Nevin Manimala

Trials. 2023 Feb 28;24(1):152. doi: 10.1186/s13063-023-07162-x.

ABSTRACT

BACKGROUND: Minimally invasive surgery has become popular as a surgical approach for colorectal cancer because it has fewer complications related to the abdominal incision and perioperative complications. However, the incidence of incisional hernias in laparoscopic surgery has been reported to be similar to that in open surgery. We developed a new method, the non-muscle-cutting periumbilical transverse incision, for a small incision in laparoscopic colon cancer surgery. This study aims to evaluate the effectiveness of the non-muscle-cutting periumbilical transverse incision in comparison with the midline incision in reducing the incidence of an incisional hernia in patients undergoing laparoscopic colon cancer surgery.

METHODS: This is an open-label, multi-centre, parallel, superiority, and randomised trial. Altogether, 174 patients will be allocated in a 1:1 ratio to either the midline incision or the non-muscle-cutting periumbilical transverse incision group, after stratifying by the location of the tumour (right- or left-sided). The primary outcome of this study is the incidence of incisional hernias (both symptomatic and radiologic hernias) at 12 months after surgery. The secondary outcomes include operative outcomes, 30-day postoperative complications, pathological results, and patient-reported outcomes (short form-12 health survey questionnaire and body image questionnaire). Both primary (intention-to-treat) and secondary (as-treated principles) analyses will be performed for all outcomes. The statistical significance level was set at p < 0.05 (two-sided testing).

DISCUSSION: This trial may show that the non-muscle-cutting periumbilical transverse incision will reduce the incidence of incisional hernias compared to the midline incision.

TRIAL REGISTRATION: Clinical Research Information Service (CRiS) of Republic of Korea, KCT0006082 . Registered on April 12, 2021.

PMID:36855158 | DOI:10.1186/s13063-023-07162-x

Diabetol Metab Syndr. 2023 Mar 1;15(1):32. doi: 10.1186/s13098-023-01006-z.

ABSTRACT

BACKGROUND: Diabetes mellitus is a major risk factor for heart failure. A recent consensus statement recommended annual cardiac biomarker testing (e.g. natriuretic peptide or high-sensitivity cardiac troponin) for all patients with diabetes. We aimed to identify patients at a higher risk of hospitalization for heart failure among patients with type 2 diabetes to prioritize those who would require screening.

METHODS: Overall, 1,189,113 patients who underwent two medical health checkup cycles (2009-2012 and 2011-2014) and had stable diabetic kidney disease (DKD) phenotype in the Korean National Health Insurance Service database were included in this study. After excluding those with concurrent proteinuria (PU) and reduced estimated glomerular filtration rate, three groups (no-DKD, PU⁺DKD, and PU^–DKD) were identified. A fatty liver index of ≥ 60 was defined as metabolic dysfunction-associated fatty liver disease (MAFLD). Patients were followed up until December 2018 or until outcomes developed. The Cox proportional hazard model was used to compare the risk of hospitalization for heart failure across groups.

RESULTS: During an average of 6.6 years of follow-up, 5781 patients developed hospitalization for heart failure. After adjusting for covariates, the risk of hospitalization for heart failure was highest in the PU⁺DKD group [HR 3.12, 95% CI (2.75-3.55)], followed by the PU^–DKD group [HR 1.85, 95% CI (1.73-1.99)] using the no-DKD group as the reference category. The risk of hospitalization for heart failure was comparable regardless of MAFLD status in patients who already had DKD. However, in the no-DKD group, the risk of hospitalization for heart failure was 1.4 times higher in patients with MAFLD than in those without [HR 1.41, 95% CI (1.31-1.52)].

CONCLUSIONS: In lines with the international consensus statement, we suggest that annual cardiac biomarker testing should be conducted at least in patients with DKD and/or MAFLD.

PMID:36855144 | DOI:10.1186/s13098-023-01006-z

Eur Spine J. 2023 Feb 28. doi: 10.1007/s00586-023-07621-8. Online ahead of print.

ABSTRACT

PURPOSE: Predict nonhome discharge (NHD) following elective anterior cervical discectomy and fusion (ACDF) using an explainable machine learning model.

METHODS: 2227 patients undergoing elective ACDF from 2008 to 2019 were identified from a single institutional database. A machine learning model was trained on preoperative variables, including demographics, comorbidity indices, and levels fused. The validation technique was repeated stratified K-Fold cross validation with the area under the receiver operating curve (AUROC) statistic as the performance metric. Shapley Additive Explanation (SHAP) values were calculated to provide further explainability regarding the model’s decision making.

RESULTS: The preoperative model performed with an AUROC of 0.83 ± 0.05. SHAP scores revealed the most pertinent risk factors to be age, medicare insurance, and American Society of Anesthesiology (ASA) score. Interaction analysis demonstrated that female patients over 65 with greater fusion levels were more likely to undergo NHD. Likewise, ASA demonstrated positive interaction effects with female sex, levels fused and BMI.

CONCLUSION: We validated an explainable machine learning model for the prediction of NHD using common preoperative variables. Adding transparency is a key step towards clinical application because it demonstrates that our model’s “thinking” aligns with clinical reasoning. Interactive analysis demonstrated that those of age over 65, female sex, higher ASA score, and greater fusion levels were more predisposed to NHD. Age and ASA score were similar in their predictive ability. Machine learning may be used to predict NHD, and can assist surgeons with patient counseling or early discharge planning.

PMID:36854862 | DOI:10.1007/s00586-023-07621-8

Sleep Breath. 2023 Feb 28. doi: 10.1007/s11325-023-02797-1. Online ahead of print.

ABSTRACT

BACKGROUND: No study has examined the psychometric properties of the sleep condition indicator (SCI) for screening poststroke insomnia in the Indonesian population. We aimed to develop the Indonesian version of the sleep condition indicator (ISCI) and to examine its psychometric properties for screening adult patients in late sub-acute and chronic periods after stroke.

METHODS: This was a cross-sectional study with two stages. In the first stage, the English version of the SCI was translated into the ISCI using standard procedures. The psychometric properties of the ISCI were tested in the second stage. Internal consistency and test-retest reliability of ISCI were used to evaluate reliability. A confirmatory factor analysis (CFA) was performed to test construct validity. To test concurrent and convergent validity, the Indonesian version of the insomnia severity index (ISI-INA), generalized anxiety disorder questionnaire (IGAD-7), and patient health questionnaire (IPHQ-9) were used. A receiver operating characteristic (ROC) analysis was conducted to calculate the optimal cutoff score of the ISCI on the basis of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) diagnostic criteria for insomnia.

RESULTS: A total of 160 adults with a diagnosis of stroke for more than 3 months were included (median age of 58.5 years, 31% met the DSM-5 criteria for insomnia). The ISCI had a satisfactory Cronbach’s alpha of 0.89 and test-retest reliability of 0.78. The CFA revealed that the ISCI exhibited a satisfactory model fit and was associated with the ISI-INA, IGAD-7, and IPHQ-9 (r = -0.81, -0.32, and -0.52, respectively; all P < .001). The ROC test revealed that the optimal cutoff point of ≤23 yielded the highest sensitivity (94%) and specificity (97%).

CONCLUSION: The study results revealed that the 8-item ISCI is a reliable and valid screening tool for detecting insomnia symptoms according to the DSM-5 criteria in the chronic period after stroke.

PMID:36854859 | DOI:10.1007/s11325-023-02797-1

Endocrine. 2023 Mar 1. doi: 10.1007/s12020-023-03334-6. Online ahead of print.

ABSTRACT

INTRODUCTION: Breast cancer is a leading cause of cancer morbidity and mortality in females. Decreased availability of Vitamin D within breast cells, contributed by deficiency of serum Vitamin D and polymorphisms of Vitamin D receptor genes are possible risk factors for breast cancer.

OBJECTIVES: To study the association of FokI polymorphism of the Vitamin D Receptor gene with breast cancer in females and to study the levels of Vitamin D in breast cancer patients.

MATERIALS AND METHODS: VDR gene FokI genotyping was done by PCR-RFLP method and levels of serum Vitamin D were estimated by ELISA. Statistical analysis was done with SPSS v.21.

RESULTS: Serum Vitamin D was significantly lower in newly diagnosed breast cancer patients than in healthy controls (P = 0.016). Females with serum Vitamin D levels in the highest quartile have a lesser risk of breast cancer than those with serum Vitamin D levels in the lowest quartile (O. R = 2.4421, C.I = 1.09-5.45, P = 0.029). The risk of developing breast cancer is higher in women with the polymorphic T allele for VDR FokI genotype (CT/TT) than those homozygous for the wild C allele (CC). (O.R. = 4.295, C.I. = 2.2110-8.3451, p-value = <0.0001). Levels of serum Vitamin D were significantly higher (p < 0.001) in ER + patients and significantly low in those presenting with higher stages of cancer (p = 0.009).

CONCLUSIONS: FokI polymorphism of VDR gene and low circulating Vitamin D levels increase the risk of developing breast cancer in North Indian females. Serum Vitamin D can be used as a prognostic factor.

PMID:36854857 | DOI:10.1007/s12020-023-03334-6

Funct Integr Genomics. 2023 Feb 28;23(1):70. doi: 10.1007/s10142-023-00995-4.

ABSTRACT

Body dysmorphic disorder (BDD) is a disorder associated with depression and eating disorders. It often arises from minor defects in appearance or an individual imagining that he or she is defective. However, the mechanisms causing BDD remain unclear, and its pathogenesis and adjuvant treatment methods still need to be explored. Here, we employed a liquid chromatography-mass spectrometry (LC-MS)-based metabolomics approach to identify key metabolic differences in BDD versus healthy patients. We obtained plasma samples from two independent cohorts (including eight BDD patients and eight healthy control patients). Raw data were analyzed using Compound Discoverer to determine peak alignment, retention time correction, and extraction of peak areas. Metabolite structure identification was also obtained using Compound Discoverer by of accurate mass matching (< 10 ppm) and secondary spectral matching queries of compound databases. Next, multidimensional statistical analyses were performed using the ropls R package. These analyses included: unsupervised principal component analysis, supervised partial Least-Squares Discriminant Analysis, and orthogonal partial Least-Squares Discriminant Analysis. We then identified the most promising metabolic signatures associated with BDD across all metabolomic datasets. Principal component analysis showed changes in small-molecule metabolites in patients, and we also found significant differences in metabolite abundance between the BDD and normal groups. Our findings suggest that the occurrence of BDD may be related to metabolites participating in the following KEGG pathways: ABC transporters, purine metabolism, glycine, serine and threonine metabolism, pyrimidine, pyrimidine metabolism, biosynthesis of 12-, 14-, and 16-membered macrolides, microbial metabolism in diverse environments, biosynthesis of secondary metabolites, and caffeine and insect hormone biosynthesis.

PMID:36854840 | DOI:10.1007/s10142-023-00995-4

Reprod Sci. 2023 Feb 28. doi: 10.1007/s43032-023-01201-3. Online ahead of print.

ABSTRACT

The role of MTHFR C677T polymorphism in repeated pregnancy loss (RPL) among different populations has been studied with inconsistent results. The study objective was to determine the association between MTHFR C677T polymorphisms and RPL among Arab women. The review included all the available studies investigating the association between MTHFR C677T polymorphism and RPL from 2000 until now. The searched database included Cochrane, Trip, EMBASE, and Google Scholar. Two authors independently reviewed the searched articles for eligibility, judged their risk of bias, and extracted the characteristics of the studies. Review Manager 5.3 program was used for data analysis using odds ratio (OR) at a 95% confidence interval (CI). The study revealed a statistically significant difference between cases and controls regarding combined MTHFR C677T polymorphisms (OR = 1.50, 95% CI = 1.15-1.96), MTHFR C677T heterozygous (OR = 1.41, 95% CI = 1.08-1.83), and MTHFR C677T homozygous (OR = 4.19, 95% CI = 1.87-9.39). Considerable significant heterogeneity was recorded in the three analyses (P < 0.05). The review supported the hypothesis that MTHFR C677T mutation is considered a significant risk factor for RPL among Arab women.

PMID:36854824 | DOI:10.1007/s43032-023-01201-3

Biometrics. 2023 Feb 28. doi: 10.1111/biom.13848. Online ahead of print.

ABSTRACT

False discovery rate (FDR) controlling procedures provide important statistical guarantees for replicability in signal identification based on multiple hypotheses testing. In many fields of study, FDR controlling procedures are used in high-dimensional (HD) analyses to discover features that are truly associated with the outcome. In some recent applications, data on the same set of candidate features are independently collected in multiple different studies. For example, gene expression data are collected at different facilities and with different cohorts, to identify the genetic biomarkers of multiple types of cancers. These studies provide us with opportunities to identify signals by considering information from different sources (with potential heterogeneity) jointly. This paper is about how to provide FDR control guarantees for the tests of union null hypotheses of conditional independence. We present a knockoff-based variable selection method (Simultaneous knockoffs) to identify mutual signals from multiple independent data sets, providing exact FDR control guarantees under finite sample settings. This method can work with very general model settings and test statistics. We demonstrate the performance of this method with extensive numerical studies and two real data examples. This article is protected by copyright. All rights reserved.

PMID:36854821 | DOI:10.1111/biom.13848

Eur Arch Otorhinolaryngol. 2023 Feb 28. doi: 10.1007/s00405-023-07891-4. Online ahead of print.

ABSTRACT

PURPOSE: Autosomal dominant polycystic kidney disease (ADPKD) is a renal disease with genetic transmisson. Mutations in the PKD1 and PKD2 genes, which encode integral membrane proteins of the cilia of primary renal tubule epithelial cells, are seen in ADPKD. The aim of this study was to evaluate the sinonasal epithelium, which is epithelium with cilia, by measuring the nasal mucociliary clearance time, and to investigate the effect of ADPKD on nasal mucociliary clearance.

METHODS: The study included 34 patients, selected from patients followed up in the Nephrology Clinic, and 34 age and gender-matched control group subjects. The nasal mucociliary clearance time (NMCT) was measured with the saccharin test.

RESULTS: The mean age of the study subjects was 47.15 ± 14.16 years in the patient group and 47.65 ± 13.85 years in the control group. The eGFR rate was determined as mean 72.06 ± 34.26 mL/min in the patient group and 99.79 ± 17.22 mL/min in the control group (p < 0.001). The NMCT was determined to be statistically significantly longer in the patient group (903.6 ± 487.8 s) than in the control group (580 ± 259 s) (p = 0.006).

CONCLUSIONS: The study results showed that the NMCT was statistically significantly longer in patients with ADPKD compared to the control group, but in the linear regression analysis results, no correlation was determined between eGFR and NMCT.

PMID:36854810 | DOI:10.1007/s00405-023-07891-4

J Cancer Res Clin Oncol. 2023 Feb 28. doi: 10.1007/s00432-023-04601-9. Online ahead of print.

ABSTRACT

PURPOSE: Hematotoxicity is a common side-effect of cytotoxic gastrointestinal (GI) cancer therapies. An unsolved problem is to predict the individual risk therefore to decide on treatment adaptions. We applied an established biomathematical prediction model and primarily evaluated its predictive value in patients undergoing chemotherapy for GI cancers in curative intent.

METHODS: In a prospective, observational multicenter study on patients with gastro-esophageal or pancreatic cancer (n = 28) receiving myelosuppressive adjuvant or neoadjuvant chemotherapy (FLO(T) or FOLFIRINOX), individual model parameters were learned based on patients’ observed laboratory values during the first chemotherapy cycle and further external data resources. Grades of hematotoxicity of subsequent cycles were predicted by model simulation and compared with observed data.

RESULTS: The most common high-grade hematological toxicity was neutropenia [19/28 patients (68%)]. For the FLO(T) regimen, individual grades of thrombocytopenia and leukopenia could be well predicted for cycles 2-4, as well as grades of neutropenia for cycle 2. Prediction accuracy for neutropenia in the third and fourth cycle differed by one toxicity grade on average. For the FOLFIRINOX-regimen, thrombocytopenia predictions showed a maximum deviation of one toxicity grade up to the end of therapy (8 cycles). Deviations of predictions were less than one degree on average up to cycle 4 for neutropenia, and up to cycle 6 for leukopenia.

CONCLUSION: The biomathematical model showed excellent short-term and decent long-term prediction performance for all relevant hematological side effects associated with FLO(T)/FOLFIRINOX. Clinical utility of this precision-medicine approach needs to be further investigated in a larger cohort.

PMID:36854800 | DOI:10.1007/s00432-023-04601-9