MétaCan
Menu
Back to cohort
Record W2357587481

Monitoring of blood culture submission of 72 hospitals in 2011 Shanghai

2012· article· en· W2357587481 on OpenAlexaboutno aff
Cui Yangwen, Bijie Hu, Xiaodong Gao, Jian Ma, Xie Hongmei, Sen Yan, Wei‐Zen Sun

Bibliographic record

VenueZhongguo yiyuan ganranxue zazhi · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Identification and Susceptibility Testing
Canadian institutionsnot available
Fundersnot available
KeywordsBlood cultureMedicineQuarter (Canadian coin)AntibioticsEmergency medicineInternal medicinePediatricsBiologyHistoryMicrobiology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE To investigate the submission rate of the blood culture of 72 hospitals in 2011.METHODS The data of the blood culture submission were investigated for the hospitalized patients with fever(≥38.5 ℃) from 72 hospitals under the surveillance net by Shanghai Center for Nosocomial Infection Control for 3 days once and once a quarter.RESULTS The patients enrolled from 72 hospitals in the first,second,third and fourth quarter were 54968,51089,54089 and 49421.The number of patients with fever(≥38.5 ℃) were 1602,1347,1571,and 1443,respectively,among them,the proportions of blood culture submission were 604(37.70%),572(42.78%),937(59.64%) and 640(44.35%),respectively,the submission rate was increasing;the number of patients with fever(≥39.5 ℃) was 1196 with the submission rate of 59.20%;the number of patients with CVC(≥5 days) was 937 with the submission rate of 52.50%;the submission rate of the patients who used special antibiotics was 47.25%.CONCLUSION The submission rate of the blood culture of the 72 hospitals in Shanghai needs to be further improved,it is necessary to take the steps to raise the submission rate of the blood culture.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.016
GPT teacher head0.265
Teacher spread0.249 · 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 designBench or experimental
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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueZhongguo yiyuan ganranxue zazhiSame topicBacterial Identification and Susceptibility TestingFrench-language works237,207