Evidence map›Paper›PMID 39592990›Full record

ArticleBMC cancer2024

Incidence and risk factor of blood transfusion after abdominal radical hysterectomy for cervical cancer: a 10-year retrospective study of the US nationwide inpatient sample.

Chuan Chen, BenLi Zhu, Youfeng Wang, Yangyang Zhao, Gang Chen, Ying Peng, Ying Peng, Xinyu Wang, Hao Xie, Ying Zhou and 1 more

Abstract read
In one paragraph

Article in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Chuan Chen *Department of Obstetrics and Gynecology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China.
BenLi Zhu *Department of Obstetrics and Gynecology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China.
Youfeng Wang *Faculty of Chinese Medicine, Macau University of Science and Technology, Macao, 000853, China.
Yangyang ZhaoChina Railway Fourth Bureau Group Central Hospital, Sinopharm Group, Hefei, 230001, Anhui, China.
Gang ChenDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China.
Ying PengDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China.
Ying PengDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China.
Xinyu WangDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China.
Hao XieDivision of Orthopaedic Surgery, Department of Orthopaedics, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China. hao_xie2018@163.com.
Ying ZhouDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China. caddiezy@ustc.edu.cn.
Juan LinDepartment of Gynecology, Dongguan Tungwah Hospital, Dongguan, China. linpyk@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith the rising prevalence of abdominal radical hysterectomy, the need for perioperative blood transfusion has emerged as a significant clinical challenge. Independent risk factors for blood transfusion during abdominal radical hysterectomy remains limited, and identifying these factors is needed.

methodsA retrospective analysis of data was performed using the Nationwide Inpatient Sample (NIS), focusing on patients who underwent abdominal radical hysterectomy between 2010 and 2019. Patients were categorized into two groups based on whether they received a blood transfusion. The analysis encompassed various demographic factors, including race, sex, and age, as well as length of stay (LOS), total hospitalization charges, hospital characteristics (admission type, insurance type, bed size, teaching status, geographic location, and hospital region), hospital mortality rates, comorbidities, and perioperative complications. Subsequently, both univariate and multivariate logistic regression analyses were employed to ascertain factors associated with abdominal radical hysterectomy patients requiring blood transfusions.

resultsBlood transfusions occurred in 14.84% of patients between 2010 and 2019, with a downward trend over time. Receiving a transfusion was associated with several negative outcomes, including a longer length of stay, higher total charges, and complications like thrombocytopenia, acute myocardial infarction, pneumonia, and so on. Additionally, patients who received transfusions were more likely to experience postoperative delirium, deep vein thrombosis, and wound infection. Independent risk factors for blood transfusion include Black race, Asian or Pacific Islander race, non-elective surgery, hospitalization in a rural setting, pre-existing medical conditions like coagulopathy, chronic blood loss anemia, deficiency anemia and others. Conversely, patients with private insurance, residing in the West, or Midwest/North Central regions were less likely to require a blood transfusion.

conclusionOur study highlights the concern of perioperative blood transfusion in radical hysterectomy, linked to significant complications. Reducing intraoperative blood loss and optimizing care based on patient factors are crucial for improving outcomes.

Indexed as

Blood TransfusionHysterectomyUterine Cervical NeoplasmsAdultAgedFemaleHumansIncidenceInpatientsLength of StayMiddle AgedPostoperative ComplicationsRetrospective StudiesRisk FactorsUnited StatesAbdominal radical hysterectomyBlood transfusionRisk factor

Identifiers

PMID39592990
PMCPMC11600751

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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.