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Record W3135439283 · doi:10.1097/ccm.0000000000004950

A Systematic Review of the Incidence and Outcomes of In-Hospital Cardiac Arrests in Patients With Coronavirus Disease 2019*

2021· review· en· W3135439283 on OpenAlexaboutno aff
Zheng Jie Lim, Mallikarjuna Ponnapa Reddy, J. Randall Curtis, Baki Billah, Vishad Sheth, Salim S. Hayek, David E. Leaf, Jeremy Miles, Priyank Shah, Eugene Yuriditsky, Daryl Jones, Kiran Shekar, Ashwin Subramaniam

Bibliographic record

VenueCritical Care Medicine · 2021
Typereview
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAsystoleReturn of spontaneous circulationIncidence (geometry)Pulseless electrical activityCardiopulmonary resuscitationEmergency medicineInternal medicineIntensive care medicineResuscitation

Abstract

fetched live from OpenAlex

OBJECTIVES: To investigate the incidence, characteristics, and outcomes of in-hospital cardiac arrest in patients with coronavirus disease 2019 and to describe the characteristics and outcomes for patients with in-hospital cardiac arrest within the ICU, compared with non-ICU patients with in-hospital cardiac arrest. Finally, we evaluated outcomes stratified by age. DATA SOURCES: A systematic review of PubMed, EMBASE, and preprint websites was conducted between January 1, 2020, and December 10, 2020. Prospective Register of Systematic Reviews identification: CRD42020203369. STUDY SELECTION: Studies reporting on consecutive in-hospital cardiac arrest with a resuscitation attempt among patients with coronavirus disease 2019. DATA EXTRACTION: Two authors independently performed study selection and data extraction. Study quality was assessed with the Newcastle-Ottawa Scale. Data were synthesized according to the Preferred Reporting Items for Systematic Reviews guidelines. Discrepancies were resolved by consensus or through an independent third reviewer. DATA SYNTHESIS: Eight studies reporting on 847 in-hospital cardiac arrest were included. In-hospital cardiac arrest incidence varied between 1.5% and 5.8% among hospitalized patients and 8.0-11.4% among patients in ICU. In-hospital cardiac arrest occurred more commonly in older male patients. Most initial rhythms were nonshockable (83.9%, [asystole = 36.4% and pulseless electrical activity = 47.6%]). Return of spontaneous circulation occurred in 33.3%, with a 91.7% in-hospital mortality. In-hospital cardiac arrest events in ICU had higher incidence of return of spontaneous circulation (36.6% vs 18.7%; p < 0.001) and relatively lower mortality (88.7% vs 98.1%; p < 0.001) compared with in-hospital cardiac arrest in non-ICU locations. Patients greater than or equal to 60 years old had significantly higher in-hospital mortality than those less than 60 years (93.1% vs 87.9%; p = 0.019). CONCLUSIONS: Approximately, one in 20 patients hospitalized with coronavirus disease 2019 received resuscitation for an in-hospital cardiac arrest. Hospital survival after in-hospital cardiac arrest within the ICU was higher than non-ICU locations and seems comparable with prepandemic survival for nonshockable rhythms. Although the data provide guidance surrounding prognosis after in-hospital cardiac arrest, it should be interpreted cautiously given the paucity of information surrounding treatment limitations and resource constraints during the pandemic. Further research is into actual causative mechanisms is needed.

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)0.012
metaresearch head score (Gemma)0.061
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: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.061
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.011
Bibliometrics0.0140.015
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.015
GPT teacher head0.354
Teacher spread0.338 · 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
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

Citations14
Published2021
Admission routes1
Has abstractyes

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