Artificial Intelligence Applications in Clinical Chemistry.

Artificial intelligence (AI) applications are an area of active investigation in clinical chemistry. Numerous publications have demonstrated the promise of AI across all phases of testing including preanalytic, analytic, and postanalytic phases; this includes novel methods for detecting common specimen collection errors, predicting laboratory results and diagnoses, and enhancing autoverification workflows. Although AI applications pose several ethical and operational challenges, these technologies are expected to transform the practice of the clinical chemistry laboratory in the near future.

Clinical Characteristics and Outcomes for 7,995 Patients with SARS-CoV-2 Infection.

OBJECTIVE: Severe acute respiratory syndrome virus (SARS-CoV-2) has infected millions of people worldwide. Our goal was to identify risk factors associated with admission and disease severity in patients with SARS-CoV-2. DESIGN: This was an observational, retrospective study based on real-world data for 7,995 patients with SARS-CoV-2 from a clinical data repository. SETTING: Yale New Haven Health (YNHH) is a five-hospital academic health system serving a diverse patient population with community and teaching facilities in both urban and suburban areas. POPULATIONS: The study included adult patients who had SARS-CoV-2 testing at YNHH between March 1 and April 30, 2020. MAIN OUTCOME AND PERFORMANCE MEASURES: Primary outcomes were admission and in-hospital mortality for patients with SARS-CoV-2 infection as determined by RT-PCR testing. We also assessed features associated with the need for respiratory support. RESULTS: Of the 28605 patients tested for SARS-CoV-2, 7995 patients (27.9%) had an infection (median age 52.3 years) and 2154 (26.9%) of these had an associated admission (median age 66.2 years). Of admitted patients, 2152 (99.9%) had a discharge disposition at the end of the study period. Of these, 329 (15.3%) required invasive mechanical ventilation and 305 (14.2%) expired. Increased age and male sex were positively associated with admission and in-hospital mortality (median age 80.7 years), while comorbidities had a much weaker association with the risk of admission or mortality. Black race (OR 1.43, 95%CI 1.14-1.78) and Hispanic ethnicity (OR 1.81, 95%CI 1.50-2.18) were identified as risk factors for admission, but, among discharged patients, age-adjusted in-hospital mortality was not significantly different among racial and ethnic groups. CONCLUSIONS: This observational study identified, among people testing positive for SARSCoV-2 infection, older age and male sex as the most strongly associated risks for admission and in-hospital mortality in patients with SARS-CoV-2 infection. While minority racial and ethnic groups had increased burden of disease and risk of admission, age-adjusted in-hospital mortality for discharged patients was not significantly different among racial and ethnic groups. Ongoing studies will be needed to continue to evaluate these risks, particularly in the setting of evolving treatment guidelines.

Health Care and Precision Medicine Research: Analysis of a Scalable Data Science Platform.

BACKGROUND: Health care data are increasing in volume and complexity. Storing and analyzing these data to implement precision medicine initiatives and data-driven research has exceeded the capabilities of traditional computer systems. Modern big data platforms must be adapted to the specific demands of health care and designed for scalability and growth. OBJECTIVE: The objectives of our study were to (1) demonstrate the implementation of a data science platform built on open source technology within a large, academic health care system and (2) describe 2 computational health care applications built on such a platform. METHODS: We deployed a data science platform based on several open source technologies to support real-time, big data workloads. We developed data-acquisition workflows for Apache Storm and NiFi in Java and Python to capture patient monitoring and laboratory data for downstream analytics. RESULTS: Emerging data management approaches, along with open source technologies such as Hadoop, can be used to create integrated data lakes to store large, real-time datasets. This infrastructure also provides a robust analytics platform where health care and biomedical research data can be analyzed in near real time for precision medicine and computational health care use cases. CONCLUSIONS: The implementation and use of integrated data science platforms offer organizations the opportunity to combine traditional datasets, including data from the electronic health record, with emerging big data sources, such as continuous patient monitoring and real-time laboratory results. These platforms can enable cost-effective and scalable analytics for the information that will be key to the delivery of precision medicine initiatives. Organizations that can take advantage of the technical advances found in data science platforms will have the opportunity to provide comprehensive access to health care data for computational health care and precision medicine research.

The enthesis: a review of the tendon-to-bone insertion.

The integration of tendon into bone occurs at a specialized interface known as the enthesis. The fibrous tendon to bone enthesis is established through a structurally continuous gradient from uncalcified tendon to calcified bone. The enthesis exhibits gradients in tissue organization classified into four distinct zones with varying cellular compositions, mechanical properties, and functions in order to facilitate joint movement. Damage to tendinous insertions is common in the field of orthopaedic medicine and often involves surgical intervention that requires the attempted recreation of the natural organization of tendon into bone. The difficulty associated with recreating the distinct organization may account for the surgical challenges associated with reconstruction of damaged insertion sites. These procedures are often associated with high failure rates and consequently require revision procedures. Management of tendinous injuries and reconstruction of the insertion site is becoming a popular topic in the field of orthopaedic medicine.

In vitro evaluation of the anti-bacterial effect of two preparations of platelet rich plasma compared with cefazolin and whole blood.

PURPOSE: This study investigates the antibacterial properties of two different platelet-rich plasma (PRP) platelet concentration preparations (PRPLP and PRPHP) through a time-kill assay. METHODS: Two different PRP preparations - a single spin process yielding lower white blood cells and platelet concentration (PRPLP) and one yielding high platelet and white blood cell concentration (PRPHP) - were obtained from 2 individuals. PRPLP, PRPHP, phosphate buffered saline (PBS), whole blood and Cefazolin were added to experimental reaction tubes, each containing a single bacterial inoculum of Staphylococcus aureus (S. aureus), Staphylococcus epidermidis (S. epi), methicillin-resistant Staphylococcus aureus (MRSA) or Propionibacterium acnes (P. acnes). Two dilutions (1:1,000, and 1:10,000) were plated in duplicate tubes, along with positive (blood and PBS) and negative (Cefazolin) controls and assessed at five time points (0, 1, 4, 8 and 24 hours). RESULTS: After centrifugation, platelet count of PRPLP was 386 ± 65.5 × 103/?L and PRPHP was 867 ± 234.4 × 103/?L. Both PRP products showed a significant decrease (p<0.05) in bacterial growth at 8 hours compared to whole blood. CONCLUSION: The application of PRPLP and PRPHP showed a significant decrease in bacterial growth after 8 hours for S. aureus, S. epi, MRSA and P. acnes compared to the whole blood control group. S.epi, MRSA, and P. acnes also showed a significant decrease in bacterial growth after 24 hours. Despite differences in platelet concentration and WBC concentration, no difference in antibacterial activity was seen between the two preparations.