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Pharmacogenomics, which offers a potential means by which to inform prescribing and avoid adverse drug reactions, has gained increasing consideration in other medical settings but has not been broadly evaluated during perioperative care.The Implementation of Pharmacogenomic Decision Support in Surgery (ImPreSS) Trial is a prospective, single-center study consisting of a prerandomization pilot and a subsequent randomized phase. We describe findings from the pilot period. Patients planning elective surgeries were genotyped with pharmacogenomic results, and decision support was made available to anesthesia providers in advance of surgery. Pharmacogenomic result access and prescribing records were analyzed. Surveys (Likert-scale) were administered to providers to understand utilization barriers.Of eligible anesthesiology providers, 166 of 211 (79%) enrolled. A total of 71 patients underwent genotyping and surgery (median, 62 years; 55% female; average American Society of Anesthesiologists (ASA) score, 2.6; 58 inpatients and 13 ambulatories). No patients required postoperative intensive care or pain consultations. At least 1 provider accessed pharmacogenomic results before or during 41 of 71 surgeries (58%). Faculty were more likely to access results (78%) compared to house staff (41%; P = .003) and midlevel practitioners (15%) ( P.0001). Notably, all administered intraoperative medications had favorable genomic results with the exception of succinylcholine administration to 1 patient with genomically increased risk for prolonged apnea (without adverse outcome). Considering composite prescribing in preoperative, recovery, throughout hospitalization, and at discharge, each patient was prescribed a median of 35 (range 15-83) total medications, 7 (range 1-22) of which had annotated pharmacogenomic results. Of 2371 prescribing events, 5 genomically high-risk medications were administered (all tramadol or omeprazole; with 2 of 5 pharmacogenomic results accessed), and 100 genomically cautionary mediations were administered (hydralazine, oxycodone, and pantoprazole; 61% rate of accessing results). Providers reported that although results were generally easy to access and understand, the most common reason for not considering results was because remembering to access pharmacogenomic information was not yet a part of their normal clinical workflow.Our pilot data for result access rates suggest interest in pharmacogenomics by anesthesia providers, even if opportunities to alter prescribing in response to high-risk genotypes were infrequent. This pilot phase has also uncovered unique considerations for implementing pharmacogenomic information in the perioperative care setting, and new strategies including adding the involvement of surgery teams, targeting patients likely to need intensive care and dedicated pain care, and embedding pharmacists within rounding models will be incorporated in the follow-on randomized phase to increase engagement and likelihood of affecting prescribing decisions and clinical outcomes.

Background Using middleware solutions, it is possible to implement concentration-dependent analyte-specific hemolysis rejection limits. This makes day-to-day reporting of clinical specimens more efficient and potentially lowers sample rejection rates compared to a “one-size-fits-all” approach (i.e., solely based on a single cutoff provided in the package insert). Methods Hemolysis interference studies were performed at multiple analyte concentrations for three frequently ordered tests. For each assay, concentration-dependent hemolysis rejection limits were designed based on the total allowable error (TAE) for the analyte as well as the clinical significance of such incurred inaccuracy at the respective concentrations. In general, the following rationale was used: if the interference exceeds 10% (or package insert cutoffs), a comment is placed on the result. If the interference exceeds the TAE, the result will not be reported. Reduction in specimen rejection rates were estimated by comparing the incurred specimen rejection rates when package inserts’ vs concentration-dependent hemolysis interference limits were applied to a data set in our institute during a three-month period. Results Concentration-dependent analyte-specific hemolysis rejection thresholds were designed for three commonly ordered assays that are especially susceptible to hemolysis interference. It is estimated that these novel thresholds for aspartate aminotransferase (AST), lactate dehydrogenase (LDH), and direct bilirubin (DBIL) reduced specimen rejection rates from 9.3% to 1.3%, 31.4% to 4.8%, and 19.9% to 7.1%, respectively. Conclusions Concentration-dependent analyte-specific hemolysis rejection thresholds for three commonly ordered assays can reduce rejection rates without significantly compromising the quality of test results.

Background Preeclampsia is a leading cause of maternal and neonatal mortality and morbidity worldwide. Diagnosis of the condition is currently limited to utilization of nonspecific signs and symptoms. However, identification of potential pathogenic biomarkers may support earlier diagnosis and ultimately improved prognosis. Content The current models of preeclampsia suggest that the disease has components of abnormal placentation, a degree of angiogenic imbalance and endothelial dysfunction. Angiogenic factors such as soluble fms-like tyrosine kinase-1 and soluble endoglin increase while placental growth factor concentrations decrease in the circulation weeks before the onset of the disease. Multiple studies have looked at the capacity of angiogenic factors for the prediction of preeclampsia and adverse pregnancy outcomes. Summary The goal of this review is to focus on the role of angiogenic factors in the pathogenesis of preeclampsia and use of angiogenic biomarkers for risk stratification, diagnosis, and prognosis of the disease.

In recent years, there has been increasing evidence supporting the role of germline pharmacogenomic factors predicting toxicity for anticancer therapies. Although somatic genomic data are used frequently in oncology care planning, germline pharmacogenomic testing is not. This study hypothesizes that comprehensive germline pharmacogenomic profiling could have high relevance for cancer care.Between January 2011 and August 2020, patients at the University of Chicago Medical Center were genotyped across custom germline pharmacogenomic panels for reasons unrelated to cancer care. Actionable anticancer pharmacogenomic gene/drug interactions identified by the FDA were defined including: CYP2C9 (erdafitinib), CYP2D6 (gefitinib), DPYD (5-fluorouracil and capecitabine), TPMT (thioguanine and mercaptopurine), and UGT1A1 (belinostat, irinotecan, nilotinib, pazopanib, and sacituzumab-govitecan hziy). The primary objective was to determine the frequency of individuals with actionable or high-risk genotypes across these 5 key pharmacogenes, thus potentially impacting prescribing for at least 1 of these 11 commonly prescribed anticancer therapies.Data from a total of 1586 genotyped individuals were analyzed. The oncology pharmacogene with the highest prevalence of high-risk, actionable genotypes was UGT1A1, impacting 17% of genotyped individuals. Actionable TPMT and DPYD genotypes were found in 9% and 4% of patients, respectively. Overall, nearly one-third of patients genotyped across all 5 genes (161/525, 31%) had at least one actionable genotype.These data suggest that germline pharmacogenomic testing for 5 key pharmacogenes could identify a substantial proportion of patients at risk with standard dosing, an estimated impact similar to that of somatic genomic profiling.Differences in our genes may explain why some drugs work safely in certain individuals but can cause side effects in others. Pharmacogenomics is the study of how genetic variations affect an individual's response to medications. In this study, an evaluation was done for important genetic variations that can affect the tolerability of anticancer therapy. By analyzing the genetic results of1500 patients, it was found that nearly one-third have genetic variations that could alter recommendations of what drug, or how much of, an anticancer therapy they should be given. Performing pharmacogenomic testing before prescribing could help to guide personalized oncology care.

Background Several opioids have pharmacogenomic associations impacting analgesic efficacy. However, germline pharmacogenomic testing is not routinely incorporated into supportive oncology. We hypothesized that CYP2D6 profiling would correlate with opioid prescribing and hospitalizations. Materials and Methods We analyzed 61,572 adult oncology patients from 2012 to 2018 for opioid exposures. CYP2D6 metabolizer phenotype (ultra-rapid [UM], normal metabolizer [NM], intermediate [IM], or poor [PM]), the latter two of which may cause inefficacy of codeine, tramadol, and standard-dose hydrocodone, was determined for patients genotyped for reasons unrelated to pain. The primary endpoint was number of opioid medications received during longitudinal care (IM/PMs vs. NMs). Secondary endpoint was likelihood of pain-related hospital encounters. Results Most patients with cancer (n = 34,675, 56%) received multiple opioids (average 2.8 ± 1.6/patient). Hydrocodone was most commonly prescribed (62%), followed by tramadol, oxycodone, and codeine. In the CYP2D6 genotyped cohort (n = 105), IM/PMs received a similar number of opioids (3.4 ± 1.4) as NMs (3.3 ± 1.9). However, IM/PMs were significantly more likely to experience pain-related hospital encounters compared with NMs, independent of other variables (odds ratio [OR] = 5.4; 95% confidence interval [CI], 1.2–23.6; p = .03). IM/PMs were also more likely to be treated with later-line opioids that do not require CYP2D6 metabolism, such as morphine and hydromorphone (OR = 3.3; 95% CI, 1.1–9.8; p = .03). Conclusion CYP2D6 genotype may identify patients with cancer at increased risk for inadequate analgesia when treated with typical first-line opioids like codeine, tramadol, or standard-dose hydrocodone. Palliative care considerations are an integral part of optimal oncology care, and these findings justify prospective evaluation of preemptive genotyping as a strategy to improve oncology pain management. Implications for Practice Genomic variation in metabolic enzymes can predispose individuals to inefficacy when receiving opioid pain medications. Patients with intermediate and/or poor CYP2D6 metabolizer status do not adequately convert codeine, tramadol, and hydrocodone into active compounds, with resulting increased risk of inadequate analgesia. This study showed that patients with cancer frequently receive CYP2D6-dependent opioids. However, patients with CYP2D6 intermediate and poor metabolizer status had increased numbers of pain-related hospitalizations and more frequently required the potent non-CYP2D6 opioids morphine and hydromorphone. This may reflect inadequate initial analgesia with the common “first-line” CYP2D6-metabolized opioids. Preemptive genotyping to guide opioid prescribing during cancer care may improve pain-related patient outcomes.

Objectives We sought to replace the highly hemolysis-susceptible diazo conjugated bilirubin (Bc) assay with the more robust vanadate oxidation method and determine its impact on test cancellation in the pediatric population. Methods Analytical validation of the Randox vanadate assay and comparison with the Roche diazo method were performed. The frequency of pediatric sample cancellation because of hemolysis was compared between the diazo and vanadate methods by retrospective analysis of clinical test data. Results The vanadate assay demonstrated no clinically significant interference from hemolysis up to a hemolysis index of 1,300 (approximately 13 g/L hemoglobin). There was a strong correlation with the diazo method (r2 = 0.97) but with a positive slope bias of 1.27. Implementing the vanadate method resulted in a significantly lower proportion of pediatric samples cancelled because of hemolysis compared with the diazo method (0.6% of 688 patients vs 30.6% of 10,464 patients, respectively; P < .001), with a 0.6% (n = 513) vs 43.2% (n = 6,464) reduction in test cancellations (P < .001) for children younger than 6 months of age. Conclusions The vanadate method showed robust performance against hemolysis. Its implementation resulted in a significant decrease in pediatric tests cancelled because of hemolysis.

ObjectivesTo evaluate the analytical and clinical performance of the Truvian Easy Check coronavirus disease 2019 (COVID-19) IgM/IgG anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody test.Serologic assays have become increasingly available for surveillance through the Food and Drug Administration emergency use authorization in the ongoing COVID-19 global pandemic. However, widespread application of serologic assays has been curbed by reports of faulty or inaccurate tests. Therefore, rapid COVID-19 antibody tests need to be thoroughly validated prior to their implementation.MethodsThe Easy Check device was analytically evaluated and its performance was compared with the Roche Elecsys anti-SARS-CoV-2 antibody assay. The test was further characterized for cross-reactivity using sera obtained from patients infected by other viruses. Clinical performance was analyzed with polymerase chain reaction-confirmed samples and a 2015 prepandemic reference sample set.ResultsThe Easy Check device showed excellent analytical performance and compares well with the Roche Elecsys antibody assay, with an overall concordance of 98.6%. Clinical performance showed a sensitivity of 96.6%, a specificity of 98.2%, and an overall accuracy of 98.1%.ConclusionsThe Easy Check device is a simple, reliable, and rapid test for detection of SARS-CoV-2 seropositivity, and its performance compares favorably against the automated Roche Elecsys antibody assay.

The mechanisms explaining progression to severe COVID-19 remain poorly understood. It has been proposed that immune system dysregulation/over-stimulation may be implicated, but it is not clear how such processes would lead to respiratory failure. We performed comprehensive multiparameter immune monitoring in a tightly controlled cohort of 128 COVID-19 patients, and used the ratio of oxygen saturation to fraction of inspired oxygen (SpO2 / FiO2) as a physiologic measure of disease severity. Machine learning algorithms integrating 139 parameters identified IL-6 and CCL2 as two factors predictive of severe disease, consistent with the therapeutic benefit observed with anti-IL6-R antibody treatment. However, transcripts encoding these cytokines were not detected among circulating immune cells. Rather, in situ analysis of lung specimens using RNAscope and immunofluorescent staining revealed that elevated IL-6 and CCL2 were dominantly produced by infected lung type II pneumocytes. Severe disease was not associated with higher viral load, deficient antibody responses, or dysfunctional T cell responses. These results refine our understanding of severe COVID-19 pathophysiology, indicating that aberrant cytokine production by infected lung epithelial cells is a major driver of immunopathology. We propose that these factors cause local immune regulation towards the benefit of the virus.

Objectives To analytically and clinically evaluate the semiquantitative Elecsys anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein antibody (S-Ab) assay on the Roche cobas e602 analyzer. Methods The S-Ab assay is a 1-step, double-antigen sandwich electrochemiluminescent immunoassay that semiquantitatively measures total IgG, IgM, and IgA antibodies specific for the receptor binding domain of SARS-CoV-2 spike protein in serum or plasma. The S-Ab assay was evaluated for precision, linearity, interference (by hemoglobin, bilirubin, triglycerides, and biotin), cross-reactivity, and clinical performance, and was compared to the qualitative Elecsys anti-nucleocapsid (N-Ab) immunoassay, a lateral flow device that qualitatively detects S-Ab and N-Ab, and an anti-spike enzyme-linked immunosorbent assay (ELISA). Results S-Ab assay is precise, exhibits linearity from 0.4 to 250 U/mL, is unaffected by significant cross-reactivity or interferences, and qualitatively demonstrates greater than 90% concordance with N-Ab assay and lateral flow device. Readouts of S-Ab assay correlate with ELISA, which in turn correlates strongly with SARS-CoV-2 virus neutralization assay, and exhibit 100% sensitivity and specificity for COVID-19 patient samples obtained at or more than 14 days after PCR positivity. Conclusions The S-Ab assay is a robust clinical test for qualitative and semiquantitative detection of seropositivity following SARS-CoV-2 infection or spike-encoding mRNA COVID-19 vaccination.

BackgroundPharmacogenomics has the potential to improve patient outcomes through predicting drug response. We designed and evaluated the analytical performance of a custom OpenArray® pharmacogenomics panel targeting 478 single-nucleotide variants (SNVs).MethodsForty Coriell Institute cell line (CCL) DNA samples and DNA isolated from 28 whole-blood samples were used for accuracy evaluation. Genotyping calls were compared to at least 1 reference method: next-generation sequencing, Sequenom MassARRAY®, or Sanger sequencing. For precision evaluation, 23 CCL samples were analyzed 3 times and reproducibility of the assays was assessed. For sensitivity evaluation, 6 CCL samples and 5 whole-blood DNA samples were analyzed at DNA concentrations of 10 ng/µL and 50 ng/µL, and their reproducibility and genotyping call rates were compared.ResultsFor 443 variants, all samples assayed had concordant calls with at least 1 reference genotype and also demonstrated reproducibility. However, 6 of these 443 variants showed an unsatisfactory performance, such as low PCR amplification or insufficient separation of genotypes in scatter plots. Call rates were comparable between 50 ng/µL DNA (99.6%) and 10 ng/µL (99.2%). Use of 10 ng/µL DNA resulted in an incorrect call for a single sample for a single variant. Thus, as recommended by the manufacturer, 50 ng/µL is the preferred concentration for patient genotyping.ConclusionsWe evaluated a custom-designed pharmacogenomics panel and found that it reliably interrogated 437 variants. Clinically actionable results from selected variants on this panel are currently used in clinical studies employing pharmacogenomics for clinical decision-making.