Evidence map›Paper›PMID 31827950›Full record

ArticleCase reports in hematology2019

Multiple Severe Toxicities of L-Asparaginase and Their Innovative Management during Induction Therapy of Acute Lymphoblastic Leukemia in an Adult Patient.

Guillaume Beziat, Suzanne Tavitian, Muriel Picard, Stanislas Faguer, Christian Recher, Françoise Huguet

Open access · goldAbstract readCase Reports
In one paragraph

Article in Case reports in hematology, 2019. 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
1.8field-weighted citation impact, top 15% 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, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. 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

6 authors at 2 institutions in 1 country.

Guillaume BeziatService d'Hématologie Clinique, Institut Universitaire du Cancer Oncopole, Toulouse, France.ORCID https://orcid.org/0000-0001-9135-6157
Suzanne TavitianService d'Hématologie Clinique, Institut Universitaire du Cancer Oncopole, Toulouse, France.
Muriel PicardRéanimation et Soins Intensifs, Institut Universitaire du Cancer Oncopole, Toulouse, France.
Stanislas FaguerSecteur de Réanimation de l'Unité de Transplantation d'Organes, CHU Rangueil, Toulouse, France.
Christian RecherService d'Hématologie Clinique, Institut Universitaire du Cancer Oncopole, Toulouse, France.
Françoise HuguetService d'Hématologie Clinique, Institut Universitaire du Cancer Oncopole, Toulouse, France.
Institut universitaire du cancer de Toulouse Oncopole · FRHôpital Rangueil · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

L-asparaginase is a key chemotherapeutic agent in acute lymphoblastic leukemia (ALL). It is also known for multiple and severe specific toxicities, without consensual management. We report the case of a 51-year-old man treated with L-asparaginase for recently diagnosed T-cell ALL. During the treatment, he developed a coma due to multifactorial diffuse cerebral edema, by hepatic encephalopathy, cerebral venous thrombosis, and hyperammonemia, all linked to toxicity of L-asparaginase. Specific and innovative treatments were employed to manage these toxicities: supplementation with L-carnitine, thiamine, and pyridoxine for hepatic toxicity, perfusion of sodium benzoate to decrease ammonemia, and extrahepatic albumin-based dialysis sessions, along with anticoagulation. The patient improved within two weeks and is currently alive 13 months later, in first complete remission, without sequelae, on an alleviated chemotherapy regimen.

Identifiers

PMID31827950
PMCPMC6886342
OpenAlexW2990084466

What OpenQuestion holds

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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.