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Record W4387562840 · doi:10.1001/jama.2023.20737

Red Blood Cell Transfusion in the Intensive Care Unit

2023· article· en· W4387562840 on OpenAlexfundno aff
Jorinde Raasveld, Sanne de Bruin, Merijn C. Reuland, Claudia van den Oord, Jimmy Schenk, Cécile Aubron, Jan Bakker, Maurizio Cecconi, Aarne Feldheiser, Jens Meier, Marcella C.A. Müller, Thomas Scheeren, Zoe McQuilten, Andrew W. J. Flint, Tarikul Hamid, Michaël Piagnerelli, Tina Tomić Mahečić, Jan Benes, Lene Russell, Hernán Aguirre-Bermeo, Konstantina Triantafyllopoulou, Vasiliki Chantziara, Mohan Gurjar, Sheila Nainan Myatra, Vincenzo Pota, Muhammed Elhadi, Ryszard Gawda, Mafalda Mourisco, Marcus D. Lancé, Vojislava Nešković, Matej Podbregar, Juan V. Llau, Manual Quintana‐Diaz, Maria Cronhjort, Carmen A. Pfortmueller, Nihan Yapıcı, Nathan D. Nielsen, Akshay Shah, Harm‐Jan de Grooth, Alexander P. J. Vlaar, Alisa M. Higgins, Ary Serpa Neto, K. Brady, Erica M. Wood, Alexis Poole, Tony Trapani, Meredith Young, Paul Secombe, Graham Reece, Prashanti Marella, David Brewster, Alan Rashid, Ruwan Suwandarathne, Raman Azad, Jonathan Barrett, Elisha Turner, Amber‐Louise Poulter, Lixian Chen, Vishwanath Biradar, Christina Whitehead, Sandra Peake, Alexis Tabah, Stephanie O’Connor, Michael C. Reade, Guido Janssen, Richard McAllister, Katherine Elizabeth Triplett, David Bowen, Hergen Buscher, John P. Santamaria, Dinesh Parmar, Paul Power, Craig French, Matthew Mac Partlin, Md Motiul Islam, Injamam Ull Haque, A. de Anta Román, Lionel Haentjens, Višnja Ikić, Slavica Kvolik, Robert Bojčić, Kazimir Juričić, Martin Duksa, Lukáš Bílek, I Satinský, Jan Zatloukal, Morten H. Bestle, Christian S. Meyhoff, Ana Maria Diaz-Medina, Verónica Llumiquinga, Heinert Enmanuel Gonzabay-Campos, Mohamed Elbahnasawy, Xavier Chapalain, Charlène Le Moal, Pierre-Yves Egreteau, Yoann Launey, Florian Reizine, Florence Boissier, Jean Reignier, Stéphan Ehrmann, Eddy Lebas, Gaëlle Corno, Pauline Cailliez, Pierre Garçon, Guillaume Carteaux, Antoine Kimmoun, Danai Theodoulou, Stavros Aloizos, Eleftherios Papadakis, Konstantinos Tsakalis, Giorgos Marinakis, Ioannis Georgakas, Paraskevi Tripolitsioti, Sofia Nikolakopoulou, Γεώργιος Παπαθανάκος, Chrysanthi Sklavou, Evangelia Tsika, Ourania Mousafiri, Athanasios Prekates, Georgia Micha, Athina Lavrentieva, Theodoros Aslanidis, Clementine Bostantzoglou, Evangelia Dikoudi, Silia Karaouli, Sophia Pouriki, Swapna C Vijayakumaran, Darshana Rathod, Venkat Raman Kola, Deepak Jeswani, Kadarapura Nanjundaiah Gopalakrishna, Amol Hartalkar, Ata Mahmoodpoor, Marwah Abdulkhaleq, Mariachiara Ippolito, Antonella Cotoia, Marco Covotta, Filippo Sanfilippo, Ehab Ishteiwy, Hebtallah Benzarti, Alya Abdalhadi, Ahmad Buimsaedah, Eman Abdulwahed, Khalil Tamoos, Eman Younes, Asma Abubakr Saleh Alkamkhe, Marwa Biala, Hajer Abdalla Mohammed Hwili, Najat Shaban Ben Hasan, Bushray Almiqlash, Mawadda Altair, Rema Hassan Mohamed Otman, Mohamed Fathi Al Gharyani, Omlez Mohammed Alkeelani, Hibah Bileid Bakeer, Azah Mukhtar Omar Affat, Husayn Aween, Aihab Benamwor, Mohamed Alsori, Najwa Abdelrahim, Ghannam Abdelilah, Rachael Parke, Yan Chen, Jan Mehrtens, Paweł Twardowski, Ross Freebairn, Rima Song, C. Michael Gibson, Jonathan H. Chen, Richard Moore, Mary Rose Sol Cruz, Anna Włudarczyk, Łukasz Krzych, Marta Szczukocka, Marcin Kubiak, Maciej Molsa, Magdalena Wujtewicz, Agnieszka Wieczorek, Agnieszka Misiewska-Kaczur, Marek Maslicki, Dariusz Onichimowski, Jakub Mazur, Paweł Zatorski, Ana Marta Mota, Joana Fernandes, Diana Cuesta, Elisabete Coelho, Alexandra Paula, Teresa Guimarães, Diana Adrião, Igor Mark, Elizabeta Mušič, Tomislav Mirković, Andrej Markota, Natalija Krope, Marko Kmet, Petra Forjan, Tomaž Savli, Gerardo Aguilar, Rebeca González-Celdrán, Estefanía Martínez-González, Agustín Díaz-Álvarez, M.J. Colomina, Francisco Hidalgo, Carlos Ferrando, Raquel Ferrandis, Carolina Ferrer, A. Gómez‐Luque, Disa Blomstrand, Emelie Risberg, Natalie Johansen, Henrik Rajala, Natalie Layous, Eline A. Vlot, Michiel Erkamp, Nicole P. Juffermans, Stefan van Wonderen, Lidija Kuznecova-Keppel Hesselink, Victor van Bochove, Murat Acarel, Evren Şentürk, Mahmut Alp Karahan, Aynur Camkıran Fırat, Yahya Yıldız, Osman Ekinci, Asu Özgültekin, Hüseyin Arıkan, Gamze Küçükosman, Bengü Gülhan Aydın, Mehmet Tevfik Yavuz, Alev Öztaş, Nilgün Kavrut Öztürk, Umut Sabri Kasapoğlu, Eylem Tunçay, Cenk İndelen, Halide Oğuş, Başar Erdivanlı, Ayça Sultan Şahin, Mehmet Yılmaz, Erken Sayan, Canan Uğur Yılmaz, Şenay Göksu Tomruk, Betül Başaran, Emine Kutahya, Ayfer Kaya Gök, Ayşe Özcan, İskender Kara, Seyfi Kartal, Kemal Tolga Saraçoğlu, Yelíz Bílír, Selin Eyüpoğlu, Nigar Ertuğrul Örüç, Kubilay İşsever, Jamie Patel, Jayson Clarke, Louise Ma, Tom Lawton, Brendan Sloan, S. Kannan, Richard Innes, Mark G. Carpenter, Luke Newey, Hazem Alwagih, Chris Acott, Anil Hormis, James Herdman, Osama Akrama, Rachel Baumber, Olena Khomenko, Akram Khan, Zubair Hasan, Jay S. Raval, Lauren Sutherland

Bibliographic record

VenueJAMA · 2023
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsnot available
FundersAcademy of Military Medical SciencesHumanitas Research HospitalUniverza v LjubljaniHomi Bhabha National InstituteUniversité de Bretagne OccidentaleNational and Kapodistrian University of AthensKarolinska InstitutetGentofte HospitalUniwersytet OpolskiMonash UniversityUniversiteit van AmsterdamYork UniversityUniversitair Medisch Centrum GroningenUniversity of OxfordRigshospitaletSanjay Gandhi Postgraduate Institute of Medical SciencesUniverzita Karlova v PrazeInselspital, Universitätsspital BernPontificia Universidad Católica de ChileUniversity of Bern
KeywordsMedicineRed Blood Cell TransfusionIntensive care unitBlood transfusionIntensive care medicineRed blood cellEmergency medicineInternal medicine

Abstract

fetched live from OpenAlex

Importance: Red blood cell (RBC) transfusion is common among patients admitted to the intensive care unit (ICU). Despite multiple randomized clinical trials of hemoglobin (Hb) thresholds for transfusion, little is known about how these thresholds are incorporated into current practice. Objective: To evaluate and describe ICU RBC transfusion practices worldwide. Design, Setting, and Participants: International, prospective, cohort study that involved 3643 adult patients from 233 ICUs in 30 countries on 6 continents from March 2019 to October 2022 with data collection in prespecified weeks. Exposure: ICU stay. Main Outcomes and Measures: The primary outcome was the occurrence of RBC transfusion during ICU stay. Additional outcomes included the indication(s) for RBC transfusion (consisting of clinical reasons and physiological triggers), the stated Hb threshold and actual measured Hb values before and after an RBC transfusion, and the number of units transfused. Results: Among 3908 potentially eligible patients, 3643 were included across 233 ICUs (median of 11 patients per ICU [IQR, 5-20]) in 30 countries on 6 continents. Among the participants, the mean (SD) age was 61 (16) years, 62% were male (2267/3643), and the median Sequential Organ Failure Assessment score was 3.2 (IQR, 1.5-6.0). A total of 894 patients (25%) received 1 or more RBC transfusions during their ICU stay, with a median total of 2 units per patient (IQR, 1-4). The proportion of patients who received a transfusion ranged from 0% to 100% across centers, from 0% to 80% across countries, and from 19% to 45% across continents. Among the patients who received a transfusion, a total of 1727 RBC transfusions were administered, wherein the most common clinical indications were low Hb value (n = 1412 [81.8%]; mean [SD] lowest Hb before transfusion, 7.4 [1.2] g/dL), active bleeding (n = 479; 27.7%), and hemodynamic instability (n = 406 [23.5%]). Among the events with a stated physiological trigger, the most frequently stated triggers were hypotension (n = 728 [42.2%]), tachycardia (n = 474 [27.4%]), and increased lactate levels (n = 308 [17.8%]). The median lowest Hb level on days with an RBC transfusion ranged from 5.2 g/dL to 13.1 g/dL across centers, from 5.3 g/dL to 9.1 g/dL across countries, and from 7.2 g/dL to 8.7 g/dL across continents. Approximately 84% of ICUs administered transfusions to patients at a median Hb level greater than 7 g/dL. Conclusions and Relevance: RBC transfusion was common in patients admitted to ICUs worldwide between 2019 and 2022, with high variability across centers in transfusion practices.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.267
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations73
Published2023
Admission routes1
Has abstractyes

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