Evidence map›Paper›PMID 33658610›Full record

ArticleNPJ digital medicine2021

Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices.

Nikhil Mahadevan, Yiorgos Christakis, Junrui Di, Jonathan Bruno, Yao Zhang, E Ray Dorsey, Wilfred R Pigeon, Lisa A Beck, Kevin Thomas, Yaqi Liu and 6 more

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ digital medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03490877 (Quantification of Scratch and Sleep in Atopic Dermatitis), which is not on this map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing 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.

NCT03490877 completednot on this map

Quantification of Scratch and Sleep in Atopic Dermatitis

TypeobservationalSponsorUniversity of RochesterRan2018 to 2019Enrolled45ConditionsAtopic Dermatitis, Pruritus, Sleep Disturbance
3 · Its place in the literature

Who cites it

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

  1. Pooled it
  2. Current research landscape and future prospects of in silico modeling approaches for atopic dermatitis.JID innovations : skin science from molecules to population health · 2026
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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

16 authors.

Nikhil Mahadevan *Pfizer, Inc., Cambridge, MA, USA. nmdevan816@gmail.com.ORCID http://orcid.org/0000-0003-0257-9311
Yiorgos Christakis *Pfizer, Inc., Cambridge, MA, USA.ORCID http://orcid.org/0000-0003-3371-8935
Junrui DiPfizer, Inc., Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-6325-8090
Jonathan BrunoPfizer, Inc., Cambridge, MA, USA.
Yao ZhangPfizer, Inc., Cambridge, MA, USA.
E Ray DorseyUniversity of Rochester Medical Center, Rochester, NY, USA.
Wilfred R PigeonUniversity of Rochester Medical Center, Rochester, NY, USA.
Lisa A BeckUniversity of Rochester Medical Center, Rochester, NY, USA.ORCID http://orcid.org/0000-0002-8452-667X
Kevin ThomasBoston University School of Medicine, Boston, MA, USA.
Yaqi LiuBoston University School of Medicine, Boston, MA, USA.
Madisen WickerBoston University School of Medicine, Boston, MA, USA.ORCID http://orcid.org/0000-0002-6240-0208
Chris BrooksBoston University School of Medicine, Boston, MA, USA.ORCID http://orcid.org/0000-0002-9511-5390
Nina Shaafi KabiriBoston University School of Medicine, Boston, MA, USA.ORCID http://orcid.org/0000-0001-8951-2237
Jaspreet BhanguBoston University School of Medicine, Boston, MA, USA.
Carrie NorthcottPfizer, Inc., Cambridge, MA, USA.
Shyamal PatelPfizer, Inc., Cambridge, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patients with atopic dermatitis experience increased nocturnal pruritus which leads to scratching and sleep disturbances that significantly contribute to poor quality of life. Objective measurements of nighttime scratching and sleep quantity can help assess the efficacy of an intervention. Wearable sensors can provide novel, objective measures of nighttime scratching and sleep; however, many current approaches were not designed for passive, unsupervised monitoring during daily life. In this work, we present the development and analytical validation of a method that sequentially processes epochs of sample-level accelerometer data from a wrist-worn device to provide continuous digital measures of nighttime scratching and sleep quantity. This approach uses heuristic and machine learning algorithms in a hierarchical paradigm by first determining when the patient intends to sleep, then detecting sleep-wake states along with scratching episodes, and lastly deriving objective measures of both sleep and scratch. Leveraging reference data collected in a sleep laboratory (NCT ID: NCT03490877), results show that sensor-derived measures of total sleep opportunity (TSO; time when patient intends to sleep) and total sleep time (TST) correlate well with reference polysomnography data (TSO: r = 0.72, p < 0.001; TST: r = 0.76, p < 0.001; N = 32). Log transformed sensor derived measures of total scratching duration achieve strong agreement with reference annotated video recordings (r = 0.82, p < 0.001; N = 25). These results support the use of wearable sensors for objective, continuous measurement of nighttime scratching and sleep during daily life.

Identifiers

PMID33658610
PMCPMC7930047

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Registered trials

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