Evidence map›Paper›PMID 36225536›Full record

ArticlePulmonary circulation2022

Pulmonary hypertension in patients with interstitial lung disease: a tool for early detection.

Raj Parikh, Ippokratis Konstantinidis, David M O'Sullivan, Harrison W Farber

Open access · goldAbstract read
In one paragraph

Article in Pulmonary circulation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
6.8field-weighted citation impact, top 2% of its field
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

35 citing papers in PubMed, 45 citations in OpenAlex.

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  20. Pulmonary hypertension associated with lung diseases.The European respiratory journal · 2024
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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

4 authors at 3 institutions in 1 country.

Raj ParikhDivision of Pulmonary, Critical Care, and Sleep Hartford Hospital Hartford Connecticut USA.ORCID https://orcid.org/0000-0003-3063-6002
Ippokratis KonstantinidisDepartment of Internal Medicine University of Connecticut Farmington Connecticut USA.
David M O'SullivanDepartment of Research Administration Hartford HealthCare Hartford Connecticut USA.
Harrison W FarberDivision of Pulmonary, Sleep and Critical Care Medicine Tufts Medical Center Boston Massachusetts USA.
Hartford Hospital · USTufts Medical Center · USUniversity of Connecticut · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pulmonary hypertension (PH) complicates the treatment of interstitial lung disease (ILD) patients resulting in poor functional status and worse outcomes. Early recognition of PH in ILD is important for initiating therapy and considering lung transplantation. However, no standard exists regarding which patients to screen for PH-ILD or the optimal method to do so. The aim of this study was to create a risk assessment tool that could reliably predict PH in ILD patients. We developed a PH-ILD Detection tool that incorporated history, exam, 6-min walk distance, diffusion capacity for carbon monoxide, chest imaging, and cardiac biomarkers to create an eight-component score. This tool was analyzed retrospectively in 154 ILD patients where each patient was given a score ranging from 0 to 12. The sensitivity (SN) and specificity (SP) of the PH-ILD Detection tool and an area-under-the-curve (AUC) were calculated. In this cohort, 74 patients (48.1%) had PH-ILD. A score of ≥6 on the PH-ILD Detection tool was associated with a diagnosis of PH-ILD (SN: 86.5%; SP: 86.3%; area-under-the-curve: 0.920,

Indexed as

idiopathic pulmonary fibrosisinterstitial lung diseaseprostacyclinpulmonary hypertensiontreprostinil

Identifiers

PMID36225536
PMCPMC9531548
OpenAlexW4297381138

What OpenQuestion holds

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LicenceCC BY-NC
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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.