Wolters Kluwer Health Research Articles

Psoriasis: Sind Geschlechtsunterschiede bedeutsam?

Background: Psoriasis is a common chronic inflammatory skin disease with an exceptionally high burden for women. Objective: Sex-dependent differences in disease manifestation, severity, treatment choices, subjective disease perception, and the impact on quality of life and risk factors are described and comprehensively discussed. Methods: A literature search was conducted using MEDLINE (PubMed) and the Cochrane Library for systematic reviews to investigate the challenges in treating women with psoriasis. Results and conclusions: : The incidence, prevalence, and manifestation of psoriasis of the skin are similar between different sexes. Genetic and environmental factors such as obesity and metabolic syndrome are risk factors and are not equally relevant or pronounced in women and men. Overall, women have a lower disease severity measured by the Psoriasis Area Severity Index, which is associated with a higher impairment of their life quality measured by the Dermatology Life Quality Index compared with men. In addition, women with psoriasis are more likely to have depression than men. Hormonal factors affect psoriasis, with a correlation of high estrogen levels and improvement of psoriasis. Data regarding differences in prescribing patterns of systemic treatments and the severity of psoriasis are not entirely consistent. Registry studies show that men tend to have more severe psoriasis and, in some cases, are prescribed systemic therapies more frequently. Women tend to respond better to systemic treatments and to experience more adverse events. Treatment options are the same for both sexes, except during pregnancy and lactation. Various treatment options are contraindicated due to fear of fetal or neonate harm and lack of data. Topical steroids can be prescribed with a high degree of safety during pregnancy. For other topical therapies (calcineurin inhibitors and vitamin D analogs), no studies of adverse effects in pregnancy are available, and safety data mainly stem from studies examining effects after systemic administration. Antitumor necrosis factor monoclonal antibodies (except for certolizumab pegol) have been associated with a possible increased risk of preterm birth, low gestational age, and cesarean deliveries. Prospective data on the safety of biologics other than antitumor necrosis factor-alpha antibodies to accurately assess whether novel biologics (eg, anti-interleukin 17, 12/23, 23) can be used for systemic therapy in pregnancy are lacking or currently being conducted. © 2022 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of Women’s Dermatologic Society.

Analysis and Evaluation of Intersectionality Theory for the Study of Access to Mental Health Services of Children With Refugee Background.

Multiple and complex factors contribute to the health inequities faced by refugee children accessing mental health care. Nurses play a critical role in addressing health inequities through education, practice, policy, and research. Intersectionality theory holds the potential to support nursing research that seeks to critically examine intersecting social identities and power structures that impact health inequities experienced by refugee children with mental health difficulties. Using Fawcett's framework, this article examined intersectionality theory and its applicability to the topic of inquiry. The findings revealed that much work is still required for intersectionality theory to meet the criteria for theory evaluation.

P106 Do high rheumatoid factor titres impact response to tumour necrosis factor inhibitors? Comparison of certolizumab pegol and adalimumab in patients with rheumatoid arthritis and high titres of rheumatoid factor: a post hoc analysis of a phase 4 trial.

Abstract Background/Aims In patients with rheumatoid arthritis (RA), high rheumatoid factor (RF) titres are considered a poor prognostic factor and are associated with higher disease activity, risk of radiographic progression and decreased response to TNF inhibitors (TNFis). Recent data suggests that patients with RA and high RF titre may achieve and maintain greater clinical improvement with TNFis without a crystallisable fragment (Fc) compared to TNFis with an Fc. In this analysis of the EXXELERATE trial, we assessed efficacy outcomes of certolizumab pegol (CZP), a PEGylated Fc-free TNFi, versus adalimumab (ADA; Fc-containing TNFi) in patients with RA and high RF titres. Methods The phase 4 EXXELERATE trial (NCT01500278) compared the efficacy and safety of CZP to ADA. Patients were randomised 1:1 to CZP 200 mg every two weeks (Q2W) plus methotrexate (MTX) or ADA 40 mg Q2W plus MTX. At Week 12 (Wk), patients were classified as responders or non-responders; non-responders were switched to the other TNFi with possible follow-up to Wk104. Here, we report drug plasma concentrations, mean disease activity score (DAS)28-CRP score and proportion of patients achieving low disease activity (LDA; threshold: DAS28-CRP ≤2.7) to Wk104. Results are stratified by RF titre quartile (≤Q3: ≤203 IU/mL; >Q3: >203 IU/mL; measured by Roche Tina-quant®) and reported as observed data. Results Baseline data by RF quartile were available for 453 CZP-randomised patients (≤Q3: n = 334; >Q3: n = 119) and 454 ADA-randomised patients (≤Q3: n = 347; >Q3 n = 107). Baseline characteristics were similar between CZP- and ADA-randomised patients across the RF titre quartiles. At Wk12, 66 CZP-treated patients switched to ADA and 59 ADA-treated patients switched to CZP. At Wk104, mean ADA concentrations were 22.9% lower in patients with RF >Q3 (mean [SD] 4.8 [3.0]) vs those with RF ≤Q3 (6.2 [4.0]); in CZP-treated patients, this difference was smaller (13.0%) in patients with RF >Q3 (23.3 [15.4]) vs those with RF ≤Q3 (26.7 [13.1]). For patients in RF ≤Q3, mean DAS28-CRP scores were similar between CZP- and ADA-treated patients through Wks0-104 (mean [SD] DAS28 at Wk104: 2.48 [1.18] CZP vs 2.49 [1.14] ADA). However, for patients in RF >Q3, mean [SD] DAS28-CRP scores were nominally lower in CZP- vs ADA-treated patients (Wk104: 2.50 [1.18] CZP vs 2.93 [1.22] ADA). A similar pattern was observed for the proportion of patients achieving LDA at Wk104 (≤Q3: 64.8% CZP vs 65.1% ADA; >Q3: 65.7% CZP vs 48.3% ADA). Conclusion CZP-treated patients with RA and high titre RF had similar drug concentrations and clinical responses to patients with RA and low titre RF, a pattern not observed in ADA-treated patients. These data, together with previous reports where CZP showed consistent efficacy irrespective of baseline RF titre, suggest CZP may be a suitable therapy for patients with RA and high RF titre. Disclosure J.S. Smolen: Honoraria; AbbVie, Amgen, AstraZeneca, Astro, Bristol-Myers Squibb, Celgene, Celltrion, Chugai, Gilead, ILTOO, Janssen, Lilly, Merck Sharp & Dohme, Novartis-Sandoz, Pfizer, R-Pharma, Roche, Samsung, Sanofi, and UCB Pharma. Grants/research support; AbbVie, AstraZeneca, Eli Lilly, Novartis and Roche. Other; Editor of Annals of the Rheumatic Diseases, Co-editor of Rheumatology 7E/8E, Convenor of EULAR Task Forces and T2T Task Forces. P.C. Taylor: Consultancies; AbbVie, Biogen, Eli Lilly, Fresenius, Galapagos, Gilead, GSK, Janssen, Nordic Pharma, Pfizer, Sanofi and UCB Pharma. Grants/research support; Galapagos. Y. Tanaka: Honoraria; AbbVie, AstraZeneca, BMS, Boehringer Ingelheim, Chugai, Eisai, Eli Lilly, Gilead, GSK, Pfizer, Taiho, Taisho. Member of speakers’ bureau; AbbVie, AstraZeneca, BMS, Boehringer Ingelheim, Chugai, Eisai, Eli Lilly, Gilead, GSK, Pfizer, Taiho and Taisho. Grants/research support; Chugai, Eisai, Mitsubishi-Tanabe, Taisho. C. Cara: Shareholder/stock ownership; UCB Pharma. Other; Employee of UCB Pharma. B. Lauwerys: Shareholder/stock ownership; UCB Pharma. Other; Employee of UCB Pharma. R. Xavier: Consultancies; AbbVie, AstraZeneca, Janssen, Organon, UCB Pharma. Member of speakers’ bureau; AbbVie, AstraZeneca, Janssen, Organon, and UCB Pharma. J.R. Curtis: Consultancies; AbbVie, Amgen, BMS, Corrona, Crescendo, Genentech, Janssen, Pfizer, Roche, UCB Pharma. Grants/research support; AbbVie, Amgen, BMS, Corrona, Crescendo, Genentech, Janssen, Pfizer, Roche, UCB Pharma. T.R. Mikuls: Consultancies; Horizon Therapeutics, Pfizer, Sanofi, UCB Pharma. Royalties; Elsevier, Wolters Kluwer Health (UpToDate). Grants/research support; Horizon Therapeutics. M. Weinblatt: Consultancies; AbbVie, Aclaris, Amgen, Aqtual, BMS, CorEvitas, Eli Lilly, GSK, Gilead, Horizon, Johnson and Johnson, Prometheus, Pfizer, Rani, Revolo, Sanofi, Scipher, Sci Rhom, Set Point, UCB Pharma. Grants/research support; AbbVie, Aqtual, BMS, Janssen.

The Results of Our Reader Survey Are In!

To become more acquainted with Plastic and Aesthetic Nursing (PAN) readers and help identify the strengths and weaknesses of the PAN journal, I worked collaboratively with representatives from Wolters Kluwer Health to conduct an online survey of plastic and aesthetic registered nurses who are members of the International Society of Plastic and Aesthetic Nurses. This article describes the methods and results of this reader survey.

1287. Assessing the Utility of Vertebral Body / Disc Space Fluid Cell Differential in the Diagnosis of Native Vertebral Osteomyelitis

Abstract Background Current approaches to diagnosing suspected native vertebral osteomyelitis (NVO) rely on imaging and microbiological workup, including blood and CT-guided biopsy cultures. These existing diagnostic methods often result in ambiguity, necessitating additional tests to distinguish NVO from its mimics. Our study aims to validate pilot findings demonstrating that an elevated neutrophil differential (PMN) in vertebral bone biopsy/ disc space fluid aspirate is associated with NVO. This may allow stratification of patients with suspected NVO into those who can be monitored closely versus those who may benefit from further invasive testing or empiric antibiotic therapy (Fig 1). Figure 1: Proposed workup of patients with suspected native vertebral osteomyelitis guided by disc space/ vertebral body neutrophil (PMN) differential. Methods This analysis examines a subset of patients from a prospective cohort study, enrolling adults referred to Mayo Clinic's neuroradiology department for spine biopsy. After collecting routine clinical specimens, the needle is rinsed with saline into an EDTA tube for automated cell count and differential analysis. To evaluate the predictive capacity of neutrophil (PMN) differential for NVO, logistic regression models were employed, and receiver operating characteristic (ROC) curve analyses were conducted for various PMN percentage cutoff points. Results In this preliminary analysis, 39 patients were included, comprising 7 patients with NVO and 32 patients with alternative diagnoses. Baseline characteristics are presented in Table 1. All NVO patients received antibiotics within two weeks of the spine biopsy. The median biopsy sample PMN percentage for NVO patients was 83.0 (77.5-88.0), compared to 65.0 (56.5-69.5) for those without NVO (p=0.005) (Fig 2A). The estimated relationship between the probability of NVO and each measure across the full range of percentages is illustrated in Fig 2B. The optimal ROC curve point corresponds to a PMN differential of 72.5% (sensitivity=0.86, specificity=0.81) (Fig 3).Table 1:Baseline Characteristics of Patients Included in the Preliminary AnalysisFigure 2:A) Distribution of spine biopsy neutrophil percent by native vertebral osteomyelitis (NVO) status, B) Loess nonparametric smoother showing the relationship between the probability of NVO and biopsy sample neutrophil percentage.Figure 3:ROC curve analysis of neutrophil percent and NVO Conclusion This preliminary analysis indicates that an elevated PMN differential in spine biopsy samples may serve as a valuable diagnostic tool for NVO, with results seemingly unaffected by recent antibiotic intake. The PMN differential cutoff of 72.5% exhibited notable sensitivity and specificity. Investigations are ongoing to further validate these findings Disclosures Brett Freedman, MD, Clear Choice Therapeutics: Stocks/Bonds|Medtronic: Grant/Research Support|Neuroinnovations: Stocks/Bonds Aaron J. Tande, M.D., Musculoskeletal Infection Society: Board Member|Wolters Kluwer Health - Lippincott Williams & Wilkins: Publishing royalties, financial or material support

Screening the Drug-Drug Interactions Between Antimicrobials and Other Prescribed Medications Using Google Bard and Lexicomp® Online™ Database.

Aim This study aimed tocritically appraise the drug-drug interaction (DDI) screening performance of Google Bard (Google AI, Mountain View, California, United States) by comparing it with the authorized Lexicomp® Online™ database (Wolters Kluwer Health, Philadelphia, Pennsylvania, United States). Methods This cross-sectional study was conducted between April 2023 and August 2023, and enrolled 414 prescriptions that had been collected randomly between April 2023 and June 2023. These prescriptions were processed individually by Lexicomp online and Google Bard to screen for DDIs between antimicrobials and other prescribed medications. Results The total number of DDIs based on Lexicomp and Google Bard were 90 and 68, respectively. Cohen's Kappa (κ) values showed that there was a nil to slight agreement between Lexicomp and Google Bard regarding the DDI risk rating (κ=0.01). Regarding the severity rate, there was a slight agreement between them (κ=0.02), but in terms of reliability rate, there was no agreement (κ =-0.02). Conclusion This study unveiled differences between Lexicomp and Google Bard regarding their DDI identification, severity rating, and reliability rates. It is fundamental to consider that both tools have their strengths and weaknesses and, therefore, should not be individually depended on for final clinical decisions. However, Lexicomp can be considered authoritative in screening DDIs, but Google Bard currently lacks the necessary precision and reliability for conducting such screenings.

National Health Care Decisions Day 2023.

Kathleen Ahem Gould, PhD, RN, is editor in chief of the Dimensions of Critical Care Nursing, Lippincott Williams & Wilkins, Wolters Kluwer Health, Duxbury, MA. The author has disclosed that she has no conflict of interest, significant relationship with, or financial interest in subjects or commercial companies pertaining to this article. Address correspondence and reprint requests to: Kathleen Ahem Gould, PhD, RN, 247 Washington St, Duxbury, MA 02332 ([email protected]). Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.dccnjournal.com).

Abstracts

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Health Physics Society Abstracts: 68th Annual Meeting.

Log in or Register Subscribe to journalSubscribe Get new issue alertsGet alerts Enter your Email address: Wolters Kluwer Health may email you for journal alerts and information, but is committed to maintaining your privacy and will not share your personal information without your express consent. For more information, please refer to our Privacy Policy. Subscribe to eTOC Secondary Logo Journal Logo All Articles Images Videos Podcasts Blogs Advanced Search Toggle navigation Subscribe Register Login Articles & Issues Current IssuePrevious Issues Published Ahead-of-PrintORSCollections Environmental and RadonExternal DosimetryHighly Cited ContentHomeland Security and Emergency ResponseInternal DosimetryMedical Countermeasures Against Radiological ThreatsMedical Health PhysicsNonionizing RadiationOperational Health PhysicsPress ReleasesRadiation Biology/Epidemiology VideosFor Authors Submit a ManuscriptInformation for AuthorsLanguage Editing ServicesAuthor Permissions Journal Info About the JournalEditorial BoardAffiliated SocietyAdvertisingOpen AccessSubscription ServicesReprintsRights and Permissions All Articles Images Videos Podcasts Blogs Advanced Search

549-P: Assessing Feasibility of a Diabetes Mellitus Program Using Behavioral Economics to Optimize Outreach and Self-Management Support with Technology—The DM-BOOST Project

Introduction: The DM-BOOST intervention was developed to enhance engagement with diabetes self-management training (DSMT). Participants received peer-written text message tips with nudges to reply with personal preferences. They then completed a video call with the DM-BOOST team to confirm patient portal access, review key functions, and set a diabetes behavior goal. This was later followed by receipt of a patient portal message with their goal, which they commit to sending to the DSMT provider they are scheduled to meet with. Methods: Adults with poorly controlled type 2 diabetes (HbA1c ≥ 8) received mailed invitations and a recruitment phone call. Participants (n=60) were randomized (1:1) to usual care or DM-BOOST. All participants received assistance obtaining a DSMT referral and scheduling a DSMT appointment. The primary outcome of interest was the DSMT appointment no-show/cancellation rate. Results: Enrolled participants (n=60) were 60.0% female with a mean age of 45.5 years (SD = 8.3). The average HbA1c at enrollment was 10.1% (SD = 1.8). All intervention participants (30/30) had a DSMT appointment scheduled compared to 86.7% of comparison participants (26/30). Intervention group participants had fewer DSMT no-shows/cancellations (3/30, 10%) compared to comparison group participants (10/26, 35%) (p = 0.01). Conclusions/Discussion: Technology-based interventions guided by behavioral economics can increase initial engagement with DSMT. Several system-level barriers, including challenges in obtaining referrals and scheduling appointments, were identified. Secondary outcomes, including patient-reported changes in diabetes self-efficacy, self-management skills, and treatment satisfaction are being evaluated. Future research efforts include cultural adaption of DM-BOOST for Spanish-speaking patients and rigorous implementation evaluation. Disclosure D.J.Amante: None. L.L.Shenette: None. G.Puerto: None. S.Lemon: None. D.M.Harlan: Advisory Panel; Novartis, Vertex Pharmaceuticals Incorporated, Diabeloop SA, Other Relationship; Stability Health, Wolters Kluwer Health. B.S.Gerber: Other Relationship; Abbott. Funding National Center for Advancing Translational Sciences (KL2TR001455); National Institute for Diabetes and Digestive and Kidney Diseases (1K01DK131318)

279-OR: Placental IGFBP1 Is Associated with Insulin Sensitivity during Pregnancy and Is an Early Biomarker for Gestational Diabetes

Pregnancy is associated with a profound reduction in insulin sensitivity (IS) that contributes to gestational diabetes (GDM), but the placental factors that lower IS in pregnancy are not fully known. We conducted genome-wide RNA sequencing in 450 placenta samples from a prospective pregnancy cohort (Gen3G). Participants provided plasma samples in the 1st trimester and completed 75g oral glucose tolerance tests in the late 2nd trimester, from which IS was estimated via the Matsuda index. We used regression analyses to test differential expression of 15,232 placental genes related to maternal IS, adjusting for gestational age at delivery, fetal sex, maternal age, gravidity, BMI, and 37 surrogate variables (to account for technical variability). Among the top differentially expressed genes, lower placental expression of IGFBP1 was significantly associated with lower maternal IS (P=1.7×10-4). In 837 Gen3G women, lower IGFPB1 circulating protein was strongly associated with lower IS (r=0.50, P<0.001) and predicted GDM risk (1st trimester median levels: 23,884 pg/mL in no GDM vs 14,363 pg/mL in GDM, adjusted OR=0.55 [0.39-0.75] per quartile increase; P=1.5×10-4). The association between plasma IGFBP1 and IS was replicated in two pregnancy cohorts: SPRING (n=165 with GDM risk factors, r=0.54, P<0.001) and MOMS (n=97 matched GDM cases and controls, r=0.55, P<0.001). The association of lower plasma IGFBP1 with greater risk of GDM was replicated in SPRING (adjusted OR=0.66 per quartile increase, P=0.07) and MOMS (adjusted OR=0.45 per quartile increase, P<0.001). In SPRING, plasma IGFBP1 protein were markedly elevated in the 1st and 2nd trimesters compared to postpartum (P<0.001), consistent with placental origin. Our results suggest that the placenta expresses high levels of IGFBP1, which influences IGF-1 bioavailability and is released in maternal circulation to regulate IS in pregnancy, highlighting it as a promising early plasma biomarker of GDM risk. Disclosure M.Hivert: None. S.Karumanchi: None. C.E.Powe: Consultant; Mediflix, Inc., Other Relationship; Wolters Kluwer Health. F.White: None. C.Allard: None. K.James: None. S.Majid: None. J.C.Florez: Consultant; AstraZeneca, Novo Nordisk, Other Relationship; AstraZeneca, Merck & Co., Inc. A.Edlow: Consultant; Mirvie, Inc, Research Support; Merck & Co., Inc. L.Bouchard: None. P.Jacques: None. Funding Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD094150)

1205-P: Abnormal Fetal Growth and Adverse Neonatal Outcomes in Pregnancies Affected by Both Gestational Diabetes and Hypertensive Disorders of Pregnancy

Objective: We evaluated how the co-occurrence of gestational diabetes (GDM) and hypertensive disorders of pregnancy (HDP) influence fetal growth and neonatal outcomes. Methods: In a retrospective study of 47720 singleton deliveries from a US medical center, we compared the incidence of appropriate for gestational age birthweight (AGA) in pregnancies affected by GDM alone, HDP alone, or both GDM and HDP (GDM/HDP) to that in pregnancies affected by neither disorder (Control) using generalized estimating equations (covariates: maternal age, parity, BMI, insurance type, race, marital status, and prenatal care site). Secondary outcomes were small for gestational age birthweight (SGA), large for gestational age birthweight (LGA), and a neonatal composite outcome (stillbirth, hypoglycemia, hyperbilirubinemia, respiratory distress, encephalopathy, preterm delivery, neonatal death, NICU admission). Results: Median [IQR] birthweight (BW) percentile in GDM/HDP (50 [24, 78], N=179) was similar to Control (50 [27, 73], N=35885), while GDM had increased (60 [35, 83], N=1322) and HDP had decreased (43 [18, 71], N=2749) BW percentiles. GDM (OR 0.8, P<0.001), HDP (OR 0.7, P<0.001), and GDM/HDP (OR 0.7, P=0.04) each had decreased odds of AGA. GDM had decreased SGA odds (OR 0.7, P=0.02) and increased LGA odds (OR 1.7, P<0.001). HDP had increased SGA odds (OR 2.0, P<0.001) and no difference in LGA odds (OR 0.99, P=0.914). While unadjusted rates of abnormal growth in GDM/HDP suggested that reduced AGA was due to excess LGA (14.5%) without excess SGA (7.3%), adjusted models suggested that both SGA (OR 1.3, P=0.33) and LGA (OR 1.4, P=0.12) contributed. GDM/HDP conferred the highest risk of neonatal morbidity (OR 3.4, P<0.001 compared to Control). Conclusion: Although pregnancies with GDM/HDP co-occurrence have a similar median birth weight to unaffected pregnancies, they carry an increased risk of abnormal fetal growth and neonatal morbidity. Disclosure C.A.Onuoha: None. T.Thaweethai: None. S.Hsu: None. C.C.M.Schulte: None. K.James: None. A.Kaimal: None. C.E.Powe: Consultant; Mediflix, Inc., Other Relationship; Wolters Kluwer Health.

1231-P: Influence of Diabetes on the Progression of Preclinical Stage B Heart Failure Phenotypes to Heart Failure

Introduction: The extent to which diabetes influences progression from preclinical heart failure (HF) stage B phenotypes (2021 Universal Definition) to overt HF or death is unknown. Methods: We included 4,264 adults with preclinical HF (stage A [n = 1,174] or B [n = 3,090]) who attended the Atherosclerosis Risk in Communities (ARIC) Study Visit 5 (2011-2013). Stage A was defined by HF risk factors only. Stage B1: echocardiographic abnormalities but no biomarker elevation; Stage B2: elevated NT-pro-BNP ≥125 pg/mL and/or hscTnT>14 ng/L but no echocardiographic abnormality; Stage B3: echocardiographic and biomarker abnormalities. We assessed the associations of diabetes and each preclinical stage B phenotype with incident HF and HF or death. Results: Among the participants (mean age 76 years, 62% women, 24% Black), there were 383 HF events and 730 deaths during 8.6 years of follow-up. Diabetes conferred a high absolute risk of HF across all preclinical stages B HF, but more so for the Stage B3 phenotype (Table). In cross-categories of preclinical HF stages (A and B) and diabetes status, participants with diabetes and Stage B3 had the highest risks of HF or HF and death combined, compared to those in stage A without diabetes. Conclusion: Addressing diabetes appears to be critical in stage B individuals with both echocardiographic and biomarkers abnormalities for preventing the progression to HF. Disclosure J.Echouffo tcheugui: None. C.E.Ndumele: None. S.Zhang: None. K.Matsushita: Consultant; Fukuda Denshi, Akebia Therapeutics, Inc., AMGA, Other Relationship; Kowa Company, Ltd. V.Nambi: Research Support; Amgen Inc., Kowa Pharmaceuticals America, Inc. H.Skali: Consultant; Astellas Pharma Inc., Elsevier, Wolters Kluwer Health, APM Tunisia / Hikma. E.Selvin: None. Funding National Institutes of Health (K23HL153774)

342-OR: The Impact of Insulin Secretion and Insulin Sensitivity on Cognition in Adults with Prediabetes—The Diabetes Prevention Program Outcomes Study (DPPOS)

Dysglycemia is a significant risk factor for cognitive impairment. However, which pathophysiologic determinant of dysglycemia, impaired insulin sensitivity (ISens) or insulin secretion (ISecr), or both, contributes to poorer cognitive function is not established. Among 1,054 adults with prediabetes (PreD) from the DPPOS, who did not develop diabetes, we investigated the relationship between ISecr, ISens and cognitive function, hypothesizing that lower ISens and/or lower ISecr is associated with worse cognition. Early ISecr was estimated by the mean insulinogenic index (IGI; pmol/mmol) from repeated annual oral glucose tolerance tests and ISens was estimated by the mean 1/fasting insulin from repeated fasting blood draws. ISecr and ISens were calculated over approximately 12 years of follow-up. Verbal learning (Spanish-English Verbal Learning Test [SEVLT]) and processing speed (Digital Symbol Substitution Test [DSST]) were assessed at the end of the follow-up period. Separate linear regression models were run for each cognitive outcome. Models included both mean ISecr and mean ISens as the main predictor variables and were adjusted for demographic, lifestyle, cardiovascular factors, and medications. Contrary to our hypothesis and to prior studies, higher mean ISecr was associated with poorer performance on the DSST (-0.74 points per SD increase in IGI, 95% CI: -1.43, -0.05; p=0.03). Mean ISens was not associated with DSST, nor were mean ISecr or mean ISens associated with SEVLT. These results suggest that higher insulin secretion in people with longstanding PreD may negatively impact processing speed, a critical component of executive control. This relationship could reflect a compensatory response of insulin in people with worsening metabolic dysregulation, who may also have poorer cognition. Further study is needed to replicate these findings and to understand the role of insulin in cognitive function. Disclosure A. Shapiro: None. A.H. Tjaden: None. S. Edelstein: None. S.E. Kahn: Advisory Panel; Anji Pharmaceuticals, Bayer Inc., Boehringer Ingelheim Inc., Eli Lilly and Company, Merck & Co., Inc. Other Relationship; Novo Nordisk. P. Srikanthan: None. W.C. Knowler: None. E.M. Venditti: None. S. Golden: Advisory Panel; Abbott Diabetes, Medtronic. O. Carmichael: Research Support; Eli Lilly and Company. Advisory Panel; Novo Nordisk. Research Support; Nestlé Health Science. K.M. Gadde: Research Support; BioKier, Inc., National Institute of Diabetes and Digestive and Kidney Diseases. J.A. Luchsinger: Consultant; Merck KGaA. Other Relationship; Wolters Kluwer Health. D. Research Group: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (UDK048489, UDK048339, UDK048377, UDK048349, UDK048381, UDK048468, UDK048434, UDK048485, UDK048375, UDK048514, UDK048437, UDK048413, UDK048411, UDK048406, UDK048380, UDK048397, UDK048412, UDK048404, UDK048387, UDK048407, UDK048443, UDK048400)

277-LB: Weight Cycling Is Associated with ICU Admission and Mechanical Ventilation in Adults with Diabetes Hospitalized with COVID-19

Weight variability in diabetes is an emerging risk factor for macrovascular complications and mortality, potentially via increased inflammation. We examined the impact of pre-admission weight cycling (WC) on COVID-19-related outcomes, including in-hospital mortality, ICU admission, and mechanical ventilation (MV), using a large multicenter cohort. This study included 277 adults with diabetes hospitalized with COVID-19 (March 2020-February 2021) at 5 university hospitals in the eastern US (COVIDEastDM Consortium) with body weight measurements at 0, 6, and 12 months before admission. Weight change was considered significant if it exceeded 5% in each 6-month interval. The cohort was grouped into four weight categories: unchanged (n=57; reference group), weight loss (WL; n=88), weight gain (WG; n=50) and WC (n=32), and was 54.6% male, 58.6% White, 24.2% Black, 18.5% Hispanic, with mean (SD) age 65.1 (12.6) years and HbA1c 7.7 (2.0)%. During hospitalization, 41.9% subjects were admitted to the ICU, 25.1% received MV, and 15.0% died. Age was the strongest risk factor for mortality (OR = 1.08 [95% CI: 1.03-1.13), and the presence of pre-existing comorbidity for both ICU admission (OR = 2.58 [1.13-5.90]) and MV (OR = 3.89 [1.30-11.64]). In an adjusted model, WC, but not WL or WG, was associated with ICU admission (OR = 3.09 [1.11-8.59]) and MV ((OR = 4.59 [1.48-14.19]), but not with mortality (OR = 3.19 [0.76-13.32]). The glycemic gap, shown previously to be associated with increased MV and mortality, did not change the relationship between WC and outcomes. The WC group trended toward higher peak ESR (94.3±23.1 ml/h vs. 62.2±33.5 ml/h, P=0.044) and hsCRP levels (150.0±133.9 mg/L vs. 104.1±105.3 mg/L, P=0.142). Conclusion: Weight cycling is associated with ICU admission and mechanical ventilation in adults with diabetes and COVID-19. Our findings identify a unique vulnerability of individuals with diabetes and recent weight cycling. Disclosure Y. Kang: None. R. S. Weinstock: Consultant; Jaeb Center for Health Research, Other Relationship; Wolters Kluwer Health, Research Support; Insulet Corporation, Medtronic, Eli Lilly and Company, Novo Nordisk, Boehringer Ingelheim Inc., Hemsley Charitable Trust, National Institute of Diabetes and Digestive and Kidney Diseases, Tandem Diabetes Care, Inc., Kowa Pharmaceuticals America, Inc. M. E. Mcdonnell: None. D. C. Simonson: Stock/Shareholder; Phase V Technologies, Inc., GI Windows. A. S. Chaugule: None. R. K. Garg: None. G. Gopalakrishnan: Research Support; Spruce Biosciences, Sparrow Pharmaceuticals Inc, Medtronic. K. Howard: None. J. Lebastchi: None. J. Mitri: Other Relationship; Novo Nordisk, Research Support; Kowa Company, Ltd. N. E. Palermo: Research Support; Dexcom, Inc.

49-OR: Genetic Variants Influencing Insulin Deficiency and Resistance Are Associated with Adverse Pregnancy Outcomes

Background: We tested maternal genetic determinants of insulin deficiency (ID) and insulin resistance (IR) for association with hyperglycemia-related adverse pregnancy outcomes. Methods: We applied non-negative matrix factorization to GWAS data (325 type 2 diabetes [T2D]-associated variants, 135 T2D-related traits) to derive 2 trait/variant clusters. We verified associations between cluster polygenic scores (PGSs) and ID/IR-related traits in non-pregnant women (n=35341). In pregnant women (n=1521) we tested for associations between cluster PGSs and infant birthweight (BW) percentile for gestational age and secondary outcomes (gestational diabetes [GDM], large/small for gestational age BW, hypertensive disorders, neonatal ICU admission, preterm birth) using models adjusted for age, insurance, parity, race, and principal components. Effect sizes are for a 1-SD PGS increase. Results: Cluster 1 had ID-related traits/variants (e.g., decreased insulin response and disposition index, increased fasting glucose, variants near MTNR1B, CDKAL1, C2CD4A/B SLC30A8). Outside pregnancy, the ID cluster PGS was associated with T2D (OR=1.2, p=2×10-7) and HbA1c (β=0.05%, p=2.8×10-9). In pregnancy, the ID cluster PGS was associated with higher BW percentile (β=1.7, p=0.04) and GDM (OR=1.3, p=0.004), but not other outcomes. Cluster 2 had IR-related traits/variants (e.g., decreased HDL and insulin sensitivity, increased triglycerides [TG] and fasting insulin, variants near IRS1, GRB14, LPL, FTO). Outside pregnancy, the IR cluster PGS was associated with T2D (OR=1.1, p=2×10-5), HbA1c (β=0.06 %, p=1.2×10-14), TG (β =4.2 mg/dL, p=4.4×10-15) and inversely associated with HDL (β=-1.7mg/dL, p=5.5×10-32). In pregnancy, the IR cluster PGS was associated with preterm birth (OR=1.3, p=0.006), but not BW percentile or GDM. Conclusion: Maternal genetic determinants of ID are associated with increased BW; genetic determinants of IR are associated with preterm birth. Disclosure S.Hsu: None. K.James: None. A.Medina baez: None. K.Smith: None. J.M.Mercader: None. M.Udler: None. C.E.Powe: Consultant; Mediflix, Inc., Other Relationship; Wolters Kluwer Health.

1031-P: Virtual Clinic Support—Patient-Reported Outcome Benefits

Behavioral health support can benefit those living with diabetes, but there is limited information on patient reported outcomes (PROs) associated with a virtual clinic. Adults with diabetes (n=234) received virtual care including support for CGM initiation and management over a 6-month study period. Care was led by a CDCES with support from a behavioral team. Participants completed PROs surveys 1) at baseline and 6 months to evaluate change and 2) each month on diabetes distress (DD), fear of hypoglycemia (FOH), and depression (DEP). Full list of PROs surveys included in table. A positive screen led to recommendation for a brief behavioral intervention. Participants with T1D (n=160) were 44(±14) years and mean baseline A1c of 7.8%. Participants with T2D (n=74) were 55(±12) years and mean baseline A1c of 8.1%. Participants screened positive for DD, FOH, or DEP 67% of the time with FOH as the most common concern. Of those with a positive screen, 70% of T1D and 59% of T2D participants had at least one behavioral team contact. Virtual clinic care was associated with a benefit on 7 of 9 PROs for T1D and 7 of 9 PROs for T2D (p values < 0.05; see table). For these virtual clinic adults with diabetes, PROs improved 78% of the time with noteworthy benefits of less FOH, less DD, and more glucose monitoring satisfaction. Paired with the glycemic improvements observed in this virtual clinic study, there were robust benefits on the quality of life of adults with diabetes. Disclosure K.K.Hood: Consultant; Cecelia Health. S.Oser: Advisory Panel; Cecelia Health, Dexcom, Inc., Consultant; Medscape, Research Support; Abbott Diabetes. T.Oser: Advisory Panel; Cecelia Health, Consultant; Dexcom, Inc., Medscape, Research Support; Abbott. D.Raghinaru: None. Z.Thompson: None. R.S.Weinstock: Consultant; Jaeb Center for Health Research, Other Relationship; Wolters Kluwer Health, Research Support; Insulet Corporation, Medtronic, Eli Lilly and Company, Novo Nordisk, Boehringer Ingelheim Inc., Hemsley Charitable Trust, National Institute of Diabetes and Digestive and Kidney Diseases, Tandem Diabetes Care, Inc., Kowa Pharmaceuticals America, Inc. R.Beck: Consultant; Eli Lilly and Company, Novo Nordisk, Diasome, Insulet Corporation, Research Support; Tandem Diabetes Care, Inc., Beta Bionics, Inc., Dexcom, Inc., Bigfoot Biomedical, Inc., Medtronic, Ascensia Diabetes Care, Roche Diabetes Care, Eli Lilly and Company, Novo Nordisk. G.Aleppo: Advisory Panel; Medscape, Consultant; Bayer Inc., Insulet Corporation, Research Support; Dexcom, Inc., Eli Lilly and Company, Emmes, Insulet Corporation, Fractyl Health, Inc., WellDoc, Speaker's Bureau; Dexcom, Inc. R.M.Bergenstal: Advisory Panel; Abbott Diabetes, Eli Lilly and Company, Medtronic, Novo Nordisk, Roche Diabetes Care, Zealand Pharma A/S, Consultant; Ascensia Diabetes Care, Bigfoot Biomedical, Inc., CeQur SA, Dexcom, Inc., Hygieia, Onduo LLC, Sanofi, Vertex Pharmaceuticals Incorporated, Research Support; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk, Sanofi, UnitedHealth Group. T.L.Cushman: None. R.L.Gal: None. C.Kollman: Research Support; Insulet Corporation, Dexcom, Inc., Tandem Diabetes Care, Inc. D.F.Kruger: Advisory Panel; Abbott Diabetes, Lilly, Medtronic, Novo Nordisk, Research Support; Dexcom, Inc., Beta Bionics, Inc., Speaker's Bureau; Dexcom, Inc., Lilly, Xeris Pharmaceuticals, Inc., Novo Nordisk. M.L.Johnson: Research Support; Abbott, Lilly, Insulet Corporation, NIH - National Institutes of Health, Patient-Centered Outcomes Research Institute, Novo Nordisk, Tandem Diabetes Care, Inc., Medtronic, Hemsley Charitable Trust, Jaeb Center for Health Research. T.S.Mcarthur: None. B.A.Olson: Stock/Shareholder; Abbott. Funding The Leona M. and Harry B. Helmsley Charitable Trust; Dexcom, Inc.

1454-P: Food Insecurity in People with Type 1 Diabetes and Glycemic Outcomes

Background: This multi-center study aims to explore relationships between individuals with type 1 diabetes (T1D) who are at risk for food insecurity and glycemic outcomes. Methods: Electronic health record data from T1D Exchange Quality Improvement Collaborative (T1DX-QI) categorized completed Hunger Vital Signs (HVS) questionnaires into at risk and no risk for food insecurity. At-risk individuals were defined as selecting “often true” or “sometimes true” to screening questions, whereas primary outcome was recent A1c levels. Demographic information and diabetes related covariates were assessed for potential relationships. Results: In the total T1D cohort (N=4453), 3.8% were at risk for food insecurity. Stratifying by age, 6% of youth (<18 years) and 5% of adults (>18 years) were at risk. Statistically significant differences were observed among food insecurity risk and insurance type. Of those at risk, 54% had public insurance compared with 7% private. Individuals at risk had a higher mean HbA1c when compared with individuals not at risk (9.4% vs 8.5% respectively, p<.001). The odds of an individual having an HbA1c >7% were higher in the group at risk relative to the group not at risk OR1.4 (95% CI 0.9, 2.1). Conclusion: Individuals in this population who were at risk for food insecurity also had elevated A1c levels. Interventions are needed to identify effective ways of improving food insecurity among people with T1D. Disclosure E.L.Ospelt: None. V.Raman: None. B.Seyoum: None. O.Ebekozien: Advisory Panel; Medtronic, Research Support; Eli Lilly and Company, Dexcom, Inc. N.Noor: None. J.Haw: None. S.Hsieh: None. R.S.Weinstock: Consultant; Jaeb Center for Health Research, Other Relationship; Wolters Kluwer Health, Research Support; Insulet Corporation, Medtronic, Eli Lilly and Company, Novo Nordisk, Boehringer Ingelheim Inc., Hemsley Charitable Trust, National Institute of Diabetes and Digestive and Kidney Diseases, Tandem Diabetes Care, Inc., Kowa Pharmaceuticals America, Inc. D.W.Hansen: Research Support; 3Boehringer Ingelheim Canada Ltd./Ltée, Lilly, Insulet Corporation, T1D Exchange, Medtronic. K.Cossen: None. K.Fantasia: None. I.Guttmann-bauman: None. Funding The Leona M. and Harry B. Helmsley Charitable Trust

1181-P: Substituting Protein for Fat Lowers Postprandial Glycemic Response in Gestational Diabetes

Background: Dietary guidelines in gestational diabetes mellitus (GDM) focus on carbohydrate without regard to other macronutrients. We tested the impact of fat and protein on postprandial glycemia in GDM and analyzed whether the physiology underlying GDM influenced this response. Methods: In a pilot crossover trial, participants ate two isocaloric breakfast meals with the same carbohydrate content and different protein and fat content (High protein meal: 390 kCal, 35 g protein, 9 g fat, 45 g carb, High fat meal: 411 kCal, 15 g protein, 19 g fat, 46 g carb) on subsequent days in a random order. We measured peak postprandial glucose (primary outcome) using continuous glucose monitors. We used homeostatic model assessment to determine if participants had insulin resistant (IR) or insulin deficient (ID) GDM. We used paired t-tests to test if glycemic response to the meals differed and linear regression to test if differential response to meals was influenced by having IR vs ID GDM. Results: We studied 16 women with diet-controlled GDM (median [IQR] 31 [30-33] weeks’ gestation). Mean [SD] peak glucose after the high fat meal (146 [20] mg/dl) was higher than after the high protein meal (137 [21] mg/dl) (P=0.03), but individuals varied in their differential response to the meals (range: 25 mg/dl higher after high protein meal to 35 mg/dl higher after high fat meal). Median time to peak glucose (IQR) was 72 (63-74) minutes after the high protein meal and 65 (60-73) minutes after the high fat meal (P=0.11). There was no difference in differential glycemic response to the meals in IR (n=8) vs ID (n=4) GDM (P=0.98); age (median [IQR] 36 [33-38] yrs) and BMI (median [IQR] 27 [24-30]) adjustment did not change results (P=0.82). Conclusion: On average, women with GDM have lower post prandial glucose levels after a high protein meal compared to a high fat meal with equivalent carbohydrate content. This may inform GDM dietary recommendations and motivate research on determinants of individual-level response to macronutrients. Disclosure E.A.Rosenberg: None. T.Thaweethai: None. K.James: None. E.Kelty: None. R.L.Azevedo: None. S.Nelson: None. J.L.Garry: None. E.W.Seely: None. C.E.Powe: Consultant; Mediflix, Inc., Other Relationship; Wolters Kluwer Health. Funding Robert Wood Johnson Foundation; National Institutes of Health (5F32DK12634302); Endocrine Fellows Foundation

61-LB: Blood Pressure and Lipid-Lowering Medication Adherence in Young Adults with Youth-Onset Type 2 Diabetes and Hypertension or Dyslipidemia—The TODAY2 iCount Study

Youth-onset type 2 diabetes (T2D) is associated with early development of vascular complications. Treatment of hypertension and dyslipidemia are critical to reduce morbidity. iCount examined adherence to blood pressure (BP) and lipid-lowering medications in young adults with youth-onset T2D (mean age 26 y, duration of T2D 12 y, BMI 37 kg/m2) and hypertension/nephropathy (n=196) or dyslipidemia (n=146) during the observational phase of the Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY)2 study (2017-2019). They were receiving diabetes care in their communities. Adherence was assessed with 3 monthly unannounced phone pill counts at 2 times 1 year apart. Percent low adherent (<80% pill-taking) and high-adherent (≥80% pill-taking) did not change over time. Of participants with hypertension and/or nephropathy, 80.1% were low adherent, 19.9% were high adherent. Those who were low adherent had fewer years of education (p=0.004), higher HbA1c (p=0.001) and shorter diabetes duration (p=0.031). Of those with dyslipidemia, 93.8% were low adherent, 6.2% high adherent. Those low adherent to BP (p<0.001) and lipid-lowering (p≤0.008) medications were also low adherent to oral hypoglycemic medications or insulin. Beliefs that medications are necessary were lower for those low adherent to BP and lipid-lowering medications (unadjusted analyses); concerns about medications also were lower for those low adherent to lipid-lowering medications. In adjusted multivariable analyses of participants with hypertension or nephropathy, having ≥1 material need insecurity predicted medication adherence 1 year later (p=0.010). Belief about medicines, diabetes distress, self-efficacy, depressive and anxiety symptoms, and self-management support were not 1 yr predictors of medication adherence. To prevent early vascular events, approaches that further identify and address unmet needs should be studied. Disclosure P. M. Trief: None. R. S. Weinstock: Consultant; Jaeb Center for Health Research, Other Relationship; Wolters Kluwer Health, Research Support; Insulet Corporation, Medtronic, Eli Lilly and Company, Novo Nordisk, Boehringer Ingelheim Inc., Hemsley Charitable Trust, National Institute of Diabetes and Digestive and Kidney Diseases, Tandem Diabetes Care, Inc., Kowa Pharmaceuticals America, Inc. B. K. Burke: None. H. Wen: None. S. Kalichman: None. J. D. Bulger: None. B. J. Anderson-thomas: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (R01DK110456)