Category: Statistics

Int Arch Occup Environ Health. 2023 Jan 3. doi: 10.1007/s00420-022-01950-9. Online ahead of print.

ABSTRACT

OBJECTIVE: Despite the continuous development of occupational safety, the prevalence of work-related head injuries is excessive. To promote prevention, we conducted a study evaluating the risks and pathways that precede head injuries in different economic activity sectors.

METHODS: In Finland, more than 90% of employees are covered by inclusive statutory workers’ compensation. We obtained data on occupational head injuries in 2010-2017 from an insurance company database. The European Statistics on Accidents at Work (ESAW) variables represented the characteristics of the accidents and the injury. We analysed the risk factors, contributing events and injury mechanisms in 20 industry sectors, based on the Statistical Classification of Economic Activities in the European Community (NACE).

RESULTS: In the 32,898 cases, the most commonly affected area was the eyes (49.6%). The highest incidence of head injuries was in construction (15.7 per 1000 insurance years). Construction, manufacturing, and human health and social work activities stood out due to their distinctive ESAW category counts. ‘Working with hand-held tools’ [risk ratio (RR) 2.23, 95% confidence interval (CI) 2.14-2.32] in construction and ‘operating machines’ (RR 3.32, 95% CI 3.01-3.66) and ‘working with hand-held tools’ (1.99, 1.91-2.07) in manufacturing predicted head injury. The risk related to parameters of violence and threats in health and social work activities was nearly ninefold the risk of other sectors.

CONCLUSION: The risks and pathways preceding head injuries varied considerably. The highest head injury rates were in construction and manufacturing. Violence emerged as a major risk factor in human health and social work activities.

PMID:36593301 | DOI:10.1007/s00420-022-01950-9

Sci Rep. 2023 Jan 2;13(1):13. doi: 10.1038/s41598-022-27264-x.

ABSTRACT

Risk prediction models are frequently used to identify individuals at risk of developing hypertension. This study evaluates different machine learning algorithms and compares their predictive performance with the conventional Cox proportional hazards (PH) model to predict hypertension incidence using survival data. This study analyzed 18,322 participants on 24 candidate features from the large Alberta’s Tomorrow Project (ATP) to develop different prediction models. To select the top features, we applied five feature selection methods, including two filter-based: a univariate Cox p-value and C-index; two embedded-based: random survival forest and least absolute shrinkage and selection operator (Lasso); and one constraint-based: the statistically equivalent signature (SES). Five machine learning algorithms were developed to predict hypertension incidence: penalized regression Ridge, Lasso, Elastic Net (EN), random survival forest (RSF), and gradient boosting (GB), along with the conventional Cox PH model. The predictive performance of the models was assessed using C-index. The performance of machine learning algorithms was observed, similar to the conventional Cox PH model. Average C-indexes were 0.78, 0.78, 0.78, 0.76, 0.76, and 0.77 for Ridge, Lasso, EN, RSF, GB and Cox PH, respectively. Important features associated with each model were also presented. Our study findings demonstrate little predictive performance difference between machine learning algorithms and the conventional Cox PH regression model in predicting hypertension incidence. In a moderate dataset with a reasonable number of features, conventional regression-based models perform similar to machine learning algorithms with good predictive accuracy.

PMID:36593280 | DOI:10.1038/s41598-022-27264-x

Pediatr Radiol. 2023 Jan 3. doi: 10.1007/s00247-022-05572-8. Online ahead of print.

ABSTRACT

BACKGROUND: Masking and social distancing to mitigate the spread of the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus curbed the spread of other viruses. Given a potential link between viral illnesses and ileocolic intussusception, the purpose of this study is to characterize trends in incidence, diagnosis and management of pediatric intussusception in the United States in the context of the coronavirus disease 2019 (COVID-19) pandemic.

MATERIALS AND METHODS: This cross-sectional retrospective study used the Pediatric Hospital Information System and included children (ages 0-17 years) with a primary diagnosis of intussusception (ICD-10 [International Classification of Diseases, Tenth Revision]: K56.1) from January 2018 to December 2021. Descriptive statistics and chi-square analyses were used to characterize and compare proportions pre-COVID (2018 and 2019) to 2020 and 2021.

RESULTS: Eight thousand one hundred forty-three encounters met inclusion criteria. Intussusception diagnoses declined in 2020 (n = 1,480) compared to 2019 (n = 2,321) and 2018 (n = 2,171) but returned to pre-COVID levels in 2021 (n = 2,171). Patient age was similar across years (mean age in years: 2018: 2.3; 2019: 2.1; 2020: 2.3; 2021: 2.3). There was no significant change in the proportion of patients who underwent imaging in 2020 (96% [1,415/1,480]) compared to the other years in the study (2018: 96% [2,093/2,171], P = 0.21; 2019: 97% [2,253/2,321], P = 0.80; 2021: 96% [1,415/1,480], P = 0.85). There was a statistically significant but minimal increase in the proportion of cases treated with surgery in 2020 compared to 2019 (2020: 17.8% vs. 2019: 15%, P = 0.02); however, this was not replicated in the pairwise comparison of 2020 to 2018 (2020: 17.8% vs. 2018: 16.4%, P = 0.23). There was a statistically significant increase in the proportion of cases treated with surgery in 2020 compared to 2021 (2020: 17.8% vs. 2021: 14%, P = 0.001).

CONCLUSION: Pediatric intussusception diagnoses decreased at a national level in 2020 compared to previous years, with a rebound increase in 2021. This may reflect a secondary benefit of public health interventions imposed to curb the spread of COVID-19.

PMID:36593279 | DOI:10.1007/s00247-022-05572-8

Sci Rep. 2023 Jan 2;13(1):29. doi: 10.1038/s41598-022-26956-8.

ABSTRACT

Coxiella burnetii (Cb) is a hardy, stealth bacterial pathogen lethal for humans and animals. Its tremendous resistance to the environment, ease of propagation, and incredibly low infectious dosage make it an attractive organism for biowarfare. Current research on the classification of Coxiella and features influencing its presence in the soil is generally confined to statistical techniques. Machine learning other than traditional approaches can help us better predict epidemiological modeling for this soil-based pathogen of public significance. We developed a two-phase feature-ranking technique for the pathogen on a new soil feature dataset. The feature ranking applies methods such as ReliefF (RLF), OneR (ONR), and correlation (CR) for the first phase and a combination of techniques utilizing weighted scores to determine the final soil attribute ranks in the second phase. Different classification methods such as Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), Logistic Regression (LR), and Multi-Layer Perceptron (MLP) have been utilized for the classification of soil attribute dataset for Coxiella positive and negative soils. The feature-ranking methods established that potassium, chromium, cadmium, nitrogen, organic matter, and soluble salts are the most significant attributes. At the same time, manganese, clay, phosphorous, copper, and lead are the least contributing soil features for the prevalence of the bacteria. However, potassium is the most influential feature, and manganese is the least significant soil feature. The attribute ranking using RLF generates the most promising results among the ranking methods by generating an accuracy of 80.85% for MLP, 79.79% for LR, and 79.8% for LDA. Overall, SVM and MLP are the best-performing classifiers, where SVM yields an accuracy of 82.98% and 81.91% for attribute ranking by CR and RLF; and MLP generates an accuracy of 76.60% for ONR. Thus, machine models can help us better understand the environment, assisting in the prevalence of bacteria and decreasing the chances of false classification. Subsequently, this can assist in controlling epidemics and alleviating the devastating effect on the socio-economics of society.

PMID:36593267 | DOI:10.1038/s41598-022-26956-8

Sci Rep. 2023 Jan 2;13(1):51. doi: 10.1038/s41598-022-26642-9.

ABSTRACT

The bacterial nanocellulose has been used in a wide range of biomedical applications including carriers for drug delivery, blood vessels, artificial skin and wound dressing. The total of ten morphologically different bacterial strains were screened for their potential to produce bacterial nanocellulose (BNC). Among these isolates, Bacillus sp. strain SEE-3 exhibited potent ability to produce the bacterial nanocellulose. The crystallinity, particle size and morphology of the purified biosynthesized nanocellulose were characterized. The cellulose nanofibers possess a negatively charged surface of – 14.7 mV. The SEM images of the bacterial nanocellulose confirms the formation of fiber-shaped particles with diameters of 20.12‒47.36 nm. The TEM images show needle-shaped particles with diameters of 30‒40 nm and lengths of 560‒1400 nm. X-ray diffraction show that the obtained bacterial nanocellulose has crystallinity degree value of 79.58%. FTIR spectra revealed the characteristic bands of the cellulose crystalline structure. The thermogravimetric analysis revealed high thermal stability. Optimization of the bacterial nanocellulose production was achieved using Plackett-Burman and face centered central composite designs. Using the desirability function, the optimum conditions for maximum bacterial nanocellulose production was determined theoretically and verified experimentally. Maximum BNC production (20.31 g/L) by Bacillus sp. strain SEE-3 was obtained using medium volume; 100 mL/250 mL conical flask, inoculum size; 5%, v/v, citric acid; 1.5 g/L, yeast extract; 5 g/L, temperature; 37 °C, Na₂HPO₄; 3 g/L, an initial pH level of 5, Cantaloupe juice concentration of 81.27 percent and peptone 11.22 g/L.

PMID:36593253 | DOI:10.1038/s41598-022-26642-9

Sci Rep. 2023 Jan 2;13(1):9. doi: 10.1038/s41598-022-26213-y.

ABSTRACT

Accurate tide level prediction is crucial to human activities in coastal areas. Many practical applications show that compared with traditional harmonic analysis, long short-term memory (LSTM), gated recurrent units (GRUs) and other neural networks, along with ensemble learning models, such as light gradient boosting machine (LightGBM) and eXtreme gradient boosting (XGBoost), can achieve extremely high prediction accuracy in relatively stationary time series. Therefore, this paper proposes a variable weight combination model based on LightGBM and CNN-BiGRU with relevant research. It uses the variable weight combination method to weight and synthesize the prediction results of the two base models so that the combination model has a stronger ability to capture time series features and fits the data well. The experimental results show that in contrast to the base model LightGBM, the RMSE value and MAE value of the combination model are reduced by 43.2% and 44.7%, respectively; in contrast to the base model CNN-BiGRU, the RMSE value and MAE value of the combination model are reduced by 35.3% and 39.1%, respectively. This means that the variable weight combination model can greatly improve the accuracy of tide level prediction. In addition, we use tidal data from different geographical environments to further verify the good universality of the model. This study provides a new idea and method for tide prediction.

PMID:36593233 | DOI:10.1038/s41598-022-26213-y

Clin Lymphoma Myeloma Leuk. 2022 Dec 17:S2152-2650(22)01772-4. doi: 10.1016/j.clml.2022.12.009. Online ahead of print.

ABSTRACT

OBJECTIVE: The aim was to evaluate the efficacy and safety of blinatumomab monotherapy for the treatment of relapsed/refractory acute lymphoblastic leukemia (R/R B-ALL).

METHODS: PubMed, Embase, Web of Science, and Cochrane Library were searched to collect clinical studies related to blinatumomab. The primary outcome measures were complete remission (CR), and minimal residual disease (MRD) response. Prognostic indicators included overall survival (OS) and relapse-free survival time (RFS). Grade ≥3 adverse reactions were mainly analyzed for safety, including cytokine release syndrome (CRS), neurological events and hematological toxicity. The heterogeneity was quantified by I² statistic, which reflected the proportion of the true heterogeneity to the variance of the total effect size. Studies were considered heterogeneous if the I² statistic was greater than 50%, and conversely, studies were homogeneous.

RESULTS: A total of 18 studies involving 1,373 patients were included. The analysis results showed a CR rate of 54% (95%CI:44%-64%) and an MRD response rate of 43% (95%CI:34%-51%). The CR rate was higher in patients with bone marrow (BM) blast <50% than in patients with BM blast ≥50% (71% vs. 34%). The median OS and RFS were 8.16 months (95%CI:6.64-9.69) and 6.02 months (95%CI:4.63-7.41), respectively. For safety analysis, the incidence of grade ≥3 adverse events (AEs) was 80% (95%CI:72%-88%), the incidence of grade ≥3 neurological toxicity was 7% (95%CI:4%-11%), and the incidence of grade ≥3 CRS was 3% (95%CI:2%-5%). However, the mixture of retrospective and prospective studies led to heterogeneity to some extent in this meta-analysis.

CONCLUSION: Blinatumomab is effective in the treatment of R/R B-ALL with a controlled occurrence of AEs and a reliable safety profile.

PMID:36593170 | DOI:10.1016/j.clml.2022.12.009

Vasc Endovascular Surg. 2023 Jan 2:15385744221150737. doi: 10.1177/15385744221150737. Online ahead of print.

ABSTRACT

OBJECTIVE: Limb salvage is an important concern following complete oncologic resection for extremity soft tissue sarcoma (STS). Vascular reconstruction is essential for limb salvage. The purpose of this study was to evaluate the outcomes of vascular reconstruction in patients with extremity STS.

METHODS: This is a retrospective, multi-center, case series of consecutive patients who underwent vascular reconstruction during extremity STS resection at 2 major centers in Korea. Demographics, reconstruction methods, type of conduit, surgical complications, graft patency, limb salvage rate, and patient survival were reviewed.

RESULTS: From March 2005 to December 2020, 43 patients underwent vascular reconstructions during STS resection. Among the patients, 22 (51.2%) received arterial only, and 21 (48.8%) received simultaneous arterial and venous reconstructions. For the types of conduits, autologous saphenous veins (56.2%), artificial grafts (26.3%), and cryopreserved allografts (15.8%) were used. During a median follow-up of 23.8 months (interquartile range; 7.7-54.5), the overall primary patency of the reconstructed vessels was significantly higher in arteries than in veins (82.5% vs 56.3% at 12 months, P < .001). According to the type of conduit, the primary patency rate of autogenous vein seemed higher in venous reconstruction, however, there was no statistical significance in both arterial and venous reconstruction. There was no significant difference in primary arterial patency rate (P = .132) or incidence of surgical complications including postoperative edema or wound problem whether or not simultaneous venous reconstruction was performed with arterial reconstruction. The overall limb salvage rate and patient survival were 97.4%, 95.1%, and 89.4% and 91.9%, 81.7%, and 65.4% at 12, 24, and 36 months, respectively.

CONCLUSIONS: Patency rates were poorer in venous reconstruction than in arterial reconstruction. In terms of arterial patency and postoperative complication, the role of simultaneous arterial and venous reconstruction seems not essential, however, it needs to be evaluated in future studies.

PMID:36592476 | DOI:10.1177/15385744221150737

Physiol Res. 2022 Dec 27;71(Suppl 1):S107-S113.

ABSTRACT

Arterial branches to the uterus and ovaries that pass through the mesosalpinx contribute significantly to the maintenance of the ovarian reserve. Especially arterial supply of the uterine tube is provided by a number of anastomoses between both the uterine and ovarian vessels. Knowledge on the morphologic peculiarities will allow to identify main contributors especially blood flow ultrasound examination for the purpose of ovary preserving surgery. This study aimed at identifying landmarks especially for so-called low-flow tubal vessels. Arteries of 17 female Thiel-embalmed bodies were studied along three preselected paramedian segments and measurements taken. A section was made through the center of the ovary perpendicular to uterine tube, then the mesosalpinx tissue distance was divided into 3 equivalent zones: upper, middle and lower thirds. The surface area of the mesosalpinx averaged 1088 ± 62 mm2. 47.7 ± 7.1 % of the mesosalpinx zones included macroscopically visible vessels. The lower third segment of mesosalpinx was the thickest averaging 2.4 ± 1.5 mm. One to three tubal branches were identified in the middle third of the mesosalpinx. Arterial anastomoses were found in the upper segment of the mesosalpinx, but no presence of a marginal vessel supplying the fallopian tube could be found. Statistically significant moderate positive correlations were established between the diameters of the mesosalpingeal arteries between the three zones. The mesosalpinx, uterine tube and the ovary form areas of segmental blood supply. Variants of tubal vessels appear to be a sparse source of blood supply.

PMID:36592446

Physiol Res. 2022 Dec 27;71(Suppl 1):S99-S105.

ABSTRACT

Infertility affects approximately 48 million couples globally. Despite the enormous progress of the methods of reproductive medicine that has been made since the first test-tube baby was born in 1978, the implantation rate of day-3 embryos is only around 15-20 % and 30 % of day-5 embryos. Numerous strategies aim to improve implantation rates and prevent repeated implantation failure, however there is no specific general recommendation leading to satisfying results. One of the many risk factors relevant in this regard is the uterine immunological make-up, mainly the uterine Natural Killer (uNK) cells. They orchestrate the overall immune response during implantation by influencing trophoblast invasion and vascular remodeling and throughout pregnancy, uNK cells are also the main immune cells at the maternal-foetal interface. Previously, uNK count has been correlated with various fertility issues including idiopathic reccurent miscarriage. The present study used endometrial samples collected from 256 patients with recurrent implantation failure (RIF), habitual abortion (HA) and idiopathic sterility. Samples were collected between day 19 and 21 of the menstrual cycle mainly by Pipelle endometrial sampling. The samples were fixed in formalin for 24 hours and further processed for immunohistochemistry using anti-CD56 to visualize this antigen marker of uNK cells. Immunohistochemical counting was performed to assess the low, normal, or elevated count of uNK cells. According to the one-way ANOVA test, the age of our patients did not have any influence on the count of uNK cells. With Spearman correlation analysis, we found statistically significant correlation (p-value 0.05) of -0.133 between prior miscarriage and lower uNK cell count. Using the same analysis we found statistically significant correlation (correlation 0.233 with p-value 0.01) between number of uNK cells and activation status. Patients with higher uNK cells were more frequenty diagnosed with endometriosis (p-value 0.05, correlation 0.130). Patients with an immunological factor of sterility (defined by a clinical immunologist) had a lower chance of gravidity (-0.203 with p-value 0.01). Based on our results, we can confirm that there is a correlation between RIF, HA, idiopathic sterility, endometriosis, and immunological factor of sterility (uNK cell count). The true predictive value with regard to fertility outcomes needs to be addressed in future research.

PMID:36592445