Jannetto, Paul J.

IMPORTANCE: Meropenem dosing is typically guided by creatinine-based estimated glomerular filtration rate (eGFR), but creatinine is a suboptimal GFR marker in the critically ill. OBJECTIVES: This study aimed to develop and qualify a population pharmacokinetic model for meropenem in critically ill adults and to determine which eGFR equation based on creatinine, cystatin C, or both biomarkers best improves model performance. DESIGN, SETTING, AND PARTICIPANTS: This single-center study evaluated adults hospitalized in an ICU who received IV meropenem from 2018 to 2022. Patients were excluded if they had acute kidney injury, were on kidney replacement therapy, or were treated with extracorporeal membrane oxygenation. Two cohorts were used for population pharmacokinetic modeling: a richly sampled development cohort (n = 19) and an opportunistically sampled qualification cohort (n = 32). MAIN OUTCOMES AND MEASURES: A nonlinear mixed-effects model was developed using parametric methods to estimate meropenem serum concentrations. RESULTS: The best-fit structural model in the richly sampled development cohort was a two-compartment model with first-order elimination. The final model included time-dependent weight normalized to a 70-kg adult as a covariate for volume of distribution (Vd) and time-dependent eGFR for clearance. Among the eGFR equations evaluated, eGFR based on creatinine and cystatin C expressed in mL/min best-predicted meropenem clearance. The mean (se) Vd in the final model was 18.2 (3.5) liters and clearance was 11.5 (1.3) L/hr. Using the development cohort as the Bayesian prior, the opportunistically sampled cohort demonstrated good accuracy and low bias. CONCLUSIONS AND RELEVANCE: Contemporary eGFR equations that use both creatinine and cystatin C improved meropenem population pharmacokinetic model performance compared with creatinine-only or cystatin C-only eGFR equations in adult critically ill patients.

ABSTRACT Cefepime exhibits highly variable pharmacokinetics in critically ill patients. The purpose of this study was to develop and qualify a population pharmacokinetic model for use in the critically ill and investigate the impact of various estimated glomerular filtration rate (eGFR) equations using creatinine, cystatin C, or both on model parameters. This was a prospective study of critically ill adults hospitalized at an academic medical center treated with intravenous cefepime. Individuals with acute kidney injury or on kidney replacement therapy or extracorporeal membrane oxygenation were excluded. A nonlinear mixed-effects population pharmacokinetic model was developed using data collected from 2018 to 2022. The 120 included individuals contributed 379 serum samples for analysis. A two-compartment pharmacokinetic model with first-order elimination best described the data. The population mean parameters (standard error) in the final model were 7.84 (0.24) L/h for CL1 and 15.6 (1.45) L for V1. Q was fixed at 7.09 L/h and V2 was fixed at 10.6 L, due to low observed interindividual variation in these parameters. The final model included weight as a covariate for volume of distribution and the eGFR cr-cysC (mL/min) as a predictor of drug clearance. In summary, a population pharmacokinetic model for cefepime was created for critically ill adults. The study demonstrated the importance of cystatin C to prediction of cefepime clearance. Cefepime dosing models which use an eGFR equation inclusive of cystatin C are likely to exhibit improved accuracy and precision compared to dosing models which incorporate an eGFR equation with only creatinine.

Context.— Clinical testing for Wilson disease (WD) is potentially challenging. Measuring the fraction of labile bound copper (LBC) to total copper may be a promising alternative diagnostic tool with better sensitivity and specificity than some current biomarker approaches. A dual filtration–based inductively coupled mass spectrometry (ICP-MS) assay to measure LBC in serum was developed. Objective.— To establish a reference interval for LBC and LBC to total copper (LBC fraction) in a healthy adult population, and to examine associations between total copper, LBC, and LBC fraction with age, sex, menopausal status, hormone replacement therapy, and supplement use. Design.— Serum samples were collected from healthy male (n = 110) and female (n = 104) patients between the ages of 19 and 80 years. Total copper and LBC were analyzed using ICP-MS. Results were used to calculate the LBC fraction. Reference intervals were calculated for the 2.5th and 97.5th percentiles for both LBC and LBC fraction. Results.— The reference intervals for LBC were determined to be 13 to 105 ng/mL and 12 to 107 ng/mL for female and male patients, respectively. The reference intervals for the LBC fraction were 1.0% to 8.1% and 1.2% to 10.5% for female and male patients, respectively. No significant associations were found regarding age, menopausal status, hormone replacement therapy, or vitamin and supplement use. Conclusions.— Sex-specific reference intervals have now been established for LBC and LBC fraction. These data in conjunction with further testing of WD populations can be used to assess the sensitivity and specificity of LBC fraction in screening, monitoring, and diagnosis.

Abstract Background Analytical and post-analytical errors are a persistent problem, which can be benchmarked using sigma metrics. Manual processes are associated with error rates of 3–4 sigma. Secondary review of manual reporting is meant to reduce/eliminate errors and is widely used, yet the true efficacy of manual secondary review is difficult to assess. Kidney stone analysis is a manually intensive process, requiring personnel to identify stone composition from spectra and to transcribe stone percent composition into an LIS system. Recently, we developed an AI program that allows for quantitative determination of kidney stone composition from spectra. This allows for a unique opportunity to estimate error rates associated with manual reporting and those following secondary review by means of subsequent AI quality assurance analysis. Methods Experienced technologists assessed stone composition and estimated the percent of each component (± 10%), based on Fourier transform infrared (FTIR) spectroscopy. These manual spectral composition assessments are secondarily reviewed by other experienced technologists for identity and percentage composition accuracy. The recently described Kidney stone AI spectral analysis (RokkStar) was implemented to assess reported stone composition identity and percent composition for agreement following secondary review in 159 334 stone reports. AI flagged discrepant reports were reviewed by personnel and reports were revised when appropriate. Secondary reviewer error detection rate was obtained by monitoring detection in a subset of 7440 kidney stones, and was that rate was extrapolated to establish secondary review error detection rate over the entire data set. The sum (total error) of estimated secondary reviewer error detection, and well as AI-mediated error detection, and all client reported errors were used to determine error rates in sigma following manual reporting, secondary review, and AI quality assurance. Results Manual entry led to an estimated 2060 errors in 159 334 stone reports, yielding an initial sigma value of 3.73. Secondary manual review resulted in an estimated 1909 (error detection rate of 92.5%) of these errors being detected over the entire report set, improving the sigma value to 4.61. Post-verification AI caught an additional 138 errors, leading to an improved post-AI sigma value of 5.27. Post-AI quality assurance, there were 13 remaining errors, 9 of which were manual reporting process deviations subsequently caught by laboratory staff, and 4 were reporting errors observed by client physicians. All 13 of these errors involved usual stone constituents or typographical errors that were not assessed by the current AI quality assurance version. Conclusion This study represents a unique large-scale estimate of efficacy of secondary result review by means of AI quality assurance review. While the presence of undetected errors cannot be completely ruled out, in this case the relative paucity of client reported errors, as well the alignment of the estimated rate of manual errors with previous reports may indicate that most errors were detected in this system. Importantly, manual secondary review improved errors rates by ∼0.9 sigma, and the use of AI further improved estimated overall sigma metric by ∼0.7, leading to a “world class” 5+ sigma level for this complex reporting process.

Abstract Background The legality and use of marijuana is a controversial topic. With increased prevalence of usage, cannabis detection for legal, medical, and workforce drug testing is on the rise. LC-MS/MS quantification of delta 9-carboxy tetrahydrocannabinol (delta 9-THC-COOH) in urine is accepted as the standard to detect marijuana use. One challenge faced by testing laboratories has been identifying adulterated samples. Many products/reagents can be used to manipulate the urine to avoid positive drug testing results. In this study, we developed a dilute-and-shoot strategy to separate and quantify both the delta 8- and 9-THC-COOH in urine samples and tested the effects of adulteration using a combination of nitrite and/or acids which can be used to mask cannabinoid use. Methods Five authentic delta 8- and 9-THC-COOH positive specimens, and one spiked sample were treated with strong acids (1N HCL or 10% TCA), 500 µg/mL nitrite, or a combination. After hydrolysis with sodium hydroxide, the analytes were quantified using a 6495 Mass Spectrometer coupled to a StreamSelect LC system (Agilent). LC separation was performed with a CORTECS T3 column utilizing a shallow gradient. In addition, twelve urine specimens with varying concentrations of delta 8- and 9-THC-COOH were treated with nitrite and screened using a delta 9-THC-COOH immunoassay on the Roche Cobas C501 and analyzed by LC-MS/MS. Results Nitrite did not change the physical appearance or the pH of the urine samples. Strong acid treatment also did not alter the appearance but did drop the urine pH ≤2. Pre-treated specimens with 1N HCL, 10% TCA, or 500 µg/mL of nitrite did not affect the delta 8- and 9-THC-COOH concentrations up to 6 days (refrigerated); however, specimens treated with strong acid combined with 500 µg/mL of nitrite for 30 min made both analytes undetectable. Additional experiments confirmed that 0.5 and 1 mol/L of nitrite lowered the concentration of all analytes, including internal standard, to undetectable levels in 48 h. Twelve additional specimens were collected, 3 with delta 8-THC-COOH, 3 with delta 9-THC-COOH, and 6 with both. All 12 samples screened positive using the Roche immunoassay and were quantified using the LC-MS/MS method. After treatment with 0.5 mol/L of nitrite, 10 of the 12 samples were negative using the immunoassay, but 2 samples remained positive. However, all nitrite treated specimens were negative (<LLOQ) using the LC-MS/MS method and the internal standard was eliminated. Later experiments confirmed that the delta 8- and 9-THC-COOH could be eliminated with as little as 0.1 mol/L nitrite for 30 min. Conclusion The unique dilute-and-shoot method can separate and quantify delta 8- and 9-THC-COOH. In addition, high concentrations of nitrite were shown to degrade both analytes along with the isotopically labeled internal standard. As a result, labs can distinguish true negative delta 8- and 9-THC-COOH (no analyte peaks) from nitrite adulterated specimens since the adulterated samples have no peaks for both the analytes and internal standard. A limitation of the study is that only sodium nitrite was tested. Other adulterants, such as potassium nitrite, pyridinium chlorochromate, peroxide etc. require further investigation.

Abstract Background While clinical tests are available to aid in the diagnosis of Wilson’s Disease (WD), some such as total copper determination lack sensitivity and specificity, while others such as liver tissue copper assessment are costly and invasive. WD affects copper metabolism and is known to cause low serum copper concentrations. In addition, an elevated percentage of total serum copper exists as non-protein bound or labile bound copper (LBC). Previous studies have shown that measuring the ratio of labile bound copper to total serum copper may aid in the diagnosis of WD. To support the utility of a laboratory developed test using serum LBC ratios to aid in the diagnosis of WD, serum samples from healthy donors were used to establish a reference range for LBC and the ratio of LBC to total copper in adults. Methods Serum samples were collected in trace metal free tubes from 214 donors (n = 110 male, n = 104 female) between the ages of 19–80 years old, selected against pre-determined exclusion criteria including acute hepatitis, chronic hepatitis, renal failure, biliary cirrhosis, celiac disease, and leukemia. Prior to analysis, samples went through a centrifugation-based preparation process to isolate the LBC fraction using molecular weight size exclusion filters and EDTA chelation. Samples were then analyzed via ICP-MS in kinetic energy discrimination (KED) mode to directly measure the LBC and total copper concentrations. LBC ratio values were determined from the LBC/total copper concentrations. Results Preliminary reference ranges were developed for both LBC and the LBC ratio based on the 2.5th and 97.5th percentiles with 95% confidence intervals. Established sex specific reference intervals for total copper were deemed acceptable per CLSI guidelines in document EP28-A3c, with ≤10% of results from this sample set falling outside of the established intervals. No statistically significant relationship was found in the mid-95th percentile between LBC concentration or ratio with age or sex. The reference intervals for LBC concentration were calculated as 13.41–104.66 and 11.69–106.50 ng/mL for females and males respectively. The reference intervals for LBC ratio were calculated as 1.04–8.12 and 1.17–10.48 for females and males respectively. Conclusions A reference range of LBC and LBC ratio has now been determined for the healthy adult population. Further testing can now be done on disease state populations to determine the sensitivity and specificity of LBC ratio in the detection, monitoring, or diagnosis of WD.

Abstract Posaconazole therapeutic drug monitoring (TDM) is widely utilized to assess therapeutic efficacy and safety; however, clinical effects of very high serum concentrations are unknown. A retrospective review of 90 patients receiving posaconazole for treatment or prophylaxis of invasive fungal infections with serum concentrations ≥3000 ng/mL from 1/1/2019 to 4/30/2021 evaluated the incidence and type of adverse drug reactions (ADRs). Symptomatic ADRs were very common in patients with posaconazole concentrations of ≥5000 ng/mL and 3000–4999 ng/mL (80% vs. 58.8%; P = 0.31). Posaconazole TDM should be performed for both treatment and prophylaxis indications and dose decrease for serum concentrations >3000 ng/mL should be considered.

Total joint arthroplasty (TJA) implants are composed of metals, ceramics, and/or polyethylene. Studies suggest that the debris released from metal implants may possess neurotoxic properties with reports of neuropsychiatric symptoms and memory deficits, which could be relevant to Alzheimer’s disease and related dementias. This exploratory study examined the cross-sectional correlation of blood metal concentrations with cognitive performance and neuroimaging findings in a convenience sample of 113 TJA patients with history of elevated blood metal concentrations of either titanium, cobalt and/or chromium. Associations with neuroimaging measures were observed but not with cognitive scores. Larger studies with longitudinal follow-up are warranted.