Evidence map›Paper›PMID 39507297›Full record

ArticleHealth data science2024

Robust Meta-Model for Predicting the Likelihood of Receiving Blood Transfusion in Non-traumatic Intensive Care Unit Patients.

Alireza Rafiei, Ronald Moore, Tilendra Choudhary, Curtis Marshall, Geoffrey Smith, John D Roback, Ravi M Patel, Cassandra D Josephson, Rishikesan Kamaleswaran

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Health data science, 2024. 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
–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

5 citing papers in PubMed.

  1. AI and Blood Banking: Predicting Transfusion Demand - A Systematic Review of Forecasting Approaches.Transfusion medicine and hemotherapy : offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie · 2026
    Review
  2. Article
  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

9 authors.

Alireza RafieiDepartment of Computer Science, Emory University, Atlanta, GA, USA.
Ronald MooreDepartment of Computer Science, Emory University, Atlanta, GA, USA.
Tilendra ChoudharyDepartment of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, USA.
Curtis MarshallDepartment of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, USA.
Geoffrey SmithDepartment of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA.
John D RobackDepartment of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA.
Ravi M PatelDepartment of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA.
Cassandra D JosephsonDepartment of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA.
Rishikesan KamaleswaranDepartment of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, USA.

Funding

Sepsis Physiomarkers for Appropriate Risk Knowledge of monitored patients in the ICU (SPARK-ICU)R01GM139967 · NIGMS · EMORY UNIVERSITY · PI KAMALESWARAN, RISHIKESAN · 2021 to 2025
$2.8M
Leveraging multi-omics to maximize the scientific value of pediatric sepsis biorepository and advance patient endotypingR21GM151703 · NIGMS · CINCINNATI CHILDRENS HOSP MED CTR · PI ATREYA, MIHIR R, KAMALESWARAN, RISHIKESAN · 2023 to 2024
$459k
Scalable and Interoperable framework for a clinically diverse and generalizable sepsis Biorepository using Electronic alerts for Recruitment driven by Artificial Intelligence (short title: SIBER-AI)R21GM148931 · NIGMS · EMORY UNIVERSITY · PI ESPER, ANNETTE M., KAMALESWARAN, RISHIKESAN · 2023 to 2024
$368k
NIGMS NIH HHS R01 GM139967NIGMS NIH HHS R21 GM148931NIGMS NIH HHS R21 GM151703
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Identifiers

PMID39507297
PMCPMC11538953

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.