MétaCan
Menu
Retour à la cohorte
Enregistrement W4283581867 · doi:10.1101/2022.06.21.22276677

The NeoSep Severity and Recovery scores to predict mortality in hospitalized neonates and young infants with sepsis derived from the global NeoOBS observational cohort study

2022· preprint· en· W4283581867 sur OpenAlexaff
Neal Russell, Wolfgang Stöhr, Aislinn Cook, James A. Berkley, B. Adhisivam, Ramesh Agarwal, ASM Nawshad Uddin Ahmed, Manica Balasegaram, Neema Chami, Adrie Bekker, Davide Bilardi, Cristina Gardonyi Carvalheiro, Suman Chaurasia, Viviane Rinaldi Favarin Colas, Simon Cousens, Ana Carolina Dantas de Assis, Dong Han, Angela Dramowski, Jinxing Feng, Y. Glupczynski, Srishti Goel, Herman Goossens, Doan Thi Huong Hao, Mahmudul Hasan, Tatiana Munera Huertas, Nathalie Khavessian, Angeliki Kontou, Tomislav Kostyanev, Premsak Laoyookhon, Sorasak Lochindarat, Maia De Luca, Surbhi Malhotra‐Kumar, Nivedita Mondal, Nitu Mundhra, Philippa Musoke, Marisa Márcia Mussi‐Pinhata, Ruchi Nanavati, Firdose Nakwa, Sushma Nangia, Alessandra Nardone, Borna Nyaoke, Christina W. Obiero, Ping Wang, Kanchana Preedisripipat, Shamim Qazi, Lifeng Qi, Amy Riddell, Lorenza Romani, Praewpan Roysuwan, Robin Saggers, Samir K. Saha, Kosmas Sarafidis, Valerie Tusibira, Sithembiso Velaphi, Tuba Vilken, Xiaojiao Wang, Yajuan Wang, Yonghong Yang, Sally Ellis, Julia Bielicki, A. Sarah Walker, Paul T. Heath, Mike Sharland

Notice bibliographique

RevuemedRxiv · 2022
Typepreprint
Langueen
DomaineMedicine
ThématiqueNeonatal and Maternal Infections
Établissements canadiensInstitute of Infection and Immunity
Organismes subventionnairesnon disponible
Mots-clésMedicineSepsisObservational studyPediatricsCohort studyCohortClinical trialProspective cohort studyInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Background Sepsis severity scores are used in clinical practice and trials to define risk groups. There are limited data to derive hospital-based sepsis severity scores for neonates and young infants in high-burden low- and middle-income country (LMIC) settings where trials are urgently required. We aimed to create linked sepsis severity and recovery scores applicable to hospitalized neonates and young infants in LMIC which could be used to inform antibiotic trials. Methods & Findings A prospective observational cohort study was conducted across 19 hospitals in 11 countries in sub-Saharan Africa, Asia, Latin America and Europe. Infants aged <60 days with clinical sepsis fulfilling at least two clinical or laboratory criteria (≥1 clinical) were enrolled. Primary outcome was 28-day mortality. Two prediction models were developed for 1) 28-day mortality from factors at sepsis presentation (baseline NeoSep Severity Score), and 2) daily risk of death on IV antibiotics from daily updated assessments (NeoSep Recovery Score). Multivariable Cox regression models included a randomly selected 85% of infants, with 15% for validation. 3204 infants were enrolled between 2018-2020. Median age was 5 days (IQR 2-15), 90.4% (n=2,895) were <28 days. Median birth weight was 2500g (1400-3000g), and a median of 4 clinical (IQR 2-5) and 1 laboratory (0-2) signs were present. Overall mortality was 11.3% (95%CI 10.2-12.5%; n=350). A baseline NeoSep Severity Score from infants characteristics, respiratory support, and clinical signs (no laboratory tests) at presentation had a C-index 0.77 (95%CI: 0.75-0.80) and 0.76 (0.69-0.82) in derivation and validation samples, respectively. Mortality in the validation sample was 1.6% (3/189; 95%CI: 0.5-4.6%), 11.0% (27/245; 7.7-15.6%), and 27.3% (12/44; 16.3-41.8%) in low (score 0-4), medium (5-8) and high (9-16) risk groups, respectively, with similar performance across subgroups. A related NeoSep Recovery Score based on evolving post-baseline clinical signs and supportive care discriminated well between infants who died or survived the following day or subsequent few days. The area under the ROC curve for score on day 2 and death in the following 5 days was 0.82 (95%CI 0.78-0.85) and 0.85 (95%CI 0.78-0.93) in the derivation and validation data, respectively. Conclusion The baseline NeoSep Severity Score predicted 28-day mortality and could identify infants with high risk of mortality for inclusion in hospital-based sepsis trials. The NeoSep Recovery Score predicts day-by-day inpatient mortality and could, with further validation, help to identify poor response to antibiotics. Author Summary Why was this study done? ➣ Evidence to guide hospital-based antibiotic treatment of sepsis in neonates and young infants is scarce, and clinical trials are particularly urgent in low- and middle-income (LMIC) settings where antimicrobial resistance threatens to undermine existing guidelines ➣ There is limited data to inform the design of antibiotic trials in LMIC settings, particularly to define risk stratification and inclusion and escalation criteria in hospitalised neonates and young infants What did the researchers do and find? ➣ To our knowledge this is the first global, prospective, hospital-based observational study of clinically diagnosed neonatal sepsis across 4 continents including LMIC settings, with extensive daily data collection on clinical status, antibiotic use and outcomes. ➣ There was a high mortality among infants with sepsis in LMIC hospital settings. 4 non-modifiable and 6 modifiable factors predicted mortality and were included in a NeoSep Severity score which defines patterns of mortality risk at baseline ➣ A NeoSep Recovery Score including the same modifiable factors (with the addition of cyanosis) predicted mortality on the following day during the course of treatment. What do these findings mean? ➣ The NeoSep Severity Score and NeoSep Recovery score are now informing inclusion and escalation criteria in the NeoSep1 antibiotic trial ( ISRCTN48721236 ) which aims to identify novel first- and second-line empiric antibiotic regimens for neonatal sepsis ➣ The NeoSep Severity Score could be used to predict mortality at baseline in future studies of targeting resources in routine care. With further validation, the NeoSep Recovery Score could potentially be used to identify poor response to empiric antibiotic treatment

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,017
Score d'incertitude au seuil0,972

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,026
Tête enseignante GPT0,295
Écart entre enseignants0,269 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2022
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revuemedRxivMême sujetNeonatal and Maternal InfectionsTravaux en français237 207