Characterisation of digital therapeutic clinical trials: a systematic review with natural language processing.

Digital therapeutics (DTx) are a somewhat novel class of US Food and Drug Administration-regulated software that help patients prevent, manage, or treat disease. Here, we use natural language processing to characterise registered DTx clinical trials and provide insights into the clinical development landscape for these novel therapeutics. We identified 449 DTx clinical trials, initiated or expected to be initiated between 2010 and 2030, from ClinicalTrials.gov using 27 search terms, and available data were analysed, including trial durations, locations, MeSH categories, enrolment, and sponsor types. Topic modelling of eligibility criteria, done with BERTopic, showed that DTx trials frequently exclude patients on the basis of age, comorbidities, pregnancy, language barriers, and digital determinants of health, including smartphone or data plan access. Our comprehensive overview of the DTx development landscape highlights challenges in designing inclusive DTx clinical trials and presents opportunities for clinicians and researchers to address these challenges. Finally, we provide an interactive dashboard for readers to conduct their own analyses.

Mycobacterium chelonae lung disease masquerading as Mycobacterium tuberculosis in a TB endemic country.

Mycobacterium chelonae typically affect skin and soft tissue. Pleural involvement by this organism is exceedingly rare. A young female presented with persistent respiratory complaints along with constitutional symptoms. She had already been treated with standard anti-tubercular therapy with inadequate response and had a recent onset of worsening of her symptoms. A detailed evaluation revealed M. chelonae and she responded well to antimicrobials. We report a case of Mycobacterium chelonae lung disease in an immunocompetent patient and its successful management. High index of suspicion with a correct etiological diagnosis is the need of the hour in current era of drug resistance.

Second-Line Pharmaceutical Treatments for Patients with Type 2 Diabetes.

Importance: Assessing the relative effectiveness and safety of additional treatments when metformin monotherapy is insufficient remains a limiting factor in improving treatment choices in type 2 diabetes. Objective: To determine whether data from electronic health records across the University of California Health system could be used to assess the comparative effectiveness and safety associated with 4 treatments in diabetes when added to metformin monotherapy. Design, Setting, and Participants: This multicenter, new user, multidimensional propensity score-matched retrospective cohort study with leave-one-medical-center-out (LOMCO) sensitivity analysis used principles of emulating target trial. Participants included patients with diabetes receiving metformin who were then additionally prescribed either a sulfonylurea, dipeptidyl peptidase-4 inhibitor (DPP4I), sodium-glucose cotransporter-2 inhibitor (SGLT2I), or glucagon-like peptide-1 receptor agonist (GLP1RA) for the first time and followed-up over a 5-year monitoring period. Data were analyzed between January 2022 and April 2023. Exposure: Treatment with sulfonylurea, DPP4I, SGLT2I, or GLP1RA added to metformin monotherapy. Main Outcomes and Measures: The main effectiveness outcome was the ability of patients to maintain glycemic control, represented as time to metabolic failure (hemoglobin A1c [HbA1c] ≥7.0%). A secondary effectiveness outcome was assessed by monitoring time to new incidence of any of 28 adverse outcomes, including diabetes-related complications while treated with the assigned drug. Sensitivity analysis included LOMCO. Results: This cohort study included 31 852 patients (16 635 [52.2%] male; mean [SD] age, 61.4 [12.6] years) who were new users of diabetes treatments added on to metformin monotherapy. Compared with sulfonylurea in random-effect meta-analysis, treatment with SGLT2I (summary hazard ratio [sHR], 0.75 [95% CI, 0.69-0.83]; I2 = 37.5%), DPP4I (sHR, 0.79 [95% CI, 0.75-0.84]; I2 = 0%), GLP1RA (sHR, 0.62 [95% CI, 0.57-0.68]; I2 = 23.6%) were effective in glycemic control; findings from LOMCO sensitivity analysis were similar. Treatment with SGLT2I showed no significant difference in effectiveness compared with GLP1RA (sHR, 1.26 [95% CI, 1.12-1.42]; I2 = 47.3%; no LOMCO) or DPP4I (sHR, 0.97 [95% CI, 0.90-1.04]; I2 = 0%). Patients treated with DPP4I and SGLT2I had fewer cardiovascular events compared with those treated with sulfonylurea (DPP4I: sHR, 0.84 [95% CI, 0.74-0.96]; I2 = 0%; SGLT2I: sHR, 0.78 [95% CI, 0.62-0.98]; I2 = 0%). Patients treated with a GLP1RA or SGLT2I were less likely to develop chronic kidney disease (GLP1RA: sHR, 0.75 [95% CI 0.6-0.94]; I2 = 0%; SGLT2I: sHR, 0.77 [95% CI, 0.61-0.97]; I2 = 0%), kidney failure (GLP1RA: sHR, 0.69 [95% CI, 0.56-0.86]; I2 = 9.1%; SGLT2I: sHR, 0.72 [95% CI, 0.59-0.88]; I2 = 0%), or hypertension (GLP1RA: sHR, 0.82 [95% CI, 0.68-0.97]; I2 = 0%; SGLT2I: sHR, 0.73 [95% CI, 0.58-0.92]; I2 = 38.5%) compared with those treated with a sulfonylurea. Patients treated with an SGLT2I, vs a DPP4I, GLP1RA, or sulfonylurea, were less likely to develop indicators of chronic hepatic dysfunction (sHR vs DPP4I, 0.68 [95% CI, 0.49-0.95]; I2 = 0%; sHR vs GLP1RA, 0.66 [95% CI, 0.48-0.91]; I2 = 0%; sHR vs sulfonylurea, 0.60 [95% CI, 0.44-0.81]; I2 = 0%), and those treated with a DPP4I were less likely to develop new incidence of hypoglycemia (sHR, 0.48 [95% CI, 0.36-0.65]; I2 = 22.7%) compared with those treated with a sulfonylurea. Conclusions and Relevance: These findings highlight familiar medication patterns, including those mirroring randomized clinical trials, as well as providing new insights underscoring the value of robust clinical data analytics in swiftly generating evidence to help guide treatment choices in diabetes.

Coexistence of human immunodeficiency virus infection and autoimmune hepatitis: A double trouble.

A wide spectrum of hepatobiliary manifestations occur in Human Immunodeficiency Virus (HIV)-infected patients. Among the common causes are the infectious hepatitis, drug-related hepatitis, opportunistic infections, non-alcoholic steatohepatitis, HIV cholangiopathy and neoplasm. Auto-immune hepatitis (AIH) is rarely reported in this setting. We present two different presentations of auto immune hepatitis in HIV positive patients. One developed jaundice and ascites as a consequence of liver decompensation and other exhibited cholestatic pattern. Their serology and liver biopsy confirmed autoimmune hepatitis as underlying aetiology. We would like to share the clinical improvement with simultaneous immunosuppressive therapy and combination Anti Retroviral Therapy (cART). There are no documented cases on this issue from the Indian subcontinent that we are aware of.

Immunovirological discordance among people living with human immunodeficiency virus at a center in Western India: A retrospective study.

Background and Objectives: Treatment of people living with human immunodeficiency virus (HIV) (PLHIV) is monitored using plasma HIV viral load levels and CD4 counts. Patients with either immunological nonresponse (virological suppression achieved) or virological nonresponse (immune reconstitution achieved) are termed as having a discordant response. These patients are at higher risk for acquired immunodeficiency syndrome (AIDS)-related infections/diseases/neoplasms, non-AIDS-related illnesses (cardiovascular, neurological, renal, hepatic diseases), and all-cause death. This study was conducted to assess the prevalence of immunovirological discordance among PLHIV after completion of at least 1 year of combination antiretroviral therapy (cART) at an antiretroviral therapy (ART) plus center in India and analyze contributory factors. Methods: The study was a retrospective study of PLHIV receiving cART at the ART plus clinic in Western India from January 18 to December 21. Four hundred and ninety-six patients were studied based on sample size calculated and assessed for CD4 and viral load response at 0, 6, and 12 months of ART. Results: Of the 496 patients, 48 patients (9.7%) had immunovirological discordance. Out of them, 36 patients (75%) had a virological response (immunological nonresponse) and 12 (25%) patients had an immunological response (virological nonresponse). The factors contributing to immunological nonresponse were as follows - low baseline CD4 levels (<100 cells) (36.1%), adherence <95% (33.3%), presence of opportunistic infections (16.6%), and failure on first-line therapy (11.1%). Other factors noted included higher baseline viral load (2.7%), chronic kidney disease (5.5%), and chronic hepatitis B virus co-infection (5.5%). Virological nonresponse was associated with poor adherence to therapy <95% (33%) and failure of first-line regimen (33%). Opportunistic infections were noted among 33% of patients and 8.3% of patients were found to have higher baseline viral load. Interpretation and Conclusion: Immunovirological discordance is an important factor influencing response to cART and is associated with many complications such as AIDS and non-AIDS-related events and even death. Improved adherence and timely identification and management of opportunistic infections are measures that are beneficial in reducing the incidence of immunovirological discordance.

Contextualising adverse events of special interest to characterise the baseline incidence rates in 24 million patients with COVID-19 across 26 databases: a multinational retrospective cohort study.

Background: Adverse events of special interest (AESIs) were pre-specified to be monitored for the COVID-19 vaccines. Some AESIs are not only associated with the vaccines, but with COVID-19. Our aim was to characterise the incidence rates of AESIs following SARS-CoV-2 infection in patients and compare these to historical rates in the general population. Methods: A multi-national cohort study with data from primary care, electronic health records, and insurance claims mapped to a common data model. This study's evidence was collected between Jan 1, 2017 and the conclusion of each database (which ranged from Jul 2020 to May 2022). The 16 pre-specified prevalent AESIs were: acute myocardial infarction, anaphylaxis, appendicitis, Bell's palsy, deep vein thrombosis, disseminated intravascular coagulation, encephalomyelitis, Guillain- Barré syndrome, haemorrhagic stroke, non-haemorrhagic stroke, immune thrombocytopenia, myocarditis/pericarditis, narcolepsy, pulmonary embolism, transverse myelitis, and thrombosis with thrombocytopenia. Age-sex standardised incidence rate ratios (SIR) were estimated to compare post-COVID-19 to pre-pandemic rates in each of the databases. Findings: Substantial heterogeneity by age was seen for AESI rates, with some clearly increasing with age but others following the opposite trend. Similarly, differences were also observed across databases for same health outcome and age-sex strata. All studied AESIs appeared consistently more common in the post-COVID-19 compared to the historical cohorts, with related meta-analytic SIRs ranging from 1.32 (1.05 to 1.66) for narcolepsy to 11.70 (10.10 to 13.70) for pulmonary embolism. Interpretation: Our findings suggest all AESIs are more common after COVID-19 than in the general population. Thromboembolic events were particularly common, and over 10-fold more so. More research is needed to contextualise post-COVID-19 complications in the longer term. Funding: None.

Real-world utilization of SARS-CoV-2 serological testing in RNA positive patients across the United States.

BACKGROUND: As diagnostic tests for COVID-19 were broadly deployed under Emergency Use Authorization, there emerged a need to understand the real-world utilization and performance of serological testing across the United States. METHODS: Six health systems contributed electronic health records and/or claims data, jointly developed a master protocol, and used it to execute the analysis in parallel. We used descriptive statistics to examine demographic, clinical, and geographic characteristics of serology testing among patients with RNA positive for SARS-CoV-2. RESULTS: Across datasets, we observed 930,669 individuals with positive RNA for SARS-CoV-2. Of these, 35,806 (4%) were serotested within 90 days; 15% of which occurred <14 days from the RNA positive test. The proportion of people with a history of cardiovascular disease, obesity, chronic lung, or kidney disease; or presenting with shortness of breath or pneumonia appeared higher among those serotested compared to those who were not. Even in a population of people with active infection, race/ethnicity data were largely missing (>30%) in some datasets-limiting our ability to examine differences in serological testing by race. In datasets where race/ethnicity information was available, we observed a greater distribution of White individuals among those serotested; however, the time between RNA and serology tests appeared shorter in Black compared to White individuals. Test manufacturer data was available in half of the datasets contributing to the analysis. CONCLUSION: Our results inform the underlying context of serotesting during the first year of the COVID-19 pandemic and differences observed between claims and EHR data sources-a critical first step to understanding the real-world accuracy of serological tests. Incomplete reporting of race/ethnicity data and a limited ability to link test manufacturer data, lab results, and clinical data challenge the ability to assess the real-world performance of SARS-CoV-2 tests in different contexts and the overall U.S. response to current and future disease pandemics.

Real-world performance of SARS-Cov-2 serology tests in the United States, 2020.

BACKGROUND: Real-world performance of COVID-19 diagnostic tests under Emergency Use Authorization (EUA) must be assessed. We describe overall trends in the performance of serology tests in the context of real-world implementation. METHODS: Six health systems estimated the odds of seropositivity and positive percent agreement (PPA) of serology test among people with confirmed SARS-CoV-2 infection by molecular test. In each dataset, we present the odds ratio and PPA, overall and by key clinical, demographic, and practice parameters. RESULTS: A total of 15,615 people were observed to have at least one serology test 14-90 days after a positive molecular test for SARS-CoV-2. We observed higher PPA in Hispanic (PPA range: 79-96%) compared to non-Hispanic (60-89%) patients; in those presenting with at least one COVID-19 related symptom (69-93%) as compared to no such symptoms (63-91%); and in inpatient (70-97%) and emergency department (93-99%) compared to outpatient (63-92%) settings across datasets. PPA was highest in those with diabetes (75-94%) and kidney disease (83-95%); and lowest in those with auto-immune conditions or who are immunocompromised (56-93%). The odds ratios (OR) for seropositivity were higher in Hispanics compared to non-Hispanics (OR range: 2.59-3.86), patients with diabetes (1.49-1.56), and obesity (1.63-2.23); and lower in those with immunocompromised or autoimmune conditions (0.25-0.70), as compared to those without those comorbidities. In a subset of three datasets with robust information on serology test name, seven tests were used, two of which were used in multiple settings and met the EUA requirement of PPA ≥87%. Tests performed similarly across datasets. CONCLUSION: Although the EUA requirement was not consistently met, more investigation is needed to understand how serology and molecular tests are used, including indication and protocol fidelity. Improved data interoperability of test and clinical/demographic data are needed to enable rapid assessment of the real-world performance of in vitro diagnostic tests.

From Genes to Geography, from Cells to Community, from Biomolecules to Behaviors: The Importance of Social Determinants of Health.

Much scientific work over the past few decades has linked health outcomes and disease risk to genomics, to derive a better understanding of disease mechanisms at the genetic and molecular level. However, genomics alone does not quite capture the full picture of one's overall health. Modern computational biomedical research is moving in the direction of including social/environmental factors that ultimately affect quality of life and health outcomes at both the population and individual level. The future of studying disease now lies at the hands of the social determinants of health (SDOH) to answer pressing clinical questions and address healthcare disparities across population groups through its integration into electronic health records (EHRs). In this perspective article, we argue that the SDOH are the future of disease risk and health outcomes studies due to their vast coverage of a patient's overall health. SDOH data availability in EHRs has improved tremendously over the years with EHR toolkits, diagnosis codes, wearable devices, and census tract information to study disease risk. We discuss the availability of SDOH data, challenges in SDOH implementation, its future in real-world evidence studies, and the next steps to report study outcomes in an equitable and actionable way.

Kaposi sarcoma (KS) with primary effusion lymphoma in HIV infected MSM (men having sex with men) co-infected with pulmonary tuberculosis and syphilis: a case report from India.

We describe a case of a 30-year-old MSM recently diagnosed with HIV, immunocompromised with a purplish or brown rash all over the body for 3 to 4 months. The histopathology of the cutaneous lesions and pleural effusion aspirate confirmed the diagnosis of Kaposi's sarcoma (KS) and primary effusion lymphoma (PEL). While KS is one of the AIDS-defining illnesses seen in immunocompromised patients having low CD4 count, PEL is a rare and distinct subset of AIDS-related lymphoma. Despite the widespread availability of HIV testing, HIV diagnosis gets delayed due to stigma among MSM. This case report emphasizes the importance of early suspicion for symptoms of HIV-associated opportunistic infections in high-risk populations like MSM. The report reiterates the need for an ambient stigma-free environment for improving HIV screening in this high-risk population.

Toward a causal model of chronic back pain: Challenges and opportunities.

Chronic low back pain (cLBP) afflicts 8. 2% of adults in the United States, and is the leading global cause of disability. Neuropsychiatric co-morbidities including anxiety, depression, and substance abuse- are common in cLBP patients. In particular, cLBP is a risk factor for opioid addiction, as more than 50% of opioid prescriptions in the United States are for cLBP. Misuse of these prescriptions is a common precursor to addiction. While associations between cLBP and neuropsychiatric disorders are well established, causal relationships for the most part are unknown. Developing effective treatments for cLBP, and associated co-morbidities, requires identifying and understanding causal relationships. Rigorous methods for causal inference, a process for quantifying causal effects from observational data, have been developed over the past 30 years. In this review we first discuss the conceptual model of cLBP that current treatments are based on, and how gaps in causal knowledge contribute to poor clinical outcomes. We then present cLBP as a "Big Data" problem and identify how advanced analytic techniques may close knowledge gaps and improve clinical outcomes. We will focus on causal discovery, which is a data-driven method that uses artificial intelligence (AI) and high dimensional datasets to identify causal structures, discussing both constraint-based (PC and Fast Causal Inference) and score-based (Fast Greedy Equivalent Search) algorithms.

Olfactory Dysfunction Among Asymptomatic Patients with SARS CoV2 Infection: A Case-Control Study.

Olfactory dysfunction (hyposmia, anosmia) is a well-recognized symptom in patients with coronavirus disease-19 (COVID-19). Studies of olfactory dysfunction in asymptomatic patients have not been reported. We conducted a study looking for the presence of olfactory dysfunction with an objective assessment tool in asymptomatic Covid 19 and compared it with patients with mild COVID-19 and age-matched controls. We recruited 57 male patients each of Mild COVID-19, asymptomatic Covid 19, and healthy controls for the study. All participants underwent evaluation of smell threshold by Butanol Threshold test (BTT) and ability to distinguish common odors by Smell identification test. The scores of each test were recorded on a numerical scale. The participants in all three arms were matched for age, history of smoking, and pre-existing medical conditions. The mean scores of the Butanol Threshold test in Mild COVID-19, asymptomatic Covid 19 and controls were 2.95 ± 2.25 (0-7.5), 3.42 ± 2.23 (0-7.5), and 4.82 ± 1.86 (0-8), respectively. A one-way ANOVA showed a significant difference between groups (df 2, MS 53.78, F 11.94, p < 0.005). Intergroup differences using the student T-test showed significantly low BTT scores in Mild COVID-19 (p < 0.005) and asymptomatic (p < 0.005) as compared to control. BTT scores could not distinguish between asymptomatic patients and control. The smell threshold was impaired in asymptomatic Covid 19 and Mild COVID-19. Butanol Threshold Test score could not differentiate between asymptomatic Covid 19 and controls.

Sepsis and ECMO.

Sepsis is being recognized as an important complication of extracorporeal membrane oxygenation (ECMO) and its presence is a poor prognostic marker and increases the overall mortality. The survival rate differs in the various types of cannulation techniques. Adult patients with prolonged duration of ECMO constitute the major risk population. Ventilator-associated pneumonia and bloodstream infections form the main sources of sepsis in these patients. It is important to know the most common etiological agents for sepsis in ECMO, which varies partly with the local epidemiology of the hospitals. A high index of suspicion, drawing adequate volumes for blood culture and early and timely administration of appropriate empirical antimicrobials can substantially decrease the morbidity and mortality in this high-risk population. The dosing of antimicrobials is influenced by the pharmacological variations on ECMO machine and is an important consideration. Infection control practices are of paramount importance and need to be followed meticulously to prevent sepsis in ECMO.

Identification of antiviral antihistamines for COVID-19 repurposing.

There is an urgent need to identify therapies that prevent SARS-CoV-2 infection and improve the outcome of COVID-19 patients. Although repurposed drugs with favorable safety profiles could have significant benefit, widely available prevention or treatment options for COVID-19 have yet to be identified. Efforts to identify approved drugs with in vitro activity against SARS-CoV-2 resulted in identification of antiviral sigma-1 receptor ligands, including antihistamines in the histamine-1 receptor binding class. We identified antihistamine candidates for repurposing by mining electronic health records of usage in population of more than 219,000 subjects tested for SARS-CoV-2. Usage of diphenhydramine, hydroxyzine and azelastine was associated with reduced incidence of SARS-CoV-2 positivity in subjects greater than age 61. We found diphenhydramine, hydroxyzine and azelastine to exhibit direct antiviral activity against SARS-CoV-2 in vitro. Although mechanisms by which specific antihistamines exert antiviral effects is not clear, hydroxyzine, and possibly azelastine, bind Angiotensin Converting Enzyme-2 (ACE2) and the sigma-1 receptor as off-targets. Clinical studies are needed to measure the effectiveness of diphenhydramine, hydroxyzine and azelastine for disease prevention, for early intervention, or as adjuvant therapy for severe COVID-19.

CovidCounties is an interactive real time tracker of the COVID19 pandemic at the level of US counties.

Management of the COVID-19 pandemic has proven to be a significant challenge to policy makers. This is in large part due to uneven reporting and the absence of open-access visualization tools to present local trends and infer healthcare needs. Here we report the development of CovidCounties.org, an interactive web application that depicts daily disease trends at the level of US counties using time series plots and maps. This application is accompanied by a manually curated dataset that catalogs all major public policy actions made at the state-level, as well as technical validation of the primary data. Finally, the underlying code for the site is also provided as open source, enabling others to validate and learn from this work.