The objective of this study was to evaluate the utility and impact of the Painful Periods Screening Tool (PPST) to improve healthcare delivery for people with symptoms of pelvic pain. The design of this study was a survey study. After IRB approval, patients aged 18-55 years with self-reported pelvic, abdominal, or lower back pain before, during, or after menstrual periods were invited to participate in the study from September 2020 to June 2021. Participants filled out the PPST questionnaire on the day of their Johns Hopkins clinic visit and the follow-up questionnaire 1-14 days after the clinic visit. Demographics and duration of pain were assessed, and participants who completed the PPST questionnaire were sent a follow-up questionnaire to assess utility and impact of PPST. Of the 1352 patients who met study eligibility, 1000 participants responded to both questionnaires. Most subjects (82.9%; 95% CI: 80.4-85.2%) reported having severe pelvic/abdominal or lower back pain during menses. Nine hundred fifteen participants (91.5%; 95% CI: 89.6-93.2%) reported that if given regularly, the PPST would help women discuss their pain symptoms with their healthcare provider. Six hundred seventy-eight participants (67.8%; 95% CI: 64.8-70.7%) reported that the PPST helped them initiate a conversation about their symptoms. Seven hundred seven participants (70.7%; 95% CI: 67.8-73.5%) were more comfortable discussing symptoms of pelvic pain with their provider after filling out the PPST. These findings support the utility of PPST as an endometriosis screening tool and suggest that this tool facilitated communication between patients and providers about pain symptoms.
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http://dx.doi.org/10.1007/s43032-022-01119-2 | DOI Listing |
Alzheimers Dement
December 2024
ADEL Institute of Science & Technology (AIST), ADEL, Inc., Seoul, Korea, Republic of (South).
Background: The Apolipoprotein E4 isoform (ApoE4), encoded by the APOE gene, stands out as the most influential genetic factor in late-onset Alzheimer's disease (LOAD). The ApoE4 isoform contributes to metabolic and neuropathological abnormalities during brain aging, with a strong correlation observed in APOE4-positive Alzheimer's disease cases between phosphorylated tau burden and amyloid deposition. Despite compelling evidence of APOE-mediated neuroinflammation influencing the progression of tau-mediated neurodegeneration, the molecular mechanisms underlying these phenomena remain largely unknown.
View Article and Find Full Text PDFBackground: Alzheimer's Disease (AD) is the leading form of senile dementia, affecting ∼6 million Americans and having a national economic impact of $321 billion, numbers expected to double by 2050. The major pathological hallmarks of AD include Amyloid Beta (Aβ) plaques and Tau neurofibrillary tangles (NFT). The first goal of this research was to develop novel forms of carbon dots (CD) using various precursors.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, Beijing, China;, Beijing, China.
Background: Individuals with type 2 diabetes mellitus (T2DM) face an increased risk of dementia. Recent discoveries indicate that SGLT2 inhibitors, a newer class of anti-diabetic medication, exhibit beneficial metabolic effects beyond glucose control, offering a potential avenue for mitigating the risk of Alzheimer's disease (AD). However, limited evidence exists regarding whether the use of SGLT2 inhibitors effectively reduces the risk of AD.
View Article and Find Full Text PDFBackground: TREM2 is a lipid-sensing receptor expressed by microglial sub-populations within neuropathological microenvironments, whose downstream signaling promotes microglial survival, plasticity, and migration. Multiple loss-of-function variants strongly implicate TREM2 as a key regulator of Alzheimer's disease (AD) risk. Accordingly, TREM2 antibodies are currently in development to evaluate the therapeutic potential of TREM2 agonism in neurodegenerative diseases.
View Article and Find Full Text PDFBackground: The advent of disease-modifying therapies in Alzheimer's disease (AD) necessitates a nuanced understanding of how therapies impact disease processes. Over the past decades, AD clinical trials have primarily relied on classical statistical analysis methodology such as the mixed model for repeated measures (MMRM) to estimate treatment effects. These conventional treatment effect quantifications are given as group differences in clinical outcome measures at a single visit.
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