Evidence map›Paper›PMID 33061343›Full record

ArticleInternational journal of chronic obstructive pulmonary disease2020

The Value of FENO Measurement for Predicting Treatment Response in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease.

Aiyuan Zhou, Zijing Zhou, Dingding Deng, Yiyang Zhao, Jiaxi Duan, Wei Cheng, Cong Liu, Ping Chen

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in International journal of chronic obstructive pulmonary disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07396311 (Fractional Exhaled Nitric Oxide), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 20% 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.

NCT07396311 not yet recruitingnot on this mapstarted 2026, after this paper: background citation

Fractional Exhaled Nitric Oxide (FeNO) as a Predictor of Exacerbations in COPD Patients Initiated on Triple Inhaler Therapy: A Prospective Exploratory Cohort Study

TypeobservationalSponsorChang Gung Memorial HospitalRan2026 to 2028Enrolled120ConditionsChronic Obstructive Pulmonary Disease (COPD)ArmsNo intervention assigned
3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Association of FeNO Decline Rate with Symptom Improvement in COPD: A Real-World Observational Study.International journal of chronic obstructive pulmonary disease · 2026
    Observational
  3. Review
  4. Early detection and prediction of acute exacerbation of chronic obstructive pulmonary disease.Chinese medical journal pulmonary and critical care medicine · 2023
    Review
  5. Review
  6. 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

8 authors at 1 institution in 1 country.

Aiyuan ZhouDepartment of Respiratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, People's Republic of China.
Zijing ZhouDepartment of Respiratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, People's Republic of China.
Dingding DengDepartment of Respiratory Medicine, The First Affiliated People's Hospital, Shaoyang College, Shaoyang, Hunan 422000, People's Republic of China.
Yiyang ZhaoDepartment of Respiratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, People's Republic of China.
Jiaxi DuanDepartment of Respiratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, People's Republic of China.
Wei ChengDepartment of Respiratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, People's Republic of China.ORCID 0000-0003-1025-0591
Cong LiuDepartment of Respiratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, People's Republic of China.
Ping ChenDepartment of Respiratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, People's Republic of China.
Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Fractional exhaled nitric oxide (FENO) has been shown to be a marker of airway inflammation in various pulmonary diseases, including chronic obstructive pulmonary disease (COPD). In this study, we assessed the FENO level in patients with acute exacerbations of COPD (AECOPD) and analyzed the predictive value of the FENO level for treatment response. Methods: Demographic data were collected at admission. FENO, lung function, blood gases, COPD Assessment Test (CAT), and modified Medical Research Council (mMRC) scores were measured at admission and on day 7. At the second visit, the patients were asked to report their health status; scores ranged from 1 to 5, representing "much better", "slightly better", "no change", "slightly worse", and "much worse", respectively. The treatment response was evaluated based on the patient's reported health status (responders were those who reported much better and slightly better) and lung function (responders were those who presented an increase in FEV Results: A total of 182 patients were recruited into the analysis. The FENO level positively correlated with an increase in FEV Conclusion: FENO levels, determined at hospital admission, are potential to predict the overall treatment response in AECOPD patients, including remission in subjective patient-reported health statuses and, also, improvements in lung function. Registry Number: ChiCTR-ROC-16,009,087 (http://www.chictr.org.cn/).

Indexed as

Nitric OxidePulmonary Disease, Chronic ObstructiveRespiratory Function TestsAgedBiomarkersExhalationFemaleHumansMaleBiomarkersNitric OxideCOPDexacerbationFENOlung functiontreatment response

Identifiers

PMID33061343
PMCPMC7522317
OpenAlexW3089091944

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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.