CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods

BACKGROUND

The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors.

RESULTS

Performance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical effects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less definitive and indicates performance potentially suitable for auxiliary use in the clinic.

CONCLUSIONS

Results show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly large, robust datasets for training and assessment promise further progress ahead.

Abstract P4-09-07: Characterization of Immune Contexture in HR+/HER2- and Triple Negative Breast Cancer in a Real-world Cohort

Background: Prior studies in breast cancer (BC) have demonstrated variability in the immune microenvironment of BCs across subtypes, with higher levels of immune infiltration observed in triple-negative (TN) BC. Clinical trials of immunotherapy in BC have largely targeted patients with TNBC, however many of these patients do not respond to treatment, suggesting heterogeneity across TN tumors. Further, immune infiltrated hormone receptor–positive, HER2-negative (HR+/HER2-) tumors have been observed. Patients with these tumors may benefit from immune checkpoint blockade (ICB). Identification of patients with immunogenic tumors would be valuable for future patient selection and stratification in clinical trials. In this study, we conducted comprehensive molecular profiling of a set of commercially procured BC samples to characterize the tumor microenvironment (TME) of HR+/HER2- and TN tumors and to identify patient or tumor features associated with immune infiltration. Methods: 163 surgically resected BC samples were used for this study (93 HR+/HER2-, 70 TN). Clinically validated immunohistochemistry (IHC) assays were used to evaluate the expression of two immune checkpoint (IC) molecules, PD-L1 (by VENTANA PD-L1 (SP142) Assay and Agilent PD-L1 IHC 28-8 pharmDx) and LAG3 (antibody clone 17B4). The presence of CD8+ cells was measured by IHC (Dako/Agilent clone C8/144B) and used to derive the spatial location and density (topology) of CD8+ cells within the TME. RNA sequencing (RNA-seq) was used to construct gene expression signatures representative of immune cell types. Furthermore, RNAseq data was used to identify expressed somatic mutations and to calculate the total expressed tumor mutational burden (‘eTMB’). Results: As previously reported, the prevalence of PD-L1 + tumors was higher in TN vs HR+/HER2− BC, however close to half (44.1% SP142 IC> 1%) of HR+/HER2- tumors showed some degree of PD-L1 expression. Similar patterns were observed for LAG3 IHC expression (32.3% and 64.7% of HR+ and TN tumors respectively with >1% expression). Concordant expression of the two markers (SP142 IC> 1% and LAG3 >=1% or < 1% and < 1%) was observed in approximately 80% of tumors in both subtypes. Less than 10% of tumors in both subtypes had high LAG3 (>1%) and low PD-L1(< 1%) expression. Most (82.4%) HR+/HER2- tumors in the dataset were deficient in CD8+ cells in both stroma and tumor parenchyma, however a subset (12.9%) were identified as having an ‘excluded’ CD8 pattern, and four (4.7%) were classified as ‘inflamed’. The frequency of both the excluded and inflamed states was slightly higher among the TN tumors (20.6% and 15.9% respectively). Expression of PD-L1+ occurred more frequently among tumors with higher CD8 expression. Among both TN and HR+ tumors, most ‘inflamed’ tumors were grade 3. We also examined a range of gene expression signatures representative of various immune cell subpopulations, their distribution within each subtype, and relationships with other molecular data. For example, expression of a CXCL13+ T cell signature, a cell type that has been shown to be predictive of response to anti-PD-L1 + chemo combo therapy in TNBC, was significantly higher in TN vs HR+ tumors, however, a large subset of HR+ tumors had levels of expression of the signature above the median observed in TN tumors. In addition, we noted that eTMB, while low overall, was positively correlated with certain immune-related expression signatures across HR+/HER2− samples, including signatures previously associated with improved response to ICB, as well as PD-L1 positivity. Conclusions: We observed heterogeneity in the immune profile of the real-world HR+ and TN tumors in this cohort. A subset of tumors in both subtypes expressed markers or signatures previously reported to be associated with response to ICB. (1) Cancer Cell. 2021 Dec 13;39(12):1578-1593.e8.

Citation Format: Aparna Chhibber, Lloye M. Dillon, John B. Wojcik, Vishantie Dostal, George Lee, Fayaz Seifuddin, Scott Ely, Mark D. Stern, Charlie Benson-Garnett, Mustimbo Roberts, Jenny Wu. Characterization of Immune Contexture in HR+/HER2- and Triple Negative Breast Cancer in a Real-world Cohort [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-09-07.

A fast and powerful linear mixed model approach for genotype-environment interaction tests in large-scale GWAS

Genotype-by-environment interaction (GEI or GxE) plays an important role in understanding complex human traits. However, it is usually challenging to detect GEI signals efficiently and accurately while adjusting for population stratification and sample relatedness in large-scale genome-wide association studies (GWAS). Here we propose a fast and powerful linear mixed model-based approach, fastGWA-GE, to test for GEI effect and G + GxE joint effect. Our extensive simulations show that fastGWA-GE outperforms other existing GEI test methods by controlling genomic inflation better, providing larger power and running hundreds to thousands of times faster. We performed a fastGWA-GE analysis of ~7.27 million variants on 452 249 individuals of European ancestry for 13 quantitative traits and five environment variables in the UK Biobank GWAS data and identified 96 significant signals (72 variants across 57 loci) with GEI test P-values < 1 × 10-9, including 27 novel GEI associations, which highlights the effectiveness of fastGWA-GE in GEI signal discovery in large-scale GWAS.

A statistical perspective on baseline adjustment in pharmacogenomic genome-wide association studies of quantitative change

In pharmacogenetic (PGx) studies, drug response phenotypes are often measured in the form of change in a quantitative trait before and after treatment. There is some debate in recent literature regarding baseline adjustment, or inclusion of pre-treatment or baseline value as a covariate, in PGx genome-wide association studies (GWAS) analysis. Here, we provide a clear statistical perspective on this baseline adjustment issue by running extensive simulations based on nine statistical models to evaluate the influence of baseline adjustment on type I error and power. We then apply these nine models to analyzing the change in low-density lipoprotein cholesterol (LDL-C) levels with ezetimibe + simvastatin combination therapy compared with simvastatin monotherapy therapy in the 5661 participants of the IMPROVE-IT (IMProved Reduction of Outcomes: Vytroin Efficacy International Trial) PGx GWAS, supporting the conclusions drawn from our simulations. Both simulations and GWAS analyses consistently show that baseline-unadjusted models inflate type I error for the variants associated with baseline value if the baseline value is also associated with change from baseline (e.g., when baseline value is a mediator between a variant and change from baseline), while baseline-adjusted models can control type I error in various scenarios. We thus recommend performing baseline-adjusted analyses in PGx GWASs of quantitative change.

Abstract PD6-05: Characterization of the immune landscape of primary vs metastatic breast cancer in a real-world data cohort

Breast cancer is considered to be a relatively immunologically “silent” tumor type. However, there is substantial heterogeneity in breast cancer, including differences in the immune microenvironment of tumors. For example, differences in the immune profile of primary and metastatic breast tumors have been observed. A deeper investigation of the immune profile of primary and metastatic breast tumors would enhance our understanding of late-stage breast cancer and provide insights that can guide the development of immunotherapies for primary or metastatic disease. In the current study, we explored differences in the immune microenvironment of primary and metastatic breast tumors in a clinico-genomic, real-world cohort (Tempus) of 420 subjects with breast cancer. Use of a real-world cohort for this study provided a diverse set of samples across subtypes, stages, and sites, and in particular a relatively large number of biopsies from metastatic sites as compared to other large breast cancer cohorts. Analyses were conducted using gene expression data generated by bulk RNA-sequencing of biopsies from lesions at primary (stage I-IV, N = 110) and metastatic (N = 310) sites, along with subject medical histories compiled from a variety of sources, including clinical records, pathology images, and lab reports. Differences in the immune microenvironment of assayed tumors were characterized by evaluating gene expression signatures representing immune-related processes as well as individual immune cell types, with emphasis on signatures known to be associated with response to checkpoint blockade, as well as differential expression analysis of individual genes. We observed higher expression of inflammation signatures in early stage and locally advanced primary tumors as compared to metastatic tumors (excluding lymph node biopsies), as well as enrichment of a number of immune cell types, including CD8+ T cells, regulatory T cells, B cells, and dendritic cells. We further examined individual metastatic sites (including lymph nodes, liver, brain, bone, and lung, among others), and noted variability in the immune contexture of metastatic tumors across sites. For example, we observed a trend to reduced inflammation and infiltration of certain cell types in brain and liver metastases as compared to primary tumors. Differential gene expression analysis of immune checkpoint molecules and other key immune-related genes was also conducted, revealing, for example, higher expression of IL-8 at certain metastatic sites; elevated IL-8 expression has been linked to reduced response to PD-1/PD-L1 agents and an immunosuppressive microenvironment. Finally, transcriptome-wide differential gene expression and gene set enrichment analyses were conducted using several gene-set and pathway databases (Gene Ontology, KEGG, Reactome, and Molecular Signatures Database hallmark collection). The results from these hypothesis-free analyses confirmed observations from the gene signature analyses described above; for example, inflammation-related pathways like the Hallmark “Interferon Gamma Response” and Gene Ontology “Regulation of Inflammatory Response” were enriched in primary tumors. Overall, the results of this study provide insights into the immune microenvironment of breast tumors and may be further used to inform the development of immune-oncology therapies in the space.

Citation Format: Aparna Chhibber, Kim Van Naarden Braun, Celine Han, Han Chang, Mustimbo Roberts, Bin Li. Characterization of the immune landscape of primary vs metastatic breast cancer in a real-world data cohort [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD6-05.

Germline HLA landscape does not predict efficacy of pembrolizumab monotherapy across solid tumor types

We evaluated the impact of class I and class II human leukocyte antigen (HLA) genotypes, heterozygosity, and diversity on the efficacy of pembrolizumab. Seventeen pembrolizumab clinical trials across eight tumor types and one basket trial in patients with advanced solid tumors were included (n > 3,500 analyzed). Germline DNA was genotyped using a custom genotyping array. HLA diversity (measured by heterozygosity and evolutionary divergence) across class I loci was not associated with improved response to pembrolizumab, either within each tumor type evaluated or across all patients. Similarly, HLA heterozygosity at each class I and class II gene was not associated with response to pembrolizumab after accounting for the number of tests conducted. No conclusive association between HLA genotype and response to pembrolizumab was identified in this dataset. Germline HLA genotype or diversity alone is not an important independent determinant of response to pembrolizumab and should not be used for clinical decision-making in patients treated with pembrolizumab.

Current challenges and opportunities for pharmacogenomics: perspective of the Industry Pharmacogenomics Working Group (I-PWG)

Pharmaceutical companies have increasingly utilized genomic data for the selection of drug targets and the development of precision medicine approaches. Most major pharmaceutical companies routinely collect DNA from clinical trial participants and conduct pharmacogenomic (PGx) studies. However, the implementation of PGx studies during clinical development presents a number of challenges. These challenges include adapting to a constantly changing global regulatory environment, challenges in study design and clinical implementation, and the increasing concerns over patient privacy. Advances in the field of genomics are also providing new opportunities for pharmaceutical companies, including the availability of large genomic databases linked to patient health information, the growing use of polygenic risk scores, and the direct sequencing of clinical trial participants. The Industry Pharmacogenomics Working Group (I-PWG) is an association of pharmaceutical companies actively working in the field of pharmacogenomics. This I-PWG perspective will provide an overview of the steps pharmaceutical companies are taking to address each of these challenges, and the approaches being taken to capitalize on emerging scientific opportunities.

A Microdose Cocktail to Evaluate Drug Interactions in Patients with Renal Impairment

Renal impairment (RI) is known to influence the pharmacokinetics of nonrenally eliminated drugs, although the mechanism and clinical impact is poorly understood. We assessed the impact of RI and single dose oral rifampin (RIF) on the pharmacokinetics of CYP3A, OATP1B, P-gp, and BCRP substrates using a microdose cocktail and OATP1B endogenous biomarkers. RI alone had no impact on midazolam (MDZ), maximum plasma concentration (C_max ), and area under the curve (AUC), but a progressive increase in AUC with RI severity for dabigatran (DABI), and up to ~2-fold higher AUC for pitavastatin (PTV), rosuvastatin (RSV), and atorvastatin (ATV) for all degrees of RI was observed. RIF did not impact MDZ, had a progressively smaller DABI drug-drug interaction (DDI) with increasing RI severity, a similar 3.1-fold to 4.4-fold increase in PTV and RSV AUC in healthy volunteers and patients with RI, and a diminishing DDI with RI severity from 6.1-fold to 4.7-fold for ATV. Endogenous biomarkers of OATP1B (bilirubin, coproporphyrin I/III, and sulfated bile salts) were generally not impacted by RI, and RIF effects on these biomarkers in RI were comparable or larger than those in healthy volunteers. The lack of a trend with RI severity of PTV and several OATP1B biomarkers, suggests that mechanisms beyond RI directly impacting OATP1B activity could also be considered. The DABI, RSV, and ATV data suggest an impact of RI on intestinal P-gp, and potentially BCRP activity. Therefore, DDI data from healthy volunteers may represent a worst-case scenario for clinically derisking P-gp and BCRP substrates in the setting of RI.

Multi-trait analysis of rare-variant association summary statistics using MTAR

Integrating association evidence across multiple traits can improve the power of gene discovery and reveal pleiotropy. Most multi-trait analysis methods focus on individual common variants in genome-wide association studies. Here, we introduce multi-trait analysis of rare-variant associations (MTAR), a framework for joint analysis of association summary statistics between multiple rare variants and different traits. MTAR achieves substantial power gain by leveraging the genome-wide genetic correlation measure to inform the degree of gene-level effect heterogeneity across traits. We apply MTAR to rare-variant summary statistics for three lipid traits in the Global Lipids Genetics Consortium. 99 genome-wide significant genes were identified in the single-trait-based tests, and MTAR increases this to 139. Among the 11 novel lipid-associated genes discovered by MTAR, 7 are replicated in an independent UK Biobank GWAS analysis. Our study demonstrates that MTAR is substantially more powerful than single-trait-based tests and highlights the value of MTAR for novel gene discovery.

ABCG2 regulatory single-nucleotide polymorphisms alter in vivo enhancer activity and expression

OBJECTIVES

The expression and activity of the breast cancer resistance protein (ABCG2) contributes toward the pharmacokinetics of endogenous and xenobiotic substrates. The effect of genetic variation on the activity of cis-regulatory elements and nuclear response elements in the ABCG2 locus and their contribution toward ABCG2 expression have not been investigated systematically. In this study, the effect of genetic variation on the in vitro and in vivo enhancer activity of six previously identified liver enhancers in the ABCG2 locus was examined.

METHODS

Reference and variant liver enhancers were tested for their ability to alter luciferase activity in vitro in HepG2 and HEK293T cell lines and in vivo using a hydrodynamic tail vein assay. Positive in vivo single-nucleotide polymorphisms (SNPs) were tested for association with gene expression and for altered protein binding in electrophoretic mobility shift assays.

RESULTS

Multiple SNPs were found to alter enhancer activity in vitro. Four of these variants (rs9999111, rs12508471, ABCG2RE1*2, and rs149713212) decreased and one (rs2725263) increased enhancer activity in vivo. In addition, rs9999111 and rs12508471 were associated with ABCG2 expression in lymphoblastoid cell lines, lymphocytes, and T cells, and showed increased HepG2 nuclear protein binding.

CONCLUSION

This study identifies SNPs within regulatory regions of the ABCG2 locus that alter enhancer activity in vitro and in vivo. Several of these SNPs correlate with tissue-specific ABCG2 expression and alter DNA/protein binding. These SNPs could contribute toward reported tissue-specific variability in ABCG2 expression and may influence the correlation between ABCG2 expression and disease risk or the pharmacokinetics and pharmacodynamics of breast cancer resistance protein substrates.

Lessons from the CAGI-4 Hopkins clinical panel challenge

The CAGI-4 Hopkins clinical panel challenge was an attempt to assess state-of-the-art methods for clinical phenotype prediction from DNA sequence. Participants were provided with exonic sequences of 83 genes for 106 patients from the Johns Hopkins DNA Diagnostic Laboratory. Five groups participated in the challenge, predicting both the probability that each patient had each of the 14 possible classes of disease, as well as one or more causal variants. In cases where the Hopkins laboratory reported a variant, at least one predictor correctly identified the disease class in 36 of the 43 patients (84%). Even in cases where the Hopkins laboratory did not find a variant, at least one predictor correctly identified the class in 39 of the 63 patients (62%). Each prediction group correctly diagnosed at least one patient that was not successfully diagnosed by any other group. We discuss the causal variant predictions by different groups and their implications for further development of methods to assess variants of unknown significance. Our results suggest that clinically relevant variants may be missed when physicians order small panels targeted on a specific phenotype. We also quantify the false-positive rate of DNA-guided analysis in the absence of prior phenotypic indication.

Abstract 1510: Subtype-specific cancer driver gene detection improves sensitivity to detect drivers

Identifying cancer driver mutations is a crucial step toward understanding the underlying mechanisms of oncogenesis. However, driver gene detection is complicated, considering the inherent complexity and heterogeneity of cancer.The past decade has seen the large-scale application of next-generation sequencing technologies (NGS) in cancer genomics, and many methods have been published utilizing NGS to detect novel oncogenic drivers. However, the low concordance across methods raises the concern about false positives and negatives in those findings. In particular, proper modeling of the background mutation profile (known to be affected by multiple factors) is critical to improving precision and recall in driver detection. Though intra-sample heterogeneity in the background mutation profile is considered to some extent in multiple methods, most computational driver detection methods assume a homogeneous mutational landscape across cancer samples. With more and more subtypes being discovered in various cancers, the assumption is largely untenable.

In this study, we present a driver gene detection framework taking into account the heterogeneous mutational context in a cancer cohort. Our approach improves sensitivity to detect drivers by first pre-selecting a more uniform sample subset to apply driver detection algorithms. We combine this method with enhancements to an existing ensemble approach that combines methods with different assumptions about the characteristics of driver mutations (recurrence across samples, functional impact bias and positional clustering). We apply this combined approach to ∼750 breast invasive carcinoma samples from The Cancer Genome Atlas. In this dataset, genes identified by our approach show higher enrichment in known cancer driver genes compared to other methods, and the subtype-driven method identifies additional potential drivers that are missing in overall analysis.

Citation Format: Yao Fu, Aparna Chhibber, Narges Bani-Asadi, Hugo YK Lam. Subtype-specific cancer driver gene detection improves sensitivity to detect drivers. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1510.

An ensemble approach to accurately detect somatic mutations using SomaticSeq

SomaticSeq is an accurate somatic mutation detection pipeline implementing a stochastic boosting algorithm to produce highly accurate somatic mutation calls for both single nucleotide variants and small insertions and deletions. The workflow currently incorporates five state-of-the-art somatic mutation callers, and extracts over 70 individual genomic and sequencing features for each candidate site. A training set is provided to an adaptively boosted decision tree learner to create a classifier for predicting mutation statuses. We validate our results with both synthetic and real data. We report that SomaticSeq is able to achieve better overall accuracy than any individual tool incorporated.

Genomic architecture of pharmacological efficacy and adverse events

The pharmacokinetic and pharmacodynamic disciplines address pharmacological traits, including efficacy and adverse events. Pharmacogenomics studies have identified pervasive genetic effects on treatment outcomes, resulting in the development of genetic biomarkers for optimization of drug therapy. Pharmacogenomics-based tests are already being applied in clinical decision making. However, despite substantial progress in identifying the genetic etiology of pharmacological response, current biomarker panels still largely rely on single gene tests with a large portion of the genetic effects remaining to be discovered. Future research must account for the combined effects of multiple genetic variants, incorporate pathway-based approaches, explore gene-gene interactions and nonprotein coding functional genetic variants, extend studies across ancestral populations, and prioritize laboratory characterization of molecular mechanisms. Because genetic factors can play a key role in drug response, accurate biomarker tests capturing the main genetic factors determining treatment outcomes have substantial potential for improving individual clinical care.

A genome-wide association study identifies novel loci for paclitaxel-induced sensory peripheral neuropathy in CALGB 40101

PURPOSE

Sensory peripheral neuropathy is a common and sometimes debilitating toxicity associated with paclitaxel therapy. This study aims to identify genetic risk factors for the development of this toxicity.

EXPERIMENTAL DESIGN

A prospective pharmacogenetic analysis of patients with primary breast cancer, randomized to the paclitaxel arm of CALGB 40101, was used to identify genetic predictors of the onset and severity of sensory peripheral neuropathy. A genome-wide association study in 855 subjects of European ancestry was conducted and findings were replicated in additional European (n = 154) and African American (n = 117) subjects.

RESULTS

A single nucleotide polymorphism in FGD4 was associated with the onset of sensory peripheral neuropathy in the discovery cohort [rs10771973; HR, 1.57; 95% confidence interval (CI), 1.30-1.91; P = 2.6 × 10(-6)] and in a European (HR, 1.72; 95% CI, 1.06-2.80; P = 0.013) and African American (HR, 1.93; 95% CI, 1.13-3.28; P = 6.7 × 10(-3)) replication cohort. There is also evidence that markers in additional genes, including EPHA5 (rs7349683) and FZD3 (rs10771973), were associated with the onset or severity of paclitaxel-induced sensory peripheral neuropathy.

CONCLUSIONS

A genome-wide association study has identified novel genetic markers of paclitaxel-induced sensory peripheral neuropathy, including a common polymorphism in FGD4, a congenital peripheral neuropathy gene. These findings suggest that genetic variation may contribute to variation in development of this toxicity. Validation of these findings may allow for the identification of patients at increased risk of peripheral neuropathy and inform the use of an alternative to paclitaxel and/or the clinical management of this toxicity.

Murine TMJ loading causes increased proliferation and chondrocyte maturation

The purpose of this study was to examine the effects of forced mouth opening on murine mandibular condylar head remodeling. We hypothesized that forced mouth opening would cause an anabolic response in the mandibular condylar cartilage. Six-week-old female C57BL/6 mice were divided into 3 groups: (1) control, (2) 0.25 N, and (3) 0.50 N of forced mouth opening. Gene expression, micro-CT, and proliferation were analyzed. 0.5 N of forced mouth opening caused a significant increase in mRNA expression of Pthrp, Sox9, and Collagen2a1, a significant increase in proliferation, and a significant increase in trabecular spacing in the subchondral bone, whereas 0.25 N of forced mouth opening did not cause any significant changes in any of the parameters examined. Forced mouth opening causes an increase in the expression of chondrocyte maturation markers and an increase in subchondral trabecular spacing.

Use of esmolol to control bleeding and heart rate during electroconvulsive therapy in a patient with an intracranial aneurysm

Electroconvulsive therapy (ECT) is a commonly used treatment modality for patients with major affective disorders that are unresponsive to pharmacological therapy. While ECT has been shown to be a very safe treatment, it is associated with transient hemodynamic alterations, including hypertension, which are associated with an increased risk of rupture of an intracranial aneurysm. We describe our use of the ultrashort acting beta-blocker, esmolol, for blood-pressure control in a woman with known cerebral aneurysmal disease who required ECT for treatment of recurrent major depression.

Primary fibrinolysis during supraceliac aortic clamping

PURPOSE

An increased incidence of bleeding complications has been observed after supraceliac aortic clamping (SCC). This study was performed to identify possible hemostatic abnormalities that contribute to this problem.

METHODS

A prospective cohort study over a 3-month period was performed by comparing hemostatic parameters in 10 consecutive patients who required elective SCC with those of eight concurrent randomly selected control subjects who required infrarenal clamping (IRC) for abdominal aortic reconstruction. Measures of coagulation, fibrinolysis, platelet function, temperature, hemodilution, and hepatic function were performed at selected times before, during, and after operation.

RESULTS

Aneurysm size, fibrinogen, D-dimers, prothrombin, partial thromboplastin time, platelet counts, bleeding times, hemodilution, and temperature were comparable in both groups. Patients in the SCC group, however, consistently developed a primary fibrinolytic state within 20 minutes after supraceliac clamping, reflected by significantly decreased euglobulin clot lysis times (ECLT; p < 0.0001), elevated tissue plasminogen activator (t-PA) levels (p < 0.0006), elevated t-PA-to-plasminogen activator inhibitor-1 ratios (p < 0.0001), and reduced alpha 2-antiplasmin levels (p < 0.002). SCC produced hepatocellular injury documented by elevations in both aspartate transaminase (p < 0.0001) and lactate dehydrogenase (p < 0.009).

CONCLUSIONS

SCC rapidly induces a primary fibrinolytic state manifested by increased circulating t-PA, reduced alpha 2-antiplasmin, and increased fibrinolytic activator-to-inhibitor ratios. These effects may be a result of hepatic hypoperfusion caused by SCC leading to insufficient clearance of t-PA. Antifibrinolytic agents may be of benefit if bleeding develops after aortic procedures that require supraceliac clamping.

An evaluation of preoperative anxiety in a population of parents of infants and children undergoing ambulatory surgery

We attempted to identify specific predictors of preoperative parental anxiety in a population of parents of healthy infants and children undergoing elective, outpatient surgery. We specifically examined the following factors: age of the child, whether or not the child had previous surgery, whether or not the parents' other children had previous surgery, parental gender, highest level of education obtained by the parent, and whether or not there was prior discussion between the parent and anaesthesiologist. In the immediate preoperative period, a questionnaire (State-Trait Anxiety Inventory) was given to all parents of infants and children presenting for elective, outpatient surgery. Six hundred parents of 417 children, aged two months to 16 years (mean = 4.5 years), participated in the study. They included 388 mothers and 212 fathers. Our results indicate that parents are more anxious when their child is less than one year of age and when it is the child's first surgery. When assessed separately by parental gender, both these factors were significant for mothers but not their fathers. We recommend that, although anaesthesiologists generally tailor their preoperative preparation based upon the best needs of their patients and families, they pay special attention to the groups we have identified which are at increased risk for preoperative anxiety.

The use of capnography for recognition of esophageal intubation in the neonatal intensive care unit

Failure to recognize esophageal intubation can result in severe hypoxia and permanent neurologic injury. Capnography is a standard monitoring modality in the operating room but has not been utilized fully in other environments. We used capnography at the time of endotracheal intubation in the neonatal intensive care unit (NICU) to determine whether capnography could more quickly and accurately identify endotracheal tube position than other clinical indicators of endotracheal tube position. One hundred intubation episodes were studied in 55 neonates. Capnograms were obtained 15 and 120 sec following tube placement. Intubating personnel were blinded to the capnographic data and determined endotracheal tube location (trachea vs. esophagus) by clinical criteria only. The sensitivity and specificity of capnography and clinical examination for identification of tube position were analyzed, and the time required for establishing by clinical confirmation whether the tube was in the trachea or not was compared to that required for capnography. Forty of 100 intubation attempts resulted in esophageal intubation. Capnography correctly identified these errant tube placements in 39 of 40 instances and did so in 1.6 sec (SD +/- 2.4). Capnography failed to identify successful endotracheal intubation on only one occasion. Clinical indicators of tube position required 97.1 sec (SD +/- 92.6) to identify an esophageal intubation and failed to identify successful endotracheal intubation in 5 of 60 cases. We conclude that capnography is a valuable adjunct to clinical examination to demonstrate whether an endotracheal tube is placed correctly in the trachea of neonates in the NICU.