Evidence map›Paper›PMID 35683616›Full record

ArticleJournal of clinical medicine2022

Benchmark of Intraoperative Activity in Cardiac Surgery: A Comparison between Pre- and Post-Operative Prognostic Models.

Anna Zamperoni, Greta Carrara, Massimiliano Greco, Carlotta Rossi, Elena Garbero, Giovanni Nattino, Giuseppe Minniti, Paolo Del Sarto, Guido Bertolini, Stefano Finazzi and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
0.2field-weighted citation impact, top 50% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 1 citations in OpenAlex.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 1 country.

Anna ZamperoniCà Foncello Hospital, AULSS2 Treviso, 31100 Treviso, Italy.
Greta CarraraIstituto di Ricerche Farmacologiche Mario Negri IRCCS, 20156 Milan, Italy.
Massimiliano GrecoDepartment of Biomedical Sciences, Humanitas University, 20090 Milan, Italy.ORCID 0000-0003-1003-4637
Carlotta RossiIstituto di Ricerche Farmacologiche Mario Negri IRCCS, 20156 Milan, Italy.
Elena GarberoIstituto di Ricerche Farmacologiche Mario Negri IRCCS, 20156 Milan, Italy.ORCID 0000-0003-4902-0144
Giovanni NattinoIstituto di Ricerche Farmacologiche Mario Negri IRCCS, 20156 Milan, Italy.
Giuseppe MinnitiCà Foncello Hospital, AULSS2 Treviso, 31100 Treviso, Italy.
Paolo Del SartoDepartment of Critical Care, G. Pasquinucci Heart Hospital, Fondazione Toscana G. Monasterio, 54100 Massa, Italy.
Guido BertoliniIstituto di Ricerche Farmacologiche Mario Negri IRCCS, 20156 Milan, Italy.
Stefano FinazziIstituto di Ricerche Farmacologiche Mario Negri IRCCS, 20156 Milan, Italy.ORCID 0000-0002-3525-3249
Cardiac Surgical Intensive Care Writing Committee GiViTI
Mario Negri Institute for Pharmacological Research · ITCa' Foncello Hospital · ITFondazione Toscana Gabriele Monasterio · ITHumanitas University · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesDespite its large diffusion and improvements in safety, the risks of complications after cardiac surgery remain high. Published predictive perioperative scores (EUROSCORE, STS, ACEF) assess risk on preoperative data only, not accounting for the intraopertive period. We propose a double-fold model, including data collected before surgery and data collected at the end of surgery, to evaluate patient risk evolution over time and assess the direct contribution of surgery.

methodsA total of 15,882 cardiac surgery patients from a Margherita-Prosafe cohort study were included in the analysis. Probability of death was estimated using two logistic regression models (preoperative data only vs. post-operative data, also including information at discharge from the operatory theatre), testing calibration and discrimination of each model.

resultsPre-operative and post-operative models were built and demonstrate good discrimination and calibration with AUC = 0.81 and 0.87, respectively. Relative difference in pre- and post-operative mortality in separate centers ranged from -0.36 (95% CI: -0.44--0.28) to 0.58 (95% CI: 0.46-0.71). The usefulness of this two-fold preoperative model to benchmark medical care in single hospital is exemplified in four cases.

conclusionsPredicted post-operative mortality differs from predicted pre-operative mortality, and the distance between the two models represent the impact of surgery on patient outcomes. A double-fold model can assess the impact of the intra-operative team and the evolution of patient risk over time, and benchmark different hospitals on patients subgroups to promote an improvement in medical care in each center.

Indexed as

anesthesiabypass surgerycardiac surgerycoronary arteryforecastingheart valve diseasemortality

Identifiers

PMID35683616
PMCPMC9181738
OpenAlexW4281705697

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.