Evidence map›Paper›PMID 30815148›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2018

Disease Trajectories and End-of-Life Care for Dementias: Latent Topic Modeling and Trend Analysis Using Clinical Notes.

Liqin Wang, Joshua Lakin, Clay Riley, Zfania Korach, Laura N Frain, Li Zhou

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 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

27 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  15. Machine learning approaches for electronic health records phenotyping: a methodical review.Journal of the American Medical Informatics Association : JAMIA · 2023
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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

6 authors.

Liqin WangBrigham and Women's Hospital, Boston, MA, USA.
Joshua LakinBrigham and Women's Hospital, Boston, MA, USA.
Clay RileyBrigham and Women's Hospital, Boston, MA, USA.
Zfania KorachBrigham and Women's Hospital, Boston, MA, USA.
Laura N FrainBrigham and Women's Hospital, Boston, MA, USA.
Li ZhouBrigham and Women's Hospital, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the increasing prevalence, growing costs, and high mortality of dementia in older adults in the U.S., little is known about the course of these diseases and what care dementia patients receive in their final years of life. Using a large volume of clinical notes of dementia patients over the last two years of life, we conducted automatic topic modeling to capture the trends of various themes mentioned in care provider notes, including patients' physical function status, mental health, falls, nutrition and feeding, infections, hospital care, intensive care, end-of-life care, and family and social supports. Our research contributes to the adoption and evaluation of an unsupervised machine learning method using large amounts of retrospective free-text electronic health record data to discover and understand illness and health care trajectories.

Indexed as

Electronic Health RecordsTerminal CareUnsupervised Machine LearningAgedAged, 80 and overData CollectionDementiaFemaleHumansMaleModels, TheoreticalRetrospective Studies

Identifiers

PMID30815148
PMCPMC6371376

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.