Predictability of buprenorphine-naloxone treatment retention: A multi-site analysis combining electronic health records and machine learning.

BACKGROUND AND AIMS: Opioid use disorder (OUD) and opioid dependence lead to significant morbidity and mortality, yet treatment retention, crucial for the effectiveness of medications like buprenorphine-naloxone, remains unpredictable. Our objective was to determine the predictability of 6-month retention in buprenorphine-naloxone treatment using electronic health record (EHR) data from diverse clinical settings and to identify key predictors. DESIGN: This retrospective observational study developed and validated machine learning-based clinical risk prediction models using EHR data. SETTING AND CASES: Data were sourced from Stanford University's healthcare system and Holmusk's NeuroBlu database, reflecting a wide range of healthcare settings. The study analyzed 1800 Stanford and 7957 NeuroBlu treatment encounters from 2008 to 2023 and from 2003 to 2023, respectively. MEASUREMENTS: Predict continuous prescription of buprenorphine-naloxone for at least 6 months, without a gap of more than 30 days. The performance of machine learning prediction models was assessed by area under receiver operating characteristic (ROC-AUC) analysis as well as precision, recall and calibration. To further validate our approach's clinical applicability, we conducted two secondary analyses: a time-to-event analysis on a single site to estimate the duration of buprenorphine-naloxone treatment continuity evaluated by the C-index and a comparative evaluation against predictions made by three human clinical experts. FINDINGS: Attrition rates at 6 months were 58% (NeuroBlu) and 61% (Stanford). Prediction models trained and internally validated on NeuroBlu data achieved ROC-AUCs up to 75.8 (95% confidence interval [CI] = 73.6-78.0). Addiction medicine specialists' predictions show a ROC-AUC of 67.8 (95% CI = 50.4-85.2). Time-to-event analysis on Stanford data indicated a median treatment retention time of 65 days, with random survival forest model achieving an average C-index of 65.9. The top predictor of treatment retention identified included the diagnosis of opioid dependence. CONCLUSIONS: US patients with opioid use disorder or opioid dependence treated with buprenorphine-naloxone prescriptions appear to have a high (∼60%) treatment attrition by 6 months. Machine learning models trained on diverse electronic health record datasets appear to be able to predict treatment continuity with accuracy comparable to that of clinical experts.

Open-Top Patterned Hydrogel-Laden 3D Glioma Cell Cultures for Creation of Dynamic Chemotactic Gradients to Direct Cell Migration.

The laminar flow profiles in microfluidic systems coupled to rapid diffusion at flow streamlines have been widely utilized to create well-controlled chemical gradients in cell cultures for spatially directing cell migration. However, within hydrogel-based closed microfluidic systems of limited depth (≤0.1 mm), the biomechanical cues for the cell culture are dominated by cell interactions with channel surfaces rather than with the hydrogel microenvironment. Also, leaching of poly(dimethylsiloxane) (PDMS) constituents in closed systems and the adsorption of small molecules to PDMS alter chemotactic profiles. To address these limitations, we present the patterning and integration of a PDMS-free open fluidic system, wherein the cell-laden hydrogel directly adjoins longitudinal channels that are designed to create chemotactic gradients across the 3D culture width, while maintaining uniformity across its ∼1 mm depth to enhance cell-biomaterial interactions. This hydrogel-based open fluidic system is assessed for its ability to direct migration of U87 glioma cells using a hybrid hydrogel that includes hyaluronic acid (HA) to mimic the brain tumor microenvironment and gelatin methacrylate (GelMA) to offer the adhesion motifs for promoting cell migration. Chemotactic gradients to induce cell migration across the hydrogel width are assessed using the chemokine CXCL12, and its inhibition by AMD3100 is validated. This open-top hydrogel-based fluidic system to deliver chemoattractant cues over square-centimeter-scale areas and millimeter-scale depths can potentially serve as a robust screening platform to assess emerging glioma models and chemotherapeutic agents to eradicate them.

Trends in hallucinogen-associated emergency department visits and hospitalizations in California, USA, from 2016 to 2022.

BACKGROUND AND AIMS: Hallucinogens encompass a diverse range of compounds of increasing scientific and public interest. Risks associated with hallucinogen use are under-researched and poorly understood. We aimed to compare the trends in hallucinogen-associated health-care use with alcohol- and cannabis-associated health-care use. DESIGN, SETTING AND CASES: We conducted an ecological study with publicly available data on International Classification of Diseases, 10th Revision (ICD-10) diagnosis codes associated with emergency department (ED) visits and hospitalizations from the California Department of Healthcare Access and Information (HCAI). HCAI includes primary and secondary ICD-10 codes reported with ED or hospital discharge from every non-federal health-care facility licensed in California, United States, from 2016 to 2022. MEASUREMENTS: ICD-10 codes were classified as hallucinogen-, cannabis- or alcohol-associated if they were from the corresponding category in the ICD-10 block 'mental and behavioral disorders due to psychoactive substance use'. FINDINGS: Observed hallucinogen-associated ED visits increased by 54% between 2016 and 2022, from 2260 visits to 3476 visits, compared with a 20% decrease in alcohol-associated ED visits and a 15% increase in cannabis-associated ED visits. The observed hallucinogen-associated hospitalizations increased by 55% during the same period, from 2556 to 3965 hospitalizations, compared with a 1% increase in alcohol-associated hospitalizations and a 1% increase in cannabis-associated hospitalizations. This rise in hallucinogenic ED visits was significantly different from the trend in cannabis-associated (P < 0.001) and alcohol-associated (P = 0.005) ED visits. The hallucinogen-associated hospitalizations trend also significantly differed when compared with cannabis- (P < 0.001) and alcohol-associated (P < 0.001) hospitalizations. CONCLUSIONS: Hallucinogen-associated emergency department visits and hospitalizations in California, USA, showed a large relative but small absolute increase between 2016 and 2022.

Correlating Antibiotic-Induced Dysbiosis to Clostridioides difficile Spore Germination and Host Susceptibility to Infection Using an Ex Vivo Assay.

Antibiotic-induced microbiota disruption and its persistence create conditions for dysbiosis and colonization by opportunistic pathogens, such as those causing Clostridioides difficile (C. difficile) infection (CDI), which is the most severe hospital-acquired intestinal infection. Given the wide differences in microbiota across hosts and in their recovery after antibiotic treatments, there is a need for assays to assess the influence of dysbiosis and its recovery dynamics on the susceptibility of the host to CDI. Germination of C. difficile spores is a key virulence trait for the onset of CDI, which is influenced by the level of primary vs secondary bile acids in the intestinal milieu that is regulated by the microbiota composition. Herein, the germination of C. difficile spores in fecal supernatant from mice that are subject to varying degrees of antibiotic treatment is utilized as an ex vivo assay to predict intestinal dysbiosis in the host based on their susceptibility to CDI, as determined by in vivo CDI metrics in the same mouse model. Quantification of spore germination down to lower detection limits than the colony-forming assay is achieved by using impedance cytometry to count single vegetative bacteria that are identified based on their characteristic electrical physiology for distinction vs aggregated spores and cell debris in the media. As a result, germination can be quantified at earlier time points and with fewer spores for correlation to CDI outcomes. This sets the groundwork for a point-of-care tool to gauge the susceptibility of human microbiota to CDI after antibiotic treatments.

Field-Portable Microplastic Sensing in Aqueous Environments: A Perspective on Emerging Techniques.

Microplastics (MPs) have been found in aqueous environments ranging from rural ponds and lakes to the deep ocean. Despite the ubiquity of MPs, our ability to characterize MPs in the environment is limited by the lack of technologies for rapidly and accurately identifying and quantifying MPs. Although standards exist for MP sample collection and preparation, methods of MP analysis vary considerably and produce data with a broad range of data content and quality. The need for extensive analysis-specific sample preparation in current technology approaches has hindered the emergence of a single technique which can operate on aqueous samples in the field, rather than on dried laboratory preparations. In this perspective, we consider MP measurement technologies with a focus on both their eventual field-deployability and their respective data products (e.g., MP particle count, size, and/or polymer type). We present preliminary demonstrations of several prospective MP measurement techniques, with an eye towards developing a solution or solutions that can transition from the laboratory to the field. Specifically, experimental results are presented from multiple prototype systems that measure various physical properties of MPs: pyrolysis-differential mobility spectroscopy, short-wave infrared imaging, aqueous Nile Red labeling and counting, acoustophoresis, ultrasound, impedance spectroscopy, and dielectrophoresis.

Electronic cardiac arrest triage score best predicts mortality after intervention in patients with massive and submassive pulmonary embolism.

OBJECTIVE: To determine if the cardiac arrest triage (CART) Score would better predict poor outcomes after pharmacomechanical therapy (PMT) for massive and submassive pulmonary embolism (PE) than traditional risk scores BACKGROUND: PMT for massive and submassive PE allows for clot lysis with minimal doses of fibrinolytics. Although PMT results in improved right ventricular function, and reduced pulmonary pressures and thrombus burden, predictors of poor outcome are not well-studied. METHODS: We conducted a retrospective analysis of all patients who underwent PMT for massive or submassive PE at a single institution from 2010 to 2016. The CART score and electronic CART (eCART) score, derived previously as early warning scores for hospitalized patients, were compared to pulmonary embolism severity index (PESI) comparing the area under the receiver-operator characteristic curve (AUC) for predicting 30-day mortality. RESULTS: We studied 61 patients (56 ±17 years, 44.0% male, 29.5% massive PE, mean PESI 114.6 ± 42.7, mean CART 13.5 ± 1.39, mean eCART 108.5 ± 28.6). Thirty-day mortality was 24.6%. Treatments included rheolytic thrombectomy (32.7%), catheter-directed thrombolysis (50.8%), ultrasound-assisted thrombolysis (32.7%), and mechanical thrombectomy (4.9%). There were no differences in outcome based on technique. The eCART and CART scores had higher AUCs compared to PESI in predicting 30-day mortality (0.84 vs 0.72 vs 0.69, P = .010). We found troponin I and pro-BNP were higher in higher eCART tertiles, however AUCs were 0.51 and 0.63, respectively for 30-day mortality when used as stand-alone predictors. CONCLUSION: Compared to PESI score, CART and eCART scores better predict mortality in massive or submassive PE patients undergoing PMT.

Did the 1918 influenza cause the twentieth century cardiovascular mortality epidemic in the United States?

During most of the twentieth century, cardiovascular mortality increased in the United States while other causes of death declined. By 1958, the age-standardized death rate (ASDR) for cardiovascular causes for females was 1.84 times that for all other causes, combined (and, for males, 1.79×). Although contemporary observers believed that cardiovascular mortality would remain high, the late 1950s and early 1960s turned out to be the peak of a roughly 70-year epidemic. By 1988 for females (1986 for males), a spectacular decline had occurred, wherein the ASDR for cardiovascular causes was less than that for other causes combined. We discuss this phenomenon from a demographic point of view. We also test a hypothesis from the literature, that the 1918 influenza pandemic caused the cardiovascular mortality epidemic; we fail to find support.

Trappin ovine molecule (TOM), the ovine ortholog of elafin, is an acute phase reactant in the lung.

As large animal models continue to play an important role in translating lung-directed therapeutic strategies from laboratory animals to humans, there is an increasing interest in the analysis of endogenous regulators of inflammation at both a genomic and a therapeutic level. To this end, we have sought to characterize the ovine ortholog of elafin, an important regulator of inflammation in humans. We have isolated both the elafin cDNA and gene, which have a similar structure to other species' orthologs. Interestingly, we have isolated two alleles for ovine elafin, which contain a very high number of transglutamination repeats, thought to be important in binding elafin to the interstitium. The mainly mucosal mRNA distribution for ovine elafin suggests that ovine elafin may, like its human ortholog, have functions in innate immunity. This is supported by analysis of elafin and the related protein secretory leukocyte protease inhibitor (SLPI) in ovine bronchoalveolar fluid in response to locally administered lipopolysaccharide and confirmation of them acting as "alarm" antiproteases. We have also cloned the ovine elafin cDNA into an adenoviral vector and have demonstrated correct processing of the secreted protein as well as biological activity. Overexpression of ovine elafin in a lung-derived epithelial cell line has a protective effect against the enzymes human neutrophil and porcine pancreatic elastase. The identification of the ovine elafin gene and its translated protein are important in developing practical strategies aimed at regulating inflammation in the large mammalian lung.