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
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".