Evidence map›Paper›PMID 37917132›Full record

ArticleJMIR formative research2023

Patient Journey Toward a Diagnosis of Light Chain Amyloidosis in a National Sample: Cross-Sectional Web-Based Study.

Xuelin Dou, Yang Liu, Aijun Liao, Yuping Zhong, Rong Fu, Lihong Liu, Canchan Cui, Xiaohong Wang, Jin Lu

Abstract read
In one paragraph

Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

9 authors.

Xuelin Dou *Hematology Department, Peking University People's Hospital, Beijing, China.ORCID https://orcid.org/0000-0001-7040-9272
Yang Liu *Hematology Department, Peking University People's Hospital, Beijing, China.ORCID https://orcid.org/0000-0002-8471-8460
Aijun LiaoHematology Department, Shengjing Hospital of China Medical University, Shenyang, China.ORCID https://orcid.org/0009-0003-5057-2541
Yuping ZhongHematology Department, Qingdao Municipal Hospital, Qingdao University, Qingdao, China.ORCID https://orcid.org/0000-0001-6277-1183
Rong FuHematology Department, Tianjin Medical University General Hospital, Tianjin, China.ORCID https://orcid.org/0000-0002-9928-9224
Lihong LiuHematology Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China.ORCID https://orcid.org/0000-0001-9610-7117
Canchan CuiMedical Affairs, Xi'an Janssen Pharmaceutical Ltd, Beijing, China.ORCID https://orcid.org/0009-0007-4679-7851
Xiaohong WangMedical Affairs, Xi'an Janssen Pharmaceutical Ltd, Shanghai, China.ORCID https://orcid.org/0000-0002-7239-7524
Jin LuHematology Department, Peking University People's Hospital, Beijing, China.ORCID https://orcid.org/0000-0001-5004-2741

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSystemic light chain (AL) amyloidosis is a rare and multisystem disease associated with increased morbidity and a poor prognosis. Delayed diagnoses are common due to the heterogeneity of the symptoms. However, real-world insights from Chinese patients with AL amyloidosis have not been investigated.

objectiveThis study aimed to describe the journey to an AL amyloidosis diagnosis and to build an in-depth understanding of the diagnostic process from the perspective of both clinicians and patients to obtain a correct and timely diagnosis.

methodsPublicly available disease-related content from social media platforms between January 2008 and April 2021 was searched. After performing data collection steps with a machine model, a series of disease-related posts were extracted. Natural language processing was used to identify the relevance of variables, followed by further manual evaluation and analysis.

resultsA total of 2204 valid posts related to AL amyloidosis were included in this study, of which 1968 were posted on haodf.com. Of these posts, 1284 were posted by men (median age 57, IQR 46-67 years); 1459 posts mentioned renal-related symptoms, followed by heart (n=833), liver (n=491), and stomach (n=368) symptoms. Furthermore, 1502 posts mentioned symptoms related to 2 or more organs. Symptoms for AL amyloidosis most frequently mentioned by suspected patients were nonspecific weakness (n=252), edema (n=196), hypertrophy (n=168), and swelling (n=140). Multiple physician visits were common, and nephrologists (n=265) and hematologists (n=214) were the most frequently visited specialists by suspected patients for initial consultation. Additionally, interhospital referrals were also commonly seen, centralizing in tertiary hospitals.

conclusionsChinese patients with AL amyloidosis experienced referrals during their journey toward accurate diagnosis. Increasing awareness of the disease and early referral to a specialized center with expertise may reduce delayed diagnosis and improve patient management.

Indexed as

AL amyloidosisbig datamachine modelnatural language processingnetwork analysisrare diseasesystemic light chain amyloidosisweb-based

Identifiers

PMID37917132
PMCPMC10654903

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.