metadata

license: cc-by-nc-sa-4.0
language:
  - en
tags:
  - information retrieval
  - patient similarity
  - clinical decision support
size_categories:
  - 100K<n<1M

Dataset Card for PMC-Patients

Dataset Description

Homepage: https://github.com/pmc-patients/pmc-patients
Repository: https://github.com/pmc-patients/pmc-patients
Paper: https://arxiv.org/pdf/2202.13876.pdf
Leaderboard: https://pmc-patients.github.io/
Point of Contact: zhengyun21@mails.tsinghua.edu.cn

Dataset Summary

PMC-Patients is a first-of-its-kind dataset consisting of 167k patient summaries extracted from case reports in PubMed Central (PMC), 3.1M patient-article relevance and 293k patient-patient similarity annotations defined by PubMed citation graph.

Supported Tasks and Leaderboards

Based on PMC-Patients, we define two tasks to benchmark Retrieval-based Clinical Decision Support (ReCDS) systems: Patient-to-Article Retrieval (PAR) and Patient-to-Patient Retrieval (PPR). For details, please refer to our paper and leaderboard.

Languages

English (en).

Dataset Structure

PMC-Paitents.json

This file contains all information about patients summaries in PMC-Patients, which is a list of dict with keys:

patient_id: string. A continuous id of patients, starting from 0.
patient_uid: string. Unique ID for each patient, with format PMID-x, where PMID is the PubMed Identifier of the source article of the patient and x denotes index of the patient in source article.
PMID: string. PMID for source article.
file_path: string. File path of xml file of source article.
title: string. Source article title.
patient: string. Patient summary.
age: list of tuples. Each entry is in format (value, unit) where value is a float number and unit is in 'year', 'month', 'week', 'day' and 'hour' indicating age unit. For example, [[1.0, 'year'], [2.0, 'month']] indicating the patient is a one-year- and two-month-old infant.
gender: 'M' or 'F'. Male or Female.

PAR & PPR Datasets

We present data of the two retrieval tasks in exactly the same format as BEIR. we refer the readers to their wiki page for the data format.

The PAR and PPR tasks share queries and query splits. The _id field for queries and PPR corpus is patient_uid in PMC-Patients, and the _id for PAR corpus is the PMID of the article.

Data Instances

A sample of patient in PMC-Patients.json { "patient_id": "0", "patient_uid": "7665777-1", "PMID": "33492400", "file_path": "comm/PMC007xxxxxx/PMC7665777.xml", "title": "Early Physical Therapist Interventions for Patients With COVID-19 in the Acute Care Hospital: A Case Report Series", "patient": "This 60-year-old male was hospitalized due to moderate ARDS from COVID-19 with symptoms of fever, dry cough, and dyspnea. We encountered several difficulties during physical therapy on the acute ward. First, any change of position or deep breathing triggered coughing attacks that induced oxygen desaturation and dyspnea. To avoid rapid deterioration and respiratory failure, we instructed and performed position changes very slowly and step-by-step. In this way, a position change to the 135\u00b0 prone position () took around 30 minutes. This approach was well tolerated and increased oxygen saturation, for example, on day 5 with 6 L/min of oxygen from 93% to 97%. Second, we had to adapt the breathing exercises to avoid prolonged coughing and oxygen desaturation. Accordingly, we instructed the patient to stop every deep breath before the need to cough and to hold inspiration for better air distribution. In this manner, the patient performed the breathing exercises well and managed to increase his oxygen saturation. Third, the patient had difficulty maintaining sufficient oxygen saturation during physical activity. However, with close monitoring and frequent breaks, he managed to perform strength and walking exercises at a low level without any significant deoxygenation. Exercise progression was low on days 1 to 5, but then increased daily until hospital discharge to a rehabilitation clinic on day 10.", "age": [ [ 60.0, "year" ] ], "gender": "M" }

A sample of query {"_id": "8699387-1", "text": "A 60-year-old female patient with a medical history of hypertension came to our attention because of several neurological deficits that had developed over the last few years, significantly impairing her daily life. Four years earlier, she developed sudden weakness and hypoesthesia of the right hand. The symptoms resolved in a few days and no specific diagnostic tests were performed. Two months later, she developed hypoesthesia and weakness of the right lower limb. On neurological examination at the time, she had spastic gait, ataxia, slight pronation of the right upper limb and bilateral Babinski sign. Brain MRI showed extensive white matter hyperintensities (WMHs), so leukodystrophy was suspected. However, these WMHs were located bilaterally in the corona radiata, basal ganglia, the anterior part of the temporal lobes and the medium cerebellar peduncle (A–D), and were highly suggestive of CADASIL. Genetic testing was performed, showing heterozygous mutation of the NOTCH3 gene (c.994 C<T; exon 6). The diagnosis of CADASIL was confirmed and antiplatelet prevention therapy was started. Since then, her clinical conditions remained stable, and the lesion load was unchanged at follow-up brain MRIs for 4 years until November 2020, when the patient was diagnosed with COVID-19 after a PCR nasal swab. The patient developed only mild respiratory symptoms, not requiring hospitalization or any specific treatment. Fifteen days after the COVID-19 diagnosis, she suddenly developed aphasia, agraphia and worsened right upper limb motor deficit, but she did not seek medical attention. Some days later, she reported these symptoms to her family medical doctor, and a new brain MRI was performed, showing a subacute ischemic area in the left corona radiata (E,F). Therapy with acetylsalicylic acid was switched to clopidogrel as secondary prevention, while her symptoms improved in the next few weeks. The patient underwent a carotid doppler ultrasound and an echocardiogram, which did not reveal any pathological changes. The review of the blood pressure log, both in-hospital and the personal one the patient had kept, excluded uncontrolled hypertension."}

A sample of qrels query-id corpus-id score 8647806-1 6437752-1 1 8647806-1 6946242-1 1

Data Splits

Refer to our paper.

Dataset Creation

If you are interested in the collection of PMC-Patients and reproducing our baselines, please refer to this reporsitory.

Citation Information

If you find PMC-Patients helpful in your research, please cite our work by:

@misc{zhao2023pmcpatients,
      title={PMC-Patients: A Large-scale Dataset of Patient Summaries and Relations for Benchmarking Retrieval-based Clinical Decision Support Systems}, 
      author={Zhengyun Zhao and Qiao Jin and Fangyuan Chen and Tuorui Peng and Sheng Yu},
      year={2023},
      eprint={2202.13876},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}