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Record W4323353710 · doi:10.15441/ceem.23.005

Mortality among adult patients with sepsis and septic shock in Korea: a systematic review and meta-analysis

2023· review· en· W4323353710 on OpenAlexaboutno aff
Myeong Namgung, Chiwon Ahn, Yeonkyung Park, Il‐Youp Kwak, Jungguk Lee, Moonho Won

Bibliographic record

VenueClinical and Experimental Emergency Medicine · 2023
Typereview
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsSeptic shockMedicineSepsisConfidence intervalMortality rateSurviving Sepsis CampaignShock (circulatory)Meta-analysisInternal medicineSevere sepsis

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate mortality from sepsis and septic shock in Korea during the past 10 years, we conducted a systematic review and meta-analysis. METHODS: We searched six databases for studies on mortality from sepsis and septic shock in adult patients. Primary outcomes were 28- or 30-day mortality and in-hospital mortality from sepsis and septic shock. To assess the risk of bias, we used the Newcastle-Ottawa Scale and Risk of Bias 2 tools. The protocol is registered in PROSPERO (No. CRD42022365739). RESULTS: A total of 61 studies were included. The mortality rates from sepsis and septic shock at 28 or 30 days were 22.7% (95% confidence interval [CI], 20.0%-25.6%; I2=89%) and 27.6% (95% CI, 22.3%-33.5%; I2=98%), respectively, according to the Sepsis-3 criteria. Furthermore, in accordance with the Sepsis-3 criteria, the in-hospital mortality rates were 28.1% (95% CI, 25.2%-31.1%; I2=87%) and 34.3% (95% CI, 27.2%-42.2%; I2=97%), respectively. CONCLUSION: The mortality rates from sepsis and septic shock in Korea are high. In the case of septic shock, the in-hospital mortality rate is approximately 30%.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.709
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0120.001
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)0.0010.000

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 head0.355
GPT teacher head0.512
Teacher spread0.157 · 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.

Study designMeta-analysis
Domainnot available
GenreReview

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

Citations25
Published2023
Admission routes1
Has abstractyes

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