Evidence map›Paper›PMID 35971023›Full record

ArticleSleep & breathing = Schlaf & Atmung2023

High prevalence of sleep-disordered breathing in the intensive care unit - a cross-sectional study.

Abigail A Bucklin, Wolfgang Ganglberger, Syed A Quadri, Ryan A Tesh, Noor Adra, Madalena Da Silva Cardoso, Michael J Leone, Parimala Velpula Krishnamurthy, Aashritha Hemmige, Subapriya Rajan and 14 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sleep & breathing = Schlaf & Atmung, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
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

24 authors.

Abigail A Bucklin *Department of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Wolfgang Ganglberger *Department of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Syed A QuadriClinical Data Animation Center (CDAC), MGH, Boston, MA, USA.
Ryan A TeshDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Noor AdraDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Madalena Da Silva CardosoDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Michael J LeoneDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Parimala Velpula KrishnamurthyDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Aashritha HemmigeDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Subapriya RajanDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Ezhil PanneerselvamDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Luis PaixaoDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Jasmine HigginsDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Muhammad Abubakar AyubDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Yu-Ping ShaoDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Elissa M YeDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Brian CoughlinDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Haoqi SunDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
Sydney S CashDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
B Taylor ThompsonDepartment of Medicine, MGH, Boston, MA, USA.
Oluwaseun AkejuHenry and Allison McCance Center for Brain Health, MGH, Boston, MA, USA.
David KullerMyAir Inc, Boston, MA, USA.
Robert J ThomasClinical Data Animation Center (CDAC), MGH, Boston, MA, USA.
M Brandon WestoverDepartment of Neurology, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA. mwestover@mgh.harvard.edu.ORCID 0000-0003-4803-312X

Funding

Data-Driven Sleep Biomarkers of Brain Health, Heart Health, and MortalityR01HL161253 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI CLIFFORD, GARI DAVID, MIGNOT, EMMANUEL J · 2022 to 2025
$8.3M
Integrative Motor Activity Biomarker for the Risk of Alzheimer's RiskRF1AG064312 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI HU, KUN · 2019 to 2019
$3.6M
Multimodal Network Connectivity Architecture (MOCA) of the Brain and its Role in the Recovery of Consciousness in Comatose Cardiac Arrest PatientsR01NS102574 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI GREER, DAVID MATTHEW, WU, ONA · 2018 to 2022
$3.4M
Investigation of Sleep in the Intensive Care Unit (ICU-SLEEP)R01NS102190 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI WESTOVER, MICHAEL BRANDON · 2018 to 2022
$3.2M
Big Data and Deep Learning for the Interictal-Ictal-Injury ContiuumR01NS107291 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI WESTOVER, MICHAEL BRANDON · 2018 to 2022
$2.8M
Establishing a Brain Health Index from the Sleep ElectroencephalogramRF1NS120947 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI CASH, SYDNEY S, THOMAS, ROBERT JOSEPH · 2021 to 2021
$2.4M
NHLBI NIH HHS R01 HL161253NIA NIH HHS RF1 AG064312NIH HHS 1R01NS102190NIH HHS 1R01NS102574NIH HHS 1R01NS107291NIH HHS 1RF1AG064312NINDS NIH HHS R01 NS102190NINDS NIH HHS R01 NS102574NINDS NIH HHS R01 NS107291NINDS NIH HHS RF1 NS120947
6 · The paper itself

Abstract

purposeSleep-disordered breathing may be induced by, exacerbate, or complicate recovery from critical illness. Disordered breathing during sleep, which itself is often fragmented, can go unrecognized in the intensive care unit (ICU). The objective of this study was to investigate the prevalence, severity, and risk factors of sleep-disordered breathing in ICU patients using a single respiratory belt and oxygen saturation signals.

methodsPatients in three ICUs at Massachusetts General Hospital wore a thoracic respiratory effort belt as part of a clinical trial for up to 7 days and nights. Using a previously developed machine learning algorithm, we processed respiratory and oximetry signals to measure the 3% apnea-hypopnea index (AHI) and estimate AH-specific hypoxic burden and periodic breathing. We trained models to predict AHI categories for 12-h segments from risk factors, including admission variables and bio-signals data, available at the start of these segments.

resultsOf 129 patients, 68% had an AHI ≥ 5; 40% an AHI > 15, and 19% had an AHI > 30 while critically ill. Median [interquartile range] hypoxic burden was 2.8 [0.5, 9.8] at night and 4.2 [1.0, 13.7] %min/h during the day. Of patients with AHI ≥ 5, 26% had periodic breathing. Performance of predicting AHI-categories from risk factors was poor.

conclusionsSleep-disordered breathing and sleep apnea events while in the ICU are common and are associated with substantial burden of hypoxia and periodic breathing. Detection is feasible using limited bio-signals, such as respiratory effort and SpO

Indexed as

Sleep Apnea, ObstructiveSleep Apnea SyndromesCross-Sectional StudiesHumansHypoxiaIntensive Care UnitsPolysomnographyPrevalenceApneaCritical careIntensive care unitMachine learningSleep-disordered breathing

Identifiers

PMID35971023
PMCPMC9931933

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Registered trials

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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 OpenQuestion graph.