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Record W4213097276 · doi:10.3390/curroncol29020097

Analysis of Prognostic Risk Factors and Establishment of Prognostic Scoring System for Secondary Adult Hemophagocytic Syndrome

2022· article· en· W4213097276 on OpenAlexvenueno aff
Qiaolei Zhang, Youyan Lin, Yejiang Bao, Yuan Jin, Xiujin Ye, Yamin Tan

Bibliographic record

VenueCurrent Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIntensive care medicineInternal medicineOncologyBioinformaticsBiology

Abstract

fetched live from OpenAlex

Introduction: The objective of this paper is to identify the prognostic risk factors of secondary adult hemophagocytic syndrome (HLH) in hospitalized patients and establish a simple and convenient prognostic scoring system. Method:We reviewed 162 adult patients secondary with HLH treated in Zhejiang Cancer Hospital and the First Affiliated Hospital of Medical College of Zhejiang University from January 2014 to December 2018 were enrolled to form the test group; from January 2019 to February 2021, 162 adult patients in the hospitals constituted the validation group. The HLH prognosis scoring system was constructed according to the risk factors, and the patients were divided into three risk groups: low risk, medium risk, and high risk. The scoring system was verified by Kaplan–Meier method and log rank test survival analysis. The discrimination ability was evaluated according to the receiver operating characteristic (ROC) curve. Results: Univariate and multivariate analysis showed that the independent risk factors for the prognosis of HLH were male sex, activated partial prothrombin time (APTT) greater than 36 s, lactate dehydrogenase (LDH) greater than 1000 U/L, and C-reactive protein (CRP) greater than 100 mg/L. The area under the ROC curve was 0.754 (95% Cl: 0.678–0.829). The patients were divided into a low-risk group (0–1), a medium-risk group (2–4), and a high-risk group (5–6). The 5-year overall survival (OS) rate were 87.5%, 41.8% and 12.8%, respectively (p < 0.001). The area under ROC curve was 0.736 (95% Cl: 0.660–0.813) in the validation group, and the 2-year OS of patients in low-risk, medium-risk and high-risk groups were 88.0%, 45.1% and 16.7%, respectively (p < 0.001). Conclusion:The new prognostic scoring system can accurately predict the prognosis of secondary adult HLH and can further provide basis for the accurate treatment of secondary adult HLH.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.024
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.048
GPT teacher head0.350
Teacher spread0.302 · 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 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

Citations11
Published2022
Admission routes1
Has abstractyes

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