Introduction: To objectify self-reported sleep disorders in individuals with post-COVID-syndrome (PCS), we aimed to investigate the prevalence and nature of sleep disturbances by polysomnography (PSG) in PCS compared to healthy individuals. Methods: People with PCS (n = 21) and healthy controls (CON, n = 10) were included in this prospective trial. At baseline, clinical and social anamnesis, lung function, 1 min sit-to-stand test (STST) and Pittsburgh Sleep Quality Index (PSQI) were assessed. For a single-night, sleep health was evaluated by video-PSG. The apnoea/hypopnea index (AHI) was used as the primary outcome. Results: Twenty patients with PCS (50 ± 11 y, BMI 27.1 m2/kg, SARS-CoV-2 infection 8.5 ± 4.5 months ago) and 10 CON participants (46 ± 10 y, BMI 23.0 m2/kg, no SARS-CoV-2 infection in the history) completed the study. Forced vital capacity (p = 0.018), STST repetitions (p < 0.001), and symptoms of dyspnoea (at rest: p = 0.002, exertion: p < 0.001) were worse in PCS compared to CON. PSQI score (PCS: 7.5 ± 4.7 points) was higher in PCS compared to CON (Δ = 3.7 points, 95% CI [0.4–7.1] p = 0.015), indicating poor sleep in 80% of patients with PCS. Although PSG showed comparable sleep stage distributions in both groups, AHI (Δ = 9.0 n/h, 95% CI [3.3–14.8], p = 0.002), PLM index (Δ = 5.1 n/h, 95% CI [0.4–9.8], p = 0.017), and the prevalence of sleep apnoea (60% vs. 10%, p = 0.028) was significantly higher in PCS compared to CON. Conclusion: Quantifiable subjective limitations of sleep have been revealed by PSG data in this PCS cohort. More than half of PCS patients had signs of sleep apnoea, highlighting the importance of sleep screening in PCS.

Symptoms of fatigue, muscle weakness (37–63%), and sleep difficulties (26–31%) have been shown to be the most common consequences of post-COVID-19 syndrome (PCS) [1‒4]. Hospitalization due to COVID-19 increases the prevalence of sleep disturbances to 62%, which can persist for at least 1 year [5]. The consequences of poor sleep are multifaceted and can result in daytime sleepiness, reduced concentration and performance, and poor quality of life have. Additionally, it has been shown to contribute to morbidity in other conditions [6], which highlights the clinical importance of a good sleep quality.

So far, sleep disorders have been largely evaluated by questionnaires and clinical anamnesis in PCS. Beyond the subjectively perceived impairment, it remains unclear, if sleep problems are quantifiable via polysomnography (PSG), the gold standard of sleep health measurement. Therefore, the aim of this prospective trial was to objectively measure sleep health in subjects with PCS and to compare it to healthy individuals by conducting a single-night PSG.

Subject Population

Twenty-one subjects with PCS and 10 healthy controls (CON) without a known history of SARS-CoV-2 infection were included in this trial (NCT05124548, ethics approval number: 149/21). All patients have given written informed consent. According to WHO definition, PCS was defined as symptoms 3 months from the start of COVID-19, which last at least 2 months and cannot be explained by an alternative diagnosis. PCS group was recruited during inpatient pulmonary rehabilitation (Schoen Clinic Berchtesgadener Land, Germany), the CON group consisted of healthy volunteers who live near the reference centre. In the clinical history, none of the included participants had been tested by PSG or had a diagnosis of sleep apnoea.

Assessments

The baseline assessment included a clinical and social anamnesis, measurement of lung function, blood gases, exercise performance and physiological responses of 1 min sit-to-stand test (STST) on oxygenation and dyspnoea (rated on a 10-point visual analogue scale [VAS]). Only in the PCS group, post-COVID functional scale (PCFS), Canadian criteria for the diagnosis of chronic fatigue syndrome and the Ordinal Scale for Clinical Improvement (OSCI) were assessed. Subjective sleep quality was evaluated by the Pittsburgh Sleep Quality Index (PSQI) [7]. For objective sleep health measurement, participants underwent a single-night assessment of sleep via video-PSG [8], in the sleep laboratory at the Schoen Clinic. The apnoea-hypopnoea index (AHI) as an indicator for sleep apnoea was used as the primary outcome.

Statistical Methods

Data were checked for consistency and normality. Bootstrap t tests, Pearson correlation analyses, Fisher’s exact, and Person’s χ2 test were used to analyse data (NCSS 2022, LLC. Kaysville, UT, USA). p values <5% were considered statistically significant.

Thirty out of 31 subjects (n = 20 PCS: 50 ± 11 y; comorbidities of dyslipidaemia (n = 6), arterial hypertension (n = 3), coronary heart disease (n = 2), depression (n = 2), anxiety (n = 1), overweight (n = 1), osteoporosis (n = 1), anaemia (n = 1); Ordinal Scale for Clinical Improvement [OSCI] score (0–8 pts): 3 ± 1 points, and n = 10 CON: 46 ± 10 y) were included in the final analysis. Significant between-group differences were observed in BMI (Δ = 4.1 kg/m2, 95% CI (0.2–8.0), p = 0.039), forced vital capacity (Δ = 10.1%, 95% CI [0.7–19.4], p = 0.018), STST (Δ = 18.6 repetitions, 95% CI [9.7–27.6], p < 0.001), and symptoms of dyspnoea (VAS) at rest (Δ = 1.4 points, 95% CI [0.6–2.3], p = 0.002) as well as at exertion (Δ = 4.6 points, 95% CI [3.9–5.3], p < 0.001). PCS group (OSCI score: 3 ± 1 points, PCFS: 2.8 ± 0.9 points, chronic fatigue symptoms: 35% of cases, unable to work: 30% of cases) had a positive SARS-CoV-2 PCR test result 8.5 ± 4.5 months before baseline study visit.

Nocturnal Sleep

PSQI showed significant higher values in PCS compared to CON (Δ = 3.7, 95%CI [0.4–7.1] p = 0.015) (online suppl. Fig. S1; for all online suppl. material, see https://doi.org/10.1159/000536272). Eighty percent of PCS (10% CON) were classified as “poor sleeper” (PSQI >5 points [7]). PSG data are summarized in Table 1. The SpO2 min between-group difference of 5.0% (p = 0.066) was above the threshold of clinical meaningfulness (≥4 patients [9]). Sixty percent of PCS patients dropped below the preventive threshold of 90% (10% in CON).

Table 1.

Overview of polysomnography sleep data

PCS group (n = 20)CON group (n = 10)Between-group difference (mean difference, 95% CI)p value
Sleep architecture (PSG)     
 Time in bed, min 532±34 560±52 27.8 (−4.6 to 60.3) 0.045
 Total sleep time, min 376±65 437±42 60.7 (14.2–107.2) 0.006
 Wake time during TIB, min 157±66 123±57 −34.1 (−84.5 to 16.3) 0.09* 
 Sleep efficacy, % 70.6±11.9 78.4±8.0 7.8 (−0.9 to 16.4) 0.002
 Sleep stage N1, % in TST 7.8±4.6 5.8±2.6 −2.0 (−5.3 to 1.3) 0.11* 
 Sleep stage N2, % of TST 54.1±7.0 54.9±3.6 0.9 (−4.0 to 5.7) 0.36* 
 Sleep stage N3, % of TST 20.7±5.3 19.9±4.7 −0.7 (−4.8 to 3.4) 0.36* 
 REM sleep, % of TST 17.4±4.6 19.3±3.7 1.9 (−1.6 to 5.3) 0.14* 
Oxygenation (PSG) 
 SpO2 during wake time, % 95±2 96±1 1.1 (−0.3 to 2.4) 0.06* 
 SpO2 during NREM, % 94±2 95±1 1.2 (−0.2 to 2.7) 0.024
 SpO2 during REM, % 94±3 96±1 1.4 (−0.3 to –3.2) 0.050
 SpO2 min during TIB, % 85±8 91±4 5.0 (−0.4 to 10.4) 0.017
 Time SpO2 <90%, % of TIB 6.1±18.7 0.1±0.2 −6.0 (−18.3 to 6.3) 0.17* 
Nocturnal events (PSG), n/h 
 Apnoea-hypopnoea index 10.6±11.5 1.6±2.5 −9.0 (−14.8 to −3.3) 0.002
 Apnoea index 4.9±6.8 0.9±1.5 −4.0 (−7.4 to −0.6) 0.012
 Obstructive apnoea index 2.7±4.1 0.5±0.6 −2.2 (−4.2 to −0.2) 0.016
 Central apnoea index 2.0±3.0 0.4±1.0 −1.5 (−3.6 to 0.4) 0.06* 
 Mixed apnoea index 0.2±0.4 0.1±0.1 −0.1 (−0.3 to 0.1) 0.12* 
 Hypopnoea index 5.7±5.8 0.7±1.1 −5.1 (−7.9 to −2.2) 0.001
 Arousal index 13.4±9.9 8.9±8.2 22.4 (−44.3 to 89.2) 0.23* 
 PLM index 7.1±9.4 2.0±1.9 −5.1 (−9.8 to −0.4) 0.017
PCS group (n = 20)CON group (n = 10)Between-group difference (mean difference, 95% CI)p value
Sleep architecture (PSG)     
 Time in bed, min 532±34 560±52 27.8 (−4.6 to 60.3) 0.045
 Total sleep time, min 376±65 437±42 60.7 (14.2–107.2) 0.006
 Wake time during TIB, min 157±66 123±57 −34.1 (−84.5 to 16.3) 0.09* 
 Sleep efficacy, % 70.6±11.9 78.4±8.0 7.8 (−0.9 to 16.4) 0.002
 Sleep stage N1, % in TST 7.8±4.6 5.8±2.6 −2.0 (−5.3 to 1.3) 0.11* 
 Sleep stage N2, % of TST 54.1±7.0 54.9±3.6 0.9 (−4.0 to 5.7) 0.36* 
 Sleep stage N3, % of TST 20.7±5.3 19.9±4.7 −0.7 (−4.8 to 3.4) 0.36* 
 REM sleep, % of TST 17.4±4.6 19.3±3.7 1.9 (−1.6 to 5.3) 0.14* 
Oxygenation (PSG) 
 SpO2 during wake time, % 95±2 96±1 1.1 (−0.3 to 2.4) 0.06* 
 SpO2 during NREM, % 94±2 95±1 1.2 (−0.2 to 2.7) 0.024
 SpO2 during REM, % 94±3 96±1 1.4 (−0.3 to –3.2) 0.050
 SpO2 min during TIB, % 85±8 91±4 5.0 (−0.4 to 10.4) 0.017
 Time SpO2 <90%, % of TIB 6.1±18.7 0.1±0.2 −6.0 (−18.3 to 6.3) 0.17* 
Nocturnal events (PSG), n/h 
 Apnoea-hypopnoea index 10.6±11.5 1.6±2.5 −9.0 (−14.8 to −3.3) 0.002
 Apnoea index 4.9±6.8 0.9±1.5 −4.0 (−7.4 to −0.6) 0.012
 Obstructive apnoea index 2.7±4.1 0.5±0.6 −2.2 (−4.2 to −0.2) 0.016
 Central apnoea index 2.0±3.0 0.4±1.0 −1.5 (−3.6 to 0.4) 0.06* 
 Mixed apnoea index 0.2±0.4 0.1±0.1 −0.1 (−0.3 to 0.1) 0.12* 
 Hypopnoea index 5.7±5.8 0.7±1.1 −5.1 (−7.9 to −2.2) 0.001
 Arousal index 13.4±9.9 8.9±8.2 22.4 (−44.3 to 89.2) 0.23* 
 PLM index 7.1±9.4 2.0±1.9 −5.1 (−9.8 to −0.4) 0.017

Data are provided as mean ± standard deviation or as indicated.

Significant differences (p < 0.05) are marked in bold.

PSQI, Pittsburgh Sleep Quality Index; TIB, time in bed; TST, total sleep time; NREM, non-rapid eye movement; REM, rapid eye movement.

*One-sided p value.

Significantly more PCS patients compared to CON (60 vs. 10%, p = 0.028) met the criteria for a sleep apnoea diagnosis [8], whereas n = 9 (45%) suffered from mild (AHI range 5–14), n = 1 (5%) from moderate (AHI range 15–29) and n = 2 (10%) from severe sleep apnoea (AHI >30). As a result, an automatic continuous positive airway pressure (APAP) therapy was initialized in 40% of PCS patients (0% of CON). The frequency of apnoea and hypopnoea events did not differ between REM and NREM periods in PCS.

In this prospective trial, we found that 8.5 months after COVID-19 diagnosis, patients with PCS but not CON showed impaired sleep in most cases. PSG revealed a higher AHI, a higher frequency of PLM events and a lower sleep efficacy in patients with PCS compared to CON. Sixty percent of PCS patients were diagnosed with central, obstructive, or mixed sleep apnoea.

Subjective Sleep Health

In the past, self-reported sleep health has been evaluated in PCS by using different questionnaires. Recently published trials reported worse overall sleep health [6, 10], especially in the dimensions of sleep regularity, satisfaction, alertness, timing, efficiency and duration from pre to 6 months following COVID-19 [6]. The results of these studies were in line with the sleep quality from our cohort where we found an elevated PSQI score of 7.5 points (compared to 9.7 points [10]), and the majority of PCS patients reported impaired sleep (80% compared to 82.3% [10], “poor sleeper”: PSQI >5 patients [7]).

Objective Sleep Pattern

In patients with acute COVID-19, the prevalence of sleep apnoea has been shown to be high. In a sleep apnoea test, 34% of patients showed signs of obstructive and 41% of central sleep apnoea [11]. To our knowledge, this is the first trial evaluating sleep health by PSG in PCS compared to CON. To date, there are 2 publications which evaluated sleep via PSG in PCS without a CON group. Heidbreder et al. [12] found that in a small PCS cohort with suspected sleep disorders (n = 11), 36% of patients were diagnosed with obstructive sleep apnoea (OSA) 60 days after COVID-19 diagnosis. Although the mean AHI was around normal (3.8/h), there was an elevated AHI >5/h in 45% of cases (AHI >15/h in 27%). The authors found isolated REM sleep without atonia in 36% of cases, which is recognized as a prodromal stage of REM sleep behaviour disorder. This may reflect the involvement of the central nervous system in PCS-related sleep alterations. On one side, a prevalence of only 20% of central sleep apnoea events in our study suggests a secondary role of the central nervous system in the occurrence of sleep disturbances in PCS. However, we also observed that PLM was significantly more frequent in PCS, which is assumed to be related to abnormalities of the dopamine-neurotransmission in the central nervous system and might indicate a relevant contribution of the central nervous system in sleep disorders after COVID-19. Along these lines, it has been hypothesized that PCS may result from neuro-inflammatory events in the brain [13] which might be an explanatory approach for PLM in PCS.

Our data did not support the finding from a report of 2 cases [14] that in PCS, sleep apnoea only occurred during the REM sleep period. In our cohort, the prevalence of nocturnal events did not differ between REM and NREM sleep period. As the cases additionally suffered from fatigue symptoms, one can speculate that fatigue may alter sleep characteristics in PCS. As 90% of CON subjects did not show any sleep irregularities, these data yielded first information about sleep alterations due to PCS.

Clinical Relevance

In general, poor sleep quality has been found to be associated with poor quality of life [6], increased severity of depression, anxiety and post-traumatic stress [10] highlighting the general clinical importance of a good sleep quality. In survivors of COVID-19, untreated sleep apnoea was associated with a higher expression of pro-inflammatory cytokines and poorer metabolic and neurocognitive outcomes [15]. Patients with newly diagnosed sleep apnoea have been shown to be at higher risk to develop a lower respiratory tract infection [16]. Further, sleep disturbances are discussed as a potential cause of impaired lung function (FVC) and dyspnoea in PCS [5], which might have contributed to a reduced FVC and elevated dyspnoea levels in our PCS cohort.

As a longer time period since COVID-19 diagnosis has been found to be independently associated with poorer sleep health [6], a screening for sleep disturbances is important, especially if patients report impaired sleep. In case of OSA diagnosis after PSG, first data revealed that symptoms can be diminished 7 days after initializing APAP therapy in PCS [14].

Limitations

Firstly, the majority of patients with PCS reported weight gain since COVID-19. As an elevated BMI is an important risk factor for sleep apnoea [17] which was only observed in PCS, this might indicate a higher risk for sleep apnoea in PCS patients, independently of PCS. Nevertheless, BMI did not correlate to AHI in PCS (r = 0.011, p = 0.964) leaving open the possibility that elevated BMI and diagnosis of sleep apnoea do not indicate causality. Secondly, as we included PCS patients during pulmonary rehabilitation, these patients have a history of respiratory issues which is not generalized to the whole PCS cohort.

To conclude, sleep is objectively impaired in most PCS patients, even 8.5 months following COVID-19 diagnosis. PSG revealed an elevated AHI and more frequent PLM, which might explain the impaired sleep reported. As a poor sleep quality deteriorates quality of life and may amplify symptoms of dyspnoea or fatigue, a screening for sleep disturbances and a subsequent personalized treatment, e.g., with APAP therapy, education about good sleep hygiene, treating fears and worries, is of particular interest, in order to restore sleep quality, daily life activity and participation for long-term.

This study protocol was reviewed and approved by the Ethics Committee of Philipps University of Marburg, approval number 149/21. Consent to participate statement: Written informed consent was obtained from participants to participate in the study.

The authors have no conflicts of interest to declare.

This study was not supported by any sponsor or funder.

The authors confirm contribution to the paper as follows: study conception and design: I.J., T.S., R.G., D.L., C.S., and A.R.K.; data collection: I.J., A.S., T.S., R.G., and D.L.; analysis and interpretation of results: I.J., A.S., T.S., W.H., and C.D.; draft manuscript preparation: I.J., T.S., C.D., W.H., and A.R.K. All authors reviewed the results and approved the final version of the manuscript.

Data are available on request from the corresponding author (I.J.). The data are not publicly available due to due to ethical restrictions.

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