Publications by authors named "S Suchindran"
Background: Diagnostic stewardship is the science of improving diagnostic test use. Whether electronic health record (EHR) design influences clinician diagnostic testing behavior and electronic medical record interventions can improve diagnostic stewardship outcomes are key questions. We leveraged the natural experiment of a recent change in EHR platforms to investigate if changing how 2 commonly misused tests, blood cultures for acid-fast bacilli (AFB) and fungi, are displayed affected their use.
View Article and Find Full Text PDFPurpose: To evaluate safety, tolerability, and anti-tumor response of lete-cel, genetically modified autologous T-cells expressing a T-cell receptor specific for NY-ESO-1/LAGE-1a shared epitope, alone or in combination with pembrolizumab, in human leukocyte antigen HLA-A*02-positive (HLA-A*02:01-, HLA-A*02:05-, and/or HLA-A*02:06-) patients with New York esophageal squamous cell carcinoma 1 (NY-ESO-1)- and/or LAGE-1a-positive non-small cell lung cancer (NSCLC).
Experimental Design: Study 208749 was a single-arm study of lete-cel alone. Study 208471 was a multi-arm study of lete-cel alone or in combination with pembrolizumab in patients with advanced or recurrent NSCLC.
Derivation of a risk-adjusted model to predict antibiotic prescribing among hospitalists in an academic healthcare network.
Antimicrob Steward Healthc Epidemiol
October 2024
Background: Among inpatients, peer-comparison of prescribing metrics is challenging due to variation in patient-mix and prescribing by multiple providers daily. We established risk-adjusted provider-specific antibiotic prescribing metrics to allow peer-comparisons among hospitalists.
Methods: Using clinical and billing data from inpatient encounters discharged from the Hospital Medicine Service between January 2020 through June 2021 at four acute care hospitals, we calculated bimonthly (every two months) days of therapy (DOT) for antibiotics attributed to specific providers based on patient billing dates.
Article Synopsis
- Pneumonia can be caused by various pathogens, and distinguishing between typical bacterial, atypical bacterial, and viral infections is challenging, prompting the use of host response-based diagnostics alongside traditional methods.
- Researchers conducted experiments on mice infected with different types of pneumonia (including influenza) to analyze gene expression and develop diagnostic signatures that reflect the host's immune response.
- The study found that these signatures were highly accurate, with a superb area under the receiver operator curve (auROC), and showed promising validation in human data, indicating a consistent host response across species.
Article Synopsis
- The study implemented a prospective index-cluster sampling strategy (ICSS) to identify presymptomatic respiratory viral infections among first-year college students through daily symptom diaries and close contact tracing.
- A total of 1,379 participants were enrolled from 2009 to 2015, with 288 becoming index cases (ICs) and 882 being close contacts (CCs), resulting in 13% of CCs developing respiratory illnesses.
- The findings indicated that geographic clustering of ICs and CCs didn't significantly enhance the detection of viral transmission, and only a small percentage of CCs carried the same virus as their associated ICs.