Evidence map›Paper›PMID 28442899›Full record

ArticleInternational journal of chronic obstructive pulmonary disease2017

Approaches to drug therapy for COPD in Russia: a proposed therapeutic algorithm.

Kirill A Zykov, Svetlana I Ovcharenko

Open access · goldAbstract read
In one paragraph

Article in International journal of chronic obstructive pulmonary disease, 2017. 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
0.4field-weighted citation impact, top 34% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Russian guidelines for the management of COPD: algorithm of pharmacologic treatment.International journal of chronic obstructive pulmonary disease · 2018
    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

2 authors at 2 institutions in 1 country.

Kirill A ZykovLaboratory of Pulmonology, Moscow State University of Medicine and Dentistry named after A.I. Evdokimov.
Svetlana I OvcharenkoI.M. Sechenov First Moscow State Medical University, Moscow, Russia.
Moscow State University of Medicine and Dentistry · RUSechenov University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Until recently, there have been few clinical algorithms for the management of patients with COPD. Current evidence-based clinical management guidelines can appear to be complex, and they lack clear step-by-step instructions. For these reasons, we chose to create a simple and practical clinical algorithm for the management of patients with COPD, which would be applicable to real-world clinical practice, and which was based on clinical symptoms and spirometric parameters that would take into account the pathophysiological heterogeneity of COPD. This optimized algorithm has two main fields, one for nonspecialist treatment by primary care and general physicians and the other for treatment by specialized pulmonologists. Patients with COPD are treated with long-acting bronchodilators and short-acting drugs on a demand basis. If the forced expiratory volume in one second (FEV

Indexed as

AlgorithmsDecision Support TechniquesAdrenergic beta-2 Receptor AgonistsBronchodilator AgentsClinical Decision-MakingClinical ProtocolsDrug Administration ScheduleForced Expiratory VolumeHumansLungMuscarinic AntagonistsPatient SelectionPractice Guidelines as TopicPredictive Value of TestsPulmonary Disease, Chronic ObstructiveRussiaAdrenergic beta-2 Receptor AgonistsBronchodilator AgentsMuscarinic AntagonistsbronchodilatorsCOPDspirometrysymptomstreatmenttreatment algorithm

Identifiers

PMID28442899
PMCPMC5396832
OpenAlexW2607180954

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.