Search

I've had Nina Simone's “sinnerman” on repeat for months. The propulsive force of Simone's 1965 live version of this gospel song drives its ten-minute ferocity straight into the contemporary American zeitgeist. As she tells her audience in the lead-up to a lesser-known performance of the song, recorded in 1961, Simone learned “Sinnerman” when she was a “little bitty girl in revival meetings. It happened when my mother and lots more like her tried to save souls.” The song's judgment-day tale of redemption's refusal is told doubly, both by the sinner—“I cried rock / don't you see I need you, rock”—and by those from whom the sinner begs, if not forgiveness, then simply some measure of mercy from the divine justice to come: “Oh sinnerman, where you gonna run to?” The break in the middle of the 1965 recording strips the song down to Simone's handclaps on the second and fourth beats. All that remains is the tenuous intensity of the time neither of redemption nor of damnation but merely of “accompaniment” in the in-between (Tomlinson and Lipsitz). Called forth from that time, in all of Simone's live recordings, and missing from those of Les Baxter or the Weavers just a few years earlier, comes the insurgent cry for “Power!” over and over, to the point of near exhaustion.

Documentation of adverse drug reactions (ADRs) is a key factor in guiding future prescribing. However, incomplete documentation is common and often fails to distinguish implicated drugs as true allergies. This in turn leads to unnecessary avoidance of implicated drug classes and may result in sub-optimal prescribing. Pharmacovigilance (PV) programs utilize a systematic approach to clarify ADR documentation and are known to improve patient safety. Yet it remains unclear if PV alters prescribing. Or, if the existence of the ADR documentation itself continues to prompt avoidance of implicated drugs. To address this, our work presents a retrospective cohort study assessing if clarification of antibiotic ADRs by a hospital-wide PV team was associated with future, safe, re-prescribing at a freestanding pediatric hospital in the midwestern United States. First, we compared the likelihood of future prescribing in an antibiotic class with an active ADR, as compared to alternative drug classes, between PV-clarified and non-clarified patients. Second, we assessed differences in adverse event rates 30-days after future prescribing based on PV clarification status. For robustness, analyses were performed on patients with ADRs in four antibiotic classes: penicillin-based beta-lactams (n = 45,642), sulfonamides/trimethoprim (n = 5,329), macrolides (n = 3,959), and glycopeptides (n = 622). Results illustrate that clarification of an ADR by PV was associated with an increased odds of future prescribing in the same drug class (Odds Ratio [95%-CI]): penicillin-based beta-lactams (1.59 [1.36–1.89]), sulfonamides/trimethoprim (2.29 [0.89–4.91]), macrolides (0.77 [0.33–1.61]), and glycopeptide (1.85 [1.12–3.20]). Notably, patients clarified by PV experienced no increase in the rate of adverse events within 30-days following the prescribing of antibiotics in the same class as an active ADR. Overall, this study provides strong evidence that PV reviews safely increase the rate of re-prescribing antibiotics even in the presence of an existing implicated drug ADR. [ABSTRACT FROM AUTHOR]

The 13C‐pantoprazole breath test (PAN‐BT) is a safe, noninvasive, in vivo CYP2C19 phenotyping probe for adults. Our objective was to evaluate PAN‐BT performance in children, with a focus on discriminating individuals who, according to guidelines from the Clinical Pharmacology Implementation Consortium (CPIC), would benefit from starting dose escalation versus reduction for proton pump inhibitors (PPIs). Children (n = 65, 6–17 years) genotyped for CYP2C19 variants *2, *3, *4, and *17 received a single oral dose of 13C‐pantoprazole. Plasma concentrations of pantoprazole and its metabolites, and changes in exhaled 13CO2 (termed delta‐over‐baseline or DOB), were measured 10 times over 8 h using high performance liquid chromatography with ultraviolet detection and spectrophotometry, respectively. Pharmacokinetic parameters of interest were generated and DOB features derived using feature engineering for the first 180 min postadministration. DOB features, age, sex, and obesity status were used to run bootstrap analysis at each timepoint (Ti) independently. For each iteration, stratified samples were drawn based on genotype prevalence in the original cohort. A random forest was trained, and predictive performance of PAN‐BT was evaluated. Strong discriminating ability for CYP2C19 intermediate versus normal/rapid metabolizer phenotype was noted at DOBT30 min (mean sensitivity: 0.522, specificity: 0.784), with consistent model outperformance over a random or a stratified classifier approach at each timepoint (p < 0.001). With additional refinement and investigation, the test could become a useful and convenient dosing tool in clinic to help identify children who would benefit most from PPI dose escalation versus dose reduction, in accordance with CPIC guidelines. [ABSTRACT FROM AUTHOR]

Black Panther. Comic book series. Reginald Hudlin (w); John Romita, Jr., et al. (a). New York: Marvel, [new series] 2005-ongoing. One cannot help but notice retrospectively a certain uncanniness about [...]

The 13 C-pantoprazole breath test (PAN-BT) is a safe, noninvasive, in vivo CYP2C19 phenotyping probe for adults. Our objective was to evaluate PAN-BT performance in children, with a focus on discriminating individuals who, according to guidelines from the Clinical Pharmacology Implementation Consortium (CPIC), would benefit from starting dose escalation versus reduction for proton pump inhibitors (PPIs). Children (n = 65, 6-17 years) genotyped for CYP2C19 variants *2, *3, *4, and *17 received a single oral dose of 13 C-pantoprazole. Plasma concentrations of pantoprazole and its metabolites, and changes in exhaled 13 CO 2 (termed delta-over-baseline or DOB), were measured 10 times over 8 h using high performance liquid chromatography with ultraviolet detection and spectrophotometry, respectively. Pharmacokinetic parameters of interest were generated and DOB features derived using feature engineering for the first 180 min postadministration. DOB features, age, sex, and obesity status were used to run bootstrap analysis at each timepoint (T i ) independently. For each iteration, stratified samples were drawn based on genotype prevalence in the original cohort. A random forest was trained, and predictive performance of PAN-BT was evaluated. Strong discriminating ability for CYP2C19 intermediate versus normal/rapid metabolizer phenotype was noted at DOB T30 min (mean sensitivity: 0.522, specificity: 0.784), with consistent model outperformance over a random or a stratified classifier approach at each timepoint (p < 0.001). With additional refinement and investigation, the test could become a useful and convenient dosing tool in clinic to help identify children who would benefit most from PPI dose escalation versus dose reduction, in accordance with CPIC guidelines., (© 2022 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)