An open source knowledge graph ecosystem for the life sciences.

Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, and methods exist to construct them automatically. However, tackling complex biomedical integration problems requires flexibility in the way knowledge is modeled. Moreover, existing KG construction methods provide robust tooling at the cost of fixed or limited choices among knowledge representation models. PheKnowLator (Phenotype Knowledge Translator) is a semantic ecosystem for automating the FAIR (Findable, Accessible, Interoperable, and Reusable) construction of ontologically grounded KGs with fully customizable knowledge representation. The ecosystem includes KG construction resources (e.g., data preparation APIs), analysis tools (e.g., SPARQL endpoint resources and abstraction algorithms), and benchmarks (e.g., prebuilt KGs). We evaluated the ecosystem by systematically comparing it to existing open-source KG construction methods and by analyzing its computational performance when used to construct 12 different large-scale KGs. With flexible knowledge representation, PheKnowLator enables fully customizable KGs without compromising performance or usability.

Ontologizing health systems data at scale: making translational discovery a reality.

Common data models solve many challenges of standardizing electronic health record (EHR) data but are unable to semantically integrate all of the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide computable representations of biological knowledge and enable the integration of heterogeneous data. However, mapping EHR data to OBO ontologies requires significant manual curation and domain expertise. We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Using OMOP2OBO, we produced mappings for 92,367 conditions, 8611 drug ingredients, and 10,673 measurement results, which covered 68-99% of concepts used in clinical practice when examined across 24 hospitals. When used to phenotype rare disease patients, the mappings helped systematically identify undiagnosed patients who might benefit from genetic testing. By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping.

Reproducible variability: assessing investigator discordance across 9 research teams attempting to reproduce the same observational study.

OBJECTIVE: Observational studies can impact patient care but must be robust and reproducible. Nonreproducibility is primarily caused by unclear reporting of design choices and analytic procedures. This study aimed to: (1) assess how the study logic described in an observational study could be interpreted by independent researchers and (2) quantify the impact of interpretations' variability on patient characteristics. MATERIALS AND METHODS: Nine teams of highly qualified researchers reproduced a cohort from a study by Albogami et al. The teams were provided the clinical codes and access to the tools to create cohort definitions such that the only variable part was their logic choices. We executed teams' cohort definitions against the database and compared the number of subjects, patient overlap, and patient characteristics. RESULTS: On average, the teams' interpretations fully aligned with the master implementation in 4 out of 10 inclusion criteria with at least 4 deviations per team. Cohorts' size varied from one-third of the master cohort size to 10 times the cohort size (2159-63 619 subjects compared to 6196 subjects). Median agreement was 9.4% (interquartile range 15.3-16.2%). The teams' cohorts significantly differed from the master implementation by at least 2 baseline characteristics, and most of the teams differed by at least 5. CONCLUSIONS: Independent research teams attempting to reproduce the study based on its free-text description alone produce different implementations that vary in the population size and composition. Sharing analytical code supported by a common data model and open-source tools allows reproducing a study unambiguously thereby preserving initial design choices.

Knowledge-Driven Mechanistic Enrichment of the Preeclampsia Ignorome.

Preeclampsia is a leading cause of maternal and fetal morbidity and mortality. Currently, the only definitive treatment of preeclampsia is delivery of the placenta, which is central to the pathogenesis of the disease. Transcriptional profiling of human placenta from pregnancies complicated by preeclampsia has been extensively performed to identify differentially expressed genes (DEGs). The decisions to investigate DEGs experimentally are biased by many factors, causing many DEGs to remain uninvestigated. A set of DEGs which are associated with a disease experimentally, but which have no known association to the disease in the literature are known as the ignorome. Preeclampsia has an extensive body of scientific literature, a large pool of DEG data, and only one definitive treatment. Tools facilitating knowledge-based analyses, which are capable of combining disparate data from many sources in order to suggest underlying mechanisms of action, may be a valuable resource to support discovery and improve our understanding of this disease. In this work we demonstrate how a biomedical knowledge graph (KG) can be used to identify novel preeclampsia molecular mechanisms. Existing open source biomedical resources and publicly available high-throughput transcriptional profiling data were used to identify and annotate the function of currently uninvestigated preeclampsia-associated DEGs. Experimentally investigated genes associated with preeclampsia were identified from PubMed abstracts using text-mining methodologies. The relative complement of the text-mined- and meta-analysis-derived lists were identified as the uninvestigated preeclampsia-associated DEGs (n=445), i.e., the preeclampsia ignorome. Using the KG to investigate relevant DEGs revealed 53 novel clinically relevant and biologically actionable mechanistic associations.

Ketamine Mitigates Neurobehavioral Deficits in a Canine Model of Hypothermic Circulatory Arrest.

Hypothermic circulatory arrest is a protective technique used when complete cessation of circulation is required during cardiac surgery. Prior efforts to decrease neurologic injury with the NMDA receptor antagonist MK801 were limited by unacceptable side effects. We hypothesized that ketamine would provide neuroprotection without dose-limiting side effects. Canines were peripherally cannulated for cardiopulmonary bypass, cooled to 18°C, and underwent 90 minutes of circulatory arrest. Ketamine-treated canines (n = 5; total dose 2.85 mg/kg) were compared to untreated controls (n = 10). A validated neurobehavioral deficit score was obtained at 24, 48, and 72 hours (0 = no deficits/normal exam; higher score represents increasing deficits). Biomarkers of neuronal injury in the cerebrospinal fluid were examined at baseline and at 8, 24, 48, and 72 hours. Brain histopathologic injury was scored at 72 hours (higher score indicates more necrosis and apoptosis). Ketamine-treated canines had significantly improved, lower neurobehavioral deficit scores compared to controls (overall P = 0.003; 24 hours: median 72 vs 112, P = 0.030; 48 hours: 47 vs 90, P = 0.021; 72 hours: 30 vs 89, P = 0.069). Although the histopathologic injury scores of ketamine-treated canines (median 12) were lower than controls (16), there was no statistical difference (P = 0.10). Levels of phosphorylated neurofilament-H and neuron specific enolase, markers of neuronal injury, were significantly lower in ketamine-treated animals (P = 0.010 and = 0.039, respectively). Ketamine significantly reduced neurologic deficits and biomarkers of injury in canines after hypothermic circulatory arrest. Ketamine represents a safe and approved medication that may be useful as a pharmacologic neuroprotectant during cardiac surgery with circulatory arrest.

Concept recognition as a machine translation problem.

BACKGROUND: Automated assignment of specific ontology concepts to mentions in text is a critical task in biomedical natural language processing, and the subject of many open shared tasks. Although the current state of the art involves the use of neural network language models as a post-processing step, the very large number of ontology classes to be recognized and the limited amount of gold-standard training data has impeded the creation of end-to-end systems based entirely on machine learning. Recently, Hailu et al. recast the concept recognition problem as a type of machine translation and demonstrated that sequence-to-sequence machine learning models have the potential to outperform multi-class classification approaches. METHODS: We systematically characterize the factors that contribute to the accuracy and efficiency of several approaches to sequence-to-sequence machine learning through extensive studies of alternative methods and hyperparameter selections. We not only identify the best-performing systems and parameters across a wide variety of ontologies but also provide insights into the widely varying resource requirements and hyperparameter robustness of alternative approaches. Analysis of the strengths and weaknesses of such systems suggest promising avenues for future improvements as well as design choices that can increase computational efficiency with small costs in performance. RESULTS: Bidirectional encoder representations from transformers for biomedical text mining (BioBERT) for span detection along with the open-source toolkit for neural machine translation (OpenNMT) for concept normalization achieve state-of-the-art performance for most ontologies annotated in the CRAFT Corpus. This approach uses substantially fewer computational resources, including hardware, memory, and time than several alternative approaches. CONCLUSIONS: Machine translation is a promising avenue for fully machine-learning-based concept recognition that achieves state-of-the-art results on the CRAFT Corpus, evaluated via a direct comparison to previous results from the 2019 CRAFT shared task. Experiments illuminating the reasons for the surprisingly good performance of sequence-to-sequence methods targeting ontology identifiers suggest that further progress may be possible by mapping to alternative target concept representations. All code and models can be found at: https://github.com/UCDenver-ccp/Concept-Recognition-as-Translation .

Inflammatory profile in a canine model of hypothermic circulatory arrest.

BACKGROUND: Hypothermic circulatory arrest (HCA) is a technique used for complex repair of the aorta, but it can be associated with neurologic morbidity. To better understand the molecular changes that underlie ischemic brain injury, we assessed gene expression and cytokine/chemokine polypeptide concentration in brain tissue and cerebrospinal fluid (CSF) of canines that underwent two hours of HCA. MATERIALS AND METHODS: Adult male canines were cannulated peripherally for cardiopulmonary bypass, cooled to 18°C, and arrested for two hours. Animals were euthanized two, eight, or 24 hours post-HCA (n = 8 per group), and their brains were compared to brains from eight normal canines, using gene expression microarray analysis, cytokine assay, and histopathology. RESULTS: Two to eight hours after HCA, pro-inflammatory cytokine mRNAs increased markedly, and gene expression was enriched within signaling pathways related to neuroinflammation or ischemic injury. Concentrations of pro-inflammatory cytokine polypeptides IL-6, IL-8, IL-1ß, and CCL2 were very low in normal canine brain, whereas anti-inflammatory IL-10 and TGF-ß1 were expressed at moderate levels. Pro-inflammatory cytokine concentrations rose robustly in cerebral tissue and CSF after HCA. IL-6 and IL-8 peaked at eight hours and declined at 24 hours, while IL-1ß and CCL2 remained elevated. Concentrations of anti-inflammatory IL-10 and TGF-ß1 were maintained after HCA, with a significant increase in TGF-ß1 at 24 hours. CONCLUSIONS: These cytokines represent potential diagnostic markers for ischemic neurologic injury that could be used to assess neurologic injury in patients undergoing HCA. The cellular mechanisms underlying this pro-inflammatory, ischemic-induced injury represent potential targets for neuroprotection in the future.

Impact of the New Pulmonary Hypertension Definition on Heart Transplant Outcomes: Expanding the Hemodynamic Risk Profile.

BACKGROUND: At the recent 6th World Symposium on Pulmonary Hypertension (PH), the definition of PH was redefined to include lower pulmonary artery pressures in the setting of elevated pulmonary vascular resistance (PVR). However, the relevance of this change to subjects with PH due to left-heart disease as well as the preoperative assessment of heart transplant (HT) recipients is unknown. METHODS: The United Network for Organ Sharing database was queried to identify adult recipients who underwent primary HT from 1996 to 2015. Recipients were subdivided into those with mean pulmonary artery pressure (mPAP) < 25 mm Hg and ≥ 25 mm Hg. Exploratory univariable analysis was undertaken to identify candidate risk factors associated with 30-day and 1-year survival (conditional on 30-day survival) in recipients with mPAP < 25 mm Hg, and subsequently, parsimonious multivariable Cox proportional hazards models were constructed to assess the independent association with PVR. RESULTS: Over the study period, 32,465 patients underwent HT, including 12,257 (38%) with mPAP < 25 mm Hg. The median age was 55 years (interquartile range, 47-62) and the median PVR was 1.5 Wood units (WU) (interquartile range, 1-2.2) in recipients with mPAP < 25 mm Hg. After controlling for confounders, PVR was independently associated with increased risk for 30-day mortality (hazard ratio, 1.16; 95% CI, 1.05-1.27; P < .01), but not conditional 1-year mortality (hazard ratio, 1.03; 95% CI, 0.94-1.12; P = .55). PVR ≥ 3 WU was associated with an absolute 1.9% increase in 30-day mortality in those with mPAP < 25 mm Hg, a similar risk to recipients with PVR ≥ 3 WU and mPAP ≥ 25 mm Hg. CONCLUSIONS: Elevated PVR remains associated with a significant increase in the hazard for 30-day mortality after cardiac transplantation, even in the setting of lower pulmonary artery pressures. These data support the validity of the new definition of pulmonary hypertension.

American Board of Thoracic Surgery 10-Year Maintenance of Certification Exam Improves and Validates Knowledge Acquisition.

BACKGROUND: Previous "high-stakes" examinations by the American Board of Thoracic Surgery (ABTS) required remote testing, were noneducational, and were not tailored to individual practices. Given the ABTS mission of public safety and diplomate education, the ABTS Maintenance of Certification (MOC) examination was revised in 2015 to improve the educational experience and validate knowledge acquired. METHODS: The ABTS-MOC Committee developed a web-based, secure examination tailored to the specialty-specific practice profile (cardiac, general thoracic, cardiothoracic, congenital) of the individual surgeon. After an initial answer to each question, an educational critique was reviewed before returning to the initial question and logging a second (final) response. Intraexam learning was assessed by comparing scores before and after reading the critique. Diplomate feedback was obtained. RESULTS: A total of 988 diplomates completed the 10-year MOC examination between 2015 and 2017. Substantive learning was demonstrated with an 18%, 17%, 20%, and 9% improvement in cardiac, general thoracic, cardiothoracic, and congenital final scores, respectively. This improvement was most notable among diplomates with the lowest initial scores. Fewer diplomates failed the new exam (<1% vs 2.3%). Diplomate postexam survey highlighted marked improvements in clinical relevance (35% vs 78%), convenience (37% vs 78%), and learning (15% vs 45%). Over 80% acknowledged educational value, and 97% preferred the new format. CONCLUSIONS: The new MOC process demonstrates increased knowledge acquisition through a convenient, secure, web-based practice-focused examination. This approach provides feedback, identifies baseline knowledge gaps for individual diplomates, and validates new knowledge attained.

Comparing Frailty Markers in Predicting Poor Outcomes after Transcatheter Aortic Valve Replacement.

INTRODUCTION: Frailty is an important component of risk prognostication in transcatheter aortic valve replacement (TAVR). Objective markers of frailty, including sarcopenia, the modified Frailty Index (mFI), and albumin levels, have emerged, but little is known how such markers compare to each other in predicting outcomes after TAVR. We sought to define and compare these markers in predicting long-term outcomes after TAVR. METHODS: Patients who underwent TAVR at our institution from 2011 to 2016 were included. Indexed cross-sectional areas of the lumbosacral muscles on preoperative computed tomography scans were used to assess sarcopenia. Optimal cutoffs for sarcopenia were defined using a statistically validated method. mFI was calculated using an 11-point scale of clinical characteristics. The primary outcome was 2-year all-cause mortality. Adjusted survival analysis was used to analyze outcomes. RESULTS: A total of 381 patients were included in this study. Sarcopenia of the psoas muscles was associated with an increased risk of mortality on univariate (HR: 2.3, P = 0.01) and multivariate (HR: 2.5, P = 0.01) analysis. Sarcopenia of the paravertebral muscles was associated with increased risk of mortality only on univariate analysis (HR: 2.1, P = 0.03). Increased preoperative albumin levels were associated with decreased risk of mortality on univariate (HR: 0.3, P < 0.01) and multivariate analysis (HR: 0.3, P < 0.01). The (mFI) was not associated with mortality on univariate or multivariate analysis. DISCUSSION: Novel cutoffs for sarcopenia of the psoas muscles were determined and associated with decreased survival after TAVR. Sarcopenia and albumin levels may be better tools for risk prediction than mFI in TAVR.

Correlating Oxygen Delivery During Cardiopulmonary Bypass With the Neurologic Injury Biomarker Ubiquitin C-Terminal Hydrolase L1 (UCH-L1).

OBJECTIVE: The authors sought to assess the relationship between low oxygen delivery (DO2) during cardiopulmonary bypass (CPB) and a neuron-specific biomarker of neurologic injury, ubiquitin C-terminal hydrolase L1 (UCH-L1). DESIGN: Retrospective analysis of patient charts and prospectively collected blood samples. SETTING: University-affiliated tertiary care hospital. PARTICIPANTS: Adult patients undergoing cardiac surgery on CPB. INTERVENTIONS: Serum UCH-L1 levels were drawn at baseline and 6 and 24 hours after CPB cessation. DO2 was computed from perfusion records, with area-under-the-curve (AUC) computations performed to account for distance of DO2 excursions below predefined DO2 thresholds and the amount of time spent below them. Strokes were defined radiographically using computed tomography and magnetic resonance imaging. MEASUREMENTS AND MAIN RESULTS: Forty-three adults were included (median age 65 y, interquartile range 59-72). Three patients experienced strokes (imaged at 2, 7, and 8 d postoperatively). Most patients underwent isolated coronary artery bypass grafting (41%, 18 patients) or isolated aortic valve replacement (30%, 13). Median UCH-L1 levels differed from baseline to 6 and 24 hours after CPB (40, 232, and 166 pg/mL, respectively; p < 0.001). On multivariable linear regression analysis controlling for baseline and surgical variables, only DO2 AUC <225 was significantly associated with 6-hour UCH-L1 levels (p = 0.001), whereas only DO2 AUC <300 was significantly associated with 24- hour levels (p < 0.001). The 3 patients who experienced radiographic strokes had nonsignificantly elevated 24-hour UCH-L1 levels compared with control patients (585 v 151 pg/mL, p = 0.11). CONCLUSIONS: This is the first study to demonstrate an independent association between DO2 during CPB and elevations of a brain injury biomarker; additional study is needed to clarify the clinical significance of these results.

Strategic Review Process for an Accountable Care Organization and Emerging Accountable Care Best Practices.

Accountable Care Organizations (ACOs), like other care entities, must be strategic about which initiatives they support in the quest for higher value. This article reviews the current strategic planning process for the Johns Hopkins Medicine Alliance for Patients (JMAP), a Medicare Shared Savings Program Track 1 ACO. It reviews the 3 focus areas for the 2017 strategic review process - (1) optimizing care coordination for complex, at-risk patients, (2) post-acute care, and (3) specialty care integration - reviewing cost savings and quality improvement opportunities, associated best practices from the literature, and opportunities to leverage and advance existing ACO and health system efforts in each area. It then reviews the ultimate selection of priorities for the coming year and early thoughts on implementation. After the robust review process, key stakeholders voted to select interventions targeted at care coordination, post-acute care, and specialty integration including Part B drug and imaging costs. The interventions selected incorporate a mixture of enhancing current ACO initiatives, working collaboratively and synergistically on other health system initiatives, and taking on new projects deemed targeted, cost-effective, and manageable in scope. The annual strategic review has been an essential and iterative process based on performance data and informed by the collective experience of other organizations. The process allows for an evidence-based strategic plan for the ACO in pursuit of the best care for patients.

Sympathectomy for Stabilization of Heart Failure Due to Drug-Refractory Ventricular Tachycardia.

We describe the novel use of bilateral cardiac sympathectomy in a woman with end-stage heart failure caused by ventricular tachycardia refractory to standard medical therapy who was under consideration for heart transplantation. Postoperatively, our patient has not experienced any symptoms of ventricular tachycardia, has returned to normal physical activity, and is no longer under consideration for transplantation as a result of the improvement in her cardiac function. Bilateral sympathectomy can be more effective than unilateral sympathectomy or percutaneous stellate ganglion blockade in patients with refractory ventricular tachycardia. Careful patient selection is necessary to identify patients who will benefit most from the procedure.

A Novel Risk Score to Predict New Onset Atrial Fibrillation in Patients Undergoing Isolated Coronary Artery Bypass Grafting.

BACKGROUND: Atrial fibrillation (AF) is common after cardiac surgery and contributes to increased morbidity and mortality. Our objective was to derive and validate a predictive model for AF after CABG in patients, incorporating novel echocardiographic and laboratory values. METHODS: We retrospectively reviewed patients at our institution without preexisting dysrhythmia who underwent on-pump, isolated CABG from 2011-2015. The primary outcome was new onset AF lasting >1 hour on continuous telemetry or requiring medical treatment. Patients with a preoperative echocardiographic measurement of left atrial diameter were included in a risk model, and were randomly divided into derivation (80%) and validation (20%) cohorts. The predictors of AF after CABG (PAFAC) score was derived from a multivariable logistic regression model by multiplying the adjusted odds ratios of significant risk factors (P < .05) by a factor of 4 to derive an integer point system. RESULTS: 1307 patients underwent isolated CABG, including 762/1307 patients with a preoperative left atrial diameter measurement. 209/762 patients (27%) developed new onset AF including 165/611 (27%) in the derivation cohort. We identified four risk factors independently associated with postoperative AF which comprised the PAFAC score: age > 60 years (5 points), White race (5 points), baseline GFR < 90 mL/min (4 points) and left atrial diameter > 4.5 cm (4 points). Scores ranged from 0-18. The PAFAC score was then applied to the validation cohort and predicted incidence of AF strongly correlated with observed incidence (r = 0.92). CONCLUSION: The PAFAC score is easy to calculate and can be used upon ICU admission to reliably identify patients at high risk of developing AF after isolated CABG.

OWL-NETS: Transforming OWL Representations for Improved Network Inference.

Our knowledge of the biological mechanisms underlying complex human disease is largely incomplete. While Semantic Web technologies, such as the Web Ontology Language (OWL), provide powerful techniques for representing existing knowledge, well-established OWL reasoners are unable to account for missing or uncertain knowledge. The application of inductive inference methods, like machine learning and network inference are vital for extending our current knowledge. Therefore, robust methods which facilitate inductive inference on rich OWL-encoded knowledge are needed. Here, we propose OWL-NETS (NEtwork Transformation for Statistical learning), a novel computational method that reversibly abstracts OWL-encoded biomedical knowledge into a network representation tailored for network inference. Using several examples built with the Open Biomedical Ontologies, we show that OWL-NETS can leverage existing ontology-based knowledge representations and network inference methods to generate novel, biologically-relevant hypotheses. Further, the lossless transformation of OWL-NETS allows for seamless integration of inferred edges back into the original knowledge base, extending its coverage and completeness.

Improving precision in concept normalization.

Most natural language processing applications exhibit a trade-off between precision and recall. In some use cases for natural language processing, there are reasons to prefer to tilt that trade-off toward high precision. Relying on the Zipfian distribution of false positive results, we describe a strategy for increasing precision, using a variety of both pre-processing and post-processing methods. They draw on both knowledge-based and frequentist approaches to modeling language. Based on an existing high-performance biomedical concept recognition pipeline and a previously published manually annotated corpus, we apply this hybrid rationalist/empiricist strategy to concept normalization for eight different ontologies. Which approaches did and did not improve precision varied widely between the ontologies.

Coreference annotation and resolution in the Colorado Richly Annotated Full Text (CRAFT) corpus of biomedical journal articles.

BACKGROUND: Coreference resolution is the task of finding strings in text that have the same referent as other strings. Failures of coreference resolution are a common cause of false negatives in information extraction from the scientific literature. In order to better understand the nature of the phenomenon of coreference in biomedical publications and to increase performance on the task, we annotated the Colorado Richly Annotated Full Text (CRAFT) corpus with coreference relations. RESULTS: The corpus was manually annotated with coreference relations, including identity and appositives for all coreferring base noun phrases. The OntoNotes annotation guidelines, with minor adaptations, were used. Interannotator agreement ranges from 0.480 (entity-based CEAF) to 0.858 (Class-B3), depending on the metric that is used to assess it. The resulting corpus adds nearly 30,000 annotations to the previous release of the CRAFT corpus. Differences from related projects include a much broader definition of markables, connection to extensive annotation of several domain-relevant semantic classes, and connection to complete syntactic annotation. Tool performance was benchmarked on the data. A publicly available out-of-the-box, general-domain coreference resolution system achieved an F-measure of 0.14 (B3), while a simple domain-adapted rule-based system achieved an F-measure of 0.42. An ensemble of the two reached F of 0.46. Following the IDENTITY chains in the data would add 106,263 additional named entities in the full 97-paper corpus, for an increase of 76% percent in the semantic classes of the eight ontologies that have been annotated in earlier versions of the CRAFT corpus. CONCLUSIONS: The project produced a large data set for further investigation of coreference and coreference resolution in the scientific literature. The work raised issues in the phenomenon of reference in this domain and genre, and the paper proposes that many mentions that would be considered generic in the general domain are not generic in the biomedical domain due to their referents to specific classes in domain-specific ontologies. The comparison of the performance of a publicly available and well-understood coreference resolution system with a domain-adapted system produced results that are consistent with the notion that the requirements for successful coreference resolution in this genre are quite different from those of the general domain, and also suggest that the baseline performance difference is quite large.

Perioperative Low Arterial Oxygenation Is Associated With Increased Stroke Risk in Cardiac Surgery.

BACKGROUND: Both patient characteristics and intraoperative factors have been associated with a higher risk of stroke after cardiac surgery. We hypothesized that poor systemic oxygenation in the perioperative period is associated with increased risk of stroke following cardiopulmonary bypass. METHODS: In this study of 251 adult patients who underwent cardiopulmonary bypass procedures at a single center from 2003 to 2006, cases (patients with a postoperative stroke at least 24 hours after surgery) were matched 1:2 to controls without stroke. Minimum and average partial pressure of oxygen in arterial blood (PaO2) values, from arterial blood gas values during and up to 24 hours after surgery, were evaluated as continuous and categorical predictors. Conditional logistic regression models adjusted for potential confounders (demographics, comorbidities, and intraoperative variables) were used to evaluate associations between PaO2 variables and stroke status. RESULTS: Lower nadir PaO2 values were associated with postoperative stroke, with estimated odds of stroke increasing over 20% (adjusted odds ratio [OR], 1.23; 95% confidence interval [CI], 1.07-1.41) per 10 mm Hg lower nadir PaO2, and similarly increased odds of stroke per lower quartile of nadir PaO2 (OR, 1.60; 95% CI, 1.19-2.16). When average PaO2 was considered, odds of stroke was also increased (adjusted OR, 1.39 per lower quartile of mean PaO2; 95% CI, 1.05-1.83). Having a nadir PaO2 value in the lowest versus any other quartile was associated with an estimated 2.41-fold increased odds of stroke (95% CI, 1.22-4.78). Quartile of nadir but not average PaO2 results remained significant after adjustment for multiple comparisons. CONCLUSIONS: Odds of stroke after cardiac surgery are increased in patients with a low minimum PaO2 within 24 hours of surgery. Results should be validated in an independent cohort. Further characterizing the underlying etiology of hypoxic episodes will be important to improve patient outcomes.