A retrospective study of distribution of HIV associated malignancies among inpatients from 2007 to 2020 in China

HIV-associated malignancies are responsible for morbidity and mortality increasingly in the era of potent antiretroviral therapy. This study aimed to investigate the distribution of HIV-associated malignancies among inpatients, the immunodeficiency and the effect of antiretroviral therapy (ART) on spectrum of HIV-associated malignancies. A total of 438 cases were enrolled from 2007 to 2020 in Beijing Ditan Hospital. Demographic, clinical and laboratory data, managements, and outcomes were collected and analyzed retrospectively. Of 438 cases, 433 were assigned to non-AIDS-defining cancers (NADCs) (n = 200, 45.7%) and AIDS-defining cancers (ADCs) (n = 233, 53.2%), 5 (1.1%) with lymphoma were not specified further. No significant change was observed in the proportion of NADCs and ADCs as time goes on. Of NADCs, lung cancer (n = 38, 19%) was the most common type, followed by thyroid cancer (n = 17, 8.5%). Patients with ADCs had lower CD4 counts(104.5/μL vs. 314/μL), less suppression of HIVRNA(OR 0.23, 95%CI 0.16–0.35) compared to those with NADCs. ART did not affect spectrum of NADCs, but affect that of ADCs (between patients with detectable and undetectable HIVRNA). ADCs remain frequent in China, and NADCs play an important role in morbidity and mortality of HIV positive population.

Index60 Identifies Individuals at Appreciable Risk for Stage 3 Among an Autoantibody-Positive Population With Normal 2-Hour Glucose Levels: Implications for Current Staging Criteria of Type 1 Diabetes

<u>Objective</u><b>:</b> We assessed whether Index60, a composite measure of fasting C-peptide, 60-minute C-peptide, and 60-minute glucose, could improve the metabolic staging of type 1 diabetes for progression to clinical disease (stage 3) among autoantibody positive (Ab+) individuals with normal 2-hour glucose values (<140 mg/dL). <p><u>Research Design and Methods</u>: We analyzed 3058 Type 1 Diabetes TrialNet Pathway to Prevention participants, with 2-hour glucose<140 mg/dL and Index60<1.00 values from baseline OGTTs. Characteristics associated with type 1 diabetes (younger age, greater autoantibody positivity [Ab+], higher HLA DR3-DQ2/DR4-DQ8 prevalence, lower C-peptide) were compared among four mutually exclusive groups: top 2-hour glucose quartile only [HI-2HGLU], top Index60 quartile only [HI-IND60], both top quartiles [HI-BOTH], neither top quartile [LO-BOTH]. Additionally, within the 2-hour glucose distribution of <140 mg/dL, and separately within the Index60<1.00 distribution, comparisons were made between those above or below the medians.</p> <p><u>Results</u>: HI-IND60 and HI-BOTH were younger, with greater frequency of >2 Ab+, and lower C-peptide levels than either HI-2HGLU or LO-BOTH (all p<0.001). The cumulative incidence for stage 3 was greater for HI-IND60 and HI-BOTH than either HI-2HGLU or LO-BOTH (all p<0.001). Those with Index60 values above the median were younger, had higher ≥2Ab+ (p<0.001) and DR3-DQ2/DR4-DQ8 prevalence (p<0.001), and lower AUC C-peptide levels (p<0.001) than those below. Those above the 2-hour glucose median had higher AUC C-peptide levels (p<0.001), but otherwise did not differ from those below. </p> <p><u>Conclusion</u>: Index60 identifies individuals with characteristics of type 1 diabetes at appreciable risk for progression who would otherwise be missed by 2-hour glucose staging criteria. </p>

Index60 Identifies Individuals at Appreciable Risk for Stage 3 Among an Autoantibody-Positive Population With Normal 2-Hour Glucose Levels: Implications for Current Staging Criteria of Type 1 Diabetes

<u>Objective</u><b>:</b> We assessed whether Index60, a composite measure of fasting C-peptide, 60-minute C-peptide, and 60-minute glucose, could improve the metabolic staging of type 1 diabetes for progression to clinical disease (stage 3) among autoantibody positive (Ab+) individuals with normal 2-hour glucose values (<140 mg/dL). <p><u>Research Design and Methods</u>: We analyzed 3058 Type 1 Diabetes TrialNet Pathway to Prevention participants, with 2-hour glucose<140 mg/dL and Index60<1.00 values from baseline OGTTs. Characteristics associated with type 1 diabetes (younger age, greater autoantibody positivity [Ab+], higher HLA DR3-DQ2/DR4-DQ8 prevalence, lower C-peptide) were compared among four mutually exclusive groups: top 2-hour glucose quartile only [HI-2HGLU], top Index60 quartile only [HI-IND60], both top quartiles [HI-BOTH], neither top quartile [LO-BOTH]. Additionally, within the 2-hour glucose distribution of <140 mg/dL, and separately within the Index60<1.00 distribution, comparisons were made between those above or below the medians.</p> <p><u>Results</u>: HI-IND60 and HI-BOTH were younger, with greater frequency of >2 Ab+, and lower C-peptide levels than either HI-2HGLU or LO-BOTH (all p<0.001). The cumulative incidence for stage 3 was greater for HI-IND60 and HI-BOTH than either HI-2HGLU or LO-BOTH (all p<0.001). Those with Index60 values above the median were younger, had higher ≥2Ab+ (p<0.001) and DR3-DQ2/DR4-DQ8 prevalence (p<0.001), and lower AUC C-peptide levels (p<0.001) than those below. Those above the 2-hour glucose median had higher AUC C-peptide levels (p<0.001), but otherwise did not differ from those below. </p> <p><u>Conclusion</u>: Index60 identifies individuals with characteristics of type 1 diabetes at appreciable risk for progression who would otherwise be missed by 2-hour glucose staging criteria. </p>

Analysis of the impact of sex and age on the variation in the prevalence of antinuclear autoantibodies in Polish population: a nationwide observational, cross-sectional study

The detection of antinuclear autoantibody (ANA) is dependent on many factors and varies between the populations. The aim of the study was first to assess the prevalence of ANA in the Polish adult population depending on age, sex and the cutoff threshold used for the results obtained. Second, we estimated the occurrence of individual types of ANA-staining patterns. We tested 1731 patient samples using commercially available IIFA using two cutoff thresholds of 1:100 and 1:160. We found ANA in 260 participants (15.0%), but the percentage of positive results strongly depended on the cutoff level. For a cutoff threshold 1:100, the positive population was 19.5% and for the 1:160 cutoff threshold, it was 11.7%. The most prevalent ANA-staining pattern was AC-2 Dense Fine speckled (50%), followed by AC-21 Reticular/AMA (14.38%) ANA more common in women (72%); 64% of ANA-positive patients were over 50 years of age. ANA prevalence in the Polish population is at a level observed in other highly developed countries and is more prevalent in women and elderly individuals. To reduce the number of positive results released, we suggest that Polish laboratories should set 1:160 as the cutoff threshold.

33. Evaluation of Rural-Urban Differences in Hospitalization and Mortality Rates for US COVID-19 Patients in the United States

Background Rural communities are among the most vulnerable and resource-scarce populations in the United States. Rural data is rarely centralized, precluding comparability across regions, and no significant studies have studied this population at scale. The purpose of this study is to present findings from the National COVID Cohort Collaborative (N3C) to provide insight into future research and highlight the urgent need to address health disparities in rural populations. N3C Patient Distribution This figure shows the geospatial distribution of the N3C COVID-19 positive population. N3C contains data from 55 data contributors from across the United States, 40 of whom include sufficient location information to map by ZIP Code centroid spatially. Of those sites, we selected 27 whose data met our minimum robustness qualifications for inclusion in our study. This bubble map is to scale with larger bubbles representing more patients. A. shows all N3C patients. B. shows only urban N3C distribution. C. shows the urban-adjacent rural patient distribution. D. shows the nonurban-adjacent rural patient distribution, representing the most isolated patients in N3C. Methods This retrospective cohort of 573,018 patients from 27 hospital systems presenting with COVID-19 between January 2020 and March 2021, of whom 117,897 were admitted (see Data Analysis Plan diagram for inclusion/exclusion criteria), analyzes outcomes and 30-day survival for the hospitalized population by the degree of rurality. Multivariate Cox regression analysis and mixed-effects models were used to estimate the association between rurality, hospitalization, and all-cause mortality, controlling for major risk factors associated with rural-urban health discrepancies and differences in health system outcomes. The difference in distribution by rurality is described as well as supplemented by population-level statistics to confirm representativeness. Data Analysis Plan This data analysis plan includes an overview of study inclusion and exclusion criteria, the matrix for data robustness to determine potential sites to include, and our covariate selection, model building, and residual testing strategy. Results This study demonstrates a significant difference between hospital admissions and outcomes in urban versus urban-adjacent rural (UAR) and nonurban-adjacent rural (NAR) lines. Hospital admissions for UAR (OR 1.41, p&lt; 0.001, 95% CI: 1.37 – 1.45) and NAR (OR 1.42, p&lt; 0.001, 95% CI: 1.35 – 1.50) were significantly higher than their urban counterparts. Similar distributions were present for all-cause mortality for UAR (OR 1.39, p&lt; 0.001, 95% CI: 1.30 – 1.49) and NAR (OR 1.38, p&lt; 0.001, 95% CI: 1.22 – 1.55) compared to urban populations. These associations persisted despite adjustments for significant differences in BMI, Charlson Comorbidity index Score, gender, age, and the quarter of diagnosis for COVID-19. Baseline Characteristics Hospitalized COVID-19 Positive Population by Rurality Category, January 2020 – March 2021 Survival Curves in Hospitalized Patients Over 30 Days from Day of Admission This figure shows a survival plot of COVID-19 positive hospitalized patients in N3C by rural category (A), Charlson Comorbidity Index (B), Quarter of Diagnosis (C), and Age Group (D) from hospital admission through day 30. Events were censored at day 30 based on the incidence of death or transfer to hospice care. These four factors had the highest predictive power of the covariates evaluated in this study. Unadjusted and Adjusted Odds Ratios for Hospitalization and All-Cause Mortality by Rural Category, January 2020 – March 2021 This figure shows the adjusted and unadjusted odds ratios for being hospitalized or dying after hospitalization for the COVID-19 positive population in N3C. Risk is similar between adjusted and unadjusted models, suggesting a real impact of rurality on all-cause mortality. A shows the unadjusted odds ratios for admission to the hospital after a positive COVID-19 diagnosis for all N3C patients. B shows the unadjusted odds ratios for all-cause mortality at any point after hospitalization for COVID-19 positive patients. C shows the adjusted odds ratios for being admitted to the hospital after a positive COVID-19 diagnosis for all N3C patients. D shows the adjusted odds ratios for all-cause mortality for all-cause mortality at any point after hospitalization for COVID-19 positive patients. Adjusted models include adjustments for gender, race, ethnicity, BMI, age, Charlson Comorbidity Index (CCI) composite score, rurality, and quarter of diagnosis. The data provider is included as a random effect in all models. Conclusion In N3C, we found that hospitalizations and all-cause mortality were greater among rural populations when compared to urban populations after adjustment for several factors, including age and co-morbidities. This study also identified key demographic and clinical disparities among rural patients that require further investigation. Disclosures Sally L. Hodder, M.D., Gilead (Advisor or Review Panel member)Merck (Grant/Research Support, Advisor or Review Panel member)Viiv Healthcare (Grant/Research Support, Advisor or Review Panel member)

Prevalence of diabetes mellitus and hypertension amongst the HIV-positive population at a district hospital in eThekwini, South Africa

Background: Life expectancies of HIV-positive patients have been increasing with the rapid implementation of antiretroviral therapy (ART). This has led to an increase in comorbidities such as diabetes mellitus (DM) and hypertension (HT) amongst the HIV population. The burden of the non-communicable diseases (NCDs) such as DM and HT need to be quantified in order to ensure that patients receive optimal integrated care as patients often access care at different clinics compromising holistic care.Aim: The aim of the study was to determine the prevalence of DM and HT amongst the HIV-positive population.Setting: The study was conducted at Wentworth Hospital, a district facility in South Durban, KwaZulu-Natal.Methods: This cross-sectional study was undertaken to determine the prevalence of two NCDs, namely DM and HT in HIV-positive patients attending the ART clinic at a district hospital in the eThekwini district. We compared the socio-demographic and clinical profiles of those with and without comorbidities. A sample of 301 HIV-positive patients were administered a structured questionnaire.Results: Of the 301 patients, 230 (76.41%) had HIV only (95% confidence interval [CI]: 71.25–80.89) and 71 (23.59%) had HIV and at least one comorbidity, namely DM and/or HT (95% CI: 19.11-28.75). Hypertension was the most prevalent comorbidity. This study revealed that there was no association between the duration of ART and comorbidities. Older age and body mass index (BMI) were associated with comorbidities, whilst gender and ethnicity were not associated.Conclusion: Non-communicable diseases such as DM and HT do pose a burden for HIV-positive patients attending the ARV clinic at this district facility. This study highlights the definite need to plan for the increased burden of NCDs as HIV-positive patients live longer and gain weight.

Mitochondrial DNA Haplogroup Related to the Prevalence of Helicobacter pylori

Mitochondria are essential organelles that are not only responsible for energy production but are also involved in cell metabolism, calcium homeostasis, and apoptosis. Targeting mitochondria is a key strategy for bacteria to subvert host cells’ physiology and promote infection. Helicobacter (H.) pylori targets mitochondria directly. However, mitochondrial genome (mtDNA) polymorphism (haplogroup) is not yet considered an important factor for H. pylori infection. Here, we clarified the association of mitochondrial haplogroups with H. pylori prevalence and the ability to perform damage. Seven mtDNA haplogroups were identified among 28 H. pylori-positive subjects. Haplogroup B was present at a higher frequency and haplotype D at a lower one in the H. pylori population than in that of the H. pylori-negative one. The fibroblasts carrying high-frequency haplogroup displayed a higher apoptotic rate and diminished mitochondrial respiration following H. pylori infection. mtDNA mutations were accumulated more in the H. pylori-positive population than in that of the H. pylori-negative one in old age. Among the mutations, 57% were located in RNA genes or nonsynonymous protein-coding regions in the H. pylori-positive population, while 35% were in the H. pylori-negative one. We concluded that gastric disease caused by Helicobacter virulence could be associated with haplogroups and mtDNA mutations.