Feasibility of estimating cardiac indices using cardiac surgery anesthesia records in a multicenter cohort

Cardiac index (CI) is a key physiologic indicator correlated with end-organ perfusion in cardiac surgical patients, yet it is not routinely measured in all cases. This study evaluated the accuracy of estimating CI using routinely available physiologic monitor data, adjusted for relevant patient, physiologic, and procedural factors documented in perioperative anesthesia records. We analyzed anesthesia records from adult cardiac surgical patients with thermodilution-based CI measurements across seven US hospitals from 2014 to 2022. Four published formulas-based on intraoperative blood pressure and heart rate-were used to estimate CI in generalized linear models, with adjustment for perioperative patient and procedure characteristics. Bland-Altman analysis compared adjusted CI estimates to reference thermodilution CI values. The ability of each estimator to classify patients with low CI (< 2.2 L/min/m²) was assessed for concordance. In a cohort of 5,989 patients, the median (IQR = interquartile range) thermodilution-based CIs were 2.1 (1.8-2.6) and 2.4 (2.0-2.9) L/min/m² before and after cardiopulmonary bypass, respectively. The best-performing formula, Liljestrand and Zander, achieved mean absolute errors of 0.45 and 0.47 L/min/m² before and after bypass, respectively. However, its reliability in classifying low CI was limited (Cohen's kappa = 0.26 pre-bypass, 0.20 post-bypass). Routinely collected physiologic and patient data can be used to generate population-level cardiac index estimates in adult cardiac surgery patients when appropriately adjusted, though individual-level discrimination of low CI is limited. These findings inform future large-scale perioperative hemodynamic research.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Monitoring and Computing
Published
2025-12-24
DOI
https://doi.org/10.1007/s10877-025-01400-0
Primary Topic
Hemodynamic Monitoring and Therapy
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Feasibility of estimating cardiac indices using cardiac surgery anesthesia records in a multicenter cohort

Michael R. Mathis, Graciela B. Mentz, Emily A. Balczewski, Karandeep Singh
Journal of Clinical Monitoring and Computing
Hemodynamic Monitoring and Therapy
article

Feasibility of estimating cardiac indices using cardiac surgery anesthesia records in a multicenter cohort

Michael R. Mathis, Graciela B. Mentz, Emily A. Balczewski, Karandeep Singh
article en

Abstract

Cardiac index (CI) is a key physiologic indicator correlated with end-organ perfusion in cardiac surgical patients, yet it is not routinely measured in all cases. This study evaluated the accuracy of estimating CI using routinely available physiologic monitor data, adjusted for relevant patient, physiologic, and procedural factors documented in perioperative anesthesia records. We analyzed anesthesia records from adult cardiac surgical patients with thermodilution-based CI measurements across seven US hospitals from 2014 to 2022. Four published formulas-based on intraoperative blood pressure and heart rate-were used to estimate CI in generalized linear models, with adjustment for perioperative patient and procedure characteristics. Bland-Altman analysis compared adjusted CI estimates to reference thermodilution CI values. The ability of each estimator to classify patients with low CI (< 2.2 L/min/m²) was assessed for concordance. In a cohort of 5,989 patients, the median (IQR = interquartile range) thermodilution-based CIs were 2.1 (1.8-2.6) and 2.4 (2.0-2.9) L/min/m² before and after cardiopulmonary bypass, respectively. The best-performing formula, Liljestrand and Zander, achieved mean absolute errors of 0.45 and 0.47 L/min/m² before and after bypass, respectively. However, its reliability in classifying low CI was limited (Cohen's kappa = 0.26 pre-bypass, 0.20 post-bypass). Routinely collected physiologic and patient data can be used to generate population-level cardiac index estimates in adult cardiac surgery patients when appropriately adjusted, though individual-level discrimination of low CI is limited. These findings inform future large-scale perioperative hemodynamic research.

Journal of Clinical Monitoring and Computing
University of Michigan (US), University of California San Diego (US), Michigan Medicine (US), Center for Innovation (US)
Yale University, University of Washington, National Institutes of Health, University of California, San Diego, Medical School, University of Michigan, Department of Anesthesiology and Pain Medicine, University of Washington, National Heart, Lung, and Blood Institute, National Institute of General Medical Sciences, National Institute of Diabetes and Digestive and Kidney Diseases
Peace, Justice and strong institutions
Openalex Percentile: Top 27%
Hemodynamic Monitoring and Therapy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.