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Record W2769167068 · doi:10.1186/s13643-017-0622-4

Prevalence and prognosis of acutely ill patients with organ failure at arrival to hospital: protocol for a systematic review

2017· review· en· W2769167068 on OpenAlexaboutno aff
Peter Bank Pedersen, Asbjørn Hróbjartsson, Daniel Nielsen, Daniel Pilsgaard Henriksen, Mikkel Brabrand, Annmarie Touborg Lassen

Bibliographic record

VenueSystematic Reviews · 2017
Typereview
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineProtocol (science)Emergency medicineIntensive care medicineCritically illAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Acutely ill patients are a heterogeneous group, and some of these suffer from organ failure. As the prognosis of organ failure improves with early treatment, it is important to identify these patients as early as possible. Most studies on organ failure have been performed in intensive care settings, or on selected groups of patients, where a high prevalence and mortality have been reported. Before patients arrive to the intensive care unit, or the general ward, most of them have passed through the emergency department (ED), where diagnosis and treatment has been initiated. The prevalence and prognosis of acutely ill patients, with organ failure, at arrival have been studied in some selected groups, but methods and results differ. This systematic review aims to identify, summarize, and analyze studies of prevalence and prognosis of new onset organ failure in acutely ill undifferentiated patients, at arrival to hospital. The result of the review will assist physicians working in an ED, when assessing patients' risk of organ failure and their associated prognosis. METHODS: The information sources used are electronic databases, PubMed, Cochrane Library, EMBASE, and CINAHL; references in included studies and review articles; and authors' personal files. One author will perform the title and abstract screening and exclude obviously ineligible studies. By an independent full-text screening, two authors will decide on the eligibility for the remaining studies. Eligible studies will include an unselected group of acutely ill adult patients at arrival to hospital, with one or more organ failures (respiratory, renal, cerebral, circulatory, hepatic, or coagulation failure). Included studies will have assessed the prevalence or prognosis, defined as mortality or ICU transfer, of new onset organ failure. From included studies, bibliographical and study description data, patient characteristics, and data related to prevalence of organ failure and prognosis will be extracted. We will assess risk of bias in included studies using the Quality in Prognosis Studies tool for prognostic studies and the Newcastle-Ottawa Scale for observational studies. We expect heterogeneity and to conduct a qualitative synthesis of the results. If, however, heterogeneity is low, we will conduct a random effects meta-analysis stratified by basic study design. DISCUSSION: This review will summarize and analyze studies of prevalence and prognosis of acutely ill patients, with organ failure at arrival to hospital, assist ED physicians assessing the risk of organ failure in unselected patients, and guide recommendations for further research. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42017060871.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.047
metaresearch head score (Gemma)0.069
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.047
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0470.069
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0180.016
Bibliometrics0.0140.013
Science and technology studies0.0030.004
Scholarly communication0.0060.008
Open science0.0040.005
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0430.004

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 head0.163
GPT teacher head0.436
Teacher spread0.272 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreProtocol

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

Citations8
Published2017
Admission routes1
Has abstractyes

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