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Background: Identifying and monitoring adverse effects (AEs) are integral to ensuring patient safety in clinical trials. Research sponsors and regulatory bodies have put into place a variety of policies and procedures to guide researchers in protecting patient safety during clinical trials. However, it remains unclear how these policies and procedures should be adapted for trials in implementation science. As a starting point, we develop a conceptual model that traces causal pathways leading from implementation strategies to AEs, propose a definition and classification of such effects, and provide recommendations for monitoring and oversight., Main Text: We propose four major types of adverse effects for implementation trials. First, we characterize implementation strategies that lead to "proper use" of an intervention that align with AEs as conceptualized and reported in clinical trials. Second, we characterize a strategy's AEs mediated through "misuse" which involves inappropriate utilization of an evidence-based intervention (EBI). Third, we characterize a strategy which focuses on one EBI and may inadvertently cause the inappropriate discontinuation or "disuse" of other EBIs already in place, thus inducing AEs. Finally, we characterize strategies that may cause AEs by reducing the use of an EBI in the target population (i.e., "nonuse"). Based on these considerations, we propose an extended definition of adverse effects that includes harms that are causally related to implementation strategies, termed Implementation strategy Adverse Effects (IAEs). We recommend researchers, oversight committees, sponsors, and other stakeholders work together prior to trials to determine the best approaches for identifying, monitoring, and reporting IAEs., Conclusions: In this paper, we develop a conceptual model to identify four types of AEs in implementation trials clarifying the mechanisms linking implementation strategies to patterns of use of the EBI and potential patient-level harms. We propose a new definition that links implementation strategies to AEs that can be used to guide conceptualization, monitoring, and oversight of potential harms in future implementation trials. Our work represents an important step towards understanding adverse effects in implementation trials and lays the groundwork for future advancement in the conceptualization of other types of adverse effects (e.g., harms to providers) encountered in implementation trials., Competing Interests: Declaration of Competing Interest MDH has received travel support from the World Heart Federation and consulting fees from PwC Switzerland. MDH has an appointment at The George Institute for Global Health, which has a patent, license, and has received investment funding with intent to commercialize fixed-dose combination therapy through its social enterprise business, George Medicines. The other authors declare that they have no competing interests., (Copyright © 2025 Elsevier Inc. All rights reserved.)

Background: The management and outcomes of nontuberculous mycobacterial (NTM) infections in solid organ transplant (SOT) recipients are poorly characterized. We aimed to describe the management and 1-y mortality of these patients., Methods: Retrospective, multinational, 1:2 matched case-control study included SOT recipients aged 12 y old or older diagnosed with NTM infection between January 1, 2008, and December 31, 2018. Controls were matched on transplanted organs, NTM treatment center, and posttransplant survival at least equal to the time to NTM diagnosis. The primary aim was 1-y mortality after NTM diagnosis. Differences between cases and controls were compared using the log-rank test, and Cox regression models were used to identify factors associated with mortality at 12 mo among cases., Results: In 85 patients and 169 controls, the median age at the time of SOT was 54 y (interquartile range, 40-62 y), 59% were men, and the lungs were the most common site of infection after SOT (57.6%). One-year mortality was significantly higher in cases than in controls (20% versus 3%; P < 0.001), and higher mortality was associated with lung transplantation (hazard ratio 3.27; 95% confidence interval [1.1-9.77]; P = 0.034). Median time (interquartile range) from diagnosis to treatment initiation (20 [4-42] versus 11 [3-21] d) or the reduction of net immunosuppression (36% versus 45%, hazard ratio 1.35 [95% CI, 0.41-4.43], P = 0.618) did not differ between survivors and those who died., Conclusions: NTM disease in SOT recipients is associated with a higher mortality risk, especially among lung transplant recipients. Time to NTM treatment and reduction in net immunosuppression were not associated with mortality., Competing Interests: The authors declare no funding or conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

In a new respiratory virus pandemic, optimizing allocation of scarce medical resources becomes an urgent challenge. Infection prognosis takes on particular importance when allocating scarce antiviral antibodies and drugs, which are most effective when administered before the onset of severe disease. During arrival of the COVID-19 pandemic to the United States in 2020, we conducted a prognostic biomarker discovery and validation effort based upon metabolomic profiling with a liquid-chromatography-mass spectrometer (LC-MS) type used clinically for rapid toxicology. We obtained urine specimens from 163 patients presenting for evaluation. We obtained LC-MS profiles in the initial cohort and used machine learning methods to define a simplified urine metabolomic signature associated with respiratory failure or death by 90 days. This signature was composed of three metabotypes linked to intestinal microbiome metabolism and anticonvulsant use, with a receiver-operator characteristic area under the curve (ROC AUC) of 89.4%. Blinded application of this signature to the subsequent validation cohort yielded a ROC AUC of 81.2%. A model trained on the two baseline metabotypes present before intubation exhibited similar performance in the validation cohort. This study demonstrates the plausibility and promise of rapid metabolome-based prognostic discovery and validation in the opening wave of a pandemic. The approach used here could be used to inform therapeutic and resource allocation decisions early in a future epidemic.IMPORTANCEIn a new respiratory virus pandemic, the ability to identify patients at greatest risk for severe disease is essential to direct scarce medical resources to those most likely to benefit from them. Tools to predict disease severity are best developed early in a pandemic, but laboratory-based resources to develop these may be limited by available technology and by infection precautions. Here, we show that an accessible metabolic profiling approach could identify a prognostic signature of severe disease in the initial wave of COVID-19, when patients presenting for care often exceeded the available doses of convalescent plasma and remdesivir. In a future pandemic, this approach, alongside efforts to identify clinical disease severity predictors, could improve patient outcomes and facilitate therapeutic trials by identifying individuals at high risk for severe disease., Competing Interests: The authors declare no conflict of interest.

Background: Recipients of health services value not only convenience but also respectful, kind, and helpful providers. To date, research to improve person-centred HIV treatment has focused on making services easier to access (eg, differentiated service delivery) rather than the interpersonal experience of care. We developed and evaluated a person-centred care (PCC) intervention targeting practices of health-care workers., Methods: Using a stepped-wedge, cluster-randomised design, we randomly allocated 24 HIV clinics stratified by size in Zambia into four groups and introduced a PCC intervention that targeted caring aspects of the behaviour of health-care workers in one group every 6 months. The intervention entailed training and coaching for health-care workers on PCC practices (to capacitate), client experience assessment with feedback to facilities (to create opportunities), and small performance-based incentives (to motivate). In a probability sample of clients who were pre-trained on a client experience exit survey and masked to facility intervention status, we evaluated effects on client experience by use of mean score change and also proportion with poor encounters (ie, score of ≤8 on a 12-point survey instrument). We examined effects on missed visits (ie, >30 days late for next scheduled encounter) in all groups and retention in care at 15 months in group 1 and group 4 by use of electronic health records. We assessed effects on treatment success at 15 months (ie, HIV RNA concentration <400 copies per mL or adjudicated care status) in a prospectively enrolled subset of clients from group 1 and group 4. We estimated treatment effects with mixed-effects logistic regression, adjusting for sex, age, and baseline care status. This trial is registered at the Pan-African Clinical Trials Registry (202101847907585), and is completed., Findings: Between Aug 12, 2019, and Nov 30, 2021, 177 543 unique clients living with HIV made at least one visit to one of the 24 study clinics. The PCC intervention reduced the proportion of poor visits based on exit surveys from 147 (23·3%) of 632 during control periods to 33 (13·3%) of 249 during the first 6 months of intervention, and then to eight (3·5%) of 230 at 6 months or later (adjusted risk difference [aRD] for control vs ≥6 months intervention -16·9 percentage points, 95% CI -24·8 to -8·9). Among all adult scheduled appointments, the PCC intervention reduced the proportion of missed visits from 90 593 (25·3%) of 358 741 during control periods to 40 380 (22·6%) of 178 523 in the first 6 months, and then 52 288 (21·5%) of 243 350 at 6 months or later (aRD for control vs the intervention -4·2 percentage points, 95% CI -4·8 to -3·7). 15-month retention improved from 33 668 (80·2%) of 41 998 in control to 35 959 (83·6%) of 43 005 during intervention (aRD 5·9 percentage points, 95% CI 0·6 to 11·2), with larger effects in clients newly starting treatment (aRD 12·7 percentage points, 1·4 to 23·9). We found no effect on treatment success (based on viral load) in a nested subcohort (379 [83·7%] of 453 in the control phase vs 402 [83·8%] of 480 in the intervention phase; aRD 0·9 percentage points, -5·4 to 7·2)., Interpretation: Improving the caring aspects of health-care worker behaviour is feasible in public health settings, enhances client experience, reduces missed appointments, and increases retention., Funding: The Bill & Melinda Gates Foundation., Competing Interests: Declaration of interests AM and EHG report funding from the US National Institutes of Health during the conduct of this study. CBH reports grants from the Gates Foundation, outside the submitted work. CBH reports consulting for the Bill & Melinda Gates Medical Research Institute. EHG receives educational grants from ViiV Healthcare, outside the submitted work. AM has received funding from Gilead, outside the submitted work. IE-W is an employee of Johnson & Johnson and receives a salary and stock. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)