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The Pan African Medical Journal 2024the provision of essential preconception care services for HIV-positive pregnant women is crucial to prevent HIV transmission to infants. This includes pregnancy...
INTRODUCTION
the provision of essential preconception care services for HIV-positive pregnant women is crucial to prevent HIV transmission to infants. This includes pregnancy intention screening services, adequate viral load monitoring and suppression before conception, and necessary nutritional support. In Nyeri County, the prevalence of Mother-to-Child Transmission (MTCT) of HIV is 5.3%, which is higher than the global threshold of 5%. This study aims to evaluate the impact of pre-conception care services in preventing HIV transmission to infants in Nyeri County. The study objectives are to assess the utilization of pre-conception care services among HIV-positive women, specifically focusing on pregnancy intention screening, viral load monitoring and suppression, and access to nutritional assessment services before pregnancy. Additionally, the study aims to investigate the relationship between the provision of pre-conception care services and infant HIV outcomes.
METHODS
this cross-sectional retrospective descriptive study employed stratified sampling to select eight level 4 and level 5 hospitals in Nyeri County. The target population consisted of HIV-infected women seeking postnatal care in these facilities, with a sample size of 252 women who had HIV-exposed infants under two years old and were receiving post-natal care at the respective hospitals. Sociodemographic characteristics, including age, marital status, and education level, were collected. Data analysis involved both descriptive and inferential statistics.
RESULTS
our findings revealed that only 34.2% of HIV-positive women seeking postnatal care had received information or services related to pregnancy intention screening, a crucial aspect of pre-conception care. Almost half (46.4%) of the women who participated in the study had undergone viral load measurements before pregnancy, which is another critical component of preconception care. Additionally, 85.6% of these women had received nutritional services during pregnancy from their healthcare providers. Interestingly, all women who received any pre-conception care services reported that their infants were alive and tested HIV-negative.
CONCLUSION
preconception care is crucial in preventing mother-to-child transmission of HIV. Efforts should be made to ensure that all HIV-infected women planning to conceive have access to preconception care services.
Topics: Humans; Infectious Disease Transmission, Vertical; Female; HIV Infections; Pregnancy; Adult; Pregnancy Complications, Infectious; Preconception Care; Cross-Sectional Studies; Retrospective Studies; Young Adult; Viral Load; Infant, Newborn; Infant; Mass Screening; Adolescent; Postnatal Care; Prevalence; Pregnancy Outcome
PubMed: 38933429
DOI: 10.11604/pamj.2024.47.144.37196 -
Health Science Reports Jun 2024Lung cancer is ranked as the second most prevalent form of cancer worldwide. Nonsmall cell lung cancer (NSCLC) represents the predominant histological subtype. Research...
BACKGROUND AND AIMS
Lung cancer is ranked as the second most prevalent form of cancer worldwide. Nonsmall cell lung cancer (NSCLC) represents the predominant histological subtype. Research suggests that one-third of lung cancer patients also experiencing depression. Antidepressants play an indispensable role in the management of NSCLC. Despite significant advancements in treatment, lung cancer patients still face a high mortality rate. Major depressive disorder (MDD) and related antidepressants involved in treatment efficacy and prognosis of NSCLC. However, there has been a lack of screening and analysis regarding genes and networks associated with both NSCLC and MDD.
METHODS
To investigate the correlation between MDD and NSCLC, our discovery and validation analysis included four datasets from the Gene Expression Omnibus database from NSCLC or MDD. Differential gene expression (DEGs) analysis, GO and KEGG Pathway, and protein-protein interaction network analyzes to identify hub genes, networks, and associated observations link between MDD and NSCLC.
RESULTS
The analysis of two datasets yielded a total of 84 downregulated and 52 upregulated DEGs. Pathway enrichment analyzes indicated that co-upregulated genes were enriched in the regulation of positive regulation of cellular development, collagen-containing extracellular matrix (ECM), cytokine binding, and axon guidance. We identified 20 key genes, which were further analyzed using the MCODE plugin to identify two core subnetworks. The integration of functionally similar genes provided valuable insights into the potential involvement of these hub genes in diverse biological processes including angiogenesis humoral immune response regulation inflammatory response organization ECM network.
CONCLUSION
We have identified a total of 136 DEGs that participate in multiple biological signaling pathways. A total of 20 hub genes have demonstrated robust associations, potentially indicating novel diagnostic and therapeutic targets for both diseases.
PubMed: 38933422
DOI: 10.1002/hsr2.2167 -
OncoTargets and Therapy 2024To establish a modified nomogram model for pancreatic neuroendocrine carcinoma (pNEC) patients with liver metastasis via single-center clinical data, and to provide...
OBJECTIVE
To establish a modified nomogram model for pancreatic neuroendocrine carcinoma (pNEC) patients with liver metastasis via single-center clinical data, and to provide guidelines for improving the diagnosis and treatment of patients.
METHODS
A retrospective analysis of clinical data from pNEC patients with liver metastasis at Peking Union Medical College Hospital (January 2000 to November 2023) was conducted. Univariate and multivariate Cox regression analyses were employed to identify prognostic factors for overall survival (OS). Kaplan-Meier curves were generated, and a modified nomogram predictive model was developed to illustrate the prognosis of pNEC patients with liver metastasis. Calibration plots and C-index were used to validate the model's feasibility, accuracy, and reliability.
RESULTS
Forty-five participants with the rare cancer type pNEC and liver metastasis were included in the study. Kaplan-Meier curves revealed that primary tumor resection (PTR), chemotherapy or targeted therapy, and tumor size equal to or less than 5cm significantly improved OS compared to those without PTR, chemotherapy or targeted therapy, and tumor size larger than 5cm. Multivariate Cox regression analysis identified PTR, a combination of chemotherapy and targeted therapy, and tumor size as independent prognostic factors for OS. The predictive nomogram model exhibited acceptable performance with a C-index of 0.744 (0.639-0.805) through bootstrapping.
CONCLUSION
Combining chemotherapy with targeted therapy enhances the survival of pNEC patients with liver metastasis. The modified nomogram model and predictive score table offer valuable references and insights for both clinicians and patients.
PubMed: 38933411
DOI: 10.2147/OTT.S466213 -
Case Reports in Dentistry 2024Bone resorption following tooth loss might compromise retention, stability, and support of conventional removable prostheses, and for this reason, implant-supported...
Bone resorption following tooth loss might compromise retention, stability, and support of conventional removable prostheses, and for this reason, implant-supported overdentures are suggested as a viable alternative for completely edentulous patients. Bars, telescopic attachments, or stud attachments have been used to provide retention through a different mechanism of action based on specific design characteristics. The purpose of this report is to thoroughly describe the applied protocol for the fabrication of an implant overdenture supported by two bars incorporating stud attachments. A 67-year-old male patient presented to the Postgraduate Clinic of the National and Kapodistrian University in Athens seeking dental rehabilitation. The remaining teeth were characterized with poor prognosis, mainly due to their periodontal status. The proposed treatment plan included the placement of four implants in the maxilla and two implants in the mandible and the fabrication of implant-supported overdentures. The diagnostic stages revealed adequate prosthetic space that would enable the fabrication of a bar substructure for the maxillary overdenture. To combine the benefits of bars and stud attachments, two bars with four attachments were fabricated. Evaluation of the delivered prosthesis revealed adequate retention, support, and stability achieved with minimal palatal coverage. Patient's reported satisfaction and quality of life were increased. Recall appointments at one, six, and twelve months did not reveal any adverse effects or patient's complaints. According to the present case report, different types of attachments may be used after careful study of each case. More studies are needed to report on different aspects of the chosen treatment plan.
PubMed: 38933360
DOI: 10.1155/2024/2818034 -
Frontiers in Cell and Developmental... 2024
PubMed: 38933331
DOI: 10.3389/fcell.2024.1439921 -
Frontiers in Neurology 2024Acute Ischemic Stroke (AIS) remains a leading cause of mortality and disability worldwide. Rapid and precise prognostication of AIS is crucial for optimizing treatment...
BACKGROUND
Acute Ischemic Stroke (AIS) remains a leading cause of mortality and disability worldwide. Rapid and precise prognostication of AIS is crucial for optimizing treatment strategies and improving patient outcomes. This study explores the integration of machine learning-derived radiomics signatures from multi-parametric MRI with clinical factors to forecast AIS prognosis.
OBJECTIVE
To develop and validate a nomogram that combines a multi-MRI radiomics signature with clinical factors for predicting the prognosis of AIS.
METHODS
This retrospective study involved 506 AIS patients from two centers, divided into training (n = 277) and validation ( = 229) cohorts. 4,682 radiomic features were extracted from T1-weighted, T2-weighted, and diffusion-weighted imaging. Logistic regression analysis identified significant clinical risk factors, which, alongside radiomics features, were used to construct a predictive clinical-radiomics nomogram. The model's predictive accuracy was evaluated using calibration and ROC curves, focusing on distinguishing between favorable (mRS ≤ 2) and unfavorable (mRS > 2) outcomes.
RESULTS
Key findings highlight coronary heart disease, platelet-to-lymphocyte ratio, uric acid, glucose levels, homocysteine, and radiomics features as independent predictors of AIS outcomes. The clinical-radiomics model achieved a ROC-AUC of 0.940 (95% CI: 0.912-0.969) in the training set and 0.854 (95% CI: 0.781-0.926) in the validation set, underscoring its predictive reliability and clinical utility.
CONCLUSION
The study underscores the efficacy of the clinical-radiomics model in forecasting AIS prognosis, showcasing the pivotal role of artificial intelligence in fostering personalized treatment plans and enhancing patient care. This innovative approach promises to revolutionize AIS management, offering a significant leap toward more individualized and effective healthcare solutions.
PubMed: 38933326
DOI: 10.3389/fneur.2024.1379031 -
Frontiers in Immunology 2024To investigate the prediction of pathologic complete response (pCR) in patients with non-small cell lung cancer (NSCLC) undergoing neoadjuvant immunochemotherapy (NAIC)...
OBJECTIVES
To investigate the prediction of pathologic complete response (pCR) in patients with non-small cell lung cancer (NSCLC) undergoing neoadjuvant immunochemotherapy (NAIC) using quantification of intratumoral heterogeneity from pre-treatment CT image.
METHODS
This retrospective study included 178 patients with NSCLC who underwent NAIC at 4 different centers. The training set comprised 108 patients from center A, while the external validation set consisted of 70 patients from center B, center C, and center D. The traditional radiomics model was contrasted using radiomics features. The radiomics features of each pixel within the tumor region of interest (ROI) were extracted. The optimal division of tumor subregions was determined using the K-means unsupervised clustering method. The internal tumor heterogeneity habitat model was developed using the habitats features from each tumor sub-region. The LR algorithm was employed in this study to construct a machine learning prediction model. The diagnostic performance of the model was evaluated using criteria such as area under the receiver operating characteristic curve (AUC), accuracy, specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV).
RESULTS
In the training cohort, the traditional radiomics model achieved an AUC of 0.778 [95% confidence interval (CI): 0.688-0.868], while the tumor internal heterogeneity habitat model achieved an AUC of 0.861 (95% CI: 0.789-0.932). The tumor internal heterogeneity habitat model exhibits a higher AUC value. It demonstrates an accuracy of 0.815, surpassing the accuracy of 0.685 achieved by traditional radiomics models. In the external validation cohort, the AUC values of the two models were 0.723 (CI: 0.591-0.855) and 0.781 (95% CI: 0.673-0.889), respectively. The habitat model continues to exhibit higher AUC values. In terms of accuracy evaluation, the tumor heterogeneity habitat model outperforms the traditional radiomics model, achieving a score of 0.743 compared to 0.686.
CONCLUSION
The quantitative analysis of intratumoral heterogeneity using CT to predict pCR in NSCLC patients undergoing NAIC holds the potential to inform clinical decision-making for resectable NSCLC patients, prevent overtreatment, and enable personalized and precise cancer management.
Topics: Humans; Carcinoma, Non-Small-Cell Lung; Lung Neoplasms; Male; Female; Neoadjuvant Therapy; Middle Aged; Retrospective Studies; Aged; Tomography, X-Ray Computed; Treatment Outcome; Machine Learning; Immunotherapy; Adult; Pathologic Complete Response
PubMed: 38933281
DOI: 10.3389/fimmu.2024.1414954 -
Frontiers in Immunology 2024Extracellular particles (EPs), particularly extracellular vesicles, play a crucial role in regulating various pathological mechanisms, including immune dysregulations...
BACKGROUND
Extracellular particles (EPs), particularly extracellular vesicles, play a crucial role in regulating various pathological mechanisms, including immune dysregulations post-trauma. Their distinctive expression of cell-specific markers and regulatory cargo such as cytokines or micro-ribonucleic acid suggests their potential as early biomarkers for organ-specific damage and for identifying patients at risk for complications and mortality. Given the critical need for reliable and easily assessable makers to identify at-risk patients and guide therapeutic decisions, we evaluated the early diagnostic value of circulating EPs regarding outcomes in severely injured multiple-trauma patients.
METHODS
Plasma samples were collected from 133 severely injured trauma patients (Injury Severity Score (ISS) ≥16) immediately upon arrival at the emergency department (ED). Patients were categorized into survivors and non-survivors. Injury characteristics and outcomes related to sepsis, pneumonia, or early (<1 day after admission) and late mortality were assessed. Circulating EPs, cytokine profiles, and blood counts of platelets and leukocytes were determined. Receiver operating characteristic analyses were conducted.
RESULTS
Despite no significant differences in injury pattern or severity, non-survivors exhibited significantly elevated counts of circulating EPs compared to survivors. The optimal cut-off for EPs <200 nm indicating non-survivors was 17380/µl plasma, with a sensitivity of 77% and a specificity of 61% in predicting in-hospital mortality. Later non-survivors received significantly higher numbers of units of packed red blood cells [8.54 ± 5.45 vs. 1.29 ± 0.36 units], had higher serum lactate [38.00 ± 7.51 vs. 26.98 ± 1.58 mg/dL], significantly lower platelet counts [181.30 ± 18.06 vs. 213.60 ± 5.85 *10³/µL] and lower heart rates [74.50 ± 4.93 vs. 90.18 ± 2.06 beats/minute] upon arrival at the ED compared to survivors.
CONCLUSION
Our results demonstrate the high diagnostic potential of elevated concentrations of circulating EPs <200 nm for identifying patients at risk of mortality after severe trauma. This parameter shows comparable sensitivity to established clinical predictors. Early evaluation of EPs concentration could complement assessment markers in guiding early therapeutic decisions.
Topics: Humans; Male; Female; Middle Aged; Adult; Hospital Mortality; Biomarkers; Extracellular Vesicles; Injury Severity Score; Aged; Wounds and Injuries; Prognosis; Cytokines; Multiple Trauma; ROC Curve
PubMed: 38933277
DOI: 10.3389/fimmu.2024.1390380 -
Frontiers in Immunology 2024This study seeks to enhance the accuracy and efficiency of clinical diagnosis and therapeutic decision-making in hepatocellular carcinoma (HCC), as well as to optimize...
BACKGROUND
This study seeks to enhance the accuracy and efficiency of clinical diagnosis and therapeutic decision-making in hepatocellular carcinoma (HCC), as well as to optimize the assessment of immunotherapy response.
METHODS
A training set comprising 305 HCC cases was obtained from The Cancer Genome Atlas (TCGA) database. Initially, a screening process was undertaken to identify prognostically significant immune-related genes (IRGs), followed by the application of logistic regression and least absolute shrinkage and selection operator (LASSO) regression methods for gene modeling. Subsequently, the final model was constructed using support vector machines-recursive feature elimination (SVM-RFE). Following model evaluation, quantitative polymerase chain reaction (qPCR) was employed to examine the gene expression profiles in tissue samples obtained from our cohort of 54 patients with HCC and an independent cohort of 231 patients, and the prognostic relevance of the model was substantiated. Thereafter, the association of the model with the immune responses was examined, and its predictive value regarding the efficacy of immunotherapy was corroborated through studies involving three cohorts undergoing immunotherapy. Finally, the study uncovered the potential mechanism by which the model contributed to prognosticating HCC outcomes and assessing immunotherapy effectiveness.
RESULTS
SVM-RFE modeling was applied to develop an OS prognostic model based on six IRGs (CMTM7, HDAC1, HRAS, PSMD1, RAET1E, and TXLNA). The performance of the model was assessed by AUC values on the ROC curves, resulting in values of 0.83, 0.73, and 0.75 for the predictions at 1, 3, and 5 years, respectively. A marked difference in OS outcomes was noted when comparing the high-risk group (HRG) with the low-risk group (LRG), as demonstrated in both the initial training set (0.0001) and the subsequent validation cohort (0.0001). Additionally, the SVMRS in the HRG demonstrated a notable positive correlation with key immune checkpoint genes (CTLA-4, PD-1, and PD-L1). The results obtained from the examination of three cohorts undergoing immunotherapy affirmed the potential capability of this model in predicting immunotherapy effectiveness.
CONCLUSIONS
The HCC predictive model developed in this study, comprising six genes, demonstrates a robust capability to predict the OS of patients with HCC and immunotherapy effectiveness in tumor management.
Topics: Humans; Carcinoma, Hepatocellular; Liver Neoplasms; Immunotherapy; Prognosis; Biomarkers, Tumor; Male; Female; Transcriptome; Middle Aged; Gene Expression Regulation, Neoplastic; Gene Expression Profiling; Support Vector Machine; Treatment Outcome
PubMed: 38933262
DOI: 10.3389/fimmu.2024.1371829 -
Frontiers in Immunology 2024Programmed cell death protein-1 (PD-1) inhibitor-based therapy has demonstrated promising results in metastatic gastric cancer (MGC). However, the previous researches...
OBJECTIVE
Programmed cell death protein-1 (PD-1) inhibitor-based therapy has demonstrated promising results in metastatic gastric cancer (MGC). However, the previous researches are mostly clinical trials and have reached various conclusions. Our objective is to investigate the efficacy of PD-1 inhibitor-based treatment as first-line therapy for MGC, utilizing real-world data from China, and further analyze predictive biomarkers for efficacy.
METHODS
This retrospective study comprised 105 patients diagnosed with MGC who underwent various PD-1 inhibitor-based treatments as first-line therapy at West China Hospital of Sichuan University from January 2018 to December 2022. Patient characteristics, treatment regimens, and tumor responses were extracted. We also conducted univariate and multivariate analyses to assess the relationship between clinical features and treatment outcomes. Additionally, we evaluated the predictive efficacy of several commonly used biomarkers for PD-1 inhibitor treatments.
RESULTS
Overall, after 28.0 months of follow-up among the 105 patients included in our study, the objective response rate (ORR) was 30.5%, and the disease control rate (DCR) was 89.5% post-treatment, with two individuals (1.9%) achieving complete response (CR). The median progression-free survival (mPFS) was 9.0 months, and the median overall survival (mOS) was 22.0 months. According to both univariate and multivariate analyses, favorable OS was associated with patients having Eastern Cooperative Oncology Group performance status (ECOG PS) of 0-1. Additionally, normal baseline levels of carcinoembryonic antigen (CEA), as well as the combination of PD-1 inhibitors with chemotherapy and trastuzumab in patients with human epidermal growth factor receptor 2 (HER2)-positive MGC, independently predicted longer PFS and OS. However, microsatellite instability/mismatch repair (MSI/MMR) status and Epstein-Barr virus (EBV) infection status were not significantly correlated with PFS or OS extension.
CONCLUSION
As the first-line treatment, PD-1 inhibitors, either as monotherapy or in combination therapy, are promising to prolong survival for patients with metastatic gastric cancer. Additionally, baseline level of CEA is a potential predictive biomarker for identifying patients mostly responsive to PD-1 inhibitors.
Topics: Humans; Stomach Neoplasms; Male; Female; Retrospective Studies; Middle Aged; Aged; Immune Checkpoint Inhibitors; Programmed Cell Death 1 Receptor; Adult; China; Biomarkers, Tumor; Treatment Outcome; Neoplasm Metastasis; Antineoplastic Combined Chemotherapy Protocols; East Asian People
PubMed: 38933261
DOI: 10.3389/fimmu.2024.1370860