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Nevin Manimala Statistics

Effectiveness of physiotherapy in children with functional constipation

Pediatr Surg Int. 2024 Jun 1;40(1):147. doi: 10.1007/s00383-024-05733-w.

ABSTRACT

PURPOSE: The objective was to compare the immediate effects of pharmacological versus physiotherapy intervention versus a combination of physiotherapy and pharmacological treatment, as well as the quality of life and the recurrence of symptoms in children with functional constipation after 3 months.

METHODS: A total of 69 children with functional constipation between the ages of 5 and 14 years of either gender were assessed and randomly assigned to one of three groups: Group A, B, and C. Visual Analogue Scale, Bristol Stool Form Scale, frequency of defecation, PedsQL GI symptom scale, and PedsQL Generic Core Scale were used as outcome measures. Pharmacology was used to treat Group A, physiotherapy was used to treat Group B, and a combination of both was used to treat Group C.

RESULTS: The study revealed statistically significant results on Visual Analogue Scale, Bristol Stool Form Scale, and frequency of defecation in all groups. However, no significant changes were observed on the PedsQL GI symptom scale and the Generic Core scale in Group A, whereas significant changes were observed in Groups B and C.

CONCLUSION: In this study, we found that there were significant differences in the short- and long-term effects across all groups. More changes occurred in Group C than in Groups A and B.

PMID:38824249 | DOI:10.1007/s00383-024-05733-w

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Nevin Manimala Statistics

Surgery versus no surgery in platinum-sensitive relapsed ovarian cancer: final overall survival analysis of the SOC-1 randomized phase 3 trial

Nat Med. 2024 Jun 1. doi: 10.1038/s41591-024-02981-0. Online ahead of print.

ABSTRACT

Surgery for platinum-sensitive, relapsed ovarian cancer (PSROC) is widely practiced but had contradictory survival outcomes in previous studies. In this multicenter, open-label, phase 3 trial, women with PSROC, and having had one previous therapy and no platinum-based chemotherapy (platinum-free interval) of 6 months or more, were randomly assigned to either the surgery group (182 patients) or the no-surgery group (control) (175 patients). Patients with resectable diseases were eligible according to the international model (iMODEL), combined with a positron emission tomography-computed tomography imaging. Overall survival (OS) and progression-free survival were coprimary endpoints in hierarchical testing, and a significantly longer progression-free survival with surgery was previously reported. Final analysis of OS was planned at data maturity of 59%. Between 19 July 2012 and 3 June 2019, 357 patients were enrolled. Median follow-up was 82.5 months. Median OS was 58.1 months with surgery and 52.1 months for control (hazard ratio (HR) 0.80, 95% confidence interval (CI) 0.61-1.05, P = 0.11). The predefined threshold for statistical significance was not met, but prespecified sensitivity analysis was performed. Overall, 61 of 175 (35%) patients in control had crossed over to surgery following subsequent relapse, and adjusted HR for death in the surgery group compared with control was 0.76, 95% CI 0.58-0.99. In subgroup analysis of relapse sites by imaging, median survival was not estimable in the surgery group and was 69.5 months in control in patients with <20 sites (HR 0.69, 95% CI 0.46-1.03). Patients with a complete resection had the most favorable outcome, with a median OS of 73.0 months. Twenty-four of 182 (13.2%) patients remained relapse free and alive >60 months in the surgery group as compared with five of 175 (2.9%) patients in the control group. In patients with PSROC, surgery did not increase OS in the intention-to-treat population but resulted in a prolongation of survival following adjustment of crossover.ClinicalTrials.gov registration: NCT01611766 .

PMID:38824243 | DOI:10.1038/s41591-024-02981-0

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Nevin Manimala Statistics

Her-2/neu gene amplification and its correlation with other prognostic factors in Iranian breast cancer patients

Mol Biol Rep. 2024 Jun 1;51(1):718. doi: 10.1007/s11033-024-09667-3.

ABSTRACT

BACKGROUND: Breast cancer is one of the most common diseases in females, arising from overexpression of a variety of oncogenes like HER2/neu. The amplification rate of this gene is variable in different breast cancer patients. In this study, the amplification of the HER2/neu oncogene was distinguished in breast cancer patients and its correlation with prognostic factors. Also, the simultaneous effect of prognostic factors on the occurrence of a specific prognostic factor was investigated.

MATERIALS AND METHODS: The multiplex PCR technique was used to assay the amplification of the HER2/neu oncogene in breast cancer patients. After extracting DNA from 100 tumor tissue and 8 normal breast tissue samples, the amplification of the HER2/neu gene was distinguished by the co-amplification of a single-copy reference gene, γ-IFN, and the target gene HER2/neu in the PCR reaction and using the Gel analyzer software. SPSS 23 and STATA 9.1 software were used for statistical analysis.

RESULTS: The HER2/neu gene was amplification in 30% of the tumor samples. The statistical analysis showed a statistically significant relationship between HER2/neu gene amplification and progesterone receptors. Amplification of the HER2/neu gene significantly increases the chance of lymph node involvement. Also, the amplification of this gene in tumors with histological grade II tissue is more than grade I.

CONCLUSION: The amplification of the HER2/neu gene can be used as an independent prognostic factor in predicting lymph node involvement and histological grade in breast cancer patients.

PMID:38824224 | DOI:10.1007/s11033-024-09667-3

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Nevin Manimala Statistics

Estimation of rice yield using multivariate analysis techniques based on meteorological parameters

Sci Rep. 2024 Jun 1;14(1):12626. doi: 10.1038/s41598-024-63596-6.

ABSTRACT

This study aims to develop predictive models for rice yield by applying multivariate techniques. It utilizes stepwise multiple regression, discriminant function analysis and logistic regression techniques to forecast crop yield in specific districts of Haryana. The time series data on rice crop have been divided into two and three classes based on crop yield. The yearly time series data of rice yield from 1980-81 to 2020-21 have been taken from various issues of Statistical Abstracts of Haryana. The study also utilized fortnightly meteorological data sourced from the Agrometeorology Department of CCS HAU, India. For comparing various predictive models’ performance, evaluation of measures like Root Mean Square Error, Predicted Error Sum of Squares, Mean Absolute Deviation and Mean Absolute Percentage Error have been used. Results of the study indicated that discriminant function analysis emerged as the most effective to predict the rice yield accurately as compared to logistic regression. Importantly, the research highlighted that the optimum time for forecasting the rice yield is 1 month prior to the crops harvesting, offering valuable insight for agricultural planning and decision-making. This approach demonstrates the fusion of weather data and advanced statistical techniques, showcasing the potential for more precise and informed agricultural practices.

PMID:38824223 | DOI:10.1038/s41598-024-63596-6

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Nevin Manimala Statistics

Construction and validation of a clinical risk model based on machine learning for screening characteristic factors of lymphovascular space invasion in endometrial cancer

Sci Rep. 2024 Jun 1;14(1):12624. doi: 10.1038/s41598-024-63436-7.

ABSTRACT

This study aimed to identify factors that affect lymphovascular space invasion (LVSI) in endometrial cancer (EC) using machine learning technology, and to build a clinical risk assessment model based on these factors. Samples were collected from May 2017 to March 2022, including 312 EC patients who received treatment at Xuzhou Medical University Affiliated Hospital of Lianyungang. Of these, 219 cases were collected for the training group and 93 for the validation group. Clinical data and laboratory indicators were analyzed. Logistic regression and least absolute shrinkage and selection operator (LASSO) regression were used to analyze risk factors and construct risk models. The LVSI and non-LVSI groups showed statistical significance in clinical data and laboratory indicators (P < 0.05). Multivariable logistic regression analysis identified independent risk factors for LVSI in EC, which were myometrial infiltration depth, cervical stromal invasion, lymphocyte count (LYM), monocyte count (MONO), albumin (ALB), and fibrinogen (FIB) (P < 0.05). LASSO regression identified 19 key feature factors for model construction. In the training and validation groups, the risk scores for the logistic and LASSO models were significantly higher in the LVSI group compared with that in the non-LVSI group (P < 0.001). The model was built based on machine learning and can effectively predict LVSI in EC and enhance preoperative decision-making. The reliability of the model was demonstrated by the significant difference in risk scores between LVSI and non-LVSI patients in both the training and validation groups.

PMID:38824215 | DOI:10.1038/s41598-024-63436-7

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Nevin Manimala Statistics

Application of pervious concrete pavement in the “breathe in-breathe out” design for sponge cities in China

Environ Sci Pollut Res Int. 2024 Jun 2. doi: 10.1007/s11356-024-33760-6. Online ahead of print.

ABSTRACT

Sponge city construction is an ideal approach to mitigate the degradation of urban water environments. Among road materials, permeable concrete pavement stands out due to its unique structure that allows rainwater runoff to flow through its pores. This paper analyzes the current application status and the prospect of different permeable pavement designs in China’s sponge cities, aiming to offer valuable insights for urban planning and construction. Statistical analysis summarizes the spatial-temporal distribution patterns of urban flooding disasters in China and their causes. By comparing the characteristics and advantages of pervious concrete pavement with traditional concrete pavement, the potential of permeable concrete pavement in sponge city construction is summarized through case studies. The findings highlight that by adjusting the pore size, permeable concrete pavement can collect rainwater while filtering impurities, thereby purifying surface runoff. The range of the pervious coefficient should ideally fall within the range of 4~8 mm/s. In addition, the pavement’s large contact area with the air and internal water evaporation contributes to its self-regulating capability, reducing the occurrence of extreme temperatures. Related experiments have shown that from 8 am to 12 pm, pervious concrete pavement can reduce the temperature by approximately 1 °C compared to conventional concrete. From 12 pm to 8 pm, this temperature difference increases to approximately 3 °C. To meet the needs of environmental protection and resource utilization, permeable concrete pavement can serve as an ideal tool to achieve green and low-carbon development.

PMID:38824209 | DOI:10.1007/s11356-024-33760-6

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Nevin Manimala Statistics

Enhancing ecological uncertainty predictions in pollution control games through dynamic Bayesian updating

Sci Rep. 2024 Jun 1;14(1):12594. doi: 10.1038/s41598-024-63234-1.

ABSTRACT

This study presents a dynamic Bayesian game model designed to improve predictions of ecological uncertainties leading to natural disasters. It incorporates historical signal data on ecological indicators. Participants, acting as decision-makers, receive signals about an unknown parameter-observations of a random variable’s realization values before a specific time, offering insights into ecological uncertainties. The essence of the model lies in its dynamic Bayesian updating, where beliefs about unknown parameters are refined with each new signal, enhancing predictive accuracy. The main focus of our paper is to theoretically validate this approach, by presenting a number of theorems that prove its precision and efficiency in improving uncertainty estimations. Simulation results validate the model’s effectiveness in various scenarios, highlighting its role in refining natural disaster forecasts.

PMID:38824183 | DOI:10.1038/s41598-024-63234-1

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Nevin Manimala Statistics

Breakfast consumption, saturated fat intake, and body mass index among medical and non-medical students: a cross-sectional analysis

Sci Rep. 2024 Jun 1;14(1):12608. doi: 10.1038/s41598-024-63440-x.

ABSTRACT

Changes in dietary patterns and body weight have become a focus of research in undergraduate students. This study compared breakfast consumption, intake of foods high in saturated fat, and BMI between medical and non-medical students. A comparative cross-sectional study was conducted in 4,561 Peruvian university students, of whom 1,464 (32.1%) were from the medical field and 3,097 (67.9%) from the non-medical field. We compared the frequency of breakfast consumption (categorized as regular: 6 to 7 days/week; occasional: 3 to 5 days/week; and rarely or never: 0 to 2 days/week) and the frequency of consumption of foods high in saturated fat. We created simple and multiple linear and Poisson regression models with robust variance to evaluate the association of the mentioned variables with academic fields. Non-medical students (Adjusted Prevalence Ratio [PR] = 0.92, 95% CI 0.86-0.99; p = 0.008) were less likely to eat breakfast regularly compared to medical students. Likewise, consumption of foods high in saturated fats was higher in non-medical students (B = 1.47, 95% CI 0.91-2.04; p < 0.001) compared to medical students. Similarly, the mean BMI of these students was significantly higher than that of medical students (B = 0.33, 95% CI 0.12-0.53; p = 0.002). Although medical students reported relatively healthy eating habits and a lower BMI, there is a widespread need to promote improved diet and lifestyle among the entire university population to reduce the risks of communicable diseases and improve quality of life.

PMID:38824182 | DOI:10.1038/s41598-024-63440-x

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Nevin Manimala Statistics

Interaction analysis of subgroup effects in randomized trials: the essential methodological points

Sci Rep. 2024 Jun 1;14(1):12619. doi: 10.1038/s41598-024-62896-1.

ABSTRACT

Subgroup analysis aims to identify subgroups (usually defined by baseline/demographic characteristics), who would (or not) benefit from an intervention under specific conditions. Often performed post hoc (not pre-specified in the protocol), subgroup analyses are prone to elevated type I error due to multiple testing, inadequate power, and inappropriate statistical interpretation. Aside from the well-known Bonferroni correction, subgroup treatment interaction tests can provide useful information to support the hypothesis. Using data from a previously published randomized trial where a p value of 0.015 was found for the comparison between standard and Hemopatch® groups in (the subgroup of) 135 patients who had hand-sewn pancreatic stump closure we first sought to determine whether there was interaction between the number and proportion of the dependent event of interest (POPF) among the subgroup population (patients with hand-sewn stump closure and use of Hemopatch®), Next, we calculated the relative excess risk due to interaction (RERI) and the “attributable proportion” (AP). The p value of the interaction was p = 0.034, the RERI was – 0.77 (p = 0.0204) (the probability of POPF was 0.77 because of the interaction), the RERI was 13% (patients are 13% less likely to sustain POPF because of the interaction), and the AP was – 0.616 (61.6% of patients who did not develop POPF did so because of the interaction). Although no causality can be implied, Hemopatch® may potentially decrease the POPF after distal pancreatectomy when the stump is closed hand-sewn. The hypothesis generated by our subgroup analysis requires confirmation by a specific, randomized trial, including only patients undergoing hand-sewn closure of the pancreatic stump after distal pancreatectomy.Trial registration: INS-621000-0760.

PMID:38824173 | DOI:10.1038/s41598-024-62896-1

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Nevin Manimala Statistics

A squalene analog 4,4′-diapophytofluene from coconut leaves having antioxidant and anti-senescence potentialities toward human fibroblasts and keratinocytes

Sci Rep. 2024 Jun 1;14(1):12593. doi: 10.1038/s41598-024-63547-1.

ABSTRACT

Coconut (Cocos nucifera) leaves, an unutilized resource, enriched with valuable bioactive compounds. Spectral analysis of purified pentane fraction of coconut leaves revealed the presence of a squalene analog named 4,4′-diapophytofluene or in short 4,4′-DPE (C30H46). Pure squalene standard (PSQ) showed cytotoxicity after 8 µg/ml concentration whereas 4,4′-DPE exhibited no cytotoxic effects up to 16 µg/ml concentration. On senescence-induced WI38 cells, 4,4′-DPE displayed better percentage of cell viability (164.5% at 24 h, 159.4% at 48 h and 148% at 72 h) compared to PSQ and BSQ (bio-source squalene) with same time duration. Similar trend of result was found in HaCaT cells. SA-β-gal assay showed that number of β-galactosidase positive cells were significantly decreased in senescent cells (WI38 and HaCaT) after treated with 4,4′-DPE than PSQ, BSQ. Percentage of ROS was increased to 60% in WI38 cells after olaparib treatment. When PSQ, BSQ and 4,4′-DPE were applied separately on these oxidative-stress-induced cells for 48 h, the overall percentage of ROS was decreased to 39.3%, 45.6% and 19.3% respectively. This 4,4′-DPE was found to be more effective in inhibiting senescence by removing ROS as compared to squalene. Therefore, this 4,4′-DPE would be new potent senotherapeutic agent for pharmaceuticals and dermatological products.

PMID:38824160 | DOI:10.1038/s41598-024-63547-1