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Record W2963718678 · doi:10.1001/jamacardio.2019.2467

Demographics, Care Patterns, and Outcomes of Patients Admitted to Cardiac Intensive Care Units

2019· article· en· W2963718678 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJAMA Cardiology · 2019
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsUniversity of TorontoToronto General HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineAcute coronary syndromeEmergency medicinePopulationTIMIIntensive care unitIntensive careRetrospective cohort studyMedical diagnosisCoronary care unitPediatricsIntensive care medicineInternal medicinePercutaneous coronary interventionMyocardial infarction

Abstract

fetched live from OpenAlex

Importance: Single-center and claims-based studies have described substantial changes in the landscape of care in the cardiac intensive care unit (CICU). Professional societies have recommended research to guide evidence-based CICU redesigns. Objective: To characterize patients admitted to contemporary, advanced CICUs. Design, Setting, and Participants: This study established the Critical Care Cardiology Trials Network (CCCTN), an investigator-initiated multicenter network of 16 advanced, tertiary CICUs in the United States and Canada. For 2 months in each CICU, data for consecutive admissions were submitted to the central data coordinating center (TIMI Study Group). The data were collected and analyzed between September 2017 and 2018. Main Outcomes and Measures: Demographics, diagnoses, management, and outcomes. Results: Of 3049 participants, 1132 (37.1%) were women, 797 (31.4%) were individuals of color, and the median age was 65 years (25th and 75th percentiles, 55-75 years). Between September 2017 and September 2018, 3310 admissions were included, among which 2557 (77.3%) were for primary cardiac problems, 337 (10.2%) for postprocedural care, 253 (7.7%) for mixed general and cardiac problems, and 163 (4.9%) for overflow from general medical ICUs. When restricted to the initial 2 months of medical CICU admissions for each site, the primary analysis population included 3049 admissions with a high burden of noncardiovascular comorbidities. The top 2 CICU admission diagnoses were acute coronary syndrome (969 [31.8%]) and heart failure (567 [18.6%]); however, the proportion of acute coronary syndrome was highly variable across centers (15%-57%). The primary indications for CICU care included respiratory insufficiency (814 [26.7%]), shock (643 [21.1%]), unstable arrhythmia (521 [17.1%]), and cardiac arrest (265 [8.7%]). Advanced CICU therapies or monitoring were required for 1776 patients (58.2%), including intravenous vasoactive medications (1105 [36.2%]), invasive hemodynamic monitoring (938 [30.8%]), and mechanical ventilation (652 [21.4%]). The overall CICU mortality rate was 8.3% (95% CI, 7.3%-9.3%). The CICU indications that were associated with the highest mortality rates were cardiac arrest (101 [38.1%]), cardiogenic shock (140 [30.6%]), and the need for renal replacement therapy (51 [34.5%]). Notably, patients admitted solely for postprocedural observation or frequent monitoring had a mortality rate of 0.2% to 0.4%. Conclusions and Relevance: In a contemporary network of tertiary care CICUs, respiratory failure and shock predominated indications for admission and carried a poor prognosis. While patterns of practice varied considerably between centers, a substantial, low-risk population was identified. Multicenter collaborative networks, such as the CCCTN, could be used to help redesign cardiac critical care and to test new therapeutic strategies.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.293
Teacher spread0.267 · 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