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Record W2926603168 · doi:10.3389/fphys.2019.00328

Aging and Comorbidities in Acute Pancreatitis I: A Meta-Analysis and Systematic Review Based on 194,702 Patients

2019· review· en· W2926603168 on OpenAlexaboutno aff
Katalin Márta, Alina-Marilena Lãzãrescu, Nelli Farkas, Péter Mátrai, Irina M. Cazacu, Máté Ottóffy, Tamás Habon, Bálint Erőss, Áron Vincze, Gábor Veres, László Czakó, Patrícia Sarlós, Zoltán Rakonczay, Péter Hegyi

Bibliographic record

VenueFrontiers in Physiology · 2019
Typereview
Languageen
FieldMedicine
TopicPancreatitis Pathology and Treatment
Canadian institutionsnot available
FundersNational Research, Development and Innovation OfficeEmberi Eroforrások MinisztériumaMagyar Tudományos Akadémia
KeywordsFunnel plotMedicineMeta-analysisPublication biasIncidence (geometry)Systematic reviewAcute pancreatitisInternal medicineMortality rateRandom effects modelMEDLINEForest plot

Abstract

fetched live from OpenAlex

Acute pancreatitis (AP) is one of the most common cause of hospitalization among gastrointestinal diseases worldwide. Although most of the cases are mild, approximately 10%-20% of patients develop a severe course of disease with higher mortality rate. Scoring systems consider age as a risk factor of mortality and severity (BISAP;>60yrs, JPN>70 yrs, RANSON;>55yrs, APACHE II>45 yrs). If there is a correlation between ageing and the clinical features of AP, how does age influence mortality and severity? This study aimed to systematically review the effects of aging on AP. A comprehensive systematic literature search was conducted in the Embase, Cochrane and Pubmed databases. A meta-analysis was performed using the preferred reporting items for systematic review and meta-analysis statement (PRISMA). A total of 1100 articles were found. After removing duplicates and articles containing insufficient or irrelevant data, 33 publications involving 194 702 AP patients were analyzed.Seven age categories were determined and several mathematical models, including conventional mathematical methods (linear regression), meta-analyses (random effect model and heterogeneity tests), meta-regression, funnel plot and Egger’s test for publication bias were performed. Quality assessment was conducted using the modified Newcastle–Ottawa scale.The meta-analysis was registered in the PROSPERO database (CRD42017079253). Aging greatly influences the outcome of AP. There was a low severe AP incidence in patients under 30(1.6%); however, the incidence of severe AP showed a continuous, linear increase between 20 and 70(0.193%/year) of up to 9.6%. The mortality rate was 0.9% in patients under 20 and demonstrated a continuous linear elevation until 59,however from this age the mortality rate started elevating with 9 times higher rate until the age of 70.The mortality rate between 20 and 59 grew 0.086%/year and 0.765%/year between 59 and 70. Overall, patients above 70 had a 19 times higher mortality rate than patients under 20. The mortality rate rising with age was confirmed by meta-regression (coefficient:0.037CI:0.006–0.068,p=0.022;adjustedr2:13.8%),and severity also (coefficient:0.035CI:0.019–0.052,p<0.001;adjusted r2:31.6%). Our analysis shows a likelihood of severe pancreatitis, as well as, pancreatitis-associated mortality is more common with advanced age. Importantly,the rapid elevation of mortality above the age of 59 suggests the involvement of additional deteriorating factors such as co-morbidity in elderly.

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)0.010
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.022
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0160.043
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.042
GPT teacher head0.319
Teacher spread0.278 · 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 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

Citations53
Published2019
Admission routes1
Has abstractyes

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