Nevin Manimala

Sci Rep. 2021 Oct 28;11(1):21288. doi: 10.1038/s41598-021-00017-y.

ABSTRACT

Diffusion on networks is an important concept in network science observed in many situations such as information spreading and rumor controlling in social networks, disease contagion between individuals, and cascading failures in power grids. The critical interactions in networks play critical roles in diffusion and primarily affect network structure and functions. While interactions can occur between two nodes as pairwise interactions, i.e., edges, they can also occur between three or more nodes, which are described as higher-order interactions. This report presents a novel method to identify critical higher-order interactions in complex networks. We propose two new Laplacians to generalize standard graph centrality measures for higher-order interactions. We then compare the performances of the generalized centrality measures using the size of giant component and the Susceptible-Infected-Recovered (SIR) simulation model to show the effectiveness of using higher-order interactions. We further compare them with the first-order interactions (i.e., edges). Experimental results suggest that higher-order interactions play more critical roles than edges based on both the size of giant component and SIR, and the proposed methods are promising in identifying critical higher-order interactions.

PMID:34711855 | DOI:10.1038/s41598-021-00017-y

Appl Immunohistochem Mol Morphol. 2021 Oct 27. doi: 10.1097/PAI.0000000000000982. Online ahead of print.

ABSTRACT

Dysregulation of epigenetic mechanisms, reflected by loss of expression of 5-hydroxymethylcytosine (5-hmC) is being increasingly recognized as a marker of aggressive behavior in several neoplasms; however, the role of such epigenetic modifiers in pancreatic neuroendocrine tumors (PanNETs) has not been studied. Annotated cohort of 60 PanNETs was evaluated for 5-hmC expression using immunohistochemistry. Univariable and multivariable analyses were performed. To determine intratumor heterogeneity of 5-hmC expression, 26 additional synchronous metastatic deposits of PanNETs from 8 patients were evaluated for 5-hmC expression. 5-hmC level showed significant association with the presence of distant metastases (P=0.02), female sex (P=0.04), and Ki-67 proliferation index (P=0.002). A multivariate model created using the stepwise logistic regression analysis showed the presence of nodal metastases (odds ratio=6.15), lymphovascular invasion (odds ratio=4.07) and lack of 5-hmC expression (odds ratio=5.34) were predictive of the risk of distant metastasis in PanNETs with a c-statistic of 0.845. Epigenetic intratumoral heterogeneity of 5-hmC expression was seen in 37.5% cases (3/8). Our work provides evidence that epigenetic regulators are involved in the pathobiology of PanNETs and immunohistochemical analysis of 5-hmC may be able to refine prognostic evaluation of these tumors.

PMID:34711739 | DOI:10.1097/PAI.0000000000000982

Epidemiology. 2021 Oct 4. doi: 10.1097/EDE.0000000000001432. Online ahead of print.

ABSTRACT

Electronic health records (EHRs) offer unprecedented opportunities to answer epidemiologic questions. However, unlike in ordinary cohort studies or randomized trials, EHR data are collected somewhat idiosyncratically. In particular, patients who have more contact with the medical system have more opportunities to receive diagnoses, which are then recorded in their EHRs. The goal of this paper is to shed light on the nature and scope of this phenomenon, known as informative presence, which can bias estimates of associations. We show how this can be characterized as an instance of misclassification bias. As a consequence, we show that informative presence bias can occur in a broader range of settings than previously thought, and that simple adjustment for the number of visits as a confounder may not fully correct for bias. Additionally, where previous work has considered only under-diagnosis, investigators are often concerned about over-diagnosis; we show how this changes the settings in which bias manifests. We report on a comprehensive series of simulations to shed light on when to expect informative presence bias, how it can be mitigated in some cases, and cases in which new methods need to be developed.

PMID:34711733 | DOI:10.1097/EDE.0000000000001432

Ann Plast Surg. 2021 Oct 26. doi: 10.1097/SAP.0000000000003041. Online ahead of print.

ABSTRACT

BACKGROUND: The purposes of this study were to compare applicant statistics to resident physician demographics among several surgical subspecialties (SSSs), to identify trends of gender and underrepresented minorities in medicine (UIM), and to evaluate current diversity among these specialties.

METHODS: Graduate medical education reports from 2009 to 2019 were queried to determine trends among programs. Further identification of gender and UIM statistics was obtained in 4 several SSSs: integrated plastic surgery, orthopedic surgery (OS), otolaryngology surgery (ENT), and neurosurgery (NS). These were compared with Association of American Medical Colleges data of residency applicants for the respective years.

RESULTS: Significant differences were seen among gender and UIM(s) of the applicant pool when compared with resident data. All specialties had significantly fewer American Indian and African American residents compared with applicants. Significant differences between applicants and residents were also found among Hispanic, Native Hawaiian, and female demographics. All SSSs had a significant positive trend for the percentage of female residents. Significant differences between specialties were identified among African American, Hispanic, and female residents. Orthopedic surgery and NS had significantly higher percentage of African American residents compared with ENT and integrated plastic surgery. Neurosurgery had significantly higher percentage of Hispanic residents compared with OS and ENT. Integrated plastic surgery and ENT had significantly higher percentage of female residents compared with OS and NS.

CONCLUSIONS: There has been significant increase in number of residency programs and resident positions since 2009. However, increase in female residents and UIM(s) among SSSs has not matched the pace of growth.

PMID:34711732 | DOI:10.1097/SAP.0000000000003041

Chin Med J (Engl). 2021 Oct 26. doi: 10.1097/CM9.0000000000001798. Online ahead of print.

ABSTRACT

BACKGROUND: In-hospital mortality in patients with coronavirus disease 2019 (COVID-19) is high. Simple prognostic indices are needed to identify patients at high-risk of COVID-19 health outcomes. We aimed to determine the usefulness of the CONtrolling NUTritional status (CONUT) index as a potential prognostic indicator of mortality in COVID-19 patients upon hospital admission.

METHODS: Our study design is of a retrospective observational study in a large cohort of COVID-19 patients. In addition to descriptive statistics, a Kaplan-Meier mortality analysis and a Cox regression were performed, as well as receiver operating curve (ROC).

RESULTS: From February 5, 2020 to January 21, 2021, there was a total of 2968 admissions for COVID-19 at our hospital, corresponding to 2844 patients. Overall, baseline (within 4 days of admission) CONUT index could be scored for 1627 (57.2%) patients. Patients’ age was 67.3 ± 16.5 years and 44.9% were women. The CONUT severity distribution was: 194 (11.9%) normal (0-1); 769 (47.2%) light (2-4); 585 (35.9%) moderate (5-8); and 79 (4.9%) severe (9-12). Mortality of 30 days after admission was 3.1% in patients with normal risk CONUT, 9.0% light, 22.7% moderate, and 40.5% in those with severe CONUT (P < 0.05). An increased risk of death associated with a greater baseline CONUT stage was sustained in a multivariable Cox regression model (P < 0.05). An increasing baseline CONUT stage was associated with a longer duration of admission, a greater requirement for the use of non-invasive and invasive mechanical ventilation, and other clinical outcomes (all P < 0.05). The ROC of CONUT for mortality had an area under the curve (AUC) and 95% confidence interval of 0.711 (0.676-0746).

CONCLUSION: The CONUT index upon admission is potentially a reliable and independent prognostic indicator of mortality and length of hospitalization in COVID-19 patients.

PMID:34711718 | DOI:10.1097/CM9.0000000000001798

Heart. 2021 Oct 28:heartjnl-2021-319750. doi: 10.1136/heartjnl-2021-319750. Online ahead of print.

ABSTRACT

OBJECTIVE: The initial data of the International Study on Acute Coronary Syndromes – ST Elevation Myocardial Infarction COVID-19 showed in Europe a remarkable reduction in primary percutaneous coronary intervention procedures and higher in-hospital mortality during the initial phase of the pandemic as compared with the prepandemic period. The aim of the current study was to provide the final results of the registry, subsequently extended outside Europe with a larger inclusion period (up to June 2020) and longer follow-up (up to 30 days).

METHODS: This is a retrospective multicentre registry in 109 high-volume primary percutaneous coronary intervention (PPCI) centres from Europe, Latin America, South-East Asia and North Africa, enrolling 16 674 patients with ST segment elevation myocardial infarction (STEMI) undergoing PPPCI in March/June 2019 and 2020. The main study outcomes were the incidence of PPCI, delayed treatment (ischaemia time >12 hours and door-to-balloon >30 min), in-hospital and 30-day mortality.

RESULTS: In 2020, during the pandemic, there was a significant reduction in PPCI as compared with 2019 (incidence rate ratio 0.843, 95% CI 0.825 to 0.861, p<0.0001). This reduction was significantly associated with age, being higher in older adults (>75 years) (p=0.015), and was not related to the peak of cases or deaths due to COVID-19. The heterogeneity among centres was high (p<0.001). Furthermore, the pandemic was associated with a significant increase in door-to-balloon time (40 (25-70) min vs 40 (25-64) min, p=0.01) and total ischaemia time (225 (135-410) min vs 196 (120-355) min, p<0.001), which may have contributed to the higher in-hospital (6.5% vs 5.3%, p<0.001) and 30-day (8% vs 6.5%, p=0.001) mortality observed during the pandemic.

CONCLUSION: Percutaneous revascularisation for STEMI was significantly affected by the COVID-19 pandemic, with a 16% reduction in PPCI procedures, especially among older patients (about 20%), and longer delays to treatment, which may have contributed to the increased in-hospital and 30-day mortality during the pandemic.

TRIAL REGISTRATION NUMBER: NCT04412655.

PMID:34711661 | DOI:10.1136/heartjnl-2021-319750

Diabetes Care. 2021 Oct 28:dc210957. doi: 10.2337/dc21-0957. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate the risk of incident dementia according to fasting glucose levels and presence of comorbidities.

RESEARCH DESIGN AND METHODS: Using a health insurance claims database and the results of biennial health examinations in South Korea, we selected 8,400,950 subjects aged ≥40 years who underwent health examinations in 2009-2010. We followed them until 2016. Subjects’ baseline characteristics were categorized by presence of diabetes (yes/no) and glycemic status as normoglycemia, impaired fasting glucose (IFG), new-onset diabetes, or known diabetes (duration <5 years or ≥5 years). We estimated adjusted hazard ratios (aHRs) for dementia occurrence in each category.

RESULTS: During the observation period of 48,323,729 person-years, all-cause dementia developed in 353,392 subjects (4.2%). Compared with normoglycemia, aHRs (95% CI) were 1.01 (1.01-1.02) in IFG, 1.45 (1.44-1.47) in new-onset diabetes, 1.32 (1.30-1.33) in known diabetes <5 years, and 1.62 (1.60-1.64) in known diabetes ≥5 years. We found that associations between ischemic heart disease and chronic kidney disease with incident dementia were affected by the presence of diabetes. Ischemic stroke showed a greater association with incident dementia than diabetes.

CONCLUSIONS: Mild degrees of hyperglycemia and presence of comorbidities were associated with incident dementia. Intervention during the prodromal stage of a chronic disease (e.g., prediabetes) could be considered for dementia prevention.

PMID:34711638 | DOI:10.2337/dc21-0957

Emerg Med J. 2021 Oct 28:emermed-2021-211431. doi: 10.1136/emermed-2021-211431. Online ahead of print.

ABSTRACT

INTRODUCTION: A significant proportion of ED attendances in children may be non-urgent attendances (NUAs), which could be better managed elsewhere. This study aimed to quantify NUAs and urgent attendances (UAs) in children to ED and determine which children present in this way and when.

METHODS: Dataset extracted from the CUREd research database containing linked data on the provision of care in Yorkshire and Humber. Analysis focused on children’s ED attendances (April 2014-March 2017). Summary statistics and odds ratios (OR) comparing NUAs and UAs were examined by: age, mode and time of arrival and deprivation alongside comparing summary statistics for waiting, treatment and total department times.

RESULTS: NUAs were more likely in younger children: OR for NUA in children aged 1-4 years, 0.82 (95% CI: 0.80 to 0.83), age 15 years, 0.39 (95% CI: 0.38 to 0.40), when compared with those under 1 year. NUAs were more likely to arrive out of hours (OOHs) compared with in hours: OR 1.19 (95% CI 1.18 to 1.20), and OOHs arrivals were less common in older children compared with those under 1 year: age 1-4 years, 0.87 (95% CI: 0.84 to 0.89) age 15 years, 0.66 (95% CI: 0.63 to 0.69). NUAs also spent less total time in the ED, with a median (IQR) of 98 min (60-147) compared with 127 min (80-185) for UAs.

CONCLUSION: A substantial proportion of ED attendances in children are NUAs. Our data suggest there are particular groups of children for whom targeted interventions would be most beneficial. Children under 5 years would be such a group, particularly in providing accessible, timely care outside of usual community care opening hours.

PMID:34711634 | DOI:10.1136/emermed-2021-211431

J Nucl Med. 2021 Oct 28:jnumed.121.262618. doi: 10.2967/jnumed.121.262618. Online ahead of print.

ABSTRACT

Background: Radiomics has been applied to predict recurrence in several disease sites, but current approaches are typically restricted to analyzing tumor features, neglecting non-tumor information in the rest of the body. The purpose of this work was to develop and validate a model incorporating non-tumor radiomics, including whole body features, to predict treatment outcomes in patients with previously untreated locoregionally advanced cervical cancer. Methods: We analyzed 127 cervical cancer patients treated definitively with chemoradiotherapy and intracavitary brachytherapy. All patients underwent pretreatment whole body ¹⁸F-FDG PET/CT. To quantify effects due to the tumor itself, the gross tumor volume (GTV) was directly contoured on the PET/CT. Meanwhile, to quantify effects arising from the rest of the body, the planning target volume (PTV) was deformably registered from each planning CT to the PET/CT, and a semi-automated approach combining seed-growing and manual contour review generated whole body muscle, bone, and fat segmentations on each PET/CT. A total of 965 radiomic features were extracted for GTV, PTV, muscle, bone, and fat. 95 patients were used to train a Cox model of disease recurrence including both radiomic and clinical features (age, stage, tumor grade, histology, and baseline complete blood cell counts), using bagging and split-sample-validation for feature reduction and model selection. To further avoid overfitting, the resulting models were tested for generalization on the remaining 32 patients, by calculating a risk score based on Cox regression and evaluating the c-index (c-index > 0.5 indicates predictive power). Results: Optimal performance was seen in a Cox model including one clinical biomarker (whether or not a tumor was stage III-IVA), two GTV radiomic biomarkers (PET gray-level size-zone matrix small area low gray level emphasis and zone entropy), one PTV radiomic biomarker (major axis length) and one whole body radiomic biomarker (CT Bone root mean square). In particular, stratification into high- and low-risk groups, based on the linear risk score from this Cox model, resulted in a hazard ratio [95% CI] of 0.019 [0.004, 0.082], an improvement over stratification based on clinical stage alone, which had a hazard ratio of 0.36 [0.16, 0.83]. Conclusion: Incorporating non-tumor radiomic biomarkers can improve the performance of prognostic models compared to using only clinical and tumor radiomic biomarkers. Future work should look to further test these models in larger, multi-institutional cohorts.

PMID:34711618 | DOI:10.2967/jnumed.121.262618

J Nucl Med. 2021 Oct 28:jnumed.121.263158. doi: 10.2967/jnumed.121.263158. Online ahead of print.

NO ABSTRACT

PMID:34711615 | DOI:10.2967/jnumed.121.263158