Pharmacotherapy最新文献

Study objective: Neonatal opioid withdrawal syndrome (NOWS) is a condition that often occurs in neonates born to mothers who received methadone treatment for opioid use disorder during pregnancy. Early identification and treatment of infants at risk of NOWS may improve clinical outcomes. The purpose of this study was to evaluate whether maternal and umbilical cord plasma concentrations of methadone and its metabolite, 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP), could predict the need for NOWS treatment.

Design: Single-center prospective study.

Setting: University of Michigan Neonatal Intensive Care Unit.

Patients: The study included 11 opioid-dependent mother-infant dyads, where the mothers were treated with methadone at 34 weeks' gestation or later.

Intervention: Maternal and cord blood samples were collected from the study participants.

Measurements and main results: Maternal and cord plasma concentrations of methadone and EDDP were determined. Six out of the 11 infants required treatment for NOWS. Maternal methadone plasma concentrations were comparable between infants requiring and not requiring NOWS treatment (329.1 ± 229.7 ng/mL vs. 413.2 ± 329.8 ng/mL). However, the average cord plasma methadone concentration in infants who did not require NOWS treatment was 2.9-fold higher than in those who required the treatment (120.0 ± 88.6 ng/mL vs. 40.9 ± 24.4 ng/mL), although the difference was not statistically significant. The ratios of maternal-to-cord methadone plasma concentrations were significantly higher in patients who required treatment for NOWS compared with those who did not (7.7 ± 1.9 vs. 3.5 ± 1.6, p = 0.003). Maternal and cord plasma EDDP concentrations and the maternal-to-cord plasma EDDP concentration ratios did not differ between patients who required and did not require treatment for NOWS.

Conclusions: The results suggest that methadone permeability across the blood-placental barrier may affect in utero exposure to methadone, and the maternal-to-cord methadone plasma concentration ratio could be a potential biomarker for predicting the need for NOWS treatment.

The strength of evidence for specific ambulatory care prescribing cascades, in which a marker drug is used to treat an adverse event caused by an index drug, has not been well characterized. To perform a structured, systematic, and transparent review of the evidence supporting ambulatory care prescribing cascades. Ninety-four potential prescribing cascades identified through a previously published systematic review. Systematic search of the literature to further characterize prescribing cascades. (1) Grading of evidence based on observational studies investigating associations between index and marker drugs, including: Level I-strong evidence [i.e. multiple high-quality studies]; Level II-moderate evidence [i.e. single high-quality study]; Level III-fair evidence [no high-quality studies but one or more moderate-quality studies]; and Level IV-poor evidence [other]. (2) Listing of the adverse event associated with the index drug in the product's United States Food and Drug Administration (FDA) label. (3) Synthesis of the evidence supporting mechanisms linking index drugs and associated adverse events. Of 99 potential cascades, 94 were supported by one or more confirmatory observational studies and were therefore included in this review. The 94 cascades related to 30 types of adverse drug reactions affecting 10 different anatomic/physiologic systems and were investigated by a total of 88 confirmatory studies, including prescription sequential symmetry analysis (n = 51), cohort (n = 30), and case-control (n = 7) studies. Overall, the evidence from observational studies was strong for 18 (19.1%) prescribing cascades, moderate for 61 (64.9%), fair for 13 (13.8%), and poor for 2 (2.1%). Although the evidence supporting mechanisms that link index drugs and associated adverse events was variable, FDA labels included information about the adverse event associated with the index drug for most (n = 86) but not all of the 94 prescribing cascades. Although we identified 18 of 94 prescribing cascades supported by strong clinical evidence and most adverse events associated with index drugs are included in FDA label, the evidentiary basis for prescribing cascades varies, with many requiring further evidence of clinical relevance.

Background: Fall-related injuries are a significant health issue that occur in 25% of older adults and account for a significant number of trauma-related hospitalizations. Although medication intensification may increase the risk of hospital readmissions in non-trauma patients, data on a geriatric trauma population are lacking.

Objective: The primary objective was to evaluate the effect of medication intensification on 30-day hospital readmissions in geriatric patients hospitalized for fall-related injuries.

Methods: This multicenter, retrospective cohort study included patients with geriatric who presented to one of three trauma centers within a large, health-system between January 1, 2018 and December 31, 2020. Patients at least 65 years old admitted with a fall-related injury were eligible for inclusion. Patients were grouped according to medication changes at discharge, which included intensified and non-intensified groups. Medication intensification included increased dose(s) or initiation of new agents. The primary outcome was the 30-day hospital readmission rate.

Results: Of the 870 patients included (median [interquartile range, IQR] age, 82 [74-89] years, 522 (60%) female, and 220 (25%) with a previous fall), there were 471 (54%) and 399 (46%) patients in the intensified and non-intensified groups, respectively. The intensified group had a higher 30-day hospital readmission rate (21% intensified vs. 16% non-intensified, p = 0.043; number needed to harm 20) based on an unweighted analysis. According to a weighted propensity score logistic regression, medication intensification was associated with higher 30-day hospital readmissions (24% [95% confidence interval [CI] 19-31%] intensified vs. 15% [95% CI 11-20%] non-intensified, p = 0.018). These results were consistent within competing risk models accounting for death (cause-specific model: hazard ratio [HR] 1.63 [95% CI 1.07-2.49], p = 0.023; Fine-Gray model: HR 1.64 [95% CI 1.07-2.50], p = 0.022).

Conclusions: In a geriatric trauma population hospitalized after a fall, intensification of medications may pose an increased risk of 30-day hospital readmission.

Objectives: The immunomodulators tocilizumab and baricitinib improve outcomes in severely ill patients with coronavirus disease 2019 (COVID-19); however, comparative analyses of clinical outcomes related to these agents are lacking. A tocilizumab national shortage shifted treatment to baricitinib in critically ill patients, allowing for an outcome comparison in a similar population. The purpose of this study is to compare clinical outcomes in critically ill COVID-19 patients who received tocilizumab and those who received baricitinib.

Design: Retrospective, observational cohort study using generalized estimating equation models, accounting for clustering by hospital and known confounders, to estimate the proportional odds of the ordinal World Health Organization Clinical Progression Scale (WHO-CPS) score at day 14, the primary outcome. Secondary outcomes included WHO-CPS score at day 7.

Setting: Multiple hospitals within the Cleveland Clinic Health System.

Patients: Adult patients admitted for COVID-19 between January 2021 and November 2021.

Interventions: Receipt of tocilizumab, before its shortage, or baricitinib, during shortage.

Measurements and main results: In total, 507 patients were included; 217 received tocilizumab and 290 received baricitinib. Over 96% of patients required ICU admission and 98% received concomitant dexamethasone. Tocilizumab recipients had higher (worse) baseline WHO-CPS scores. After adjustment, tocilizumab use was associated with higher odds of a worse day 14 WHO-CPS score compared with baricitinib (adjusted odds ratio [OR] 1.65 [95% confidence interval (CI) 1.10-2.48]). Similarly, after adjustment, tocilizumab use was associated with higher odds of a worse day 7 WHO-CPS score (adjusted OR 1.65 [95% CI 1.22-2.24]).

Conclusions: Baricitinib use was associated with better WHO-CPS scores at day 14 and day 7 compared with tocilizumab in a cohort of critically ill patients with COVID-19. The odds of having a one unit increase in WHO-CPS score at day 14 was 71% higher with tocilizumab than baricitinib. No difference in mortality or adverse effects was noted.

Introduction: Cefazolin is the leading antibiotic used to prevent surgical site infections worldwide. Consensus guidelines recommend adjustment of the cefazolin dose above and below 120 kg without regard to body composition. Algorithms exist to repurpose radiologic data into body composition (morphomics) and inform dosing decisions in obesity.

Objectives: To compare the current standard of body weight to morphomic measurements as covariates of cefazolin pharmacokinetics and aid dose stratification of cefazolin in patients with obesity undergoing colorectal surgery.

Methods: This prospective study measured cefazolin plasma, fat, and colon tissue concentrations in colorectal surgery patients in order to develop a morphomics-informed population pharmacokinetic (PopPK) model to guide dose adjustments. A physiologically-based pharmacokinetic (PBPK) model was also constructed to inform tissue partitioning in morbidly obese patients (n = 21, body mass index ≥35 kg/m² with one or more co-morbid conditions).

Results: Morphomics and pharmacokinetic data were available in 58 patients with a median [min, max] weight and age of 95.9 [68.5, 148.8] kg and 55 [25, 79] years, respectively. The plasma-to-subcutaneous fat partition coefficient was predicted to be 0.072 and 0.060 by the PopPK and PBPK models, respectively. The estimated creatinine clearance (eCL_cr ) and body depth at the third lumbar vertebra (body depth_L3) were identified as covariates of cefazolin exposure. The probability of maintaining subcutaneous fat concentrations above 2 μg/mL for 100% of a 4-h surgical period was below 90% when eCLcr ≥105 mL/min and body depth_L3 ≥ 300 mm and less sensitive to the rate of infusion between 5 and 60 min.

Conclusions: Kidney function and morphomics were more informative than body weight as covariates of cefazolin target site exposure. Data from more diverse populations, consensus on target cefazolin exposure, and comparative studies are needed before a change in practice can be implemented.

Introduction: Vancomycin is frequently used for prolonged courses in treating osteoarticular infections despite a high rate of adverse drug events (ADE). The objective of this study was to evaluate the safety and effectiveness of transitioning to oral therapy compared to continuing parenteral vancomycin in patients with orthopedic infections.

Methods: We conducted a single-center, retrospective cohort study of patients with orthopedic infections discharged on parenteral vancomycin with a planned duration of at least 4 weeks. We compared rates of ADE while on vancomycin to rates of ADE after switching to an oral regimen. As a secondary analysis, we compared unplanned hospital readmission within 60 days and treatment failure at 1 year between patients who were transitioned to oral antibiotics within 4 weeks of vancomycin initiation and those that were not.

Results: Two hundred twenty-eight patients met the inclusion criteria. Vancomycin was associated with significantly greater toxicity compared to oral regimens. Fifty-one patients had an adverse event while on vancomycin (5.87 ADE per 1000 patient-days) while 9 patients had an adverse event on oral therapy (1.49 ADE per 1000 patient-days) (Rate difference 4.39 per 1000 patient days, 95% CI: 2.52 to 6.26 events per 1000 patient-days). In proportional hazards analysis, transition to an oral antibiotic regimen was independently associated with a lower rate of ADE (aHR 0.12, 95% CI: 0.02-0.86). Forty-one patients (18%) were transitioned to oral therapy within 4 weeks; these patients did not have an increased rate of unplanned readmission (12.2% vs 17.1%) or treatment failure (17.1% vs 21.9%).

Conclusions: Patients transitioned to oral therapy within 4 weeks of discharge had significantly fewer adverse events and similar incidences of 1-year treatment failure compared to patients maintained on parenteral vancomycin. Substituting oral antibiotics for parenteral vancomycin is a potential strategy to minimize vancomycin toxicity during the treatment of orthopedic infections.

Study objective: Levocarnitine (L-carnitine) has shown promise as a metabolic-therapeutic for septic shock, where mortality approaches 40%. However, high-dose (≥ 6 grams) intravenous supplementation results in a broad range of serum concentrations. We sought to describe the population pharmacokinetics (PK) of high-dose L-carnitine, test various estimates of kidney function, and assess the correlation of PK parameters with pre-treatment metabolites in describing drug response for patients with septic shock.

Design: Population PK analysis was done with baseline normalized concentrations using nonlinear mixed effect models in the modeling platform Monolix. Various estimates of kidney function, patient demographics, dose received, and organ dysfunction were tested as population covariates.

Data source: We leveraged serum samples and metabolomics data from a phase II trial of L-carnitine in vasopressor-dependent septic shock. Serum was collected at baseline (T0); end-of-infusion (T12); and 24, 48, and 72 h after treatment initiation.

Patients and intervention: Patients were adaptively randomized to receive intravenous L-carnitine (6 grams, 12 grams, or 18 grams) or placebo.

Measurements and main results: The final dataset included 542 serum samples from 130 patients randomized to L-carnitine. A two-compartment model with linear elimination and a fixed volume of distribution (17.1 liters) best described the data and served as a base structural model. Kidney function estimates as a covariate on the elimination rate constant (k) reliably improved model fit. Estimated glomerular filtration rate (eGFR), based on the 2021 Chronic Kidney Disease Epidemiology collaboration (CKD-EPI) equation with creatinine and cystatin C, outperformed creatinine clearance (Cockcroft-Gault) and older CKD-EPI equations that use an adjustment for self-identified race.

Conclusions: High-dose L-carnitine supplementation is well-described by a two-compartment population PK model in patients with septic shock. Kidney function estimates that leverage cystatin C provided superior model fit. Future investigations into high-dose L-carnitine supplementation should consider baseline metabolic status and dose adjustments based on renal function over a fixed or weight-based dosing paradigm.

Study objective: To estimate the prevalence of potential moderate to severe drug-drug interactions (DDIs) involving nirmatrelvir/ritonavir, identify interacting medications, and evaluate risk factors associated with potential DDIs.

Design: Cross-sectional study.

Data source: Electronic health records from the National COVID Cohort Collaborative Enclave, one of the largest COVID-19 data resources in the United States.

Patients: Outpatients aged ≥18 years and started nirmatrelvir/ritonavir between December 23, 2021 and March 31, 2022.

Intervention: Nirmatrelvir/ritonavir.

Measurements: The outcome is potential moderate to severe DDIs, defined as starting interacting medications reported by National Institutes of Health 30 days before or 10 days after starting nirmatrelvir/ritonavir.

Main results: Of 3214 outpatients who started nirmatrelvir/ritonavir, the mean age was 56.8 ± 17.1 years, 39.5% were male, and 65.8% were non-Hispanic white. Overall, 521 (16.2%) were potentially exposed to at least one moderate to severe DDI, most commonly to atorvastatin (19.2% of all DDIs), hydrocodone (14.0%), or oxycodone (14.0%). After adjustment for covariates, potential DDIs were more likely among individuals who were older (odds ratio [OR] 1.16 per 10-year increase, 95% confidence interval [CI] 1.08-1.25), male (OR 1.36, CI 1.09-1.71), smokers (OR 1.38, CI 1.10-1.73), on more co-medications (OR 1.35, CI 1.31-1.39), and with a history of solid organ transplant (OR 3.63, CI 2.05-6.45).

Conclusions: One in six of individuals receiving nirmatrelvir/ritonavir were at risk of a potential moderate or severe DDI, underscoring the importance of clinical and pharmacy systems to mitigate such risks.

Study objective: The effects of the sodium-dependent glucose transporter-2 inhibitor ipragliflozin were compared with metformin in a previous study, which revealed that ipragliflozin reduced visceral fat content by 12%; however, the underlying mechanism was unclear. Therefore, this sub-analysis aimed to compare metabolomic changes associated with ipragliflozin and metformin that may contribute to their biological effects.

Design: A sub-analysis of a randomized controlled study.

Setting: Chiba University Hospital and ten hospitals in Japan.

Patients: Fifteen patients with type 2 diabetes in the ipragliflozin group and 15 patients with type 2 diabetes in the metformin group with matching characteristics, such as age, sex, baseline A1C, baseline visceral fat area, smoking status, and concomitant medication.

Interventions: Ipragliflozin 50 mg or metformin 1000 mg daily.

Measurements: The clinical data were reanalyzed, and metabolomic analysis of serum samples collected before and 24 weeks after drug administration was performed using capillary electrophoresis time-of-flight mass spectrometry.

Main results: The reduction in the mean visceral fat area after 24 weeks of treatment was significantly larger (p = 0.002) in the ipragliflozin group (-19.8%) than in the metformin group (-2.5%), as were the subcutaneous fat area and body weight. The A1C and blood glucose levels decreased in both groups. Glutamic pyruvic oxaloacetic transaminase, γ-glutamyl transferase, uric acid, and triglyceride levels decreased in the ipragliflozin group. Low-density lipoprotein cholesterol levels decreased in the metformin group. After ipragliflozin administration, N2-phenylacetylglutamine, inosine, guanosine, and 1-methyladenosine levels increased, whereas galactosamine, glucosamine, 11-aminoundecanoic acid, morpholine, and choline levels decreased. After metformin administration, metformin, hypotaurine, methionine, methyl-2-oxovaleric acid, 3-nitrotyrosine, and cyclohexylamine levels increased, whereas citrulline, octanoic acid, indole-3-acetaldehyde, and hexanoic acid levels decreased.

Conclusions: Metabolites that may affect visceral fat reduction were detected in the ipragliflozin group. Studies are required to further elucidate the underlying mechanisms.