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Record W2770042889 · doi:10.1093/cid/cix690

Incidence, Risk Factors and Outcome of Pre-engraftment Gram-Negative Bacteremia After Allogeneic and Autologous Hematopoietic Stem Cell Transplantation: An Italian Prospective Multicenter Survey

2017· article· en· W2770042889 on OpenAlexfundno aff
Corrado Girmenia, Alice Bertaina, Alfonso Piciocchi, Katia Perruccio, Alessandra Algarotti, Alessandro Busca, Chiara Cattaneo, Anna Maria Raiola, Stefano Guidi, Anna Paola Iori, Anna Candoni, Giuseppe Irrera, Giuseppe Milone, G. Marcacci, Rosanna Scimè, Maurizio Musso, Laura Cudillo, Simona Sica, Luca Castagna, Paolo Corradini, Francesco Marchesi, Domenico Pastore, Emilio Paolo Alessandrino, C. Annaloro, Fabio Ciceri, Stella Santarone, Luca Nassi, Claudio Farina, Claudio Viscoli, Gian María Rossolini, Francesca Bonifazi, Alessandro Rambaldi, Saveria Capria, Angela Mastronuzzi, Daria Pagliara, Paola Bernaschi, Lucia Amico, Alessandra Carotti, Antonella Mencacci, Benedetto Bruno, Cristina Costa, Angela Passi, G Ravizzola, Emanuele Angelucci, Anna Marchese, Patrizia Pecile, Giovanna Ventura, Renato Fanin, Claudio Scarparo, Angelo Pasquale Barbaro, Salvatore Leotta, Cristina Becchimanzi, Daniela Donnarumma, Stefania Tringali, Maria Teresa Baldi, Renato Scalone, Alessandra Picardi, William Arcese, Carla Fontana, Sabrina Giammarco, Teresa Spanu, Roberto Crocchiolo, Erminia Casari, Alberto Mussetti, Eutilia Conte, Fabrizio Ensoli, G. Miragliotta, P. Marone, Milena Arghittu, Raffaella Greco, Alessandra Forcina, Paola Chichero, Paolo Di Bartolomeo, Paolo Fazii, Vesselina Kroumova, Nunzia Decembrino, Marco Zecca, Giovanni Pisapia, Giulia Palazzo, Edoardo Lanino, Maura Faraci, Elio Castagnola, Roberto Bandettini, Rocco Pastano, Simona Sammassimo, Rita Passerini, Piero Maria Stefani, Filíppo Gherlinzoni, Roberto Rigoli, Lucia Prezioso, Benedetta Cambò, Adriana Calderaro, Angelo Michele Carella, Nicola Cascavilla, Maria Labonia, Ivana Celeghini, Nicola Mordini, Federica Piana, Adriana Vacca, Marco Sanna, Giovanni Podda, Maria Teresa Corsetti, Andrea Rocchetti, Daniela Cilloni, Marco De Gobbi, Ornella Bianco, Franca Fagioli, Francesca Carraro, Gianfranco De Intinis, Alessandro Severino, Anna Proia, Gabriella Parisi, Daniele Vallisa, Massimo Confalonieri, Domenico Russo, Michele Malagola, Piero Galieni, Sadia Falcioni, Valeria Travaglini, R Raimondi, Carlo Borghero, Giacomina Pavan, Arcangelo Prete, Tamara Belotti, Simone Ambretti, Manuela Imola, Anna Maria Mianulli, Maria Federica Pedna, Simone Cesaro, Giuliana Lo Cascio, Antonella Ferrari, Monica Piedimonte, Iolanda Santino, Monica Calandrelli, Attilio Olivieri, Francesca Orecchioni, M Mirabile, Riccardo Centurioni, Luciana Gironacci, Daniela Caravelli, Susanna Gallo, Marco Filippi, Luca Cupelli, Teresa Dentamaro, Silvana Falco, Ospedale S Eugenio, Serena Marotta, Antonio M. Risitano, Dora Lula, Pellegrino Musto, Giuseppe Pietrantuono, Antonio Traficante, Elisabetta Cerchiara, Maria Cristina Tirindelli, Giordano Dicuonzo, Anna Chierichini, Barbara Anaclerico

Bibliographic record

VenueClinical Infectious Diseases · 2017
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsnot available
FundersHumanitas Research HospitalUniversità degli Studi di MilanoInfectious Diseases Society of AmericaOntario Institute for Regenerative MedicineOPEC Fund for International DevelopmentPfizer
KeywordsMedicineHematopoietic stem cell transplantationInternal medicineBacteremiaHazard ratioTransplantationCumulative incidenceNeutropeniaIncidence (geometry)Confidence intervalGastroenterologySurgeryImmunologyChemotherapyAntibioticsMicrobiologyBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Gram-negative bacteremia (GNB) is a major cause of illness and death after hematopoietic stem cell transplantation (HSCT), and updated epidemiological investigation is advisable. METHODS: We prospectively evaluated the epidemiology of pre-engraftment GNB in 1118 allogeneic HSCTs (allo-HSCTs) and 1625 autologous HSCTs (auto-HSCTs) among 54 transplant centers during 2014 (SIGNB-GITMO-AMCLI study). Using logistic regression methods. we identified risk factors for GNB and evaluated the impact of GNB on the 4-month overall-survival after transplant. RESULTS: The cumulative incidence of pre-engraftment GNB was 17.3% in allo-HSCT and 9% in auto-HSCT. Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa were the most common isolates. By multivariate analysis, variables associated with GNB were a diagnosis of acute leukemia, a transplant from a HLA-mismatched donor and from cord blood, older age, and duration of severe neutropenia in allo-HSCT, and a diagnosis of lymphoma, older age, and no antibacterial prophylaxis in auto-HSCT. A pretransplant infection by a resistant pathogen was significantly associated with an increased risk of posttransplant infection by the same microorganism in allo-HSCT. Colonization by resistant gram-negative bacteria was significantly associated with an increased rate of infection by the same pathogen in both transplant procedures. GNB was independently associated with increased mortality at 4 months both in allo-HSCT (hazard ratio, 2.13; 95% confidence interval, 1.45-3.13; P <.001) and auto-HSCT (2.43; 1.22-4.84; P = .01). CONCLUSIONS: Pre-engraftment GNB is an independent factor associated with increased mortality rate at 4 months after auto-HSCT and allo-HSCT. Previous infectious history and colonization monitoring represent major indicators of GNB. CLINICAL TRIALS REGISTRATION: NCT02088840.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.368
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations160
Published2017
Admission routes1
Has abstractyes

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