Daily Anesthesiology Research Analysis
Three impactful anesthesiology studies stood out today: a prospective cohort in Anesthesiology showed significant skin tone–related bias in pediatric NIRS readings; a methodological paper in Anesthesia & Analgesia introduced a robust new concordance metric (with a Python package) for comparing cardiac output monitors; and a large retrospective cohort demonstrated improved surgical outcomes with transfusion-free care and patient blood management.
Summary
Three impactful anesthesiology studies stood out today: a prospective cohort in Anesthesiology showed significant skin tone–related bias in pediatric NIRS readings; a methodological paper in Anesthesia & Analgesia introduced a robust new concordance metric (with a Python package) for comparing cardiac output monitors; and a large retrospective cohort demonstrated improved surgical outcomes with transfusion-free care and patient blood management.
Research Themes
- Equity and bias in physiologic monitoring
- Methodological innovation for cardiac output concordance assessment
- Perioperative patient blood management and transfusion avoidance
Selected Articles
1. Near-infrared Spectroscopy and Skin Tone in Children: A Prospective Cohort Study.
In 110 children undergoing cardiac catheterization, skin tone measured by spectrophotometry was strongly associated with NIRS bias using the INVOS 5100C. Darker skin categories showed a 10–13% greater negative bias versus lighter skin when compared against mixed venous saturation.
Impact: This is one of the first prospective pediatric studies to quantify skin tone–related bias in NIRS against a physiologic gold standard, highlighting a critical equity gap in monitoring.
Clinical Implications: Clinicians should interpret cerebral NIRS values with caution in children with darker skin tones, consider device-specific bias, and advocate for calibration/validation across skin tones. Protocols may require adjusted thresholds or supplemental monitoring to ensure equitable care.
Key Findings
- Darker skin tone (ITA 5–6) was associated with a −12.8% mean bias versus mixed venous saturation compared with −2.5% for ITA 3–4 and 0.3% for ITA 1–2.
- Skin tone (ITA) was an independent predictor of NIRS bias in multivariable regression (coefficient 0.173; P < 0.001).
- Findings are specific to the INVOS 5100C system and suggest the need for improved validation across skin tones.
Methodological Strengths
- Prospective design with objective spectrophotometric skin tone measurement (ITA).
- Comparison against mixed venous saturation as a physiologic reference standard with multivariable adjustment.
Limitations
- Single-center, pediatric cardiac catheterization cohort may limit generalizability.
- Findings are device-specific (INVOS 5100C) and may not extend to other NIRS systems.
Future Directions: Cross-platform validation across diverse skin tones, development of correction algorithms or calibration standards, and evaluation of clinical decision thresholds to mitigate inequities.
BACKGROUND: Retrospective studies suggest that pulse oximetry overestimates saturation in children from races that may be associated with darker skin tone. Near-infrared spectroscopy (NIRS) relies on similar optical technology, but less is known about the effect of skin tone on NIRS. This study aimed to quantify the effect of skin tone on NIRS performance. METHODS: Consecutive patients under 21 yr old undergoing cardiac catheterization were enrolled (N = 110). Skin tone was measured using spectrophotometry. Regional oxygen saturation was recorded from a Medtronic (USA) INVOS 5100C NIRS device placed on the forehead and was compared to the mixed venous saturation. Multivariable linear regressions were used to determine the effect of skin tone measured by individual typology angle (ITA). RESULTS: Mean bias was larger for patients with darker skin in ITA categories 5 and 6 at -12.8% compared to ITA categories 3 and 4 at -2.5% with a difference of 10.3% (95% CI, 4.4 to 16.3; P < 0.001) and ITA categories 1 and 2 at 0.3% with a difference of 13.1% (95% CI, 7.5 to 18.7; P < 0.001). ITA was associated with NIRS bias in multivariable regression analysis (coefficient, 0.173; P < 0.001). CONCLUSIONS: Darker skin tone is associated with worse NIRS performance and lower NIRS values compared to mixed venous saturation for the INVOS 5100C system. This may lead to differences in care and contribute to inequities in outcomes. Better validation guidelines are needed to ensure equity in performance across varying skin tones.
2. Error Field Concordance Analysis: A New Statistical Method and Python Package to Assess Cardiac Output Concordance.
The authors introduce Error Field Concordance Analysis, a color-coded Cartesian approach that quantifies concordance and discordance without exclusion zones, outperforming traditional 4-quadrant and polar plot methods in simulations. A public Python package facilitates adoption.
Impact: Provides a more discriminative, transparent, and shareable method to evaluate agreement of cardiac output monitors, addressing known pitfalls of widely used approaches.
Clinical Implications: When validating or comparing cardiac output technologies, adopting this method can reduce misclassification from exclusion zones and better detect discordance and noise, improving device assessment and procurement decisions.
Key Findings
- Error Field Concordance Analysis distinguishes strong/loose concordance, noise, and discordance without excluding data.
- It outperforms 4-quadrant analysis and demonstrates critical shortcomings of polar plots.
- A Python package (PIP-installable) enables easy application of the method.
Methodological Strengths
- Clear mathematical framework with simulation-based benchmarking across multiple concordance scenarios.
- Open-source implementation enabling reproducibility and wide adoption.
Limitations
- Performance shown primarily on simulated datasets; limited demonstration on real-world clinical data.
- Clinical thresholds and interpretation guidelines for the new metric require consensus.
Future Directions: Validate on multi-center clinical datasets, define clinically meaningful thresholds, and integrate into device validation standards and regulatory submissions.
BACKGROUND: Determining the concordance between different cardiac output (CO) measurement methods is important in perioperative and intensive care medicine. Two frequently used statistical methods are 4-quadrant plot and polar plot analyses, but these methods have limitations (eg, 4-quadrant plot cannot distinguish well between tight concordance and loose concordance, while polar plot analysis requires complex transformation of data and does not quantify discordance). We propose a new approach, error field concordance analysis, which uses the strengths of the 4-quadrant plot and polar plot analyses while removing their main weaknesses. This tool aims to intuitively use the Cartesian plane to provide an easily interpretable score for concordance assessment. In addition, we provide a Python package available through the Package Installer for Python (PIP) to offer easy access for applying this new method. METHODS: We propose and explain error field concordance analysis, which uses a color-coded Cartesian approach, weighs the magnitude of concordance, and allows calculation of the concordance angle. We also develop the mathematical basis for computing concordance using error field concordance analysis. We compare error field concordance analysis with 4-quadrant plot and polar plot analyses using simulated data to demonstrate strong concordance, loose concordance, total noise, and strong discordance to compare these strategies and identify potential pitfalls. RESULTS: Error field concordance analysis can clearly differentiate strong concordance, loose concordance, total noise, and strong discordance without excluding data. Error field concordance analysis outperforms 4-quadrant plot analysis by detecting loss of concordance, discordance, and noise. As a result of having no exclusion zone, the data are not subject to artificial inflation of the metric in the presence of little observed change in the underlying data. We again demonstrate that the polar plot method has poor discriminant capacity compared to other methods and additionally has a critical flaw that renders it unreliable. CONCLUSIONS: Error field concordance analysis intuitively displays color-coded data on a Cartesian plane and provides an easily interpretable score for both concordance and discordance.
3. Outcomes of Nontransfusable and Transfusable Patients After Major Noncardiac Surgery: A Retrospective Cohort Study.
Across 25,979 major noncardiac surgeries, transfusion-free care was associated with substantially lower mortality and complications versus transfusable patients. Among transfusable patients, PBM reduced mortality and complications but was linked to higher 30-day readmissions.
Impact: Large-scale, rigorously adjusted evidence supporting transfusion minimization strategies provides pragmatic guidance for perioperative blood management.
Clinical Implications: Implement and prioritize PBM pathways (anemia optimization, hemostasis, restrictive transfusion) and consider transfusion-free protocols where appropriate. Monitor for potential increases in readmissions and address discharge planning and follow-up.
Key Findings
- Transfusion-free management had lower in-hospital mortality (OR 0.33) and fewer renal and respiratory complications versus transfusable patients.
- Among transfusable patients, PBM reduced mortality (OR 0.79), surgical site, renal, and respiratory complications, and length of stay.
- PBM was associated with higher 30-day readmissions (OR 1.28), warranting attention to post-discharge care.
Methodological Strengths
- Very large sample with propensity score–adjusted multivariable models across numerous outcomes.
- Comparative evaluation across three care models within one hospital network over 12 years.
Limitations
- Retrospective observational design with potential residual confounding and selection bias.
- Readmission coding and reasons were not deeply explored; generalizability beyond two hospitals may be limited.
Future Directions: Prospective multicenter PBM trials clarifying causal effects and exploring drivers of readmissions; cost-effectiveness and patient-centered outcomes analyses.
BACKGROUND: Patients admitted to HELIOS Klinikum in Gotha and Erfurt, Germany, received one of 3 models of care. Nontransfusable patients received transfusion-free blood management, whereas transfusable patients received either patient blood management (PBM) or no PBM. Few studies have compared outcomes in patients undergoing these models of care within 1 hospital network. Our primary aim was to compare adult nontransfusable patients undergoing major surgery to transfusable patients. Our secondary aim was to compare transfusable patients receiving PBM strategies to those receiving no PBM. METHODS: A retrospective cohort study of 25,979 major adult noncardiac surgical admissions to 2 German hospitals between 2008 and 2020. We applied propensity score methods to multivariable regression models adjusting for age, sex, admission hemoglobin, comorbidities, surgical procedure group, surgical complexity, and admission year. Outcomes included in-hospital mortality, surgical site complications, renal complications, respiratory complications, acute myocardial infarction (AMI), readmissions within 30 days, length of stay, estimated blood loss, transfusion rate, and transfusion reactions. RESULTS: Patients receiving transfusion-free blood management had lower mortality (odds ratio [OR] 0.33, 95% confidence interval [CI], 0.26-0.42; P < .001), renal complications (OR 0.40, 95% CI, 0.34-0.48; P < .001), respiratory complications (OR 0.43, 95% CI, 0.37-0.49; P < .001), readmissions (OR 0.54, 95% CI, 0.48-0.60; P < .001), and shorter hospital stay (risk ratio [RR] 0.91, 95% CI, 0.90-0.93; P < .001) compared to transfusable patients. There were no AMI complications in the transfusion-free group compared to 0.3% (n = 78) in the transfusable group. Surgical site complications were not significantly different between groups (OR 0.94, 95% CI, 0.86-1.02; P = .140). In our secondary analysis of transfusable patients, PBM was associated with lower mortality (OR 0.79, 95% CI, 0.66-0.95; P = .012), surgical site complications (OR 0.62, 95% CI, 0.57-0.69, P < .001), renal complications (OR 0.76, 95% CI, 0.65-0.88; P < .001), respiratory complications (OR 0.68, 95% CI, 0.60-0.78; P < .001), and shorter hospital stay when compared to no PBM (RR 0.86, 95% CI, 0.85-0.87; P < .001). Hospital readmissions were higher in the PBM group (OR 1.28, 95% CI, 1.18-1.40; P < .001). The proportion of patients receiving a red cell transfusion, units transfused per patient, and estimated blood loss were lower in the PBM group when compared to no PBM. There were no transfusion complications coded in the PBM or no PBM groups. CONCLUSIONS: Our primary and secondary analyses demonstrate addressing anemia and minimizing or avoiding transfusion is associated with improved outcomes. The results of the study highlight the important role transfusion-free care and PBM have in improving outcomes for patients undergoing major surgery.