Daily Anesthesiology Research Analysis
Three impactful studies span perioperative neurology and outcomes science. Prehospital point-of-care GFAP testing accurately distinguishes intracerebral hemorrhage from ischemic stroke within 6 hours, enabling earlier targeted care. Two large BJA analyses show that perioperative genetic risk profiling (APOE/AD polygenic scores) stratifies neurocognitive vulnerability, and a validated 5-level discharge status metric (measured at day 90) captures patient-centered recovery at scale.
Summary
Three impactful studies span perioperative neurology and outcomes science. Prehospital point-of-care GFAP testing accurately distinguishes intracerebral hemorrhage from ischemic stroke within 6 hours, enabling earlier targeted care. Two large BJA analyses show that perioperative genetic risk profiling (APOE/AD polygenic scores) stratifies neurocognitive vulnerability, and a validated 5-level discharge status metric (measured at day 90) captures patient-centered recovery at scale.
Research Themes
- Prehospital biomarker diagnostics for neurocritical triage
- Genetic risk stratification for perioperative neurocognitive disorders
- Patient-centered postoperative outcomes and recovery measurement
Selected Articles
1. Rapid Diagnosis of Intracerebral Hemorrhage in Patients With Acute Stroke by Measuring Prehospital GFAP Levels on a Point-of-Care Device (DETECT).
In a prospective diagnostic accuracy study of 353 suspected stroke patients sampled prehospital within 6 hours, plasma GFAP measured on a 15-minute point-of-care platform was markedly higher in ICH versus ischemic stroke or stroke mimics. This Class II evidence supports GFAP as a prehospital discriminator that could enable earlier triage, blood pressure control, and anticoagulation reversal pending validation of age-specific thresholds.
Impact: Demonstrates a feasible prehospital biomarker strategy to distinguish hemorrhagic from ischemic stroke, a time-critical decision with direct therapeutic consequences.
Clinical Implications: Emergency systems could integrate prehospital GFAP testing to route ICH patients to appropriate centers and initiate early blood pressure reduction and anticoagulation reversal. Protocols will need validated age-adjusted cutoffs and workflow integration.
Key Findings
- Prehospital plasma GFAP was substantially higher in ICH (median 208 pg/mL) than in ischemic stroke (30 pg/mL) or stroke mimics (48 pg/mL).
- Samples were collected within 6 hours of symptom onset and processed on a 15-minute point-of-care platform (i-STAT Alinity).
- Class II evidence supports GFAP’s diagnostic accuracy to distinguish ICH from IS/SM and suggests moderate-to-high positive predictive value.
- Findings motivate larger external validation with optimized eligibility and age-specific cutoffs to operationalize prehospital triage.
Methodological Strengths
- Prospective diagnostic accuracy design with prehospital sampling within a defined time window.
- Use of a rapid point-of-care platform with clear clinical pathways in view (triage, BP control, reversal).
Limitations
- Single-center study with modest sample sizes in the ICH and stroke mimic groups.
- Prehospital blood was analyzed in-hospital; true field deployment and age-specific thresholds require external validation.
Future Directions: Validate GFAP cutoffs across ages and comorbidities in multi-center EMS networks, evaluate combined biomarker panels, and test clinical impact on time-to-treatment and patient outcomes.
BACKGROUND AND OBJECTIVES: The rapid identification of intracerebral hemorrhage (ICH) in patients with symptoms of acute stroke is decisive for prehospital triage and initiation of targeted therapies. Glial fibrillary acidic protein (GFAP) is a highly promising blood-biomarker indicating ICH. In this study, we investigated the potential of a new GFAP test run on a point-of-care platform for distinguishing ICH from ischemic stroke (IS) and stroke mimics (SM) in the prehospital phase. METHODS: This prospective diagnostic accuracy study was conducted at the RKH Klinikum Ludwigsburg, a tertiary care hospital in Baden-Württemberg, Germany. Patients with symptoms of acute stroke admitted within 6 hours of symptom onset were enrolled. Blood samples were collected in the prehospital phase. Plasma GFAP measurements were performed on the i-STAT-Alinity device (duration: 15 minutes) in-hospital. The gold standard was the final diagnosis categorized ICH, IS, or SM. RESULTS: A total of 353 patients were enrolled (mean age 74.6 ± 13.4 years; 46.7% female). GFAP concentrations were elevated in patients with ICH (n = 76; median 208 pg/mL [interquartile range 60-5,907]) compared with IS (n = 258; 30 pg/mL [29-51]) and SM (n = 19; 48 pg/mL [29-97]; DISCUSSION: Laboratory GFAP measurements on a point-of-care platform in blood samples collected from patients with symptoms of acute stroke in the prehospital phase can help to identify ICH with moderate to high PPV. Following confirmation in larger independent cohorts using optimized eligibility criteria and validated age-specific cutoff values, GFAP testing could facilitate optimized triage and the initiation of blood pressure-lowering therapy and anticoagulation reversal in earlier time frames. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that elevated plasma GFAP levels within 6 hours of symptom onset accurately distinguish patients with ICH from IS and SM.
2. Perioperative polygenic and APOE-based genetic risk assessment for neurocognitive disorders: a biobank study.
In over 33,000 surgical patients, APOE ε4 carriers had higher odds of delirium, mild cognitive impairment, and Alzheimer’s disease, and an AD polygenic risk score independently predicted AD risk in European ancestry patients. These findings position genetic risk profiling as a complementary tool to enhance preoperative neurocognitive risk assessment.
Impact: Bridges genomics and perioperative medicine at scale, providing evidence that common genetic markers identify patients at risk for perioperative neurocognitive disorders.
Clinical Implications: Preoperative evaluation could incorporate APOE and AD polygenic risk to flag patients for enhanced delirium prevention, cognitive monitoring, and tailored anesthetic/surgical strategies. Implementation requires ethical counseling, ancestry-aware interpretation, and integration with clinical risk factors.
Key Findings
- Among 33,526 surgical patients, 25% carried at least one APOE ε4 allele; ε4 status was associated with delirium (OR 1.32), MCI (OR 1.70), and AD (OR 3.42).
- An AD polygenic risk score was associated with Alzheimer’s disease in patients of European ancestry (OR 2.25; FDR < 0.001).
- Findings support the feasibility of perioperative genetic risk profiling to augment neurocognitive risk stratification.
Methodological Strengths
- Very large biobank cohort with standardized genotyping and EHR-linked outcomes.
- Multivariable logistic modeling with FDR control across multiple neurocognitive endpoints.
Limitations
- Observational design limits causal inference; potential misclassification of outcomes.
- Generalizability may be constrained by ancestry composition (predominantly European ancestry).
Future Directions: Prospective perioperative trials testing genetics-informed delirium prevention bundles and evaluating cost-effectiveness, equity, and consent models across ancestries.
BACKGROUND: Preoperative risk assessment is a critical step in developing targeted preventive and therapeutic strategies. Although genetic biomarkers have shown considerable promise in assessing and stratifying dementia risk, their application in the perioperative period remains unexplored. Given the recognised effects of surgery and anaesthesia on perioperative cognitive trajectories, this study aimed to evaluate the preoperative neurocognitive genetic risk profiles of a surgical population and their influence on postoperative outcomes. METHODS: Data from the Mass General Brigham Biobank were analysed for male and female surgical patients aged 40-89 yr without a previous diagnosis of Alzheimer's disease. The polygenic risk score for Alzheimer's disease was calculated, and apolipoprotein E (APOE) genotypes were inferred from the study participants. Logistic regression was used to examine the associations between APOE genotype and the polygenic risk score for Alzheimer's disease with neurocognitive disorders. RESULTS: The surgical population comprised 33 526 patients, of whom 86% had European ancestry and 25% carried at least one APOE-ε4 allele. Among patients of European ancestry, the polygenic risk score for Alzheimer's disease was associated with higher risk of Alzheimer's disease (odds ratio [OR], 2.25 [95% confidence interval, 1.64-3.09]; false discovery rate [FDR] <0.001). Patients carrying APOE-ε4 alleles had an increased risk of neurocognitive disorders (e.g. delirium: OR, 1.32 [1.19-1.47], FDR <0.001; mild cognitive impairment: OR, 1.70 [1.49-1.94], FDR <0.001; and Alzheimer's disease: OR, 3.42 [2.72-4.29], FDR <0.001). CONCLUSIONS: APOE genotypes and polygenic risk scores are valuable for exploring neurocognitive genetic risk profiles in surgical populations and have the potential to enhance preoperative risk assessment strategies.
3. Description and validation of the Postoperative Discharge Recovery State outcome: a patient-partnered population-based cohort study.
A patient-partnered, population-scale study defined and validated a 5-level Postoperative Discharge Recovery State, measured at key time points (notably day 90), with evidence of construct, convergent, and predictive validity in 84,422 older adults. Although an ordinal prediction model underperformed, the outcome itself offers a patient-centered alternative to binary discharge metrics.
Impact: Establishes a scalable, patient-centered ordinal outcome that captures recovery location over time, enabling more nuanced perioperative research and quality improvement.
Clinical Implications: Health systems and perioperative programs can adopt a day-90 discharge recovery state to benchmark recovery beyond mortality and length of stay, aligning metrics with what matters to older adults (returning home).
Key Findings
- Defined a 5-level Postoperative Discharge Recovery State (dead, hospitalized, long-term care, rehabilitation, home) and validated it at postoperative day 90.
- In 84,422 older adults, 93.9% were at home at day 90; validity (construct, convergent with DAH, predictive) and reliability were demonstrated.
- A prespecified ordinal regression model had limited accuracy (c-statistic 0.700; poor calibration), indicating prediction tools require further development.
Methodological Strengths
- Very large, linked administrative dataset with patient partnership guiding outcome selection and timing.
- Comprehensive validity assessment (construct, convergent, predictive) and internal-external validation attempts.
Limitations
- Retrospective use of administrative data may introduce misclassification bias and residual confounding.
- The prespecified prediction model’s calibration/performance was insufficient for clinical deployment.
Future Directions: Refine prediction models, assess responsiveness over multiple postoperative time points, and test implementation for benchmarking and value-based care.
BACKGROUND: Older adults prioritise independent return home after surgery. Most discharge outcomes are binary composites that do not incorporate temporal information. We defined and validated a novel ordinal outcome, the Postoperative Discharge Recovery State, and prioritised its temporal measurement, to overcome these limitations. METHODS: This retrospective cohort study was conducted with patient partnership. Adults ≥65 yr having major, elective, noncardiac, non-orthopaedic surgery were identified from 2012 to 2022 using linked, routinely collected data in Ontario, Canada. Construct, convergent, and predictive validity were estimated. A multivariable ordinal regression model was derived and internally-externally validated. RESULTS: We included 84 422 older adult surgical patients. At the patient-prioritised postoperative day 90, the distribution of patients across Postoperative Discharge Recovery State categories was: (1) dead (2718; 3.2%); (2) hospitalised (1696; 2.0%); (3) in long-term care (179; 0.2%); (4) in rehabilitation (593; 0.7%); and (5) at home (79 236; 93.9%). Directionally expected associations with baseline characteristics supported construct validity. Consistency in associations over time supported reliability. Relationships with days alive and at home supported convergent (ρ=0.373) and predictive (fewer days at home with worse recovery state) validity. A prespecified ordinal logistic regression model had inadequate accuracy (c-statistic 0.700, poor calibration) to support its clinical use. CONCLUSIONS: The Postoperative Discharge Recovery State is a 5-level ordinal outcome that can be applied at key time points after surgery to quantify the proportion of patients in patient-prioritised discharge locations. Validity and reliability support utility, but further development will be required to maximise information gain relative to binary outcomes.