Nevin Manimala

PLoS Genet. 2023 Oct 16;19(10):e1010977. doi: 10.1371/journal.pgen.1010977. Online ahead of print.

ABSTRACT

Chronic pain is at epidemic proportions in the United States, represents a significant burden on our public health system, and is coincident with a growing opioid crisis. While numerous genome-wide association studies have been reported for specific pain-related traits, many of these studies were underpowered, and the genetic relationship among these traits remains poorly understood. Here, we conducted a joint analysis of genome-wide association study summary statistics from seventeen pain susceptibility traits in the UK Biobank. This analysis revealed 99 genome-wide significant risk loci, 65 of which overlap loci identified in earlier studies. The remaining 34 loci are novel. We applied leave-one-trait-out meta-analyses to evaluate the influence of each trait on the joint analysis, which suggested that loci fall into four categories: loci associated with nearly all pain-related traits; loci primarily associated with a single trait; loci associated with multiple forms of skeletomuscular pain; and loci associated with headache-related pain. Overall, 664 genes were mapped to the 99 loci by genomic proximity, eQTLs, and chromatin interaction and ~15% of these genes showed differential expression in individuals with acute or chronic pain compared to healthy controls. Risk loci were enriched for genes involved in neurological and inflammatory pathways. Genetic correlation and two-sample Mendelian randomization indicated that psychiatric, metabolic, and immunological traits mediate some of these effects.

PMID:37844115 | DOI:10.1371/journal.pgen.1010977

J Laparoendosc Adv Surg Tech A. 2023 Oct 16. doi: 10.1089/lap.2023.0259. Online ahead of print.

ABSTRACT

Background: Postoperative gastrointestinal fistula (PGF) is one of the main causes of abdominal infection and perioperative death. This study was designed to investigate the risk factors of PGF, anastomotic fistula (AF), and duodenal stump fistula (DSF) for patients who underwent radical distal gastrectomy. Materials and Methods: In this retrospective observational study, 2652 gastric cancer cases who received radical distal gastrectomy from 2010 to 2020 were selected as research subjects. Subsequently, we adopted the univariate and multivariate logistic regression analysis as statistical method to screen the risk factors for PGF, AF, and DSF, respectively. Results: In univariate analysis, gender (P = .022), operative time (P = .013), intraoperative blood loss (P < .001), tumor diameter (P = .002), and tumor stage (P < .001) were related to PGF. Multivariate logistic regression analysis identified the male (odds ratio [OR] = 2.691, P = .042), massive intraoperative hemorrhage (OR = 1.002, P = .008), and advanced tumor (OR = 2.522, P = .019) as independent predictors for PGF. Moreover, diabetes (OR = 4.497, P = .008) and massive intraoperative hemorrhage (OR = 1.003, P = .010) were proved to be associated with AF, while massive intraoperative hemorrhage (OR = 1.001, P = .050) and advanced tumor (OR = 6.485, P = .005) were independent risk factors of DSF. Conclusions: The gender, intraoperative hemorrhage, tumor stage, and diabetes were expected to be used as predictors of PGF for radical distal gastrectomy.

PMID:37844093 | DOI:10.1089/lap.2023.0259

PLoS One. 2023 Oct 16;18(10):e0293027. doi: 10.1371/journal.pone.0293027. eCollection 2023.

ABSTRACT

A potential direct correlation between systemic inflammation and physiological aging has been suggested, along with whether there is a higher expression of inflammatory markers in otherwise healthy older adults. Cross-sectional data were extracted from the publicly available 2016 Health and Retirement Survey, a nationally representative survey of older adults in the United States. A subset of participants (n = 9934) consented to a blood draw at the time of recruitment and were measured for high sensitivity C-reactive protein (hs-CRP), Interleukin (IL-6, IL-10, IL-1RA), soluble tumor necrosis factor receptor (sTNFR-1) and transforming growth factor beta 1 (TGF-β1). We included 9,188 participants, representative of 83,939,225 nationally. After adjusting for sex and the number of comorbidities, there remained a significant positive correlation between age and ln (log adjusted) IL-6, and ln sTNFR-1, and a significant inverse correlation between age and ln IL-1RA, ln TGF-β1, and ln hs-CRP. Among the subset of participants who reported none of the available comorbidities (n = 971), there remained an independent correlation of age with ln IL-6 and ln sTNFR-1. After adjusting for age, sex, and number of reported comorbidities, there was a statistically significant correlation between increased ln IL-6, ln IL-10, ln sTNFR-1, and ln hs-CRP with death. This study highlights the existence of a correlation between serum biomarkers of inflammation and aging, not only in the whole population, but also in the smaller subset who reported no comorbidities, confirming the existence of a presence of low-grade inflammation in aging, even in healthy elders. We also highlight the existence of a correlation between inflammatory markers and overall mortality. Future studies should address a possible threshold of systemic inflammation where mortality significantly increases, as well as explore the effectiveness of anti-inflammatory treatments on morbidity and mortality in healthy aging subjects.

PMID:37844090 | DOI:10.1371/journal.pone.0293027

PLoS Negl Trop Dis. 2023 Oct 16;17(10):e0011699. doi: 10.1371/journal.pntd.0011699. Online ahead of print.

ABSTRACT

BACKGROUND: India suffers ~58,000 annual deaths due to snakebites. The ‘Big Four’ snakes (Russell’s viper, Indian cobra, common krait, and saw-scaled viper) that are responsible for most bites cause diverse clinical effects. Delayed treatment increases the risk of serious complications and treatment costs. Although government hospitals offer free treatment for snakebites in India, most patients opt for private healthcare, which is an out-of-pocket expense as they often lack health insurance coverage. This study aims to determine snakebite treatment costs in private tertiary care hospitals in Tamil Nadu, India and identifies the key factors contributing to treatment costs.

METHODOLOGY/PRINCIPAL FINDINGS: The treatment cost details for 913 snakebite victims were collected from 10 private tertiary care hospitals across Tamil Nadu. The data were classified into hospital, pharmacy, investigation, and laboratory costs, and analysed to determine various factors that contribute to the costs. The results demonstrate that the average treatment costs vary widely for different snakes. The hospital and pharmacy costs are higher than investigation and laboratory costs for all snakebites. Notably, Russell’s viper bites cost significantly more than the bites from other snakes. Overall, the type of snake, nature of complications, specialist treatments required, and arrival time to hospitals were identified as some of the key factors for higher treatment costs.

CONCLUSIONS/SIGNIFICANCE: These data demonstrate that ~80% of snakebite patients can be treated with INR 100,000 (~GBP 1000 or USD 1200) or less. This study emphasises the urgent need to improve rural medical care by providing appropriate training for healthcare professionals and essential resources to facilitate early assessment of patients, administer the initial dose of antivenom and refer the patients to tertiary care only when needed. Moreover, the outcome of this study forms a basis for developing appropriate policies to regulate snakebite treatment costs and provide affordable medical insurance for vulnerable communities.

PMID:37844081 | DOI:10.1371/journal.pntd.0011699

PLoS One. 2023 Oct 16;18(10):e0292258. doi: 10.1371/journal.pone.0292258. eCollection 2023.

ABSTRACT

The Monetary Choice Questionnaire (MCQ) is a widely used behavioral task that measures the rate of delay discounting (i.e., k), the degree to which a delayed reward loses its present value as a function of the time to its receipt. Both 21- and 27-item MCQs have been extensively validated and proven valuable in research. Different methods have been developed to streamline MCQ scoring. However, existing scoring methods have yet to tackle the issue of missing responses or provide clear guidance on imputing such data. Due to this lack of knowledge, the present study developed and compared three imputation approaches that leverage the MCQ’s structure and prioritize ease of implementation. Additionally, their performance was compared with mode imputation. A Monte Carlo simulation was conducted to evaluate the performance of these approaches in handling various missing responses in each observation across two datasets from prior studies that employed the 21- and 27-item MCQs. One of the three approaches consistently outperformed mode imputation across all performance measures. This approach involves imputing missing values using congruent non-missing responses to the items corresponding to the same k value or introducing random responses when congruent answers are unavailable. This investigation unveils a straightforward method for imputing missing data in the MCQ while ensuring unbiased estimates. Along with the investigation, an R tool was developed for researchers to implement this strategy while streamlining the MCQ scoring process.

PMID:37844072 | DOI:10.1371/journal.pone.0292258

Environ Sci Technol. 2023 Oct 16. doi: 10.1021/acs.est.3c04805. Online ahead of print.

ABSTRACT

The exposome concept aims to consider all environmental stressors simultaneously. The dimension of the data and the correlation that may exist between exposures lead to various statistical challenges. Some methodological studies have provided insight regarding the efficiency of specific modeling approaches in the context of exposome data assessed once for each subject. However, few studies have considered the situation in which environmental exposures are assessed repeatedly. Here, we conduct a simulation study to compare the performance of statistical approaches to assess exposome-health associations in the context of multiple exposure variables. Different scenarios were tested, assuming different types and numbers of exposure-outcome causal relationships. An application study using real data collected within the INMA mother-child cohort (Spain) is also presented. In the simulation experiment, assessed methods showed varying performance across scenarios, making it challenging to recommend a one-size-fits-all strategy. Generally, methods such as sparse partial least-squares and the deletion-substitution-addition algorithm tended to outperform the other tested methods (ExWAS, Elastic-Net, DLNM, or sNPLS). Notably, as the number of true predictors increased, the performance of all methods declined. The absence of a clearly superior approach underscores the additional challenges posed by repeated exposome data, such as the presence of more complex correlation structures and interdependencies between variables, and highlights that careful consideration is essential when selecting the appropriate statistical method. In this regard, we provide recommendations based on the expected scenario. Given the heightened risk of reporting false positive or negative associations when applying these techniques to repeated exposome data, we advise interpreting the results with caution, particularly in compromised contexts such as those with a limited sample size.

PMID:37844068 | DOI:10.1021/acs.est.3c04805

Clin Lab. 2023 Oct 1;69(10). doi: 10.7754/Clin.Lab.2023.230408.

ABSTRACT

BACKGROUND: The aim was to explore the diagnostic value of serum free light chain (sFLC) and other laboratory indicators for the patients with light chain multiple myeloma (LCMM).

METHODS: We performed a retrospective study including 82 LCMM cases and 43 healthy subjects as the observation and control groups, respectively. The observation group was further divided into two subgroups: κ- and λ-type LCMM. Sixteen quantitative indicators were collected and the difference among groups was compared. We also evaluated the positive detection rate (PDR) of four qualitative indicators for M protein detection. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of sixteen indicators.

RESULTS: Fourteen indicators showed statistical differences between the control group and κ- or λ-type LCMM subgroup. The κ and λ sFLC ratio (rFLC) and the difference between κ and λ FLC (dFLC) showed differences among the three groups. Among the four qualitative indicators of M protein detection, rFLC showed the highest PDR for both κ- and λ-type LCMM. Among the three combinations with rFLC or uIFE did not show statistical differences. ROC curve analysis indicated a relatively high diagnostic value of dFLC for both κ- and λ-type LCMM.

CONCLUSIONS: We should be vigilant about the missed diagnosis by observing the changes of MM-related indicators, particularly dFLC and the six other indicators with high diagnostic value. rFLC can improve the diagnostic ability of LCMM.

PMID:37844061 | DOI:10.7754/Clin.Lab.2023.230408

Clin Lab. 2023 Oct 1;69(10). doi: 10.7754/Clin.Lab.2023.230512.

ABSTRACT

BACKGROUND: The Helicobacter pylori eradication rate with standard triple therapy (STT) is continuously decreasing due to clarithromycin resistance. This study aimed to investigate the eradication rate of empirical and tailored therapy and explore various factors affecting this eradication rate using clarithromycin resistance test data for the last 4 years at a single institution in Daegu.

METHODS: From August 2018 to July 2021, a total of 1,395 patients diagnosed with H. pylori infection based on rapid urea testing and histology at Keimyung University Dongsan Hospital were retrospectively examined. Participants were classified into the empirical and tailored therapy groups according to the results of the clarithromycin resistance test using the polymerase chain reaction.

RESULTS: The overall eradication rate of empirical STT was 72.8%, and the eradication rate by year was 71.6% in 2018, 77.4% in 2019, 70.3% in 2020, and 70.6% in 2021; the differences were not statistically significant (p = 0.173). No significant difference was noted in the eradication rate according to gender, age, type of proton pump inhibitors, and use of probiotics. Significant differences were noted in the eradication rate according to the treat-ment period: 69.7% in the 7-day, 67.3% in the 10-day, and 81.4% in the 14-day group (p = 0.001). The eradication rate with STT was 87.4% in the non-resistant group. In the case of clarithromycin resistance, treatment was mainly with bismuth quadruple therapy (BQT), and the eradication rate was 86.1%. The eradication rate was higher with administration of BQT for 10 days or 14 days than for administration of BQT for 7 days, but with no statistical significance (p = 0.364).

CONCLUSIONS: Extending the treatment period of STT helped in improving the eradication rate, and tailored therapy through clarithromycin resistance testing showed superior results when compared to empirical therapy.

PMID:37844041 | DOI:10.7754/Clin.Lab.2023.230512

Clin Lab. 2023 Oct 1;69(10). doi: 10.7754/Clin.Lab.2023.230517.

ABSTRACT

BACKGROUND: The study investigates the prognostic impact of D-dimer levels in patients with cardiogenic shock (CS). Although D-dimer levels were found to be associated with prognosis in various clinical settings such as heart failure or acute myocardial infarction (AMI), the prognostic role of D-dimer levels in CS patients has not yet been clarified.

METHODS: Consecutive CS patients with and without concomitant AMI were prospectively included from 2019 to 2021. The prognostic impact of D-dimer levels was tested for 30-day all-cause mortality within the entire study cohort and stratified by the presence or absence of AMI. Statistical analyses included C-statistics, Kaplan-Meier, and multivariate Cox regression analyses.

RESULTS: One hundred and twenty-three consecutive CS patients were included with an overall all-cause mortality at 30 days of 55%. The median D-dimer level on admission was 8.44 mg/L, whereas D-dimer levels were higher in 30-day non-survivors compared to survivors (median 13.0 vs. 5.2 mg/L; p = 0.011). D-dimer levels above the median were associated with an increased risk of 30-day all-cause mortality compared to patients with lower D-dimer levels (66% vs. 54%, log rank p = 0.050; HR = 1.594; 95% CI 0.979 – 2.594; p = 0.061), especially in patients with non-AMI-related CS (65% vs. 30%, log rank p = 0.010). The prognostic value of D-dimer levels was still demonstrated after multivariate adjustment (HR = 1.024; 95% CI 1.004 – 1.045; p = 0.020).

CONCLUSIONS: D-dimer measurement may be a reliable biomarker to predict the risk of 30-day mortality in CS patients, especially in patients with non-AMI related CS.

PMID:37844039 | DOI:10.7754/Clin.Lab.2023.230517

Carbohydr Polym. 2023 Dec 15;322:121338. doi: 10.1016/j.carbpol.2023.121338. Epub 2023 Aug 28.

ABSTRACT

Machine learning (ML) has been used for many clinical decision-making processes and diagnostic procedures in bioinformatics applications. We examined eight algorithms, including linear discriminant analysis (LDA), logistic regression (LR), k-nearest neighbor (KNN), random forest (RF), gradient boosting machine (GBM), support vector machine (SVM), Naïve Bayes classifier (NB), and artificial neural network (ANN) models, to evaluate their classification and prediction capabilities for four tissue types in Wolfiporia extensa using their monosaccharide composition profiles. All 8 ML-based models were assessed as exemplary models with AUC exceeding 0.8. Five models, namely LDA, KNN, RF, GBM, and ANN, performed excellently in the four-tissue-type classification (AUC > 0.9). Additionally, all eight models were evaluated as good predictive models with AUC value > 0.8 in the three-tissue-type classification. Notably, all 8 ML-based methods outperformed the single linear discriminant analysis (LDA) plotting method. For large sample sizes, the ML-based methods perform better than traditional regression techniques and could potentially increase the accuracy in identifying tissue samples of W. extensa.

PMID:37839831 | DOI:10.1016/j.carbpol.2023.121338