Characterizing neurocognitive symptoms in older adults with primary hyperparathyroidism

项目总结

PROJECT SUMMARY Primary hyperparathyroidism (PHPT) is a common endocrine disorder affecting ~1 million older (age ≥ 65 years) Americans. Untreated PHPT is associated with osteoporosis, fractures, kidney stones, renal function decline, and cardiovascular-related morbidity. However, more than 80% of patients with PHPT lack classic symptoms such as kidney stones; they are often “asymptomatic” even as bone loss and renal decline silently occur. Neurocognitive (NC) symptoms, including memory impairment and cognitive dysfunction (“brain fog”), are common subjective complaints and may be the only symptoms with which patients present. Studies utilizing objective neurocognitive testing have found that PHPT patients have significantly diminished concentration levels, impairments in nonverbal learning processes, and compromised constructional and visuospatial memory. These impairments result in significant functional decline and decreased quality of life (QoL) in older adults – the very subpopulation that prizes the preservation of cognition as a critical health metric. Parathyroidectomy, commonly done as an outpatient procedure, is the first-line treatment for PHPT and is often curative. Several studies have demonstrated improvements (and even normalization) in cognitive function and quality of life following surgery. Nonetheless, PHPT is too often overlooked as a diagnosis, and up to 70% of older adults are undertreated for PHPT even when they meet the criteria for surgical treatment. Further, no studies on NC symptoms in older adults with PHPT have been conducted to date. Thus, there is a paucity of data on PHPT-associated NC symptoms among older adults, including specific cognitive deficits that may be prevalent among them and their response to treatment. In this proposal, we aim to (a) prospectively characterize NC symptoms and treatment-response patterns for older adults with PHPT using a validated subjective survey instrument and a battery of 3 objective NC measures and (b) develop an artificial intelligence-based strategy incorporating machine learning and natural language processing techniques, to expedite PHPT diagnosis. All studies will be conducted within the Duke University Health System. The aims of the proposal are: 1: Characterize NC symptoms of older adults with PHPT 2: Delineate factors associated with treatment-response patterns among older patients with PHPT-associated NC symptoms 3: Develop an artificial intelligence-based algorithm to expedite the diagnosis of PHPT among older adults with or without NC symptoms