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Record W4396520780 · doi:10.1016/j.bja.2024.03.038

Risk factors, biomarkers, and mechanisms for persistent inflammation, immunosuppression, and catabolism syndrome (PICS): a systematic review and meta-analysis

2024· review· en· W4396520780 on OpenAlexaboutno aff
Karan R. Chadda, Ellen E. Blakey, Thomas Davies, Zudin Puthucheary

Bibliographic record

VenueBritish Journal of Anaesthesia · 2024
Typereview
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsnot available
FundersAriad PharmaceuticalsBaxter International
KeywordsImmunosuppressionMeta-analysisCatabolismInflammationMedicineIntensive care medicineImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Introduction Persistent inflammation, immunosuppression, and catabolism syndrome (PICS) has been proposed as an endotype of chronic critical illness (CCI). The aim of this systematic review is to synthesise the available evidence of risk factors, biomarkers, and biological mechanisms underlying PICS. Methods MEDLINE, CENTRAL, and EMBASE were searched on June 2, 2023. Our population of interest was adult intensive care unit survivors. The exposure group was patients with PICS and the comparator group was patients with no PICS, CCI, or rapid recovery. Mean differences were pooled for each biomarker using a random effects DerSimonian–Laird method. Risk of bias assessment was done using the Newcastle–Ottawa Scale. Results Six papers were included. Five were single-centre retrospective cohort studies, and one was a prospective cohort study, with sample sizes ranging from 22 to 391 patients. Two studies showed an increased incidence of PICS with age, and two studies showed an association between PICS and Charlson Comorbidity Index scores. PICS was associated with requiring mechanical ventilation in four studies. Meta-analysis showed a 34.4 mg L −1 higher C-reactive protein (95% confidence interval [CI] 12.7–56.2 mg L −1 ; P <0.01), a 4.4 g L −1 lower albumin (95% CI 0.5–8.3 g L −1 ; P <0.01), and a 0.36×10 9 L −1 lower lymphocyte count (95% CI 0.25–0.47×10 9 L −1 ; P =0.01) in the PICS compared with the non-PICS group. There are a large variety of other potential biomarkers but limited validation studies. The overall quality of evidence is limited, and these results should be interpreted accordingly. Conclusions While older patients and those with co-morbidities could be at greater risk for PICS, acquired risk factors, such as injury severity, are potentially more predictive of PICS than intrinsic patient characteristics. There are many potential biomarkers for PICS, but limited validation studies have been conducted. Persistent myeloid-derived suppressor cell expansion, the continual release of danger-associated molecular patterns and pathogen-associated molecular patterns propagating inflammation, and bioenergetic failure are all mechanisms underlying PICS that could offer potential for novel biomarkers and therapeutic interventions. Clinical trial registration International Prospective Register of Systematic Reviews (PROSPERO; CRD42023427749).

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)0.014
metaresearch head score (Gemma)0.031
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.031
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0210.035
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.074
GPT teacher head0.337
Teacher spread0.262 · 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

Citations30
Published2024
Admission routes1
Has abstractyes

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