Evidence map›Paper›PMID 35958558›Full record

ReviewFrontiers in immunology2022

Kidney transplantation in systemic sclerosis: Advances in graft, disease, and patient outcome.

Federica Maritati, Michele Provenzano, Sarah Lerario, Valeria Corradetti, Claudia Bini, Marco Busutti, Valeria Grandinetti, Vania Cuna, Gaetano La Manna, Giorgia Comai

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Towards a Model of Big Health Care Data Analytics in Panama: Chronic Kidney Disease.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2022
    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

10 authors at 2 institutions in 1 country.

Federica MaritatiNephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy.
Michele ProvenzanoNephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy.
Sarah LerarioNephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy.
Valeria CorradettiNephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy.
Claudia BiniNephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy.
Marco BusuttiNephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy.
Valeria GrandinettiNephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy.
Vania CunaNephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy.
Gaetano La MannaNephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy.
Giorgia ComaiNephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy.
Azienda USL di Bologna · ITUniversity of Bologna · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systemic sclerosis (SSc) is an immune-mediated rheumatic disease characterized by vascular abnormalities, tissue fibrosis, and inflammation. Renal disease occurring in patients with SSc may have a variable clinicopathological picture. However, the most specific renal condition associated with this disease is the scleroderma renal crisis (SRC), characterized by acute onset of renal failure and severe hypertension. SRC develops in about 20% of cases of SSc, especially in those patients with diffuse cutaneous disease. The prognosis of this condition is often negative, with a rapid progression to end-stage renal disease (ESRD). The advent of the antihypertensive angiotensin-converting enzyme inhibitors in 1980 was associated with a significant improvement in patients' survival and recovery of renal function. However, the prognosis of these patients can still be improved. The dialytic condition is associated with early death, and mortality is significantly higher than among patients undergoing renal replacement therapy (RRT) due to other conditions. Patients with SRC who show no signs of renal functional recovery despite timely blood pressure control are candidates for kidney transplantation (KT). In this review, we reported the most recent advances in KT in patients with ESRD due to SSc, with a particular overview of the risk of disease recurrence after transplantation and the evolution of other disease manifestations.

Indexed as

Acute Kidney InjuryHypertension, RenalKidney Failure, ChronicKidney TransplantationScleroderma, LocalizedScleroderma, SystemicHumansACE inhibitorskidney transplantrenal replacement therapyscleroderma renal crisissystemic sclerosis

Identifiers

PMID35958558
PMCPMC9360313
OpenAlexW4287877237

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.