Evidence map›Paper›PMID 42117080›Full record

ArticleNature and science of sleep2026

Effective Doses and Predictors of Dexmedetomidine for Inducing Specific Sleep Stages (N2/N3) in Chronic Insomnia: A Retrospective Cohort Study.

Zhenxiu Liu, Zhouquan Wu, Renqun Wang, Dandan Yin, Huichan Xv, Panqi Wang, Fuhai Ji, Jingjing Shen

Abstract read
In one paragraph

Article in Nature and science of sleep, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Zhenxiu Liu *Department of Anesthesiology and Pain, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.
Zhouquan Wu *Department of Anesthesiology, The Second People's Hospital of Changzhou, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, Jiangsu, People's Republic of China.
Renqun Wang *Department of Anesthesiology, Ningde People's hospital, Ningde, Fujian, People's Republic of China.
Dandan YinDepartment of Anesthesiology, The Second People's Hospital of Changzhou, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, Jiangsu, People's Republic of China.
Huichan XvDepartment of Anesthesiology and Pain, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.
Panqi WangDepartment of Anesthesiology and Pain, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.
Fuhai JiDepartment of Anesthesiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.ORCID 0000-0002-3269-3417
Jingjing ShenDepartment of Anesthesiology, The Second People's Hospital of Changzhou, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, Jiangsu, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Dexmedetomidine (DEX) has emerged as a potential agent for sleep modulation; however, the effective doses required to induce multimodal electroencephalography (EEG)-defined sleep stages in patients with chronic insomnia remain unclear. Objective: This study aimed to quantify the cumulative DEX doses required to induce non-rapid eye movement (NREM) stage N2 and N3 sleep and to identify clinical predictors of dose variability. Methods: In this single-center retrospective cohort study, we analyzed 252 adults with chronic insomnia who underwent standardized intravenous DEX titration under continuous multimodal EEG monitoring. The primary outcomes were the cumulative DEX doses (µg) required to induce sustained N2 or N3 sleep. Univariable and multivariable linear regression models were used to identify independent predictors, including body mass index (BMI), depressive symptom severity assessed by the Montgomery-Åsberg Depression Rating Scale (MADRS), and other clinically relevant covariates. Restricted cubic spline analyses were performed to examine potential nonlinear associations between BMI and DEX dose. Prespecified subgroup analyses stratified by age (<60 vs. ≥60 years) were conducted to assess effect modification. Results: The median effective dose was 40 µg (interquartile range [IQR], 33-48) for N2 sleep induction and 55 µg (IQR, 48-64) for N3 sleep induction. BMI was independently associated with higher DEX dose requirements for both N2 (adjusted β = 0.71; 95% CI, 0.25-1.17; P = 0.003) and N3 sleep (adjusted β = 0.48; 95% CI, 0.07-0.89; P = 0.022). Higher MADRS scores were independently associated with increased DEX dose for N2 sleep induction (adjusted β = 0.17; 95% CI, 0.01-0.34; P = 0.041) but not for N3 sleep. Restricted cubic spline analyses demonstrated significant overall associations between BMI and DEX dose for both sleep stages, while tests for nonlinearity were not statistically significant. Age was not significantly associated with DEX dose requirements, and no significant interaction by age group was observed. Conclusion: In patients with chronic insomnia, higher cumulative doses of DEX are required to induce deeper NREM sleep stages. BMI is a key determinant of DEX dose requirements for both N2 and N3 sleep, whereas depressive symptom severity appears to selectively influence N2 sleep induction. These findings support the use of individualized, multimodal EEG-guided DEX titration strategies and provide preliminary data to inform future prospective dose-finding studies.

Indexed as

body mass indexchronic insomniadepressiondexmedetomidinedose-findingpersonalized medicine

Identifiers

PMID42117080
PMCPMC13157349

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.