Nevin Manimala

Int J Health Geogr. 2021 Mar 18;20(1):13. doi: 10.1186/s12942-021-00267-z.

ABSTRACT

BACKGROUND: Cancer epidemiology studies require sufficient power to assess spatial relationships between exposures and cancer incidence accurately. However, methods for power calculations of spatial statistics are complicated and underdeveloped, and therefore underutilized by investigators. The spatial relative risk function, a cluster detection technique that detects spatial clusters of point-level data for two groups (e.g., cancer cases and controls, two exposure groups), is a commonly used spatial statistic but does not have a readily available power calculation for study design.

RESULTS: We developed sparrpowR as an open-source R package to estimate the statistical power of the spatial relative risk function. sparrpowR generates simulated data applying user-defined parameters (e.g., sample size, locations) to detect spatial clusters with high statistical power. We present applications of sparrpowR that perform a power calculation for a study designed to detect a spatial cluster of incident cancer in relation to a point source of numerous environmental emissions. The conducted power calculations demonstrate the functionality and utility of sparrpowR to calculate the local power for spatial cluster detection.

CONCLUSIONS: sparrpowR improves the current capacity of investigators to calculate the statistical power of spatial clusters, which assists in designing more efficient studies. This newly developed R package addresses a critically underdeveloped gap in cancer epidemiology by estimating statistical power for a common spatial cluster detection technique.

PMID:33736677 | DOI:10.1186/s12942-021-00267-z

World J Emerg Surg. 2021 Mar 18;16(1):12. doi: 10.1186/s13017-021-00356-1.

ABSTRACT

BACKGROUND: Senior adults fear postoperative loss of independence the most, and this might represent an additional burden for families and society. The number of geriatric patients admitted to the emergency room requiring an urgent surgical treatment is rising, and the presence of frailty is the main risk factor for postoperative morbidity and functional decline. Frailty assessment in the busy emergency setting is challenging. The aim of this study is to verify the effectiveness of a very simple five-item frailty screening tool, the Flemish version of the Triage Risk Screening Tool (fTRST), in predicting functional loss after emergency surgery among senior adults who were found to be independent before surgery.

METHODS: All consecutive individuals aged 70 years and older who were independent (activity of daily living (ADL) score ≥5) and were admitted to the emergency surgery unit with an urgent need for abdominal surgery between December 2015 and May 2016 were prospectively included in the study. On admission, individuals were screened using the fTRST and additional metrics such as the age-adjusted Charlson Comorbidity Index (CACI) and the ASA score. Thirty- and 90-day complications and postoperative decline in the ADL score where recorded. Regression analysis was performed to identify preoperative predictors of functional loss.

RESULTS: Seventy-eight patients entered the study. Thirty-day mortality rate was 12.8% (10/78), and the 90-day overall mortality was 15.4% (12/78). One in every four patients (17/68) experienced a significant functional loss at 30-day follow-up. At 90-day follow-up, only 3/17 patients recovered, 2 patients died, and 12 remained permanently dependent. On the regression analysis, a statistically significant correlation with functional loss was found for fTRST, CACI, and age≥85 years old both at 30 and 90 days after surgery. fTRST≥2 showed the highest effectiveness in predicting functional loss at 90 days with AUC 72 and OR 6.93 (95% CI 1.71-28.05). The institutionalization rate with the need to discharge patients to a healthcare facility was 7.6% (5/66); all of them had a fTRST≥2.

CONCLUSION: fTRST is an easy and effective tool to predict the risk of a postoperative functional decline and nursing home admission in the emergency setting.

PMID:33736667 | DOI:10.1186/s13017-021-00356-1

Fluids Barriers CNS. 2021 Mar 18;18(1):12. doi: 10.1186/s12987-021-00246-3.

ABSTRACT

BACKGROUND: Phase contrast magnetic resonance imaging, PC MRI, is a valuable tool allowing for non-invasive quantification of CSF dynamics, but has lacked adoption in clinical practice for Chiari malformation diagnostics. To improve these diagnostic practices, a better understanding of PC MRI based measurement agreement, repeatability, and reproducibility of CSF dynamics is needed.

METHODS: An anatomically realistic in vitro subject specific model of a Chiari malformation patient was scanned three times at five different scanning centers using 2D PC MRI and 4D Flow techniques to quantify intra-scanner repeatability, inter-scanner reproducibility, and agreement between imaging modalities. Peak systolic CSF velocities were measured at nine axial planes using 2D PC MRI, which were then compared to 4D Flow peak systolic velocity measurements extracted at those exact axial positions along the model.

RESULTS: Comparison of measurement results showed good overall agreement of CSF velocity detection between 2D PC MRI and 4D Flow (p = 0.86), fair intra-scanner repeatability (confidence intervals ± 1.5 cm/s), and poor inter-scanner reproducibility. On average, 4D Flow measurements had a larger variability than 2D PC MRI measurements (standard deviations 1.83 and 1.04 cm/s, respectively).

CONCLUSION: Agreement, repeatability, and reproducibility of 2D PC MRI and 4D Flow detection of peak CSF velocities was quantified using a patient-specific in vitro model of Chiari malformation. In combination, the greatest factor leading to measurement inconsistency was determined to be a lack of reproducibility between different MRI centers. Overall, these findings may help lead to better understanding for application of 2D PC MRI and 4D Flow techniques as diagnostic tools for CSF dynamics quantification in Chiari malformation and related diseases.

PMID:33736664 | DOI:10.1186/s12987-021-00246-3

BMC Med Inform Decis Mak. 2021 Mar 18;21(1):104. doi: 10.1186/s12911-021-01455-4.

ABSTRACT

BACKGROUND: Patients with complex health care needs may suffer adverse outcomes from fragmented and delayed care, reducing well-being and increasing health care costs. Health reform efforts, especially those in primary care, attempt to mitigate risk of adverse outcomes by better targeting resources to those most in need. However, predicting who is susceptible to adverse outcomes, such as unplanned hospitalizations, ED visits, or other potentially avoidable expenditures, can be difficult, and providing intensive levels of resources to all patients is neither wanted nor efficient. Our objective was to understand if primary care teams can predict patient risk better than standard risk scores.

METHODS: Six primary care practices risk stratified their entire patient population over a 2-year period, and worked to mitigate risk for those at high risk through care management and coordination. Individual patient risk scores created by the practices were collected and compared to a common risk score (Hierarchical Condition Categories) in their ability to predict future expenditures, ED visits, and hospitalizations. Accuracy of predictions, sensitivity, positive predictive values (PPV), and c-statistics were calculated for each risk scoring type. Analyses were stratified by whether the practice used intuition alone, an algorithm alone, or adjudicated an algorithmic risk score.

RESULTS: In all, 40,342 patients were risk stratified. Practice scores had 38.6% agreement with HCC scores on identification of high-risk patients. For the 3,381 patients with reliable outcomes data, accuracy was high (0.71-0.88) but sensitivity and PPV were low (0.16-0.40). Practice-created scores had 0.02-0.14 lower sensitivity, specificity and PPV compared to HCC in prediction of outcomes. Practices using adjudication had, on average, .16 higher sensitivity.

CONCLUSIONS: Practices using simple risk stratification techniques had slightly worse accuracy in predicting common outcomes than HCC, but adjudication improved prediction.

PMID:33736636 | DOI:10.1186/s12911-021-01455-4

BMC Med Genomics. 2021 Mar 18;14(1):84. doi: 10.1186/s12920-021-00907-0.

ABSTRACT

BACKGROUND: Recent studies have identified susceptibility genes of HBV clearance, chronic hepatitis B, liver cirrhosis, hepatocellular carcinoma, and showed the host genetic factors play an important role in these HBV-related outcomes.

METHODS: Collected samples from different outcomes of HBV infection and performed genotyping by Affymetrix 500 k SNP Array. GCTA tool, PLINK, and Bonferroni method were applied for analysis of genotyping and disease progression. ANOVA was used to evaluate the significance of the association between biomarkers and genotypes in healthy controls. PoMo, F_ST, Vcftools and Rehh package were used for building the racial tree and population analysis. F_ST statistics accesses 0.15 was used as a threshold to detect the signature of selection.

RESULTS: There are 1031 participants passed quality control from 1104 participants, including 275 HBV clearance, 92 asymptomatic persistence infection (ASPI), 93 chronic hepatitis B (CHB), 188 HBV-related decompensated cirrhosis (DC), 214 HBV-related hepatocellular carcinoma (HCC) and 169 healthy controls (HC). In the case-control study, one novel locus significantly associated with CHB (SNP: rs1264473, Gene: GRHL2, P = 1.57 × 10^-6) and HCC (SNP: rs2833856, Gene: EVA1C, P = 1.62 × 10^-6; SNP: rs4661093, Gene: ETV3, P = 2.26 × 10^-6). In the trend study across progressive stages post HBV infection, one novel locus (SNP: rs1537862, Gene: LACE1, P = 1.85 × 10^-6), and three MHC loci (HLA-DRB1, HLA-DPB1, HLA-DPA2) showed significant increased progressive risk from ASPI to CHB. Underlying the evolutionary study of HBV-related genes in public database, the derived allele of two HBV clearance related loci, rs3077 and rs9277542, are under strong selection in European population.

CONCLUSIONS: In this study, we identified several novel candidate genes associated with individual HBV infectious outcomes, progressive stages, and liver enzymes. Two SNPs that show selective significance (HLA-DPA1, HLA-DPB1) in non-East Asian (European, American, South Asian) versus East Asian, indicating that host genetic factors contribute to the ethnic disparities of susceptibility of HBV infection. Taken together, these findings provided a new insight into the role of host genetic factors in HBV related outcomes and progression.

PMID:33736632 | DOI:10.1186/s12920-021-00907-0

BMC Endocr Disord. 2021 Mar 19;21(1):52. doi: 10.1186/s12902-021-00691-z.

ABSTRACT

BACKGROUND: There are many continuous blood glucose monitoring (CGM) data-based indicators, and most of these focus on a single characteristic of abnormal blood glucose. An ideal index that integrates and evaluates multiple characteristics of blood glucose has not yet been established.

METHODS: In this study, we proposed the glycemic deviation index (GDI) as a novel integrating characteristic, which mainly incorporates the assessment of the glycemic numerical value and variability. To verify its effectiveness, GDI was applied to the simulated 24 h glycemic profiles and the CGM data of type 2 diabetes (T2D) patients (n = 30).

RESULTS: Evaluation of the GDI of the 24 h simulated glycemic profiles showed that the occurrence of hypoglycemia was numerically the same as hyperglycemia in increasing GDI. Meanwhile, glycemic variability was added as an independent factor. One-way ANOVA results showed that the application of GDI showed statistically significant differences in clinical glycemic parameters, average glycemic parameters, and glycemic variability parameters among the T2D groups with different glycemic levels.

CONCLUSIONS: In conclusion, GDI integrates the characteristics of the numerical value and the variability in blood glucose levels and may be beneficial for the glycemic management of diabetic patients undergoing CGM treatment.

PMID:33736619 | DOI:10.1186/s12902-021-00691-z

BMC Public Health. 2021 Mar 18;21(1):531. doi: 10.1186/s12889-021-10456-x.

ABSTRACT

BACKGROUND: Stroke is a devastating disease and a major cause of death and disability in China. While existing studies focused mainly on differences in stroke patients’ health care utilization by insurance type, this study assesses whether health utilization and medical costs differed by insurance type across four cities in China.

METHODS: A 5% random sample from the 2014-2016 China Urban Employees’ Basic Medical Insurance (UEBMI) and Urban Residents’ Basic Medical Insurance (URBMI) claims data were collected across four cities, Beijing, Shanghai, Tianjin, and Chongqing. Descriptive statistics and ordinary least squares regression were employed to analyze the data.

RESULTS: We found that differences in healthcare utilization and inpatient and outpatient medical expenses varied more by city-specific insurance type than they did between the UEBMI and URBMI schemes. For example, the median UEBMI medical outpatient costs in Beijing (RMB500.2) were significantly higher than UEBMI patients in Shanghai (RMB260.8), Tianjin (RMB240.8), and Chongqing (RMB293.0), and Beijing URBMI patients had significantly higher outpatient medical costs (RMB356.9) than URBMI patients in Shanghai (RMB233.4) and Chongqing (RMB211.0), which were significantly higher than Tianjin (RMB156.2). Patients in Chongqing had 66.4% (95% CI: – 0.672, – 0.649) fewer outpatient visits, 13.0% (95% CI: – 0.144, – 0.115) fewer inpatient visits, and 34.2% (95% CI: – 0.366, – 0.318) shorter length of stay than patients in Beijing. The divergence of average length of stay and out-of-pocket (OOP) expenses by insurance type was also greater between cities than the UEMBI-URBMI mean difference.

CONCLUSIONS: Significant city-specific differences in stroke patients’ healthcare utilization and medical costs reflected inequalities in health care access. The fragmented social health insurance schemes in China should be consolidated to provide patients in different cities equal financial protection and benefit packages and to improve the equity of stroke patient access to health care.

PMID:33736618 | DOI:10.1186/s12889-021-10456-x

J Perinat Med. 2021 Mar 18. doi: 10.1515/jpm-2020-0352. Online ahead of print.

ABSTRACT

OBJECTIVES: To determine the causes of fetal death among the stillbirths using two classification systems from 22 weeks of gestation in a period of three years in high-risk pregnancies. This is a retrospective observational study.

METHODS: The National Institute of Perinatal Health in Mexico City is a Level 3 care referral center attending high-risk pregnancies from throughout the country. The population consisted of patients with fetal death during a three-year period. Between January 2016 and December 2018, all stillbirths were examined in the Pathology Department by a pathologist and a medical geneticist. Stillbirth was defined as a fetal death occurring after 22 weeks of gestation.

RESULTS: Main outcome measures: Causal analysis of fetal death using the International Statistical Classification of Disease and Related Health Problems-Perinatal Mortality (ICD-PM) and initial causes of fetal death (INCODE) classification systems. A total of 297 stillborn neonates were studied. The distribution of gestational age in antepartum stillbirths (55.2%) showed a bimodal curve, 36% occurred between 24 and 27 weeks and 32% between 32 and 36 weeks. In comparison, the majority (86%) of intrapartum deaths (44.8%) were less than 28 weeks of gestation. Of the 273 women enrolled, 93 (34%) consented to a complete fetal autopsy. The INCODE system showed a present cause in 42%, a possible cause in 54% and a probable cause in 93% of patients.

CONCLUSIONS: The principal causes of antepartum death were fetal abnormalities and pathologic placental conditions and the principal causes of intrapartum death were complications of pregnancy which caused a premature labor and infections.

PMID:33735952 | DOI:10.1515/jpm-2020-0352

Blood. 2021 Mar 18:blood.2020006005. doi: 10.1182/blood.2020006005. Online ahead of print.

ABSTRACT

Sustained expression of therapeutic factor IX (FIX) levels has been achieved after adeno-associated viral (AAV) vector-based gene therapy in patients with hemophilia B. Nevertheless, patients are still at risk of vector dose-limiting toxicity, particularly liver inflammation justifying the need for more efficient vectors and a lower dosing regimen. A novel increased potency FIX (designated as CB 2679d-GT), containing three amino acid substitutions (R318Y, R338E, T343R), significantly outperformed the R338L-Padua variant after gene therapy. CB 2679d-GT demonstrated a statistically significant ~3-fold improvement in clotting activity when compared to R338L-Padua after AAV-based gene therapy in hemophilic mice. Moreover, CB 2679d-GT gene therapy showed a significantly reduced bleeding time (~5 to 8-fold) and total blood loss volume (~4-fold) compared with mice treated with the R338L-Padua, thus achieving a more rapid and robust hemostatic correction. FIX expression was sustained for at least 20 weeks with both CB 2679d-GT and R338L-Padua while immunogenicity was not significantly increased. This is a novel gene therapy study demonstrating the superiority of CB 2679d-GT highlighting its potential to obtain higher FIX activity levels and superior hemostatic efficacy following AAV directed gene therapy in hemophilia B patients than what is currently achievable with the R338L-Padua variant.

PMID:33735915 | DOI:10.1182/blood.2020006005

Hum Hered. 2021 Mar 18:1-10. doi: 10.1159/000514398. Online ahead of print.

ABSTRACT

INTRODUCTION: Breast cancer is a heterogeneous and multifactorial disease. TP53 and PAI-1 as important tumor suppressor genes are involved in the development, invasion, and metastasis of many cancers. This study’s objective was to demonstrate the combined genotype effects of these 2 genes by investigating their single nucleotide polymorphisms.

METHODS: In this case-control study, 200 individuals with breast cancer and 179 healthy individuals were studied. The genotypes were determined using the tetra-ARMS method. For data analysis, MDR, online javstat statistics package, and SPSS v.24 software were used. Also, in silico studies on the estimated effects of each of these polymorphisms were performed.

RESULTS: We showed a novel gene-gene interaction of these 2 genes and demonstrated a strong synergistic interaction for TP53/PAI-1, moderate synergistic interaction for PAI-1/age, and correlation for TP53/age. On the other hand, there was no association between the allelic and genotype frequency alone and in combination, with case-control status, using the parametric method, between TP53 and PAI-1.

DISCUSSION/CONCLUSION: Our findings suggest that the polymorphism of codon 72 of the TP53 gene was significantly associated with tumor stage (p < 0.023). In conclusion, we showed a gene-gene interaction between TP53 and PAI-1, in combination, using the MDR method.

PMID:33735891 | DOI:10.1159/000514398