Evidence map›Paper›PMID 23842748›Full record

ReviewDrugs2013

Adverse effects of immunosuppressant drugs upon airway epithelial cell and mucociliary clearance: implications for lung transplant recipients.

Rogerio Pazetti, Paulo Manuel Pêgo-Fernandes, Fabio Biscegli Jatene

Abstract readReview
PubMed Publisher
In one paragraph

Review in Drugs, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Building a Lung Transplant Program.Clinics (Sao Paulo, Brazil) · 2015
    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

3 authors at 1 institution in 1 country.

Rogerio PazettiLaboratory of Thoracic Surgery Research-LIM61, Department of Cardiopneumology, Heart Institute (InCor), Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Avenida Doutor Arnaldo, 455, 1o. Andar, Sala 1220, Pacaembu, São Paulo, SP, 01246-000, Brazil. rogeriopazetti@yahoo.com.br
Paulo Manuel Pêgo-Fernandes
Fabio Biscegli Jatene
Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optimal post-transplantation immunosuppression is critical to the survival of the graft and the patient after lung transplantation. Immunosuppressant agents target various aspects of the immune system to maximize graft tolerance while minimizing medication toxicities and side effects. The vast majority of patients receive maintenance immunosuppressive therapy consisting of a triple-drug regimen including a calcineurin inhibitor, a cell cycle inhibitor and a corticosteroid. Although these immunosuppressant drugs are frequently used after transplantation and to control inflammatory processes, limited data are available with regard to their effects on cells other than those from the immunological system. Notably, the airway epithelial cell is of interest because it may contribute to development of bronchiolitis obliterans through production of pro-inflammatory cytokines. This review focuses the current armamentarium of immunosuppressant drugs used after lung transplantation and their main side effects upon airway epithelial cells and mucociliary clearance.

Indexed as

Lung TransplantationDrug Therapy, CombinationEpithelial CellsHumansImmunosuppressive AgentsMucociliary ClearanceRespiratory MucosaImmunosuppressive Agents

Identifiers

PMID23842748
OpenAlexW2015189812

What OpenQuestion holds

Textmetadata
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.