Binomial Distribution Research Articles

Protection conferred by booster vaccine doses in hospitalized patients with COVID-19 during the SARS-CoV-2 Omicron BA.2 and BA.5 epidemics from 2022 to 2023 in Greece

BackgroundTo estimate the protection that coronavirus disease 2019 (COVID-19) vaccine doses conferred to hospitalized patients with COVID-19 against adverse outcomes and longer length of stay during the Omicron BA.2 and BA.5 subvariant epidemics in Greece. MethodsThe study was conducted from November 2022 to May 2023. Multivariable logistic and negative binomial regression models were applied to estimate the association between any adverse outcomes and length of stay with the number of COVID-19 vaccine doses. ResultsWe studied 962 patients (median age: 78 years; mean length of stay: 9.2 days), of whom 847 (88.0%) had ≥ 1 comorbidity. Of these, 39 (4.0%) were admitted to the intensive care unit, 44 (4.6%) received invasive mechanical ventilation, and 110 (11.4%) died in hospital. There were 184 (19.1%) unvaccinated patients, 125 (13.0%) with one or two vaccine doses, and 653 (67.9%) with ≥ 3 doses. In multivariable analyses, patients with ≥ 3 doses had lower odds of experiencing any adverse outcomes (adjusted odds ratio: 0.57; 95% confidence interval [CI]: 0.37–0.86) compared with unvaccinated patients. On average, patients with one or two doses and those with ≥ 3 had decreased length of hospital stay (−1.5 days [95% CIs: −2.6 to −0.4] and −2.8 days [95% CIs: −4.1 to −1.4], respectively] compared with unvaccinated patients. Other characteristics consistently associated with adverse outcomes and longer length of stay included older age, having three or more comorbidities compared with none, and being admitted to the hospital two or more weeks post-diagnosis. ConclusionsA history of ≥ 3 vaccine doses conferred significant protection against any adverse outcome and longer length of stay in hospitalized patients with COVID-19.

Identifiable historic and observable factors may predict progression to exfoliation glaucoma in newly-diagnosed exfoliation patients

To identify clinical factors associated with conversion to exfoliation glaucoma (XFG) in exfoliation syndrome (XFS) patients most at risk of progression to XFG within 3 years for increased surveillance and early preventive interventions. A retrospective patient cohort study design was employed. A source population of XFS patients 50 years and older was identified from electronic medical records in the Utah Population Database. From this, 487 study patients with one or more dilated eye exams prior to chart-confirmed XFS onset in 2011 or later, and three or more years of subsequent eye exams, were selected for study. We implemented a binomial linear mixed models with L1-penalized estimation to select variables associated with conversion. Models included a random intercept to account for within-patient correlation for eye-level data. Candidate demographic, lifestyle, systemic and ocular comorbidities data were obtained and diagnoses categorized as binary (history or no history). These potential factors between conversion and non-conversion patients were used in model selection of variables jointly predictive of conversion. Odds ratios and confidence intervals were calculated using the link logit. To determine the main outcome of conversion to XFG following an index diagnosis of XFS compared with nonconversion within 3 years, clinical records of each subject's left and right eyes were assessed to confirm XFS and date of onset and date of XFG onset, if conversion occurred. Clinical measurements, e.g. intraocular pressure (IOP), cup to disc ratio, provider notes and IOP-lowering procedures and medications were used to corroborate conversion status. Eighteen variables jointly predicted XFG conversion within 3 years correctly in 71% of patient eyes. Odds of conversion was highest for exudative age-related macular degeneration (AMD), 2.3-fold (P=0.004). Other predictive variables included nonexudative AMD (P=0.05), primary open angle glaucoma (P<0.001), obstructive sleep apnea (P=0.03), and ocular hypertension (P=0.003) diagnosed prior to XFS onset. We determined a set of clinically relevant factors that predicted which newly-diagnosed XFS patients progressed to XFG within 3 years. A planned validation will independently confirm if these prognostic indicators hold promise in other settings.

Health care disparities and bladder cancer mortality in the United States: A closer look at the social vulnerability index.

150 Background: Bladder cancer is a significant public health concern, with various factors influencing mortality rates. The Social Vulnerability Index (SVI) measures community resilience to external health stresses. This study investigates the association between bladder cancer mortality (BCM) and county-level SVI in the United States (U.S.). Methods: Mortality data from U.S. counties were obtained from the Centers for Disease Control (CDC) and Prevention Wide-Ranging Online Data for Epidemiologic Research (WONDER) database from 2015 to 2019 using the International Classification of Diseases-10th Edition (Code C67). The CDC and Agency for Toxic Substances and Disease Registry (ATSDR) county-level SVI was used as a composite measure of social vulnerability. The SVI includes several U.S. census variables grouped into four themes: Socioeconomic Status (SES), Household Characteristics, Racial and Ethnic Minority Status, and Housing Type and Transportation. Vulnerable SES variables include individuals with incomes below 150% of the federal poverty line, unemployment, those with housing cost burdens, and those without high school diplomas or health insurance. Vulnerable household variables include seniors over 65 years, children under 17 years, disabled civilians, single-parent households, and those with limited English proficiency. SVI Quartiles (Q1 being the least vulnerable and Q4 the most vulnerable) were compared to assess their impact on BCM. Negative binomial regression models were used to estimate Incidence Rate Ratios (IRRs) with 95% Confidence Intervals (CIs) using SAS software. Results: From 2015 to 2019, a total of 82,994 people died from bladder cancer, and the age-adjusted mortality rate per 1,000,000 was 42.4. A higher SVI in intermediate vulnerability quartiles was associated with a higher risk of BCM (Q2 and Q3: IRR = 1.06; 95% CI = 1.01-1.10; p = 0.009) compared to the least vulnerable quartile, Q1. Vulnerable SES had an increased risk of BCM (Q2 and Q3: IRR = 1.07; 95% CI = 1.03-1.12; p &lt; 0.001) compared to Q1. BCM was also increased in individuals with vulnerable household characteristics (Q2 and Q3: IRR = 1.06; 95% CI = 1.02-1.10; p = 0.004) compared to Q1. Q4 was not significant in comparison to Q1 for the groups mentioned above. Interestingly, Racial and Ethnic Minority Status (Hispanic, Latino, African American, etc.) was associated with lower BCM in Q2 and Q3 (IRR = 0.88; 95% CI = 0.84-0.92; p &lt; 0.001) and Q4 (IRR = 0.77; 95% CI = 0.73-0.81; p &lt; 0.001) compared to Q1. No significant mortality differences were observed among vulnerable Housing Types and Transportation. Conclusions: Bladder cancer mortality is linked to vulnerable socioeconomic and household characteristics, while racial and ethnic minority status correlates with decreased risk. Future targeted public health interventions are needed to reduce bladder cancer mortality in vulnerable populations. Bladder cancer mortality and its association with social vulnerability quartiles. Bladder Cancer Mortality Characteristic IRR 95% CI p-value Social Vulnerability Index Q1 — — Q2&amp;Q3 1.06 1.01, 1.10 0.009 Q4 0.98 0.93, 1.03 0.4 Socioeconomic Status Q1 — — Q2&amp;Q3 1.07 1.03, 1.12 &lt;0.001 Q4 1.00 0.95, 1.05 &gt;0.9 Household Characteristics Q1 — — Q2&amp;Q3 1.06 1.02, 1.10 0.004 Q4 1.05 1.00, 1.10 0.052 Racial &amp; Ethnic Minority Status Q1 — — Q2&amp;Q3 0.88 0.84, 0.92 &lt;0.001 Q4 0.77 0.73, 0.81 &lt;0.001 Housing Type &amp; Transportation Q1 — — Q2&amp;Q3 1.03 0.99, 1.08 0.2 Q4 0.98 0.93, 1.03 0.4 IRR = Incidence Rate Ratio, CI = Confidence Interval.

Salivary polyreactive antibodies and Haemophilus influenzae are associated with respiratory infection severity in young children with recurrent respiratory infections.

Recurrent respiratory tract infections (rRTIs) are a common reason for immunodiagnostic testing in children, which relies on serum antibody level measurements. However, because RTIs predominantly affect the respiratory mucosa, serum antibodies may inaccurately reflect local immune defences. We investigated antibody responses in saliva and their interplay with the respiratory microbiota in relation to RTI severity and burden in young children with rRTIs. We conducted a prospective cohort study including 100 children aged <10 years with rRTIs, their family members and healthy healthcare professionals. Total and polyreactive antibody concentrations were determined in serum and saliva (ELISA); respiratory microbiota composition (16S rRNA sequencing) and respiratory viruses (quantitative PCR) were characterised in nasopharyngeal swabs. Proteomic analysis (Olink) was performed on saliva and serum samples. RTI symptoms were monitored with a daily mobile phone application and assessed using latent class analysis and negative binomial mixed models. Serum antibody levels were not associated with RTI severity. Strikingly, 28% of salivary antibodies and only 2% of serum antibodies displayed polyreactivity (p<0.001). Salivary polyreactive IgA was negatively associated with recurrent lower RTIs (adjusted OR 0.80, 95% CI 0.67-0.94) and detection of multiple respiratory viruses (adjusted OR 0.76, 95% CI 0.61-0.96). Haemophilus influenzae abundance was positively associated with RTI symptom burden (regression coefficient 0.05, 95% CI 0.02-0.08). These results highlight the importance of mucosal immunity in RTI severity and burden, and suggest that the level of salivary polyreactive IgA and H. influenzae abundance may serve as indicators of infection severity and burden in young children with rRTIs.

Social and policy characteristics associated with injurious shootings by police in US counties: A multilevel analysis, 2015-2020.

From 2015 to 2020, shootings by police injured or killed 1769 people annually in the United States, disproportionately harming members of minoritized groups. Prior studies of the structural determinants of these inequities have largely examined state-level aggregations and fatal outcomes. This study aimed to: 1) describe state and county variation in fatal and nonfatal injurious shootings by police, and 2) analyze the relationship between state and county context and differences in county rates of injurious shootings by police. Injury data were developed from manual review of incidents listed in the Gun Violence Archive, then aggregated by county-year. Covariate selection was informed by theories of police use of force and the Social Basis of Disparities in Health conceptual framework. Fixed effects negative binomial regression models were estimated, nesting years within counties and states. Analyses controlled for county population, local reporting presence, and multiple measures of social conflict and community violence. From 2015 to 2020, 56% of counties experienced injurious shootings by police. Higher county rates of victimization were associated with greater state spending on police relative to health, county income inequality, prevalence of unmet substance use disorder needs, higher county firearm availability, and permitless concealed carry statutes. Firearm purchaser licensing polices were associated with lower incidence of injurious shootings by police. To prevent patterns of injurious shootings by police, policymakers should consider addressing undermanaged substance use disorder through crisis fund allocation and use, adopting stronger firearm licensing systems, and evaluating local strategies to combat inequities and strengthen non-policing responses to social needs.

Clinical and economic outcomes of a pharmacogenomics-enriched comprehensive medication management program in a self-insured employee population

Clinical and economic outcomes from a pharmacogenomics-enriched comprehensive medication management program were evaluated over 26 months in a self-insured U.S. employee population (n = 452 participants; n = 1500 controls) using propensity matched pre-post design with adjusted negative binomial and linear regression models. After adjusting for baseline covariates, program participation was associated with 39% fewer inpatient (p = 0.05) and 39% fewer emergency department (p = 0.002) visits, and with 21% more outpatient visits (p < 0.001) in the follow-up period compared to the control group. Results show pharmacogenomics-enriched comprehensive medication management can favorably impact healthcare utilization in a self-insured employer population by reducing emergency department and inpatient visits and can offer the potential for cost savings. Self-insured employers may consider implementing pharmacogenomics-enriched comprehensive medication management to improve the healthcare of their employees.

Influence of park visitation on physical activity, well-being and social connectedness among Australians during COVID-19.

This cross-sectional study examined associations of park visitation with physical activity (PA), well-being, and social connectedness among 1089 participants during the coronavirus disease 2019 pandemic. In August 2020, adolescents and adults in Australia self-reported demographics, usual park visitation, frequency and duration of park visits, PA, well-being and social connectedness. Multilevel linear regression models examined associations of park visitation with well-being and social connectedness. Multilevel mixed-effects negative binomial regression models examined associations between visitation and PA. Compared to not visiting a park, visitation was positively associated with well-being (B = 3.92, 95% confidence interval [CI] = 1.24, 6.60) and days/week performing PA for 30 min (B = 1.24, 95% CI = 1.11, 1.39) per day and negatively associated with social connectedness (B = -3.75, 95% CI = -7.11, -0.39). Compared to visiting a park less than once/week, visiting once/week was positively associated with well-being (B = 3.90, 95% CI = 0.53, 7.21). Visiting more than once/week was positively associated with days/week performing PA for 30 min (B = 1.37, 95% CI = 1.21, 1.58) and 60 min (B = 1.34, 95% CI = 1.09, 1.64) per day and with well-being (B = 4.19, 95% CI = 0.90, 7.49). Duration of park visits was positively associated with days/week performing PA for 30 min (B = 1.09, 95% CI = 1.04, 1.13) and 60 min (B = 1.09, 95% CI = 1.02, 1.17) per day. Our findings highlight the role of parks in positively influencing health-related outcomes and the 'dosage' of park use needed to attain health benefits.

Association between child marriage and high blood glucose level in women: A birth cohort analysis

ObjectivesChild marriage prematurely forces girls (<18 years of age) to perform adult roles prior to physical and psychological maturity. Such precocious transitions to young adulthood can have consequences on their long-term health, however, limited work has examined such relationships to date. As such, this study examines whether child marriage is associated with the risk of having hyperglycemia, or high blood glucose, in adulthood. Study designObservational study using repeated cross-sectional data. MethodsUsing data from the 2015-16 and 2019-21 waves of the India National Family Health Survey, we matched 432,080 and 418,409 women, aged 20 to 49 years, by birth year and month to create birth cohorts. Fitting multivariable binomial and multinomial logistic models, we compared the odds of having hyperglycemia across groups by marriage age (i.e., before or after age 18 years) within respective birth cohorts. ResultsWe found that the adjusted odds of having high blood glucose among women married as children were 1.12 (95% CI: 1.07 – 1.16) times that of their peers married as adults in the full-sample. The adjusted relative risks of having blood glucose levels higher than normal but lower than diabetic and diabetic ranges were 1.09 (95% CI: 1.04 – 1.14) and 1.23 (95% CI: 1.15 – 1.31), respectively, in comparison to blood glucose within normal range. These results were persistent across sub-groups of different birth cohorts. ConclusionOur findings suggest that child marriage was associated with higher risk of having high blood glucose in women, later in life.

Impact of early palliative care referral in patients with locally advanced and metastatic GI/lung cancer.

201 Background: Early palliative care improves quality of life and survival in patients with metastatic NSCLC. As a result, ASCO recommends early palliative care integration in patients with metastatic cancer. However, generalizing the benefits outside of a clinical trial may be difficult due to selection bias of patients that opt into palliative care due to advanced symptom burden and real-world resource constraints. Therefore, the benefits of this in real-world practice may not be realized. We aimed to evaluate early vs late palliative care referral impact on unplanned hospital visits and survival among GI and lung cancer patients at a large health system cancer center. Methods: The study design was a retrospective, single health system, review of patients treated at Orlando Health from 2021-2022.156 patients of all stage GI and Lung cancers were included. For these patients, early referral was defined as receiving a palliative referral within 8 weeks of cancer diagnosis. Any referral later than this was considered late and it was possible for patients to opt out of referral. Our main outcomes were unplanned hospital visits and survival. To compare the rates of these between palliative care referral groups, a multivariable negative binomial regression model was fitted. To assess any differences in survival, a multivariable cox hazard regression model was fitted. These were adjusted for age, sex, diagnosis, stage, ECOG, race, and insurance. Results: Patients with any palliative care referral had increased unplanned hospital visits and shorter survival than patients who did not have referrals. Specifically, patients with no palliative care referrals had a 62% lower relative rate of unplanned hospital visits compared to patients with early referral (RR = 0.38 [0.22-0.66], p&lt;0.001). And patients with any time referral had approximately 8 months lower restricted mean survival times (RMST) when followed for 2 years for stage 1-3 cancers than patients receiving no palliative care (14 vs 22 month RMST; stage x palliative care interaction, p &lt;0.05). In contrast, stage 4 patients had similar survival of ~14-month RMST when followed for 2 years regardless of referral. Conclusions: In real world practice palliative care referral was associated with increased unplanned hospital visits. Additionally, in this retrospective review, palliative care referral was not found to confer a survival advantage in gastrointestinal and Lung cancer patients. We postulate that this is related to selection bias in the opt in approach to palliative care referral biasing towards a sicker population with higher symptom burden and comorbidities. Our future prospective study will build upon this work through expansion of palliative care services and to better evaluate patient co-morbidities. Our goal is to increase utilization of palliative care for patients with GI and lung malignancies as part of a multidisciplinary integrative approach.

Exploring Differentially Expressed Genes and Immune Modulation in Diffuse Large B-Cell Lymphoma through RNA Sequencing Analysis.

Diffuse large B-cell lymphoma (DLBCL) is globally recognized as the most prevalent and aggressive subtype of non-Hodgkin lymphoma. While conventional treatments are effective initially, the disease can become resistant or relapse over time. This study aimed to examine the differentially expressed genes at the transcriptome level and molecular pathways in DLBCL patients. This investigation utilized RNA sequencing analysis to compare differentially expressed gene samples from five diffuse large B-cell lymphoma patients with two healthy volunteers. These participants were admitted to UKM Medical Center, Kuala Lumpur between 2019 and 2020. The differentially expressed genes were identified using the DESeq2 R package (version 1.10.1) using a negative binomial distribution model. The obtained P values were corrected with the Benjamin and Hochberg method and identified using a False Discovery Rate threshold of <0.05, with log2 fold change (FC) of ≥2 or ≤-2. Results showed 73 differentially expressed genes between the two groups, among which 70 genes were downregulated, and three genes were upregulated. The differentially expressed genes analyzed with the Reactome pathway were significantly associated with the downregulation of antimicrobial humoral response (P<0.001), neutrophil degranulation (P<0.001), chemokine receptors bind chemokines (P=0.028), defensins (P=0.028) and metabolism of angiotensinogen (P=0.040). These findings suggest that the identified pathways may contribute to cancer progression and weaken the immune response in diffuse large B-cell lymphoma patients. This study offers fresh insights into previously undiscovered downstream targets and pathways modulated by diffuse large B-cell lymphoma.

Integration of a fully automated flow cytometry system with high robustness into a Screening Station

In recent years, there has been an increasing demand for the detection of rare cells in drug discovery research, such as cells that have differentiated off-purpose or are required for immunogenicity evaluation. Since detection and quantification limits depend on the robustness of the experiment, inter-human differences in technique have a significant impact on the performance of the assay system. Here, we integrated flow cytometry into a cell experiment platform, Screening Station, to construct a robust assay system, examined each step of the flow cytometric pretreatment using Jurkat cells, and finally evaluated the overall assay performance. Cell detection rate when the experiment was performed manually was 48.8% ± 5.7% (CV=11.6%) versus 73.7%±2.0% (CV=2.8%) with the automated method. To further clarify the analytical performance of the automated method, 1-100 PD-1 expressing Jurkat cells were spiked with 1 × 105 Jurkat cells, and the lower limit of detection, linearity, and CV% were evaluated. Average detection rate was 69%, decision count was 0.985, and lower limit of detection was 4 cells (0.004%). We evaluated the CV% value of the number of detected cells per spiked cell and found our system to be highly robust, approximating a binomial distribution with a 69% recovery rate. In conclusion, we have integrated the Novocyte flow cytometry system into an automated experimental platform, Screening Station, to create a fully automated flow cytometric assay system with high robustness. Our platform can fulfill the technology needs of drug discovery for rare cell detection, which have intensified in recent years.

Model for random internalization of nanoparticles by cells

We propose a stochastic model for the internalization of nanoparticles by cells formulating cellular uptake as a compound Poisson process with a random probability of success. This is an alternative approach to the one presented by Rees [] who explained overdispersion in nanoparticle uptake and associated negative binomial distribution by considering a Poisson distribution for particle arrival and a gamma-distributed cell area. In our stochastic model, the formation of new pits is represented by the Poisson process, whereas the capturing process and the population heterogeneity are described by a random Bernoulli process with a beta-distributed probability of success. The random probability of success generates ensemble-averaged conditional transition probabilities that increase with the number of newly formed pits (self-reinforcement). As a result, an ensemble-averaged nanoparticle uptake can be represented as a Polya process. We derive an explicit formula for the distribution of the random number of pits containing nanoparticles. In the limit of the fast nucleation and low probability of nanoparticle capture, we find the negative binomial distribution. Published by the American Physical Society 2024

Multi-Scale Information Fusion and Decoupled Representation Learning for Robust Microbe-Disease Interaction Prediction

Research indicates that microbe activity within the human body significantly influences health by being closely linked to various diseases. Accurately predicting microbe-disease interactions (MDIs) offers critical insights for disease intervention and pharmaceutical research. Current advanced AI-based technologies automatically generate robust representations of microbes and diseases, enabling effective MDI predictions. However, these models continue to face significant challenges. A major issue is their reliance on complex feature extractors and classifiers, which substantially diminishes the models’ generalizability. To address this, we introduce a novel graph autoencoder framework that utilizes decoupled representation learning and multi-scale information fusion strategies to efficiently infer potential MDIs. Initially, we randomly mask portions of the input microbe-disease graph based on Bernoulli distribution to boost self-supervised training and minimize noise-related performance degradation. Secondly, we employ decoupled representation learning technology, compelling the graph neural network (GNN) to independently learn the weights for each feature subspace, thus enhancing its expressive power. Finally, we implement multi-scale information fusion technology to amalgamate the multi-layer outputs of GNN, reducing information loss due to occlusion. Extensive experiments on public datasets demonstrate that our model significantly surpasses existing top MDI prediction models. This indicates that our model can accurately predict unknown MDIs and is likely to aid in disease discovery and precision pharmaceutical research. Code and data are accessible at: https://github.com/shmildsj/MDI-IFDRL.

Combined interventions for the testing and treatment of HIV and schistosomiasis among fishermen in Malawi: a three-arm, cluster-randomised trial

Undiagnosed HIV and schistosomiasis are highly prevalent among fishermen in the African Great Lakes region. We aimed to evaluate the efficacy of lakeside interventions integrating services for HIV and male genital schistosomiasis on the prevalence of schistosomiasis, uptake of antiretroviral therapy (ART) for HIV, and voluntary male medical circumcision (VMMC) among fishermen in Malawi. We conducted a three-arm, cluster-randomised trial in 45 lakeshore fishing communities (clusters) in Mangochi, Malawi. Clusters were defined geographically by their home community as the place where fishermen leave their boats (ie, a landing site). Eligible participants were male fishermen (aged ≥18 years) who resided in a cluster. Clusters were randomly allocated (1:1:1) through computer-generated random numbers to either enhanced standard of care (SOC), which offered invitation with information leaflets to a beach clinic offering HIV testing and referral, and presumptive treatment for schistosomiasis with praziquantel; peer education (PE), in which a nominated fisherman was responsible for explaining the study leaflet to promote services to his boat crew; or peer distribution education (PDE), in which the peer educator explained the leaflet and distributed HIV self-test kits to his boat crew. The beach clinic team and fishermen were not masked to intervention allocation; however, investigators were masked until the final analysis. Coprimary composite outcomes were the proportion of participants who had at least one Schistosoma haematobium egg observed on light microscopy from 10 mL of urine filtrate and the proportion who had self-reported initiating ART or scheduling VMMC by day 28. Outcomes were analysed by intention to treat; multiple imputation for missing outcomes was done; random-effect binomial models adjusting for baseline imbalance and clustering were used to compute unadjusted and adjusted risk differences, risk ratios (RRs) and 95% CIs, and intracluster correlation coefficients for each outcome. This trial is registered with ISRCTN, ISRCTN14354324. Between March 1, 2022, and Jan 29, 2023, 45 (65·2%) of 69 clusters assessed for eligibility were enrolled in the trial, with 15 clusters per arm. Of the 6036 fishermen screened at baseline, 5207 (86·3%) were eligible for participation: 1745 (87·6%) of 1991 in the enhanced SOC group, 1687 (81·9%) of 2061 in the PE group, and 1775 (89·5%) of 1984 in the PDE group. Compared with the prevalence of active schistosomiasis in the enhanced SOC group (292 [16·7%] of 1745), 241 (13·6%) of 1775 fishermen in the PDE group (adjusted RR 0·80 [95% CI 0·69-0·94]; p=0·0054) and 263 (15·6%) of 1687 fishermen in the PE group (0·92 [0·79-1·07]; p=0·28) had schistosomiasis at day 28. 230 (13·2%) in the enhanced SOC group, 281 (16·7%) in the PE group, and 215 (12·1%) in the PDE group initiated ART or were scheduled for VMMC. ART initiation or VMMC scheduling was not significantly increased with the PDE intervention (0·88 [0·74-1·05); p=0·15) and was marginally increased with the PE intervention (1·16 [0·99-1·37]; p=0·069) when compared with the enhanced SOC group. No serious adverse events were reported in this trial. We found weak evidence for the use of peer education to increase uptake of ART and VMMC, but strong evidence for the added distribution of HIV self-test kits to promote high engagement with services and reduce the prevalence of active schistosomiasis, suggesting a high potential for scale-up in hard-to-reach communities across Malawi. Wellcome Trust and the UK National Institute for Health Research.

Influence of an AYA cancer program on cancer care delivery.

4 Background: Adolescent and young adults (AYAs, aged 13-39) with cancer face barriers to care and stagnant survival outcomes. The University of North Carolina (UNC) at Chapel Hill's AYA Cancer Program, established in 2015, aims to address these challenges. The program operates through both consultations and targeted outreach based on patient risk-stratification, offering services such as fertility counseling, enhanced access to clinical trial enrollment, a dedicated sarcoma palliative care collaborative, survivorship clinic, and psychosocial support. AYA program providers work with patients to create tailored care plans that meet AYAs' psychosocial and medical needs. To better understand the reach and impact of this novel care delivery approach, we performed a retrospective cohort study over the 8-year period of program development. Methods: Using linked electronic health record (EHR) and State Cancer Registry data, we performed a retrospective cohort study of AYA patients at UNC from 2014-2022, comparing sociodemographic and clinical criteria between those with and without AYA Cancer Program contact. Our analysis included outcomes of care utilization, complications, and supportive care measures. Using SMR propensity weighting with multivariable log binomial modeling, we evaluated associations between outcomes and AYA program contact. Factors such as age at diagnosis, race, sex, insurance status, cancer site, metastatic disease, and receipt of systemic therapy were considered in the weighting scheme. Results: Of 4,016 AYAs receiving cancer care at UNC, 670 had contact with our program. Program-engaged patients were younger at diagnosis, more likely to be Black, and had higher rates of metastatic disease or hematologic malignancies. In weighted model analyses, program patients were more likely to receive guideline recommended care, including enrollment in a clinical trial, receipt of fertility counseling and palliative care, and documented advanced care planning. Over time, our program's reach expanded from 6% to more than 25% of the total AYA population. Conclusions: Our findings indicate that AYAs contacted by our program through a consult-based, targeted outreach model represent a distinct population with higher clinical needs. Despite this complexity, they were more likely to receive guideline-recommended care, including clinical trial enrollment, fertility counseling, and palliative care. Care delivery outcomes by program contact. No Program Contact (n= 3346) Program Contact (n=670) Clinical Trial Enrollment 882 (26.4%) 301 (44.9%) 1.31 (1.14, 1.49) Fertility Counseling 77 (2.3%) 119 (17.8%) 2.09 (1.56, 2.80) Palliative Care 102 (3.0%) 125 (18.7%) 3.46 (2.44, 4.91) Advanced Care Planning 176 (5.3%) 91 (13.6%) 1.55 (1.14, 2.11)

Association between postoperative complications and hospital length of stay: a large-scale observational study of 4,495,582 patients in the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) registry

BackgroundPrecise estimates of risk-adjusted increases in postoperative length of stay (LOS) associated with postoperative complications across a range of complications and operations are not available in the existing literature.MethodsAssociations between preoperative characteristics, postoperative complications and postoperative LOS were tested using medians, interquartile ranges, and nonparametric rank sum tests in a retrospective cohort study using the 2005–2018 American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) dataset. A negative binomial model was used with postoperative LOS as the dependent variable and preoperative characteristics and postoperative complications as independent variables. The model was applied to estimate each patient’s postoperative LOS with and without each postoperative complication to measure the association between each complication and risk-adjusted change in postoperative LOS.ResultsA total of 4,495,582 patients were included. After risk-adjustment, occurrence of each postoperative complication was associated with significantly increased postoperative LOS (between + 3.9 and + 20.1 days, p < 0.0001). The longest risk-adjusted postoperative LOS increases were associated with prolonged ventilator use (+ 20.1 days), wound disruption (+ 19.4 days), and acute renal failure (+ 17.1 days).ConclusionOccurrence of any postoperative complication was associated with increased risk-adjusted postoperative LOS. Degree of increase varied by complication. These data could be useful for patient counseling, allocation of resources, discharge planning, and quality improvement efforts.

How Many Lymph Nodes are Enough in Paratesticular Rhabdomyosarcoma?

BackgroundTreatment strategies for paratesticular rhabdomyosarcoma (PT RMS) are based on stage, which requires accurate lymph node (LN) evaluation. Previous methodology for determining quantity of LN for negative nodal status is based on LN positivity rates, without accounting for the relationship between LNs or amongst patients. This study aims to quantify the chance of missing involved LNs based on LN yield (LNY) using a previously established methodology in comparison to current recommendations. MethodsUsing the National Cancer Database, patients with a diagnosis of PT RMS were queried from 2004-2018. Patients >10 years and those ≤10 years with cN1 disease were included, based on COG guidelines for who should undergo retroperitoneal LN sampling (RPLNS). The beta-binomial model was used to calculate the rate of false negative RPLNS and identified the LNY threshold to reduce the risk of a missing an involved LN node to <10%. ResultsSixty-two patients were included for analysis over the study period. Median LNY was 17 (IQR 9-28.75), and the median number of involved LNs was 2.5 (IQR 2-5). The median LN density was 0.27 (IQR 0.10-0.34). Application of the beta-binomial model identified that a LNY of 26 LNs corresponds to a <10% chance of missing occult disease (Figure 3). ConclusionPrevious models estimate that sampling of 7-12 LN is adequate for accurate staging. However, the beta binomial model quantifies sampling at least 26 LNs to reduce the chance of missing occult metastatic disease to <10% in the majority of patients. Surgeons should consider this false negative rate during RPLNS for patients with PT RMS. Level of EvidenceIII

Disease Burden and Outcome of Neonatal Admissions at the Tamale Teaching Hospital, Ghana: A Prospective Study

Objective: To determine the pattern of diseases and factors affecting the outcome of neonates admitted at the Tamale Teaching Hospital Neonatal Intensive Care Unit (TTH NICU) over three months. Methodology: A hospital-based prospective cohort design was used to collect data from participants. A sample size of 399 neonates (participants) admitted into the NICU from 1st March 2021 to 10th June 2021. Data was obtained using KoboCollect, exported into Excel for cleaning, coding and analysed using SPSS version 20. Results: This study screened a total of 450 neonates under 28 days admitted in the NICU of Tamale Teaching Hospital, Ghana, over three months. Fifty-one of them were rejected, and 399 were included in the final analysis. The mean birth weight was 2600 g (±810g), with 33.1% of the neonates having low birth weight. Three hundred and forty-one (341) (85.5%) neonates survived, while 58 (14.5%) died during hospitalisation. The pattern of diseases showed that neonatal sepsis (37.3%, n=149/399), small for gestational age or low birth weight (SGA/LBW) (33.1%, n=132/399), neonatal jaundice (28.1%, n=112/399), prematurity (23.6%, n=94/399), birth asphyxia (13.5%, n=54/399) and congenital anomalies (7.8%, n=31/399) were the most common causes of admissions. All variables which had an association with neonatal mortality (p &lt;0.05) were entered into a binomial logistic model, prematurity (AOR=6.974, 95% CI: 1.766-27.537; p=0.006) was the main predictor of mortality. Conclusion: The common causes of admission and deaths in the TTH NICU during the study were neonatal sepsis, prematurity, birth asphyxia, LBW/SGA and neonatal jaundice. This highlights the need for interventions to address these conditions as we strive to reduce institutional neonatal mortality.

Infection epidemiological effects of school closures during the second COVID-19 pandemic wave-an exemplary analysis within alower Bavarian region

The rapid global spread of the SARS-CoV‑2 virus during the COVID-19 pandemic led to widespread non-pharmaceutical interventions, such as school closures, to curb infections. This study investigates the influence of school closures on the number of new infections to reduce the existing knowledge gap in this area. The effect of school closures starting on 16December 2020, was quantified using COVID-19 infection data from the district and city of Landshut in Bavaria between November 2020 and January 2021. An interrupted time series (ITS) analysis was performed to analyze daily new infections among 6-18 year olds and the entire population in the region before and after the school closures using anegative binomial regression model. The analysis showed that the trend of daily new COVID-19 infections among 6-18 year olds significantly decreased after the school closures (incidence rate ratio (IRR) 0.93; 95% confidence interval (CI): 0.89-0.96; p < 0.001). This was also true for the entire study population (IRR 0.95; 95% CI: 0.93-0.97; p < 0.001). In the context of various concurrent measures to contain the COVID-19 pandemic, the study provides evidence for asignificant association between school closures and reduced COVID-19 infections. By optimizing the existing incomplete evidence base on the role of school closures in pandemic control, this finding can support involved stakeholders and contribute to strengthening future approaches to pandemic prevention.

Predicting Factors of Length of Stay at a Neonatal Intensive Care Unit in a Tertiary Hospital in Ghana

Objective: The aim of this research was to determine the factors that influence the length of stay in the NICU of the Korle Bu Teaching Hospital (KBTH), Accra. Methodology: This was a retrospective study involving 249 preterm infants who were admitted and discharged from the NICU, KBTH from November 2021 to October 2022. The multivariable negative binomial regression model was used to assess the factors associated with the number of hospital days among the newborns. Results: The median number of days stayed in the NICU was 12 days (IQR: 8-21). Predictor of shorter length of stay in the NICU was preterm infants with birthweight between 1500-2499g (aβ: -0.39, 95% CI: [-0.54, -0.24], p&lt;0.001). Predictors of prolonged length of stay in the NICU were late initiation of breastmilk feeding (aβ: 0.31, 95% CI: [0.01, 0.60], p=0.040), preterm infants with neonatal jaundice (aβ: 0.15, 95% CI: [0.02, 0.28], p=0.023), neonatal sepsis (aβ: 0.44, 95% CI: [0.30, 0.57], p&lt;0.001), and necrotising enterocolitis (aβ: 0.37, 95% CI: [0.16, 0.58], p&lt;0.001). Conclusion: Preterm infants who initiated breastmilk feeding late, developed neonatal sepsis, necrotising enterocolitis and neonatal jaundice were more likely to stay longer at the NICU. While those with birth weight between 1500-2499grams