Evidence map›Paper›PMID 27829879›Full record

ArticleObstetric medicine2016

Hermansky-Pudlak syndrome in pregnancy: A case report.

Lydia Yusuf, Srivasavi Dukka, Etienne Ciantar

Open access · greenAbstract readCase Reports
In one paragraph

Article in Obstetric medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 94% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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.

Lydia YusufLeeds Teaching Hospitals, NHS Trust, Leeds, UK.
Srivasavi DukkaLeeds Teaching Hospitals, NHS Trust, Leeds, UK.
Etienne CiantarDivision of Women's and Children's Health, Leeds Teaching Hospitals, NHS Trust, Leeds, UK.
Leeds Teaching Hospitals NHS Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hermansky-Pudlak syndrome is a rare autosomal recessive disorder estimated to affect 1 in 500,000 to 1,000,000 individuals worldwide. Clinically, it presents as oculocutaneous albinism combined with bleeding diathesis. This is due to the absence of dense bodies in platelets causing a delayed secondary response resulting in prolonged bleeding time despite normal platelet count and coagulation factors. This has consequences for major bleeding, the risk of which is high at delivery. In the longer term, the condition is also associated with the development of pulmonary fibrosis, inflammatory bowel disorders caused by granulomatous colitis and renal failure. We present a case of a patient with Hermansky-Pudlak syndrome diagnosed and managed through her second pregnancy by the Obstetric Haematology team in a Tertiary Unit. During her previous pregnancy at a District Hospital, they had not been aware of the diagnosis; she then had a forceps delivery and her haemoglobin dropped to 69 g/L. During this pregnancy, she was managed in a multidisciplinary setting involving obstetrics, haematology, anaesthesia and neonatology. She was induced at 39 weeks and had human leukocyte antigen-matched platelets prepared for her delivery. Her platelet count was normal throughout the pregnancy. She had a normal vaginal delivery under platelet cover and also received tranexamic acid at the time of cord clamping. Her blood loss was moderate and her haemoglobin dropped from 115 to 97 g/L. She recovered well. We discuss the diagnosis, pathology and management of this very rare condition in pregnancy and thereafter.

Indexed as

Haematologyhigh-risk pregnancyphysiologyplateletstransfusion

Identifiers

PMID27829879
PMCPMC5089347
OpenAlexW2494706811

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.