Noninvasive Assessment of Renal Fibrosis of Chronic Kidney Disease in Rats by [68Ga]Ga-FAPI-04 Small Animal PET/CT and Biomarkers.

Renal fibrosis is the most common pathological feature and common pathway of progression in chronic kidney disease (CKD). We evaluated [68Ga]Ga-FAPI-04 small animal positron emission tomography/computed tomography (PET/CT) and biomarkers as noninvasive assessments of renal fibrosis (RF) in CKD rats to generate new ideas for clinical diagnosis. A rat model of renal fibrosis was administered adenine by gavage (n = 28), and the control group was given 0.9% NaCl by gavage (n = 20). At different time points (weeks 1, 2, 4, and 6), five rats were randomly selected from the two groups for [68Ga]Ga-FAPI-04 small animal PET/CT imaging. At the same time, the expression of Fibroblast activation protein (FAP) in renal tissue and the expression levels of type III procollagen N-terminal peptide (PIIINP), transforming growth factor (TGF-ß1), Klotho, and sex-determining region Y-box protein 9 (SOX9) in blood and urine were determined. FAP was highly expressed in the renal tissue of rats in the CKD group and expression increased with the progression of renal fibrosis. [68Ga]Ga-FAPI-04 small animal PET/CT examination showed that the uptake of radioactive tracers in the CKD group was higher than that in the control group, and SUVmax (r = 0.9405) and target-to-background ratio (TBR) (r = 0.9392) were positively correlated with renal fibrosis. The serum levels of PIIINP, TGF-ß1, and SOX9 in CKD rats were significantly higher than those in the control group and were positively correlated with RF (r = 0.8234, r = 0.7733, and r = 0.7135, respectively) and SUVmax (r = 0.8412, r = 0.7763, and r = 0.6814, respectively). Compared with the control group, the level of serum Klotho decreased and was negatively correlated with RF (r = -0.6925) and SUVmax (r = -0.6322). Compared with the control group, the levels of PIIINP and TGF-ß1 in urine were positively correlated with RF (r = 0.8127 and r = 0.8077, respectively) and SUVmax (r = 0.8400 and r = 0.8177, respectively). Urine Klotho decreased compared with the control group and was negatively correlated with RF (r = -0.5919) and SUVmax (r = -0.5995). The change in urine SOX9 was not statistically significant. In conclusion, compared with renal biopsy, [68Ga]Ga-FAPI-04 small animal PET/CT shows renal fibrosis quickly and noninvasively. PIIINP, TGF-ß1, and Klotho in serum and urine may be used as biomarkers of RF, and serum SOX9 is expected to become a new diagnostic biomarker of RF.

Assessment of Biological Toxicity and Ecological Safety for Urban Black-Odor River Remediation.

The judgment and assessment of remediation effect on urban black-odor river still depend on the physical-chemical parameters and lack in ecological safety effects. A set of combined biological toxicity tests were applied to evaluate the ecological effects of one urban black-odor river before and after the remediation. The special growth rate of Chlorella vulgaris and mortality rate of Daphnia magna were used to assess acute toxicity. The Salmonella Typhimurium/Reverse Mutation Assay was applied to test the mutagenicity. The tests by C. vulgaris growth showed that there was no inhibition before and after remediation by overlying water, in contrast promoted the growth of C. vulgaris. The tests by D. magna showed slight toxicity on site 3# before remediation and nontoxic after remediation. The mutagenicity of organic extracts from overlying water at all sampling sites were positive before remediation, but were eliminated after remediation except from 3 of 4 sites on TA98 strain. The addition of the liver microsomal S9 induced the positive mutagenicity on site 4# compared to S9 absence. The results clarified the applicable and the importance of the biological toxicity tests on assessing the remediation effect and potential ecological risk of urban black-odor river.

Use of Medicare Administrative Claims to Identify a Population at High Risk for Adverse Drug Events and Hospital Use for Quality Improvement.

BACKGROUND: A system using administrative claims to monitor medication use patterns and associated adverse events is not currently available. Establishment of a standardized method to identify Medicare beneficiaries at high risk for adverse events, by assessing Medicare Part D medication claim patterns and associated outcomes, including outpatient adverse drug events (ADEs) and hospital use, enhances prevention efforts and monitoring for quality improvement efforts. OBJECTIVES: To (a) demonstrate that Medicare claims data can be used to identify a population of beneficiaries at high risk for adverse events for quality improvement and (b) define trends associated with adverse health outcomes in identified high-risk beneficiaries for quality improvement opportunities. METHODS: We used Medicare fee-for-service Part D claims data to identify a population at high risk for adverse events by evaluating medication use patterns. This population was taking at least 3 medications, 1 of which was an anticoagulant, an opioid, or an antidiabetic agent. Next, we used associated Part A claims to calculate rates of outpatient ADEs, looking for specific ICD-9-CM or ICD-10-CM codes in the principal diagnosis code position. Rates of hospital use (inpatient hospitalization, observation stays, emergency department visits, and 30-day rehospitalizations) were also evaluated for the identified high-risk population. The data were then shared for targeted quality improvement. RESULTS: We identified 8,178,753 beneficiaries at high risk for adverse events, or 20.7% of the total eligible fee-for-service population (time frame of October 2016-September 2017). The overall rate of outpatient ADEs for beneficiaries at high risk was 46.28 per 1,000, with anticoagulant users demonstrating the highest rate of ADEs (68.52/1,000), followed by opioid users (42.11/1,000) and diabetic medication users (20.72/1,000). As expected, the primary setting for beneficiaries at high risk to seek care for outpatient ADEs was the emergency department, followed by inpatient hospitalizations and observation stays. CONCLUSIONS: Medicare claims are an accessible source of data, which can be used to establish for quality improvement a population at high risk for ADEs and increased hospital use. Using medication use patterns to attribute risk and associated outcomes, such as outpatient ADEs and hospital use, is a simple process that can be readily implemented. The described method has the potential to be further validated and used as a foundation to monitor population-based quality improvement efforts for medication safety. DISCLOSURES: This work was performed under contract HHSM-500-2014-QINNCC, Modification No. 000004, funded by Centers for Medicare & Medicaid Services (CMS), an agency of the U.S. Department of Health and Human Services. CMS did not have a role in the analysis. At the time of this analysis, Digmann, Peppercorn, Zhang, Irby, and Brock were employees of Telligen, which was awarded the National Coordinating Center-Quality Improvement Organization contract from CMS, which supported the work. Ryan was an employee at Qsource, which was awarded the Quality Innovation Network-Quality Improvement Organization contract from CMS, which supported the work. Thomas was employed by CMS. The content is solely the responsibility of the authors and does not necessarily represent the official views or policies of the CMS. This work is posted on the QIOprogram.org website, as recommended in the Common Rule ( https://www.hhs.gov/ohrp/regulations-and-policy/regulations/common-rule/index.html ).