crit Care Med. 2002;165:1245–1250.
    136. Deacon NL, Catcheside PG. The role of high loop gain induced by intermittent hypoxia in the pathophysiology of obstructive sleep apnoea. Sleep Med Rev. 2015;22:3–14.
    137. Deacon-Diaz NL, Sands SA, McEvoy RD, Catcheside PG. Daytime loop gain is elevated in obstructive sleep apnea but not reduced by CPAP treatment. J Appl Physiol (1985). 2018;125:1490–1497.
    138. Martins RT, Carberry JC, Wang D, Rowsell L, Grunstein RR, Eckert DJ. Morphine alters respiratory control but not other key obstructive sleep apnoea phenotypes: a randomised trial. Eur Respir J. 2020;55:1901344.
    139. Rowsell L, Wong KKH, Yee BJ, et al. The effect of acute morphine on obstructive sleep apnoea: a randomised double-blind placebo-controlled crossover trial. Thorax. 2019;74:177–184.
    140. Bernards CM, Knowlton SL, Schmidt DF, et al. Respiratory and sleep effects of remifentanil in volunteers with moderate obstructive sleep apnea. Anesthesiology. 2009;110:41–49.
    141. Zaremba S, Shin CH, Hutter MM, et al. Continuous positive airway pressure mitigates opioid-induced worsening of sleep-disordered breathing early after bariatric surgery. Anesthesiology. 2016;125:92–104.
    142. Wang D, Somogyi AA, Yee BJ, et al. The effects of a single mild dose of morphine on chemoreflexes and breathing in obstructive sleep apnea. Respir Physiol Neurobiol. 2013;185:526–532.
    143. Waters KA, McBrien F, Stewart P, Hinder M, Wharton S. Effects of OSA, inhalational anesthesia, and fentanyl on the airway and ventilation of children. J Appl Physiol (1985). 2002;92:1987–1994.
    144. Doufas AG, Shafer SL, Rashid NHA, Kushida CA, Capasso R. Non-steady state modeling of the ventilatory depressant effect of remifentanil in awake patients experiencing moderate-to-severe obstructive sleep apnea. Anesthesiology. 2019;130:213–226.
    145. Montana MC, Juriga L, Sharma A, Kharasch ED. Opioid sensitivity in children with and without obstructive sleep apnea. Anesthesiology. 2019;130:936–945.
    146. Tomazini Martins R, Carberry JC, Gandevia SC, Butler JE, Eckert DJ. Effects of morphine on respiratory load detection, load magnitude perception, and tactile sensation in obstructive sleep apnea. J Appl Physiol (1985). 2018;125:393–400.
    147. Subramani Y, Singh M, Wong J, Kushida CA, Malhotra A, Chung F. Understanding phenotypes of obstructive sleep apnea: applications in anesthesia, surgery, and perioperative medicine. Anesth Analg. 2017;124:179–191.
    148. Lo YL, Jordan AS, Malhotra A, et al. Influence of wakefulness on pharyngeal airway muscle activity. Thorax. 2007;62:799–805.
    149. Olofsen E, Boom M, Sarton E, et al. Analgesic and respiratory depressant effects of r-dihydroetorphine: a pharmacokinetic-pharmacodynamic analysis in healthy male volunteers. Anesthesiology. 2019;131:1327–1339.
    150. Dahan A, van Dam CJ, Niesters M, et al. Benefit and risk evaluation of biased μ-receptor agonist oliceridine versus morphine. Anesthesiology. 2020;133:559–568.
    151. Algera MH, Kamp J, van der Schrier R, et al. Opioid-induced respiratory depression in humans: a review of pharmacokinetic-pharmacodynamic modelling of reversal. Br J Anaesth. 2019;122:e168–e179.
    152. Dahan A, Roozekrans M, van der Schrier R, Smith T, Aarts L. Primum non nocere or how to resolve drug-induced respiratory depression. Anesthesiology. 2013;118:1261–1263.
    153. Isono S, Tanaka A, Nishino T. Lateral position decreases collapsibility of the passive pharynx in patients with obstructive sleep apnea. Anesthesiology. 2002;97:780–785.
    154. Tagaito Y, Isono S, Tanaka A, Ishikawa T, Nishino T. Sitting posture decreases collapsibility of the passive pharynx in anesthetized paralyzed patients with obstructive sleep apnea. Anesthesiology. 2010;113:812–818.
    155. Wellman A, Malhotra A, Jordan AS, Stevenson KE, Gautam S, White DP. Effect of oxygen in obstructive sleep apnea: role of loop gain. Respir Physiol Neurobiol. 2008;162:144–151.
    156. Edwards BA, Sands SA, Owens RL, et al. The combination of supplemental oxygen and a hypnotic markedly improves obstructive sleep apnea in patients with a mild to moderate upper airway collapsibility. Sleep. 2016;39:1973–1983.
    157. Chung F, Liao P, Yang Y, et al. Postoperative sleep-disordered breathing in patients without preoperative sleep apnea. Anesth Analg. 2015;120:1214–1224.
    158. Nagappa M, Mokhlesi B, Wong J, Wong DT, Kaw R, Chung F. The effects of continuous positive airway pressure on postoperative outcomes in obstructive sleep apnea patients undergoing surgery: a systematic review and meta-analysis. Anesth Analg. 2015;120:1013–1023.
    159. Liao P, Wong J, Singh M, et al. Postoperative oxygen therapy in patients with OSA: a randomized controlled trial. Chest. 2017;151:597–611.
    160. Mehta V, Vasu TS, Phillips B, Chung F. Obstructive sleep apnea and oxygen therapy: a systematic review of the literature and meta-analysis. J Clin Sleep Med. 2013;9:271–279.
    161. Eckert DJ. Phenotypic approaches to obstructive sleep apnoea - new pathways for targeted therapy. Sleep Med Rev. 2018;37:45–59.
    162. Owens RL, Edwards BA, Eckert DJ, et al. An integrative model of physiological traits can be used to predict obstructive sleep apnea and response to non positive airway pressure therapy. Sleep. 2015;38:961–970.
    163. Eckert DJ, White DP, Jordan AS, Malhotra A, Wellman A. Defining phenotypic causes of obstructive sleep apnea: identification of novel therapeutic targets. Am J Respir Crit Care Med. 2013;188:996–1004.
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