Intravesicle Lactobacillus to Reduce Urinary Symptoms After Spinal Cord Injury

Abstract

Urinary tract infection (UTI) is the most common outpatient infection world-wide, and for people with spinal cord injury (SCI) with neurogenic bladder (NB) it is not only the most common infection, but also the most common secondary condition, cause for emergency room visits, and infectious cause of hospitalization. Despite its prevalence, attempts to ameliorate UTI among people with SCI are stymied by longstanding diagnostic challenges due to the facts that gold standard diagnostic tests (urinalysis and urine culture) have lower sensitivity and specificity for UTI in this population. With our prior work we have advanced research in this domain and prepared ourselves to uniquely propose and pursue the stated aims. Specifically, we have laid the groundwork for this project by: 1) advancing patient-centered urinary symptom measurement and interpretation through development and validation of Urinary Symptom Questionnaires for people with Neurogenic Bladder (USQNB); 2) transforming clinical dogma around healthy urine by demonstrating that healthy urine is not sterile; 3) identifying Lactobacillus as a component lacking in the urine ecosystem of people with NB; 4) obtaining regulatory approvals for first-in-human safety testing of self instilled intravesical Lactobacillus Rhamnosus GG (LGG); 5) demonstrating the safety and tolerability of instilled intravesical LGG; and 6) demonstrating utility of a novel biomarker, urine NGAL, to discriminate between levels of inflammation indicative of UTI versus those of urinary tract colonization in children with NB. Hypothesis or Objective: This proposal specifically focuses on the population of people with SCI and NB who manage their bladders with intermittent catheterization (IC).

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2023
Accession Number
AD1218023

Entities

People

  • Suzanne Groah

Organizations

  • Washington Hospital Center

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Attrition
  • Biomedical Research
  • Clinical Trials
  • Computational Biology
  • Data Analysis
  • Data Science
  • Data Sets
  • Health Services
  • Hospitals
  • Leukocytes
  • Medical Personnel
  • Microbiomes
  • Spinal Cord
  • Spinal Injuries
  • Statistical Analysis
  • Therapy

Fields of Study

  • Medicine

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