Widespread Distribution of Xylazine Detected Throughout the United States in Healthcare Patient Samples.

OBJECTIVES: Xylazine is a tranquilizer commonly added into the illicit drug supply and a likely contributor to overdoses because it does not respond to naloxone reversal. The objective of this study was to perform a retrospective data analysis on xylazine-positive samples collected from patients in various outpatient healthcare settings to illustrate geographic distribution and common copositive substances, which may also contribute to risk of adverse events. METHODS: Samples for which providers ordered testing for xylazine were subjected to enzymatic hydrolysis, extracted, and analyzed using liquid chromatography-tandem mass spectrometry. Retrospective analysis was performed on xylazine-positive samples collected from April 2021 to March 2022, to include geographic location and copositive substances. RESULTS: Xylazine was identified in 413 of 59,498 samples from adults aged 20-73 years and originated from 25 of the 39 states where xylazine testing was ordered. The most common routine substances detected with xylazine were fentanyl, buprenorphine, naloxone, cocaine, d -methamphetamine, and delta-9-tetrahydrocannabinol. The most common designer drugs detected included fentanyl analogs, isotonitazene, and designer benzodiazepines. CONCLUSIONS: Xylazine is geographically spread throughout the United States, indicative of a wide incorporation into the illicit drug supply. These findings differ from previous studies in that these samples originated from healthcare providers in routine care settings, where other reports typically involve overdose deaths. This analysis illustrates that routine testing for xylazine in outpatient settings can afford providers the opportunity to educate individuals and adjust harm reduction measures to potentially mitigate overdose risk.

Randomized prospective trial to detect and distinguish between medication nonadherence, drug-drug interactions, and disease progression in chronic cardiometabolic disease.

BACKGROUND: Disentangling nonadherence (NA), drug-drug interactions (DDIs), and disease progression from each other is an important clinical challenge for providers caring for patients with cardiometabolic diseases. NAs and DDIs are both ubiquitous and often overlooked. We studied a novel chronic disease management (CDM) test to detect medication adherence and the presence and severity of DDIs. MATERIALS AND METHODS: We conducted a prospective, randomized controlled trial of 236 primary care physicians using computer-based, simulated patients, measuring clinical care with and without access to the CDM test. The primary outcomes were whether use of the CDM test increased the accuracy of diagnoses and ordering better treatments and how effective the intervention materials were in getting participants to order the CDM test. RESULTS: Physicians given the CDM test results showed a + 13.2% improvement in their diagnosis and treatment quality-of-care scores (p < 0.001) in the NA patient cases and a + 13.6% improvement in the DDI cases (p < 0.001). The difference-in-difference calculations between the intervention and control groups were + 10.4% for NA and + 10.8% for DDI (p < 0.01 for both). After controlling for physician and practice co-factors, intervention, compared to control, was 50.4x more likely to recognize medication NA and 3.3x more likely to correctly treat it. Intervention was 26.9x more likely to identify the DDI and 15.7x more likely to stop/switch the interacting medication compared to control. We found no significant improvements for the disease progression patient cases. CONCLUSION: Distinguishing between nonadherence, drug-drug interactions, and disease progression is greatly improved using a reliable test, like the CDM test; improved diagnostic accuracy and treatment has the potential to improve patient quality of life, medication safety, clinical outcomes, and efficiency of health delivery. TRIAL REGISTRATION: clinicaltrials.gov (NCT05192590).

Estimated BNT162b2 Vaccine Effectiveness Against Infection With Delta and Omicron Variants Among US Children 5 to 11 Years of Age.

Importance: Data describing the vaccine effectiveness (VE) and durability of BNT162b2 among children 5 to 11 years of age are needed. Objective: To estimate BNT162b2 VE against SARS-CoV-2 infection among children aged 5 to 11 years during Delta and Omicron variant-predominant periods and to further assess VE according to prior SARS-CoV-2 infection status and by sublineage during the Omicron variant-predominant period. Design, Setting, and Participants: This test-negative case-control study was conducted from November 2 to December 9, 2021 (Delta variant), and from January 16 to September 30, 2022 (Omicron variant), among 160 002 children tested at a large national US retail pharmacy chain, for SARS-CoV-2 via polymerase chain reaction (PCR); 62 719 children were tested during the Delta period, and 97 283 were tested during the Omicron period. Exposure: Vaccination with BNT162b2 before SARS-CoV-2 testing vs no vaccination. Main Outcomes and Measures: The primary outcome was SARS-CoV-2 infection confirmed by PCR (regardless of the presence of symptoms), and the secondary outcome was confirmed symptomatic infection. Adjusted estimated VE was calculated from multilevel logistic regression models. Results: A total of 39 117 children tested positive and 131 686 tested negative for SARS-CoV-2 (total, 170 803; 84 487 [49%] were boys; mean [SD] age was 9 [2] years; 74 236 [43%] were White non-Hispanic or non-Latino; and 37 318 [22%] were Hispanic or Latino). Final VE analyses included 160 002 children without SARS-CoV-2 infection less than 90 days prior. The VE of 2 doses of BNT162b2 against Delta was 85% (95% CI, 80%-89%; median follow-up, 1 month) compared with the Omicron period (20% [95% CI, 17%-23%]; median follow-up, 4 months). The adjusted VE of 2 doses against Omicron at less than 3 months was 39% (95% CI, 36%-42%), and at 3 months or more, it was -1% (95% CI, -6% to 3%). Protection against Omicron was higher among children with vs without infection 90 days or more prior but decreased in all children approximately 3 months after the second dose (58% [95% CI, 49%-66%] with infection vs 37% [95% CI, 34%-41%] without infection at <3 months; 27% [95% CI, 17%-35%] with infection vs -7% [95% CI, -12% to -1%] at ≥3 months without infection). The VE of 2 doses of BNT162b2 at less than 3 months by Omicron sublineage was 40% (95% CI, 36%-43%) for BA.1, 32% (95% CI, 21%-41%) for BA.2/BA.2.12.1, and 50% (95% CI, 37%-60%) for BA.4/BA.5. After 3 months or more, VE was nonsignificant for BA.2/BA.2.12.1 and BA.4/BA.5. The VE of a booster dose was 55% (95% CI, 50%-60%) against Omicron, with no evidence of waning at 3 months or more. Conclusions and Relevance: This study suggests that, among children aged 5 to 11 years, 2 doses of BNT162b2 provided modest short-term protection against Omicron infection that was higher for those with prior infection; however, VE waned after approximately 3 months in all children. A booster dose restored protection against Omicron and was maintained for at least 3 months. These findings highlight the continued importance of booster vaccination regardless of history of prior COVID-19.

Validation of reduced S-gene target performance and failure for rapid surveillance of SARS-CoV-2 variants.

SARS-CoV-2, the virus that causes COVID-19, has many variants capable of rapid transmission causing serious illness. Timely surveillance of new variants is essential for an effective public health response. Ensuring availability and access to diagnostic and molecular testing is key to this type of surveillance. This study utilized reverse transcription polymerase chain reaction (RT-PCR) and whole genome sequencing results from COVID-19-positive patient samples obtained through a collaboration between Aegis Sciences Corporation and Walgreens Pharmacy that has conducted more than 8.5 million COVID-19 tests at ~5,200 locations across the United States and Puerto Rico. Viral evolution of SARS-CoV-2 can lead to mutations in the S-gene that cause reduced or failed S-gene amplification in diagnostic PCR tests. These anomalies, labeled reduced S-gene target performance (rSGTP) and S-gene target failure (SGTF), are characteristic of variants carrying the del69-70 mutation, such as Alpha and Omicron (B.1.1.529, BA.1, and BA.1.1) lineages. This observation has been validated by whole genome sequencing and can provide presumptive lineage data following completion of diagnostic PCR testing in 24-48 hours from collection. Active surveillance of trends in PCR and sequencing results is key to the identification of changes in viral transmission and emerging variants. This study shows that rSGTP and SGTF can be utilized for near real-time tracking and surveillance of SARS-CoV-2 variants, and is superior to the use of SGTF alone due to the significant proportion of Alpha and Omicron (B.1.1.529, BA.1, and BA.1.1) lineages known to carry the del69-70 mutation and observed to have S-gene amplification. Adopting new tools and techniques to both diagnose acute infections and expedite identification of emerging variants is critical to supporting public health.

Clinical Variation in the Treatment Practices for Medication Nonadherence, Drug-Drug Interactions, and Recognition of Disease Progression in Patients with Chronic Cardiometabolic Diseases: A Cross-Sectional Patient Simulation Study among Primary Care Physicians.

Background: Medication nonadherence in patients with chronic diseases is common, costly, and often underdiagnosed. In the United States, approximately 40-50% of patients with cardiometabolic conditions are not adherent to long-term medications. Drug-drug interactions (DDI) are also underrecognized and may lead to medication nonadherence in this patient population. Treatment complexity associated with cardiometabolic conditions contributes to increased risk for adverse drug events and DDIs. Methods: We recruited a nationally representative sample of 246 board-certified family and internal medicine physicians to evaluate how they assessed, identified, and treated medication nonadherence, DDIs, and worsening disease. Participating physicians were asked to care for three online simulated patients, each with at least one chronic cardiometabolic disease, including atrial fibrillation, heart failure, diabetes mellitus, or hypertension, and who were taking prescription medications for their disease. Physicians' scores were based on evidence-based care recommendation criteria, including overall care quality and treatment for medication nonadherence and DDIs. Results: Overall, quality-of-care scores across all cases ranged from 13% to 87% with an average of 50.8% ± 12.1%. The average overall diagnostic plus treatment score was 21.9% ± 13.6%. Participants identified nonadherence in just 3.6% of cases, DDIs in 8.9% of cases, and disease progression in 30.3% of cases. Conclusions: Based on these study results, primary care physicians were unable to adequately diagnose and treat patients with chronic cardiometabolic diseases who either suffered from medication nonadherence, DDIs, or progression of the disease. Improved standardization and technique in identifying these diagnoses is needed in primary care. Trial Registration. This trial is registered with clinicaltrials.gov, NCT05192590.

Randomized Trial to Improve Primary Care Patient Management and Patient Outcomes Using a Drug-Drug Interaction Test: Confirmation of the DECART Simulated Patient Clinical Utility Trial Results.

Drug-drug interactions (DDIs) are a serious problem in the healthcare system, leading to excess healthcare utilization and costs. We conducted a second prospective randomized, controlled trial to further establish the real-world clinical utility of a novel assay that objectively identifies potentially serious DDIs in real-world patients. Re-recruiting primary care physicians (PCPs) from our first randomized, controlled, simulated-patients study on DDIs, we experimentally introduced a definitive, urine-based mass spectrometry test intervention that the physicians could use when caring for their eligible patients. Patients were eligible if taking four or more prescription medications or suspected of taking other non-prescribed substances with potential medication interactions. The primary outcome was whether DDI testing changed clinical care. We explored a secondary outcome to see if the change in practice improved symptoms in patients with potential DDIs. A total of 169 control and 162 intervention patients were enrolled in the study, and their medical records were abstracted. In real-world patients, intervention physicians identified and/or treated a DDI at 3.0x the rate in their patient population compared to controls (21.6% vs. 7.1%, p < 0.001). Intervention physicians were more likely to discontinue or adjust the interacting agent compared to controls (62.9% vs. 8.3%, p = 0.001), and patient-reported symptoms also significantly declined (29.6% vs. 20.1%, p = 0.045). These results were nearly identical to concurrent measurements that used simulated patients, wherein intervention was more likely to both make a DDI diagnosis (56.3% vs. 21.6%, p < 0.001) and stop the interacting medications (58.3% versus 26.6%, p < 0.001). Bringing a new diagnostic test to market, particularly for an under-recognized clinical problem, requires robust data on both clinical validity and clinical utility. The results of this follow-up study showed that the use of DDI testing in real-world patients significantly improved (1) primary care patient management of drug interactions and (2) patient outcomes.

Impact of Definitive Drug-Drug Interaction Testing on Medication Management and Patient Care.

BACKGROUND AND OBJECTIVE: Aegis Sciences Corporation developed a test (InterACT Rx™) that objectively and definitively identifies substances known to interact with drug-drug interaction-prone medications commonly prescribed in the treatment of chronic pain and behavioral health disorders. The objective of this study was to assess the severity of identified drug-drug interactions, the reduction in the frequency and severity of identified drug-drug interactions, and the impact of the test on healthcare utilization. METHODS: Patients with chronic pain, behavioral health disorders, or both who had one or more drug-drug interaction tests and one or more drug-drug interactions identified in the study period were included. Drug-drug interaction test results described the number and severity of interactions and detected substances involved in drug-drug interactions. Patients' electronic medical records were obtained to analyze outpatient visits and prescription medications. The cost of outpatient visits was based on the Medicare Physician Fee Schedule. Outcomes were compared between the pre- and post-study index periods to determine the impact of the drug-drug interaction test on patient care. RESULTS: A total of 262 patients were included. The majority of drug-drug interactions detected (77.9%) at index were of moderate severity. The number of monthly all-cause and pain-related outpatient visits was reduced in the post-index period compared with the pre-index period (0.74-0.54 and 0.69-0.49, respectively). Associated costs were reduced from US$64.92 to US$51.20, and from US$62.42 to US$47.62, (p < 0.0001 for both) for all-cause and pain-related outpatient visits, respectively. Follow-up drug-drug interaction testing for 43 patients revealed that previously reported drug-drug interactions at the index test were no longer identified in the subsequent test for 39.5% of patients. CONCLUSIONS: Employing a definitive test to detect substances whose interactions may cause adverse drug events can enhance a provider's insights, drive clinical decision making, and improve patient outcomes.

Drug-Drug Interaction Assessment and Identification in the Primary Care Setting.

BACKGROUND: Drug-drug interactions (DDIs) are ubiquitous, harmful and a leading cause of morbidity and mortality. With an aging population, growth in polypharmacy, widespread use of supplements, and the rising opioid abuse epidemic, primary care physicians (PCPs) are increasingly challenged with identifying and preventing DDIs. We set out to evaluate current clinical practices related to identifying and treating DDIs and to determine if opportunities to increase prevention of DDIs and their adverse events could be identified. METHODS: In a nationally representative sample of 330 board-certified family and internal medicine practitioners, we evaluated whether PCPs assessed DDIs in the care they provided for three simulated patients. The patients were taking common prescription medications (e.g. opioids and psychiatric medications) along with other common ingestants (e.g. supplements and food) and presented with symptoms of DDIs. Physicians were scored on their ability to inquire about the patient's medications, investigate possible DDIs, evaluate the patient, and provide treatment recommendations. We scored the physicians' care recommendations against evidence-based criteria, including overall care quality and treatment for DDIs. RESULTS: Average overall quality of care score was 50.5% ± 12.0%. Despite >99% self-reported use of medication reconciliation practices and tools, physicians identified DDIs in only 15.3% of patients, with 15.5% ± 20.3% of DDI-specific treatment by the physicians. CONCLUSIONS: PCPs in this study did not recognize or adequately treat DDIs. Better methods are needed to screen for DDIs in the primary care setting.

Clinical Utility of Definitive Drug⁻Drug Interaction Testing in Primary Care.

Drug⁻drug interactions (DDIs) are a leading cause of morbidity and mortality. New tools are needed to improve identification and treatment of DDIs. We conducted a randomized controlled trial to assess the clinical utility of a new test to identify DDIs and improve their management. Primary care physicians (PCPs) cared for simulated patients presenting with DDI symptoms from commonly prescribed medications and other ingestants. All physicians, in either control or one of two intervention groups, cared for six patients over two rounds of assessment. Intervention physicians were educated on the DDI test and given access to these test reports when caring for their patients in the second round. At baseline, we saw no significant differences in making the DDI diagnosis (p = 0.071) or DDI-related treatment (p = 0.640) between control and intervention arms. By round two, providers who accessed the DDI test performed significantly better in making the DDI diagnosis (+41.6%) and performing DDI-specific treatment (+12.2%) than in the previous round, and were 9.8 and 20.4 times more likely to diagnose and identify the DDI (p < 0.001 for all). The introduction of a definitive DDI test significantly increased identification, appropriate management, and counseling of DDIs among PCPs, which has the potential to improve clinical care.

Characterization of drug-drug interactions in patients whose substance intake was objectively identified by detection in urine.

BACKGROUND: Identification of drug-drug interactions (DDIs) typically relies on patient medication lists which are prone to inaccuracies. This study describes use of a mass spectrometry test to detect recently ingested substances in urine with subsequent identification of DDIs. RESEARCH DESIGN AND METHODS: This was a retrospective analysis of the prevalence of DDIs identified in patients with chronic pain, addiction and/or behavioral health conditions in the U.S. Relationships between patient demographics, polypharmacy and the occurrence of DDIs were also described. RESULTS: Of 15,004 patients, 2964 (20%) had a DDI identified. There was a positive association between the number of substances detected in urine and the number of interactions identified (r = 0.5033, p-value = 0.0001). Of patients with polypharmacy, 15.6% had contraindicated or severe interactions identified compared to only 3.2% of those without polypharmacy. For polypharmacy patients, the youngest population studied had a much higher likelihood of having one or more DDIs identified compared to the other age groups (p-value = 0.0002). CONCLUSIONS: By utilizing a mass spectrometry test to objectively detect recently ingested substances followed by identification of DDIs, healthcare providers may be able to better characterize the true incidence of DDIs. Study findings may not be generalizable to healthcare populations outside of pain management, addiction treatment, and behavioral health.