Nevin Manimala

Eur J Med Res. 2024 May 12;29(1):282. doi: 10.1186/s40001-024-01855-y.

ABSTRACT

BACKGROUND: Radiation induced acute skin toxicity (AST) is considered as a common side effect of breast radiation therapy. The goal of this study was to design dosiomics-based machine learning (ML) models for prediction of AST, to enable creating optimized treatment plans for high-risk individuals.

METHODS: Dosiomics features extracted using Pyradiomics tool (v3.0.1), along with treatment plan-derived dose volume histograms (DVHs), and patient-specific treatment-related (PTR) data of breast cancer patients were used for modeling. Clinical scoring was done using the Common Terminology Criteria for Adverse Events (CTCAE) V4.0 criteria for skin-specific symptoms. The 52 breast cancer patients were grouped into AST 2 + (CTCAE ≥ 2) and AST 2 – (CTCAE < 2) toxicity grades to facilitate AST modeling. They were randomly divided into training (70%) and testing (30%) cohorts. Multiple prediction models were assessed through multivariate analysis, incorporating different combinations of feature groups (dosiomics, DVH, and PTR) individually and collectively. In total, seven unique combinations, along with seven classification algorithms, were considered after feature selection. The performance of each model was evaluated on the test group using the area under the receiver operating characteristic curve (AUC) and f1-score. Accuracy, precision, and recall of each model were also studied. Statistical analysis involved features differences between AST 2 – and AST 2 + groups and cutoff value calculations.

RESULTS: Results showed that 44% of the patients developed AST 2 + after Tomotherapy. The dosiomics (DOS) model, developed using dosiomics features, exhibited a noteworthy improvement in AUC (up to 0.78), when spatial information is preserved in the dose distribution, compared to DVH features (up to 0.71). Furthermore, a baseline ML model created using only PTR features for comparison with DOS models showed the significance of dosiomics in early AST prediction. By employing the Extra Tree (ET) classifiers, the DOS + DVH + PTR model achieved a statistically significant improved performance in terms of AUC (0.83; 95% CI 0.71-0.90), accuracy (0.70), precision (0.74) and sensitivity (0.72) compared to other models.

CONCLUSIONS: This study confirmed the benefit of dosiomics-based ML in the prediction of AST. However, the combination of dosiomics, DVH, and PTR yields significant improvement in AST prediction. The results of this study provide the opportunity for timely interventions to prevent the occurrence of radiation induced AST.

PMID:38735974 | DOI:10.1186/s40001-024-01855-y

Gut Pathog. 2024 May 12;16(1):27. doi: 10.1186/s13099-024-00616-w.

ABSTRACT

BACKGROUND: Enhancing our understanding of the underlying influences of medical interventions on the microbiome, resistome and mycobiome of preterm born infants holds significant potential for advancing infection prevention and treatment strategies. We conducted a prospective quasi-intervention study to better understand how antibiotics, and probiotics, and other medical factors influence the gut development of preterm infants. A controlled neonatal mice model was conducted in parallel, designed to closely reflect and predict exposures. Preterm infants and neonatal mice were stratified into four groups: antibiotics only, probiotics only, antibiotics followed by probiotics, and none of these interventions. Stool samples from both preterm infants and neonatal mice were collected at varying time points and analyzed by 16 S rRNA amplicon sequencing, ITS amplicon sequencing and whole genome shotgun sequencing.

RESULTS: The human infant microbiomes showed an unexpectedly high degree of heterogeneity. Little impact from medical exposure (antibiotics/probiotics) was observed on the strain patterns, however, Bifidobacterium bifidum was found more abundant after exposure to probiotics, regardless of prior antibiotic administration. Twenty-seven antibiotic resistant genes were identified in the resistome. High intra-variability was evident within the different treatment groups. Lastly, we found significant effects of antibiotics and probiotics on the mycobiome but not on the microbiome and resistome of preterm infants.

CONCLUSIONS: Although our analyses showed transient effects, these results provide positive motivation to continue the research on the effects of medical interventions on the microbiome, resistome and mycobiome of preterm infants.

PMID:38735967 | DOI:10.1186/s13099-024-00616-w

Biomark Res. 2024 May 12;12(1):49. doi: 10.1186/s40364-024-00590-0.

ABSTRACT

Long non-coding RNAs (lncRNAs) are closely implicated in biological processes and diseases with high inflammatory components. These molecules exhibit significant temporal and tissue specificity. However, the expression and function of lncRNAs have not been studied in patients after heart transplantation. Thus, we aimed to identify circulating lncRNAs in these patients and evaluate their diagnostic capacity as potential biomarkers for the non-invasive detection of acute cellular rejection (ACR). For them, we performed a transcriptomic study based on ncRNA-seq technology to detect lncRNAs in serum samples, matched to routine endomyocardial biopsies, from patients without rejection episode (0R, n = 12) and with mild (1R, n = 16) or moderate-severe (≥ 2R, n = 12) ACR. We identified 11,062 circulating lncRNAs in the serum of patients after heart transplantation. Moreover, 6 lncRNAs showed statistically significant expression when the different ACR grades were compared. Among them, AC008105.3, AC006525.1, AC011455.8, AL359220.1, and AC025279.1 had relevant diagnostic capacity for detection of ≥ 2R (AUC of 0.850 to 1.000) and 1R (AUC of 0.750 to 0.854) grades, along with high specificity and positive predictive values (≥ 83%). In addition, AL359220.1 and AC025279.1 were independent predictors for the presence of moderate-severe ACR (odds ratio = 31.132, p < 0.01 and C statistic = 0.939, p < 0.0001; odds ratio = 18.693, p < 0.05 and C statistic = 0.902, p < 0.001; respectively). In conclusion, we describe, for the first time, circulating lncRNAs after heart transplantation as potential candidates for non-invasive detection of ACR. AL359220.1 and AC025279.1 showed excellent diagnostic capability correlating with the severity episode and were strong independent predictors of rejection.

PMID:38735964 | DOI:10.1186/s40364-024-00590-0

Int J Equity Health. 2024 May 13;23(1):97. doi: 10.1186/s12939-024-02183-7.

ABSTRACT

BACKGROUND: Unequal access to primary healthcare (PHC) has become a critical issue in global health inequalities, requiring governments to implement policies tailored to communities’ needs and abilities. However, the place-based facility dimension of PHCs is oversimplified in current healthcare literature, and formulating the equity-oriented PHC spatial planning remains challenging without understanding the multiple impacts of community socio-spatial dynamics, particularly in remote areas. This study aims to push the boundary of PHC studies one step further by presenting a nuanced and dynamic understanding of the impact of community environments on the uneven primary healthcare supply.

METHODS: Focusing on Shuicheng, a remote rural area in southwestern China, multiple data are included in this village-based study, i.e., the facility-level healthcare statistics data (2016-2019), the statistical yearbooks, WorldPop, and Chinese GDP’s spatial distribution data. We evaluate villages’ PHC service capacity using the number of doctors and essential equipment per capita, which are the major components of China’s PHC delivery. The indicators describing community environments are selected based on extant literature and China’s planning paradigms, including town- and village-level factors. Gini coefficients and local spatial autocorrelation analysis are used to present the divergences of PHC capacity, and multilevel regression model and (heterogeneous) difference in difference model are used to examine the driving role of community environments and the dynamics under the policy intervention.

RESULTS: Despite the general improvement, PHC inequalities remain significant in remote rural areas. The village’s location, aging, topography, ethnic autonomy, and economic conditions significantly influence village-level PHC capacity, while demographic characteristics and healthcare delivery at the town level are also important. Although it may improve the hardware setting in village clinics (coef. = 0.350), the recent equity-oriented policy attempts may accelerate the loss of rural doctors (coef. = – 0.517). Notably, the associations between PHC and community environments are affected inconsistently by this round of policy intervention. The town healthcare centers with higher inpatient service capacity (coef. = – 0.514) and more licensed doctors (coef. = – 0.587) and nurses (coef. = – 0.344) may indicate more detrimental policy effects that reduced the number of rural doctors, while the centers with more professional equipment (coef. = 0.504) and nurses (coef. = 0.184) are beneficial for the improvement of hardware setting in clinics.

CONCLUSIONS: The findings suggest that the PHC inequalities are increasingly a result of joint social, economic, and institutional forces in recent years, underlining the increased complexity of the PHC resource allocation mechanism. Therefore, we claim the necessity to incorporate a broader understanding of community orientation in PHC delivery, particularly the interdisciplinary knowledge of the spatial lens of community, to support its sustainable development. Our findings also provide timely policy insights for ongoing primary healthcare reform in China.

PMID:38735959 | DOI:10.1186/s12939-024-02183-7

BMC Nurs. 2024 May 13;23(1):323. doi: 10.1186/s12912-024-01966-1.

ABSTRACT

BACKGROUND: Nurses constitute the largest body of healthcare professionals globally, positioning them at the forefront of enhancing patient safety. Despite their crucial role, there is a notable gap in the literature regarding the comprehension and competency of nursing students in patient safety within Egypt. This gap underscores the urgent need for research to explore how nursing students perceive patient safety and the extent to which these competencies are integrated into their clinical and educational experiences. Understanding these perspectives is essential for developing targeted interventions that can significantly improve patient safety outcomes. The objective of this study was to fill this gap by assessing the perspectives of nursing intern students on patient safety competencies, thereby contributing to the global efforts in enhancing patient safety education and practice.

METHODS: In this research, a cross-sectional study design was employed to investigate the topic at hand. A purposive sample of 266 nursing intern students was enrolled from the Faculty of Nursing at Mansoura University. The data were collected using a patient safety survey. Subsequently, the collected data underwent analysis through the application of descriptive and inferential statistical techniques using SPSS-20 software.

RESULTS: Among the studied intern nursing students, we found that 55.3% and 59.4% of the involved students agreed that they could understand the concept of patient safety and the burden of medical errors. Regarding clinical safety issues, 51.1% and 54.9% of the participating students agreed that they felt confident in what they had learned about identifying patients correctly and avoiding surgical errors, respectively. Concerning error reporting issues, 40.2% and 37.2% of the involved students agreed that they were aware of error reports and enumerated the barriers to incident reporting, respectively. There was a statistically significant difference between the nursing student patient safety overview domain and their age (p = 0.025).

CONCLUSIONS: Our study’s compelling data demonstrated that intern students who took part in the patient safety survey scored higher overall in all patient safety-related categories. However, problems with error reporting showed the lowest percentage. The intern students would benefit from additional educational and training workshops to increase their perspectives on patients’ safety competencies.

PMID:38735958 | DOI:10.1186/s12912-024-01966-1

Malar J. 2024 May 12;23(1):143. doi: 10.1186/s12936-024-04965-4.

ABSTRACT

BACKGROUND: Despite continuous prevention and control strategies in place, malaria remains a major public health problem in sub-Saharan Africa including Ethiopia. Moreover, prevalence of malaria differs in different geographical settings and epidemiological data were inadequate to assure disease status in the study area. This study was aimed to determine the prevalence of malaria and associated risk factors in selected rural kebeles in South Ethiopia.

METHODS: A community-based cross-sectional study was conducted between February to June 2019 in eight malaria-endemic kebeles situated in four zones in South Ethiopia. Mult-stage sampling techniques were employed to select the study zones, districts, kebeles and households. Blood sample were collected from 1674 participants in 345 households by finger prick and smears were examined by microscopy. Sociodemographic data as well as risk factors for Plasmodium infection were collected using questionnaires. Bivariate and multivariate logistic regressions were used to analyse the data.

RESULTS: The overall prevalence of malaria in the study localities was 4.5% (76/1674). The prevalence was varied among the study localities with high prevalence in Bashilo (14.6%; 33/226) followed by Mehal Korga (12.1%; 26/214). Plasmodium falciparum was the dominant parasite accounted for 65.8% (50/76), while Plasmodium vivax accounted 18.4% (14/76). Co-infection of P. falciparum and P. vivax was 15.8% (12/76). Among the three age groups prevalence was 7.8% (27/346) in age less than 5 years and 7.5% (40/531) in 5-14 years. The age groups > 14years were less likely infected with Plasmodium parasite (AOR = 0.14, 95% CI 0.02-0.82) than under five children. Non-febrile individuals 1638 (97.8%) were more likely to had Plasmodium infection (AOR = 28.4, 95% CI 011.4-70.6) than febrile 36 (2.2%). Individuals living proximity to mosquito breeding sites have higher Plasmodium infection (AOR = 6.17, 95% CI 2.66-14.3) than those at distant of breeding sites.

CONCLUSIONS: Malaria remains a public health problem in the study localities. Thus, malaria prevention and control strategies targeting children, non-febrile cases and individuals living proximity to breeding sites are crucial to reduce malaria related morbidity and mortality.

PMID:38735957 | DOI:10.1186/s12936-024-04965-4

J Orthop Surg Res. 2024 May 12;19(1):292. doi: 10.1186/s13018-024-04768-y.

ABSTRACT

BACKGROUND: In this retrospective case investigation, we analysed the data of patients with osteonecrosis of the femoral head (ONFH) to reveal demographic and clinical diagnostic features of ONFH in three northeastern provinces of China and provide a reference for its prevention, diagnosis, and treatment.

METHODS: We collected data from patients in Beijing Orthopaedic Hospital of Liaoning, focusing on the aetiology and diagnosis of ONFH. Medical records and self-designed questionnaires were used to collect information for statistical analysis, including age, aetiology, reason for glucocorticoid use, hospital level at first visit, and diagnosis.

RESULTS: In total, 906 patients with complete medical records were included in the analysis. The mean patient age was 47.65 ± 12.12 years. The peak age distribution was in the 40s for men and the 50s for women. Among the total cohort, 72 patients (7.95%; 40 men and 32 women) had traumatic ONFH, 198 (21.85%; 131 men and 67 women) had steroid-induced ONFH, 230 (25.39%; 121 men and 109 women) had idiopathic ONFH, and 406 (44.81%; 397 men and 9 women) had alcohol-induced ONFH. Six hundred and twenty patients were diagnosed with ONFH at the first visit, while 286 patients were misdiagnosed, with a diagnosis rate of 68.43%. The diagnosis rate at the first visit in tertiary hospitals was 76.14%. The diagnosis rate at the first visit in second-class hospitals was 52.07%.ONFH was most likely to be misdiagnosed as lumbar disc herniation.

CONCLUSIONS: Most patients with ONFH in three northeastern provinces of China were middle-aged, male, and had alcohol-induced ONFH. The misdiagnosis rate of ONFH at the first visit was very high, especially for misdiagnosis of lumbar disc herniation, indicating that the diagnosis of ONFH requires further improvement.

PMID:38735955 | DOI:10.1186/s13018-024-04768-y

BMC Genomics. 2024 May 13;25(1):462. doi: 10.1186/s12864-024-10373-4.

ABSTRACT

BACKGROUND: Detecting epistatic interactions (EIs) involves the exploration of associations among single nucleotide polymorphisms (SNPs) and complex diseases, which is an important task in genome-wide association studies. The EI detection problem is dependent on epistasis models and corresponding optimization methods. Although various models and methods have been proposed to detect EIs, identifying EIs efficiently and accurately is still a challenge.

RESULTS: Here, we propose a linear mixed statistical epistasis model (LMSE) and a spherical evolution approach with a feedback mechanism (named SEEI). The LMSE model expands the existing single epistasis models such as LR-Score, K2-Score, Mutual information, and Gini index. The SEEI includes an adaptive spherical search strategy and population updating strategy, which ensures that the algorithm is not easily trapped in local optima. We analyzed the performances of 8 random disease models, 12 disease models with marginal effects, 30 disease models without marginal effects, and 10 high-order disease models. The 60 simulated disease models and a real breast cancer dataset were used to evaluate eight algorithms (SEEI, EACO, EpiACO, FDHEIW, MP-HS-DHSI, NHSA-DHSC, SNPHarvester, CSE). Three evaluation criteria (pow1, pow2, pow3), a T-test, and a Friedman test were used to compare the performances of these algorithms. The results show that the SEEI algorithm (order 1, averages ranks = 13.125) outperformed the other algorithms in detecting EIs.

CONCLUSIONS: Here, we propose an LMSE model and an evolutionary computing method (SEEI) to solve the optimization problem of the LMSE model. The proposed method performed better than the other seven algorithms tested in its ability to identify EIs in genome-wide association datasets. We identified new SNP-SNP combinations in the real breast cancer dataset and verified the results. Our findings provide new insights for the diagnosis and treatment of breast cancer.

AVAILABILITY AND IMPLEMENTATION: https://github.com/scutdy/SSO/blob/master/SEEI.zip .

PMID:38735952 | DOI:10.1186/s12864-024-10373-4

BMC Oral Health. 2024 May 12;24(1):555. doi: 10.1186/s12903-024-04348-w.

ABSTRACT

OBJECTIVE: This study aimed to evaluate the effect of fence tray matching care (FTMC) in bracket bonding by measuring excess adhesive, as well as linear and angular deviations, and by comparing it with the half-wrapped tray (HWT).

MATERIALS AND METHODS: An intraoral scanner was used to acquire data on the maxillary dental arch of a patient with periodontitis.Furthermore, 20 maxillary dental arch models were 3D printed. Using 3Shape, PlastyCAD software, and 3D printing technology, 10 FTMC (method I) and HWT (method II) were obtained. By preoperative preparation, intraoperative coordination, and postoperative measurement, the brackets were transferred from the trays to the 3D-printed maxillary dental arch models. Additionally, the bracket’s excess adhesive as well as linear and angular deviations were measured, and the differences between the two methods were analyzed.

RESULTS: Excess adhesive was observed in both methods, with FTMC showing less adhesive (P< 0.001), with a statistical difference. Furthermore, HWT’s vertical, tip and torque, which was significantly greater than FTMC (P< 0.05), with no statistical difference among other respects. The study data of incisors, canines, and premolars, showed that the premolars had more adhesive residue and were more likely to have linear and angular deviations.

CONCLUSIONS: The FTMC had higher bracket bonding effect in comparison to HWT, and the adhesive residue, linear and angular deviations are smaller. The fence tray offers an intuitive view of the precise bonding of the bracket, and can remove excess adhesive to prevent white spot lesions via care, providing a different bonding method for clinical applications.

PMID:38735948 | DOI:10.1186/s12903-024-04348-w

Ital J Pediatr. 2024 May 12;50(1):96. doi: 10.1186/s13052-024-01642-9.

ABSTRACT

BACKGROUND: In 1974, the World Health Organization (WHO) established the Expanded Program on Immunization to control vaccine-preventable diseases, saving millions of lives annually. However, the coverage of basic vaccines recommended by the WHO in Africa was only 75%, which fell short of the goal of 90% by 2015. To formulate effective policies and implementation programs to reduce incomplete vaccination rates, it is important to conduct a study to determine the factors contributing to incomplete immunization among children aged 12-23 months.

METHODS: The study was conducted in 16 sub-Saharan African countries, using data extracted from the latest DHS data. It was a community-based cross-sectional survey that used two-stage stratified probability sampling sample designs. The vaccination coverage was assessed using vaccination cards and mother recalls. Multilevel multivariable logistic regression was used to determine the extent of incomplete immunization and the individual and community-level factors associated with partial immunization among children aged 12-23 months. Variables with a p-value less than 0.05 were considered statistically significant predictors of incomplete immunization.

RESULT: A total of 35, 193 weighted samples were used to determine the pooled prevalence of partial immunization. The pooled prevalence of incomplete immunization was 36.06%. In the final model factors significantly associated were: being uneducated mother(AOR:1.75;95%CI:1.48,2.05), being an unemployed mother (AOR:1.16;95%CI:1.09,1.23), no history of family planning utilization (AOR: 1.71; 95% CI: 1.61, 1.84), non-antenatal care (AOR: 1.79; 95% CI: 1.58, 2.04), non-postnatal care (AOR: 1.25; 95%CI: 1.17, 1.35), rural residence(AOR:1.50;95%CI:1.37,1.63), home delivery (AOR: 2.04; 95%CI:1.89, 2.21), having children more than five (AOR: 1.56; 95%CI: 1.13, 2.17), and non-utilization of health insurance (AOR: 1.74; 95%CI: 1.48, 2.05).

CONCLUSION: The pooled prevalence of incomplete immunization was found to be high in this investigation. Based on the findings of the study we recommended that policymakers and stakeholders prioritize enhancing prenatal and postnatal care, contraception, and reducing home birth rates to minimize the rate of incomplete immunization.

PMID:38735946 | DOI:10.1186/s13052-024-01642-9