Treatment Failure

IntroductionExtracorporeal membrane oxygenation (ECMO) is a supportive therapy, with its success dependent on effective drug therapy that reverses the pathology and/or normalizes physiology. However, the circuit that sustains life can also sequester life-saving drugs, thereby compromising the role of ECMO as a temporary support device. This ex vivo study was designed to determine the degree of sequestration of commonly used antibiotics, sedatives and analgesics in ECMO circuits.MethodsFour identical ECMO circuits were set up as per the standard protocol for adult patients on ECMO. The circuits were primed with crystalloid and albumin, followed by fresh human whole blood, and were maintained at a physiological pH and temperature for 24 hours. After baseline sampling, fentanyl, morphine, midazolam, meropenem and vancomycin were injected into the circuit at therapeutic concentrations. Equivalent doses of these drugs were also injected into four polyvinylchloride jars containing fresh human whole blood for drug stability testing. Serial blood samples were collected from the ECMO circuits and the controls over 24 hours and the concentrations of the study drugs were quantified using validated assays.ResultsFour hundred samples were analyzed. All study drugs, except meropenem, were chemically stable. The average drug recoveries from the ECMO circuits and the controls at 24 hours relative to baseline, respectively, were fentanyl 3% and 82%, morphine 103% and 97%, midazolam 13% and 100%, meropenem 20% and 42%, vancomycin 90% and 99%. There was a significant loss of fentanyl (p = 0.0005), midazolam (p = 0.01) and meropenem (p = 0.006) in the ECMO circuit at 24 hours. There was no significant circuit loss of vancomycin at 24 hours (p = 0.26).ConclusionsSequestration of drugs in the circuit has implications on both the choice and dosing of some drugs prescribed during ECMO. Sequestration of lipophilic drugs such as fentanyl and midazolam appears significant and may in part explain the increased dosing requirements of these drugs during ECMO. Meropenem sequestration is also problematic and these data support a more frequent administration during ECMO.

BackgroundLong-acting (LA) injectable therapy with cabotegravir (CAB) and rilpivirine (RPV) is currently used as maintenance treatment for human immunodeficiency virus type 1, and has a low risk for virological failure (VF). Although the risk is low, the circumstances and impact of VF in the real-world setting merit further evaluation.MethodsWe performed an in-depth clinical, virological, and pharmacokinetic analysis on the reasons behind and the impact of VF during LA CAB/RPV therapy in 5 cases from the Netherlands. Genotypic resistance testing was performed after the occurrence of VF, and drug plasma (trough) concentrations were measured after VF was established and on any other samples to assess on-treatment drug levels. CAB and RPV drug levels that were below the first quartile of the population cutoff (≤Q1) were considered to be low.ResultsFive cases who were eligible for LA CAB/RPV experienced VF despite a low predicted risk at baseline. Genotypic resistance testing revealed extensive selection of nonnucleoside reverse transcriptase inhibitor-associated mutations in all cases, and integrase strand transfer inhibitor mutations in 4 cases. All cases displayed low drug levels of either CAB, RPV, or both during the treatment course, likely contributing to the occurrence of VF. In 3 cases, we were able to identify the potential mechanisms behind these low drug levels.ConclusionsThis is the first in-depth multiple case analysis of VF on LA CAB/RPV therapy in a real-world setting. Our observations stress the need to be aware for (evolving) risk factors and the yield of a comprehensive clinical, virological, and pharmacokinetic approach in case of failure.

Rheumatoid arthritis (RA) is an autoimmune disorder characterized by inflammation and bone erosion. The exact mechanism of RA is still unknown, but various immune cytokines, signaling pathways and effector cells are involved. Disease-modifying antirheumatic drugs (DMARDs) are commonly used in RA treatment and classified into different categories. Nevertheless, RA treatment is based on a "trial-and-error" approach, and a substantial proportion of patients show failed therapy for each DMARD. Over the past decades, great efforts have been made to overcome treatment failure, including identification of biomarkers, exploration of the reasons for loss of efficacy, development of sequential or combinational DMARDs strategies and approval of new DMARDs. Here, we summarize these efforts, which would provide valuable insights for accurate RA clinical medication. While gratifying, researchers realize that these efforts are still far from enough to recommend specific DMARDs for individual patients. Precision medicine is an emerging medical model that proposes a highly individualized and tailored approach for disease management. In this review, we also discuss the potential of precision medicine for overcoming RA treatment failure, with the introduction of various cutting-edge technologies and big data.

ImportanceFailure to rescue (FTR), defined as postoperative mortality among patients with treatable complications, is a recognized patient safety concern. FTR reflects institutional capacity for timely management of deterioration and has been proposed as a quality indicator less dependent on baseline complication risk. Evidence on systematic hospital-level variation outside the US remains limited.ObjectiveTo estimate national postoperative FTR rates, quantify between-hospital variation, and identify hospitals with better- or worse-than-expected performance using risk-standardized mortality ratios (RSMRs).Design, setting, and participantsThis retrospective cohort study conducted in Switzerland applied the Agency for Healthcare Research and Quality (AHRQ) patient safety indicator 04 (PSI04) definition to administrative hospital data to all acute-care hospitals in Switzerland from January 2019 to December 2023. Participants included surgical inpatients with at least 1 PSI04-defined complication (ie, deep vein thrombosis and/or pulmonary embolism, pneumonia, sepsis, shock and/or cardiac arrest, and gastrointestinal hemorrhage and/or ulcer). Hospital-level variation was assessed using multilevel logistic regression with hospital random intercepts and summarized with RSMRs. Alternative models were estimated to explore the stability of results.ExposureAcute care hospitalization.Main outcomes and measuresIn-hospital mortality following eligible complications, expressed as crude FTR rates and RSMRs. The intraclass correlation coefficient quantified systematic performance variation.ResultsAmong 41 506 inpatients undergoing surgery with PSI04-defined complications (mean [SD] age, 67.6 [14.8] years; 24 692 [59.5%] men), 7310 in-hospital deaths occurred. The crude national FTR rate was 18.07 (95% CI, 17.66-18.50) of 100 admissions. In 61 hospitals with at least 100 cases, adjusted odds ratio for death varied between the lowest- and highest-performing hospitals from 0.56 (95% CI, 0.38-0.80) to 1.75 (95% CI, 1.59-1.92). Hospital-level variance was 0.114 (intraclass correlation coefficient, 0.034; 95% CI, 0.020-0.055). An estimated 1045 of 7114 observed FTR deaths (14.7%) within the hospital sample were attributable to below-average hospital performance. Five hospitals (8.2%) performed significantly better than expected, 42 (68.9%) as expected, and 14 (23.0%) substantially worse than expected based on RSMR 95% CIs. Poorer performance clustered in medium- and high-volume hospitals. Alternative regression models confirmed stability of results.Conclusions and relevanceIn this cross-sectional study of FTR, nearly 1 in 5 patients undergoing surgery who experienced serious complications died, with substantial between-hospital variation. Multilevel modeling indicated that institutional performance accounted for 1045 potentially avoidable deaths. These findings support FTR as an international patient safety indicator and highlight the need to investigate organizational determinants of variation to inform system-level improvement strategies.