Sleep for COVID-19: real-time meta analysis of 13 studies
@CovidAnalysis, September 2023
https://c19early.org/slmeta.html
•Statistically significant lower risk is seen for mortality, hospitalization, and cases. 10 studies from 10 independent teams in 4 countries show statistically significant
improvements.
•Meta analysis using the most serious outcome reported shows
31% [22‑40%] lower risk. Results are similar for peer-reviewed studies.
•Results are robust — in exclusion sensitivity analysis 11 of 13
studies must be excluded to avoid finding statistically significant efficacy
in pooled analysis.
•Studies analyze sleep quality before infection, and use different definitions of sleep quality.
•No treatment or intervention
is 100% effective. All practical, effective, and safe means should be used
based on risk/benefit analysis.
•All data to reproduce this paper and
sources are in the appendix.
Highlights
Good quality sleep reduces
risk for COVID-19 with very high confidence for mortality, cases, and in pooled analysis, and low confidence for hospitalization.
We show traditional outcome specific analyses and combined
evidence from all studies.
Real-time updates and corrections,
transparent analysis with all results in the same format, consistent protocol
for 56
treatments.
B
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C
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Figure 1.
A. Random effects
meta-analysis. This plot shows pooled effects, see the specific outcome analyses for individual
outcomes, and the heterogeneity section for discussion.
Effect extraction is pre-specified, using the most serious outcome reported.
For details of effect extraction see the
appendix.
B. Scatter plot showing the most
serious outcome in all studies. The diamond shows the results of random effects meta-analysis.
C. Results within the context of multiple COVID-19 treatments.
0.7% of 5,019 proposed treatments show efficacy
c19early.org.
D. Timeline of results in sleep studies. The marked dates indicate the time when efficacy was known with a statistically significant improvement of ≥10% from ≥3 studies for pooled outcomes and one or more specific outcome.
We analyze all significant studies
reporting COVID-19 outcomes as a function of sleep quality and providing adjusted results.
Search methods, inclusion criteria, effect extraction criteria (more serious
outcomes have priority), all individual study data, PRISMA answers, and
statistical methods are detailed in Appendix 1. We present random
effects meta-analysis results for all studies, individual outcomes, and peer-reviewed studies.
Table 1 summarizes the results for all studies, after exclusions, and for specific outcomes.
Figure 2, 3, 4, 5, and 6
show forest plots for random effects meta-analysis of
all studies with pooled effects, mortality results, hospitalization, cases, and peer reviewed studies.
| Improvement | Studies | Patients | Authors | |
|---|---|---|---|---|
| All studies | 31% [22‑40%] **** | 13 | 354,908 | 122 |
| Peer-reviewed studiesPeer-reviewed | 29% [20‑37%] **** | 12 | 353,097 | 120 |
| Mortality | 33% [11‑50%] ** | 3 | 313,843 | 25 |
| HospitalizationHosp. | 33% [21‑43%] **** | 2 | 46,535 | 20 |
| Cases | 14% [7‑20%] *** | 6 | 35,032 | 81 |
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Figure 2. Random effects meta-analysis for all studies with pooled effects.
This plot shows pooled effects, see the specific outcome analyses for individual
outcomes, and the heterogeneity section for discussion.
Effect extraction is pre-specified, using the most serious outcome reported.
For details of effect extraction see the
appendix.
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Figure 3. Random effects meta-analysis for mortality results.
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Figure 4. Random effects meta-analysis for hospitalization.
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Figure 5. Random effects meta-analysis for cases.
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Figure 6. Random effects meta-analysis for peer reviewed studies.
Zeraatkar analyze 356 COVID-19 trials, finding no significant
evidence that preprint results are inconsistent with peer-reviewed studies.
They also show extremely long peer-review delays, with a median of 6 months to
journal publication. A six month delay was equivalent to around 1.5 million
deaths during the first two years of the pandemic. Authors recommend using
preprint evidence, with appropriate checks for potential falsified data, which
provides higher certainty much earlier.
Effect extraction is pre-specified, using the most serious outcome reported,
see the appendix for details.
Better sleep reduces risk for COVID-19.
Statistically significant lower risk is seen for mortality, hospitalization, and cases. 10 studies from 10 independent teams in 4 countries show statistically significant
improvements.
Meta analysis using the most serious outcome reported shows
31% [22‑40%] lower risk. Results are similar for peer-reviewed studies.
Results are robust — in exclusion sensitivity analysis 11 of 13
studies must be excluded to avoid finding statistically significant efficacy
in pooled analysis.
Studies analyze sleep quality before infection, and use different definitions of sleep quality.
Ahmadi:
Retrospective 468,569 adults in the UK, showing no significant difference in COVID-19 mortality based on sleep quality.
Cloosterman:
Analysis of 2,586 participants of a running injury prevention RCT in the Netherlands, showing higher risk of COVID-19 symptoms with sleep disturbance.
Gao:
Case control study in China with 105 cases and 210 matched controls, showing COVID-19 cases associated with lack of sleep.
Holt:
Prospective survey-based study with 15,227 people in the UK, showing reduced risk of COVID-19 cases with 8 hours sleep, with statistical significance when compared with ≥9 hours. NCT04330599. COVIDENCE UK.
Huang:
Retrospective 164 COVID-19 patients and 188 controls in China, showing the risk of severe cases associated with lack of sleep.
Jones:
FinnGen Mendelian randomization study showing higher risk of COVID-19 mortality, hospitalization, and infection with insomnia.
Kim:
Retrospective 2,884 high-risk healthcare workers in France, Germany, Italy, Spain, UK, and the USA, showing shorter sleep duration associated with increased risk of COVID-19 cases and severity.
Li:
UK Biobank retrospective, 46,535 participants with sleep behavior assessed between 2006 and 2010, showing higher risk of hospitalization and mortality with poor sleep.
Marcus:
Prospective survey based study with 14,335 participants, showing risk of viral symptoms associated with shorter sleep duration.
Mohsin:
Retrospective 1,500 COVID+ patients in Bangladesh, showing lower risk of severe cases with good sleep.
Paul:
Retrospective 1,811 COVID-19 patients in the UK, showing lower risk of self-reported long COVID with good sleep quality in the month before infection.
Pływaczewska-Jakubowska:
Retrospective 1,847 COVID+ patients in Poland, showing lower moderate/severe cases with improved sleep, without statistical significance. Hospitalized patients were excluded.
Wang:
Retrospective 1,979 nurses in the USA, showing lower risk of long COVID with better sleep quality.
We performed ongoing searches of PubMed, medRxiv,
ClinicalTrials.gov, The Cochrane Library, Google Scholar, Collabovid, Research
Square, ScienceDirect, Oxford University Press, the reference lists of other
studies and meta-analyses, and submissions to the site c19early.org.
Search terms were sleep AND COVID-19. Automated searches are performed
every few hours with notification of new matches.
All studies regarding the use of sleep for COVID-19 that report
a comparison with a control group are included in the main analysis.
This is a living analysis and is updated regularly.
We extracted effect sizes and associated data from all studies.
If studies report multiple kinds of effects then the most serious
outcome is used in pooled analysis, while other outcomes are included in the
outcome specific analyses. For example, if effects for mortality and cases are
both reported, the effect for mortality is used, this may be different to the
effect that a study focused on.
If symptomatic
results are reported at multiple times, we used the latest time, for example
if mortality results are provided at 14 days and 28 days, the results at 28
days are used. Mortality alone is preferred over combined outcomes.
Outcomes with zero events in both arms were not used (the next most serious
outcome is used — no studies were excluded). For example, in low-risk
populations with no mortality, a reduction in mortality with treatment is not
possible, however a reduction in hospitalization, for example, is still
valuable.
Clinical outcome is considered more important than PCR testing status. When
basically all patients recover in both treatment and control groups,
preference for viral clearance and recovery is given to results mid-recovery
where available (after most or all patients have recovered there is no room
for an effective treatment to do better).
If only individual symptom data is available, the most serious symptom has
priority, for example difficulty breathing or low SpO2 is more
important than cough.
When results provide an odds ratio, we computed the relative risk when
possible, or converted to a relative risk according to Zhang.
Reported confidence intervals and p-values were used when available,
using adjusted values when provided. If multiple types of adjustments are
reported including propensity score matching (PSM), the PSM results are used.
Adjusted primary outcome results have preference over unadjusted results for a more
serious outcome when the adjustments significantly alter results.
When needed, conversion between reported p-values and confidence
intervals followed Altman, Altman (B), and Fisher's exact test was
used to calculate p-values for event data. If continuity correction for
zero values is required, we use the reciprocal of the opposite arm with the
sum of the correction factors equal to 1 Sweeting.
Results are expressed with RR < 1.0 favoring treatment, and using the risk of
a negative outcome when applicable (for example, the risk of death rather than
the risk of survival). If studies only report relative continuous values such
as relative times, the ratio of the time for the treatment group versus the
time for the control group is used. Calculations are done in Python
(3.11.4) with
scipy (1.11.1), pythonmeta (1.26), numpy (1.25.0), statsmodels (0.14.0), and plotly (5.15.0).
Forest plots are computed using PythonMeta Deng
with the DerSimonian and Laird random effects model (the fixed effect
assumption is not plausible in this case) and inverse variance weighting.
Mixed-effects meta-regression results are computed with R (4.1.2) using the metafor
(3.0-2) and rms (6.2-0) packages, and using the most serious sufficiently powered outcome.
We received no funding, this research is done in our spare
time. We have no affiliations with any pharmaceutical companies or political
parties.
We have classified studies as early treatment if most patients
are not already at a severe stage at the time of treatment (for example based
on oxygen status or lung involvement), and treatment started within 5 days of
the onset of symptoms. If studies contain a mix of early treatment and late
treatment patients, we consider the treatment time of patients contributing
most to the events (for example, consider a study where most patients are
treated early but late treatment patients are included, and all mortality
events were observed with late treatment patients).
We note that a shorter time may be preferable. Antivirals are typically only
considered effective when used within a shorter timeframe, for example 0-36 or
0-48 hours for oseltamivir, with longer delays not being effective
McLean, Treanor.
A summary of study results is below. Please submit
updates and corrections at https://c19early.org/slmeta.html.
Effect extraction follows pre-specified rules as detailed above
and gives priority to more serious outcomes.
For pooled analyses, the first (most serious) outcome is used, which may
differ from the effect a paper focuses on.
Other outcomes are used in outcome specific analyses.
| Ahmadi, 8/31/2021, retrospective, United Kingdom, peer-reviewed, 5 authors. | risk of death, 3.0% lower, RR 0.97, p = 0.91, adjusted per study, good vs. poor, model 2, multivariable. |
| Cloosterman, 10/21/2020, retrospective, Netherlands, peer-reviewed, 4 authors. | risk of symptomatic case, 31.6% lower, RR 0.68, p = 0.09, higher quality sleep 31 of 201 (15.4%), lower quality sleep 222 of 2,385 (9.3%), inverted to make RR<1 favor higher quality sleep, odds ratio converted to relative risk. |
| Gao, 11/5/2020, retrospective, China, peer-reviewed, survey, median age 55.0, 11 authors, study period 10 February, 2020 - 1 March, 2020. | risk of case, 35.9% lower, HR 0.64, p = 0.04, higher quality sleep 73 of 105 (69.5%) cases, 179 of 210 (85.2%) controls, NNT 4.6, inverted to make HR<1 favor higher quality sleep, case control OR, Cox proportional hazards. |
| Holt, 3/30/2021, prospective, United Kingdom, peer-reviewed, 34 authors, study period 1 May, 2020 - 5 February, 2021, trial NCT04330599 (history) (COVIDENCE UK). | risk of case, 12.3% lower, OR 0.88, p = 0.50, adjusted per study, inverted to make OR<1 favor higher quality sleep, fully adjusted, 8 hours vs. ≤6 hours, RR approximated with OR. |
| risk of case, 12.3% lower, OR 0.88, p = 0.33, adjusted per study, inverted to make OR<1 favor higher quality sleep, fully adjusted, 8 hours vs. 7 hours, RR approximated with OR. | |
| risk of case, 22.5% lower, OR 0.78, p = 0.04, adjusted per study, inverted to make OR<1 favor higher quality sleep, fully adjusted, 8 hours vs. ≥9 hours, RR approximated with OR. | |
| Huang, 11/30/2021, retrospective, China, peer-reviewed, survey, 5 authors, study period 10 February, 2020 - 28 March, 2020. | risk of severe case, 80.9% lower, RR 0.19, p = 0.02, higher quality sleep 12 of 127 (9.4%), lower quality sleep 4 of 9 (44.4%), NNT 2.9, adjusted per study, inverted to make RR<1 favor higher quality sleep, odds ratio converted to relative risk, recommended vs. lack of sleep, multivariable. |
| Jones, 7/21/2022, retrospective, multiple countries, peer-reviewed, 12 authors. | risk of death, 39.0% lower, OR 0.61, p = 0.001, inverted to make OR<1 favor higher quality sleep, RR approximated with OR. |
| risk of hospitalization, 32.0% lower, OR 0.68, p < 0.001, inverted to make OR<1 favor higher quality sleep, RR approximated with OR. | |
| risk of case, 7.4% lower, OR 0.93, p = 0.04, inverted to make OR<1 favor higher quality sleep, RR approximated with OR. | |
| Kim, 3/22/2021, retrospective, multiple countries, peer-reviewed, survey, mean age 48.0, 8 authors, study period 17 July, 2020 - 25 September, 2020. | risk of moderate/severe case, 17.0% lower, OR 0.83, p = 0.03, per extra hour of sleep, RR approximated with OR. |
| risk of case, 11.0% lower, OR 0.89, p = 0.003, per extra hour of sleep, model 3, RR approximated with OR. | |
| Li, 6/18/2021, retrospective, USA, peer-reviewed, mean age 69.4, 8 authors, study period March 2020 - December 2020. | risk of death, 43.2% lower, OR 0.57, p = 0.02, inverted to make OR<1 favor higher quality sleep, fully adjusted model C, significant poor sleep burden, RR approximated with OR. |
| risk of hospitalization, 35.9% lower, OR 0.64, p = 0.008, inverted to make OR<1 favor higher quality sleep, fully adjusted model C, significant poor sleep burden, RR approximated with OR. | |
| risk of hospitalization, 21.3% lower, OR 0.79, p = 0.02, inverted to make OR<1 favor higher quality sleep, fully adjusted model C, moderate poor sleep burden, RR approximated with OR. | |
| Marcus, 6/17/2021, prospective, multiple countries, peer-reviewed, survey, 12 authors, study period 26 March, 2020 - 3 May, 2020. | risk of symptomatic case, 16.0% lower, OR 0.84, p < 0.001, adjusted per study, per extra hour sleep, multivariable, RR approximated with OR. |
| Mohsin, 9/30/2021, retrospective, Bangladesh, peer-reviewed, survey, 10 authors, study period November 2020 - April 2021. | risk of severe case, 37.9% lower, RR 0.62, p < 0.001, higher quality sleep 327 of 948 (34.5%), lower quality sleep 273 of 552 (49.5%), NNT 6.7, adjusted per study, inverted to make RR<1 favor higher quality sleep, odds ratio converted to relative risk, sleep disturbance, multivariable. |
| Paul, 4/13/2022, retrospective, United Kingdom, preprint, survey, 2 authors. | risk of long COVID, 67.3% lower, RR 0.33, p < 0.001, adjusted per study, inverted to make RR<1 favor higher quality sleep, odds ratio converted to relative risk, very good/good vs. not good/very poor, multivariable, model 4, control prevalance approximated with overall prevalence. |
| risk of long COVID, 54.0% lower, RR 0.46, p = 0.002, adjusted per study, inverted to make RR<1 favor higher quality sleep, odds ratio converted to relative risk, very good/good vs. average, multivariable, model 4, control prevalance approximated with overall prevalence. | |
| Pływaczewska-Jakubowska, 10/24/2022, retrospective, Poland, peer-reviewed, median age 51.0, 5 authors, study period May 2020 - January 2022. | risk of moderate/severe case, 17.4% lower, OR 0.83, p = 0.06, higher quality sleep 1,225, lower quality sleep 622, adjusted per study, inverted to make OR<1 favor higher quality sleep, higher quality sleep vs. insomnia or falling asleep after midnight or nightshifts, multivariable, model 3, RR approximated with OR. |
| risk of PASC, 7.4% lower, OR 0.93, p = 0.51, higher quality sleep 1,015, lower quality sleep 502, adjusted per study, inverted to make OR<1 favor higher quality sleep, higher quality sleep vs. insomnia or falling asleep after midnight or nightshifts, multivariable, model 3, RR approximated with OR. | |
| Wang, 5/30/2023, retrospective, USA, peer-reviewed, 6 authors. | risk of PASC, 36.0% lower, RR 0.64, p < 0.001, higher quality sleep 559, lower quality sleep 180, adjusted per study, healthy sleep before and during the pandemic, multivariable. |
| risk of PASC, 18.0% lower, RR 0.82, p = 0.03, adjusted per study, healthy sleep during the pandemic, multivariable. | |
| risk of PASC, 30.0% lower, RR 0.70, p = 0.02, higher quality sleep 238, lower quality sleep 166, adjusted per study, healthy sleep before the pandemic, sleep score 5 vs. score 0 or 1, multivariable. |
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Please send us corrections, updates, or comments. Vaccines and
treatments are complementary. All practical, effective, and safe means should
be used based on risk/benefit analysis. No treatment, vaccine, or intervention
is 100% available and effective for all current and future variants. We do not
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physician who can provide personalized advice and details of risks and
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