Evidence map›Paper›PMID 40294239›Full record

ArticleCancer control : journal of the Moffitt Cancer Center

Impact of Intraoperative Blood Transfusions on Survival Rates in Ovarian Cancer Patients.

Steven Benyahia, Monica Avila, Emily Coughlin, Amreesh Mahil, Alejandra Riveron, Yi Luo, Robert Wenham, Jeffrey Huang

Abstract read
In one paragraph

Article in Cancer control : journal of the Moffitt Cancer Center. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Steven BenyahiaMorsani College of Medicine, University of South Florida, Tampa, FL, USA.ORCID 0009-0007-4869-8910
Monica AvilaDepartment of Gynecological Oncology, Moffitt Cancer Center, Tampa, FL, USA.
Emily CoughlinMorsani College of Medicine, University of South Florida, Tampa, FL, USA.
Amreesh MahilDepartment of Anesthesiology, Moffitt Cancer Center, Tampa, FL, USA.
Alejandra RiveronDepartment of Anesthesiology, Moffitt Cancer Center, Tampa, FL, USA.
Yi LuoDepartment of Machine Learning, Moffitt Cancer Center, Tampa, FL, USA.
Robert WenhamDepartment of Gynecological Oncology, Moffitt Cancer Center, Tampa, FL, USA.
Jeffrey HuangDepartment of Anesthesiology, Moffitt Cancer Center, Tampa, FL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

IntroductionOvarian cancer remains a leading cause of gynecologic cancer-related mortality worldwide. Identifying perioperative factors that influence survival outcomes is essential for optimizing care. This study evaluates the impact of perioperative factors such as intraoperative blood transfusions and hospital length of stay (LOS) on survival rates in ovarian cancer patients undergoing surgical debulking.MethodsThis retrospective study analyzed charts of 314 patients who underwent ovarian cancer surgery at a single institution between 2010 and 2018. Patients were grouped based on survival status: "Live" or "Death". Variables included demographics, tumor size, comorbidity, anesthesia time, surgery time, estimated blood loss, transfusion, readmission, hospital stay length, and survival. Statistical analyses included log-rank tests and mean survival estimations: chi-square tests and Mann-Whitney U-test. Significance was set at

Indexed as

Blood TransfusionIntraoperative CareOvarian NeoplasmsAdultAgedBlood Loss, SurgicalCytoreduction Surgical ProceduresFemaleHumansLength of StayMiddle AgedRetrospective StudiesSurvival Rateblood transfusionlength of stayovarian cancerpostoperative survival

Identifiers

PMID40294239
PMCPMC12038196

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Registered trials

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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.