Tag: pubmed

BMC Pediatr. 2024 Dec 6;24(1):801. doi: 10.1186/s12887-024-05280-2.

ABSTRACT

BACKGROUND: Pneumonia is inflammation of the lung parenchyma and is a substantial cause of childhood morbidity and mortality in developing countries. Community-acquired pneumonia (CAP) is a type of pneumonia termed when patients who develop pneumonia in the outpatient setting and have not been in any health care facilities within 90days.

OBJECTIVE: The objective of this study was to determine treatment outcome of community acquired pneumonia among hospitalized pediatric patients.

METHOD: A retrospective cohort study was conducted from April 15, 2019 to July 15, 2019 and included patients who were admitted and hospitalized in pediatrics wards from September 1, 2015 to March 30, 2019. The study included pediatric age groups between one month and fifteen years old. Study Participants were selected based on the diagnosis of Community acquired pneumonia. Systematic sampling technique was used. All the statistical data were carried out using Statistical Package for Social Sciences (SPSS 20) and descriptive statistics were presented using means with standard deviation and percentages. Binary logistic regression model was fitted to measure the association between independent and dependent variables including duration of signs and symptoms. 95% Confidence interval was used. Statistically significant at P < 0.05.

RESULTS: A total of 385 patients with Community Acquired Pneumonia were included in this study of whom 368(95.65%) were discharged and 17(4.4%) of patients were dead. Drug therapy change (AOR 20.308(3.666-112.501), P = 0.001), Prescribing and taking of large number of drugs (above 5 drugs) (AOR 0.067, CI (0.015-0.313), P = 0.001), Loss of appetite (AOR 38.641, CI (5.454-273.769), P = 0.000), and Blood transfusion (AOR 10.514, CI (1.752-63.113), P = 0.01) have significant association with the treatment outcome of death.

CONCLUSION: Poor treatment outcome (death) was accounted for 4.4% of the pediatric patients hospitalized with community acquired pneumonia in this study setting. Based on the findings of this study Community acquired pneumonia is still a cause of substantial mortality of children under 15years old while on standardized treatment strategies. Antibiotic drug therapy change, taking increased number of drugs, loss of appetite and blood transfusion are the factors that contribute to this poor treatment outcome of CAP among children under 15years old.

PMID:39643882 | DOI:10.1186/s12887-024-05280-2

BMC Musculoskelet Disord. 2024 Dec 6;25(1):1006. doi: 10.1186/s12891-024-08050-4.

ABSTRACT

BACKGROUND: The COVID-19 pandemic had a significant impact on healthcare systems and the general population. However, it remains unclear to what extent these major societal changes have had an impact on the management of hip fractures in older people in Japan. Therefore, we investigated the effect of the COVID-19 pandemic on the number of patients with hip fractures, their characteristics, and their perioperative management as a retrospective multicentre study.

METHODS: We included 1894 patients aged ≥ 65 years who underwent surgery for hip fracture at three hospitals between January 2019-December 2021. Patients were classified according to the time of injury; patients treated between January-December 2019, January-December 2020, and January-December 2021 were divided into the pre-COVID-19 group, early COVID-19 group, and late COVID-19 group, respectively. We compared age, sex, body mass index, preadmission residence, surgical procedure, length of hospital stay, waiting time for surgery, in-hospital complications, and in-hospital death.

RESULTS: Our findings suggested that the early COVID-19 and late COVID-19 groups showed a 6.8% and 7.5% reduction in the number of HF patients, respectively, compared to the pre-COVID-19 group. Waiting days for surgery, length of hospital stay, and in-hospital mortality or complication rates did not significantly change before and after the pandemic. However, infection was increased in the early COVID-19 group regarding the subgroup of complications.

CONCLUSIONS: The COVID-19 pandemic altered the characteristics of hip fractures in older individuals.

PMID:39643881 | DOI:10.1186/s12891-024-08050-4

BMC Pediatr. 2024 Dec 6;24(1):799. doi: 10.1186/s12887-024-05270-4.

ABSTRACT

BACKGROUND: One of the important problems for mothers after the birth of a premature infant is a decrease in milk production. This study aimed to investigate the effect of foot reflexology on the volume and composition of breast milk in mothers of premature infants hospitalized in the neonatal intensive care unit.

METHODS: This randomized clinical trial was conducted on 76 primiparous mothers whose premature infants up to 34 weeks were hospitalized in the neonatal intensive care unit of Ayatollah Rouhani Hospital from February 2023 to November 2023. Mothers in the intervention group received foot reflexology for 20 min on both feet (ten minutes per foot) for seven consecutive days every morning. On the first and seventh days of the study, both groups were compared in terms of milk volume (ml), triglycerides, cholesterol, albumin, total protein, and calcium (mg/dl).

RESULTS: The mean difference in breast milk characteristics before and after the intervention in the control and intervention groups were as follows: in terms of breast milk volume 12.43 and 23.51 ml, triglyceride 418.37 and 406.21, cholesterol 5.48 and 3.67, albumin 1.02 and 0.35, total protein 1.89 and 4.59, calcium was -3.54 and -1.83 mg/dL; the net difference in breast milk volume in the intervention group compared to the control group increased, which was not statistically significant but was significant in terms of value. No significant difference was observed in other components of breast milk.

CONCLUSION: In this single-center study, foot reflexology massage showed a trend towards increasing the volume of breast milk, total protein and calcium, although it was not statistically significant. Therefore, it needs further investigation.

TRIAL REGISTRATION: IRCT, IRCT20221220056872N1. Registered 22 January 2023- prospective registered, https://irct.behdasht.gov.ir/trial/67512 .

PMID:39643879 | DOI:10.1186/s12887-024-05270-4

BMC Cancer. 2024 Dec 6;24(1):1506. doi: 10.1186/s12885-024-13214-5.

ABSTRACT

BACKGROUND: Breast cancer (BC) is the most prevalent cancer among women. Teachers play a crucial role in promoting healthy behaviors, including breast cancer screening (BCS). This study aimed to assess the impact of an Health Belief Model (HBM)-based educational intervention on BCS uptake, knowledge, and beliefs among female Yemeni teachers in Klang Valley, Malaysia.

METHODS: A cluster-randomized controlled trial was conducted with 180 participants from 12 schools, randomly assigned to intervention or control groups. The intervention group participated in a 90-minute educational session, with follow-up assessments at baseline, and at 1, 3, and 6 months’ post-intervention, using validated Arabic questionnaires. Data analysis was performed using SPSS version 22.0, with Generalized Estimating Equations (GEE) applied to assess differences within and between groups over time. Statistical significance was set at P < 0.05.

RESULTS: At baseline, there were no significant differences between groups. Post-intervention, the intervention group showed significantly higher rates of breast self-examination (BSE) and clinical breast examination (CBE) compared to the control group, with adjusted odds ratios (AOR) of 17.51 (CI: 8.22-37.29) for BSE and 2.75 (CI: 1.42-5.32) for CBE. Over six months, BSE performance in the intervention group increased, with AORs improving from 11.01 (CI: 5.05-24.04) to 18.55 (CI: 8.83-38.99). Similarly, CBE uptake rose from 1.60 (CI: 1.02-2.52) to 2.27 (CI: 1.44-3.58). Secondary outcomes revealed significant gains in knowledge and beliefs in the intervention group, including increased confidence in performing BSE and reduced perceived barriers.

CONCLUSIONS: The HBM-based educational intervention effectively enhanced BCS uptake, improved knowledge, and decreased barriers to BCS among Yemeni teachers in Malaysia, highlighting the potential of targeted educational programs to promote cancer screening behaviors in underserved populations.

CLINICAL TRIAL REGISTRATION: Retrospectively registered, ANZCTR (ACTRN12618000173291). Registered on February 02, 2018.

PMID:39643866 | DOI:10.1186/s12885-024-13214-5

Eur J Nutr. 2024 Dec 7;64(1):41. doi: 10.1007/s00394-024-03523-7.

ABSTRACT

PURPOSE: Dietary macronutrients significantly impact cardiometabolic health, yet research often focuses on individual macronutrient relationships. This study aimed to explore the associations between dietary macronutrient composition and cardiometabolic health.

METHODS: This study included 33,681 US adults (49.7 ± 18.3 years; 52.5% female) from the National Health and Nutrition Examination Survey during 1999-2014. Dietary data was derived from 1 to 2 separate 24-hour recalls and cardiometabolic health included lipid profile, glycemic control, blood pressure, and adiposity collected in a mobile examination center. Associations between dietary macronutrient composition and cardiometabolic health were examined using generalized additive models adjusted for age, socio-demographics, lifestyle, and diet quality.

RESULTS: In females, triglycerides (P < 0.01) and HDL cholesterol (P < 0.01) were the least optimal in diets containing lower fat (10%) and higher carbohydrate (75%). In males, HDL cholesterol was positively associated with fat (P < 0.01) and no association with triglycerides was detected. Total-C associations were male specific (P = 0.01) and highest in diets composed of 25% protein, 30% carbohydrate, and 45% fat. In both sexes, systolic blood pressure (P ≤ 0.02) was highest in diets containing lower fat (10%) coupled with moderate protein (25%). Diastolic blood pressure associations were female specific (P < 0.01) with higher values in those consuming the upper range of fat (55%). There were no associations of macronutrient composition with glycemic control or adiposity.

CONCLUSION: This study revealed sex-specific relationships between macronutrient composition and cardiometabolic health. Future research is needed to explore these relationships across age groups.

PMID:39643829 | DOI:10.1007/s00394-024-03523-7

Comput Methods Programs Biomed. 2024 Nov 30;260:108526. doi: 10.1016/j.cmpb.2024.108526. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Accurate medical image segmentation is crucial for diagnosis and treatment planning, particularly in tumor localization and organ measurement. Despite the success of Transformer models in various domains, they still struggle to capture high-frequency features, limiting their performance in medical image segmentation, especially in edge texture extraction. To overcome this limitation and improve segmentation accuracy, this study proposes a novel model architecture aimed at enhancing the Transformer’s ability to capture and integrate both high-frequency and low-frequency features.

METHODS: Our model combines the extraction of high-frequency features using a Laplacian pyramid with the capture of low-frequency features through a Local-Global Feature Aggregation Module. A Feature Interaction Fusion module is employed to integrate these features, focusing on target areas. Additionally, a new bridging module facilitates the transfer of spatial information between the encoder and decoder via layer-wise attention mechanisms. The model’s performance was evaluated using the Synapse dataset with statistical measures such as the Dice Similarity Coefficient and Hausdorff Distance. The code is available at https://github.com/chenyuxiao123/LGHF.

RESULTS: The proposed model demonstrated state-of-the-art performance in 2D medical image segmentation, achieving a Dice Similarity Coefficient of 84.10% and a Hausdorff Distance of 12.78. The evaluation metrics indicate significant improvements compared to existing methods.

CONCLUSION: This novel model architecture, with its enhanced capability to capture and integrate both high-frequency and low-frequency features, shows significant potential for advancing medical image segmentation. The results on the Synapse dataset demonstrate its effectiveness and suggest its application could improve diagnosis and treatment planning in clinical settings.

PMID:39642402 | DOI:10.1016/j.cmpb.2024.108526

J Breath Res. 2024 Dec 6. doi: 10.1088/1752-7163/ad9b46. Online ahead of print.

ABSTRACT

Volatolomics (or volatilomics), the study of volatile organic compounds, has emerged as a crucial field of metabolomics due&#xD;to its potential for non-invasive diagnostics and disease monitoring. However, analyzing high-resolution data generated by&#xD;mass spectrometry-based instrumentation remains challenging. This comprehensive guide provides an in-depth exploration&#xD;of volatolomics data analysis, highlighting the importance of subsequent steps, including data cleaning, pretreatment, and&#xD;statistical and machine learning techniques (dimensionality reduction, clustering, classification, and variable selection). The&#xD;choice of these methods, and the integration of data handling practices, such as missing data imputation, outlier detection,&#xD;model validation, and data integration, significantly impact the identification of meaningful metabolites and the accuracy of&#xD;diagnostic conclusions. This guide aims to familiarize the reader with the implications of various data analysis techniques in&#xD;volatolomics and their suitability for different applications. It emphasizes the necessity of understanding the strengths and&#xD;limitations of each method to make informed decisions that enhance the reliability of findings. By outlining these methodologies,&#xD;the guide aims to equip researchers with the knowledge needed to navigate the complexities of volatolomics data analysis. The&#xD;careful consideration of experimental design, data collection, and processing strategies is essential for the identification of&#xD;biomarkers, ultimately advancing the field and improving the understanding of metabolic processes in health and disease.

PMID:39642393 | DOI:10.1088/1752-7163/ad9b46

Prim Care Companion CNS Disord. 2024 Dec 3;26(6):24m03777. doi: 10.4088/PCC.24m03777.

ABSTRACT

Objective: To evaluate a novel curriculum aimed to increase nonpsychiatry providers’ confidence in treating mental health conditions.

Methods: The study sample consisted of a cohort of convenience of nonbehavioral health physicians and advanced practice providers. The authors administered pre and posttests to measure provider confidence in treating specific mental health diagnoses, utilizing specific classes of psychotropic medications, and managing specific clinical scenarios. Questions were ranked using a Likert scale from 1 (least comfortable) to 5 (very comfortable). Paired sample t-tests were utilized to compare the pre- and posttest survey results. A follow-up survey was administered 1 month following the completion of the seminar, and the results were analyzed qualitatively.

Results: Twenty nonbehavioral health care providers attended an educational 2-day seminar on August 3-4, 2023. There were statistically significant improvements between the pre- and posttest measures of confidence in all 31 items measured. At 1-month follow-up, 87.5% (N = 14) rated their overall impression of the seminar as “excellent” and 12.5% (N = 2) rated their impression as “very good.” At the 1- month follow-up, 15 participants reported treating patients for depression and anxiety, compared to 13 who had done so prior to the seminar.

Conclusions: An educational seminar hosted by psychiatrists is an effective intervention for increasing provider confidence in treating mental health conditions and could serve as a valuable method for expanding the mental health workforce.

Prim Care Companion CNS Disord2024;26(6):24m03777.

Author affiliations are listed at the end of this article.

PMID:39642384 | DOI:10.4088/PCC.24m03777

J Neurosurg. 2024 Dec 6:1-12. doi: 10.3171/2024.7.JNS241102. Online ahead of print.

ABSTRACT

OBJECTIVE: Maximum extent of resection in glioma yields enhanced survival outcomes. The contemporary literature presents contradictory results regarding the benefit of intraoperative MRI (iMRI). This meta-analysis aimed to investigate the efficacy and safety of iMRI-guided surgery.

METHODS: The authors searched the PubMed, Embase, and Cochrane Reviews databases for eligible prospective randomized controlled trials through the end of February 2024. Endpoints were extent of resection, progression-free survival (PFS), overall survival, neurological functioning, and surgical complications. Individual patient data regarding PFS were reconstructed using the R package IPDfromKM.

RESULTS: From 1923 identified results, 3 randomized controlled trials with 384 patients met the inclusion criteria. Extended resections after iMRI were performed in 29.2% of the iMRI cases. Intraoperative MRI-guided glioma surgery (OR 5.40, 95% CI 3.25-8.98; p < 0.00001) outperformed conventional navigation-guided surgery in attaining gross-total resection (GTR). In patients in whom a GTR was achieved, the median time to progression was 16.0 months (95% CI 12.3-19.7 months), while the median PFS in patients with a subtotal resection was 9.7 months (95% CI 6.9-12.5 months) (p < 0.001). Despite increased GTR rates, postoperative neurological deterioration was equal among the iMRI and control groups (OR 1.0, 95% CI 0.6-1.7; p = 0.91, I2 = 0%). Intraoperative MRI use prolongs surgery by 42 minutes on average (95% CI 3.3-80.7 minutes; p = 0.03, I2 = 56%). The risk of postoperative intracranial hemorrhage (OR 1.9, 95% CI 0.2-16.9; p = 0.55, I2 = 0%) was not increased, while in one study significantly increased infections were observed in the iMRI arm.

CONCLUSIONS: Intraoperative MRI outperforms conventional surgery in achieving complete glioma resections of all contrast-enhancing tumor portions, enhancing PFS without added risk. Intraoperative MRI is a tool that facilitates these aims without reducing safety in terms of neurological deficits and surgical complications.

PMID:39642374 | DOI:10.3171/2024.7.JNS241102

J Med Internet Res. 2024 Dec 6;26:e55635. doi: 10.2196/55635.

ABSTRACT

BACKGROUND: Although significant research has explored the digital phenotype in mood disorders, the time-lagged and bidirectional relationship between mood and global positioning system (GPS) mobility remains relatively unexplored. Leveraging the widespread use of smartphones, we examined correlations between mood and behavioral changes, which could inform future scalable interventions and personalized mental health monitoring.

OBJECTIVE: This study aims to investigate the bidirectional time lag relationships between passive GPS data and active ecological momentary assessment (EMA) data collected via smartphone app technology.

METHODS: Between March 2020 and May 2022, we recruited 45 participants (mean age 42.3 years, SD 12.1 years) who were followed up for 6 months: 35 individuals diagnosed with mood disorders referred by psychiatrists and 10 healthy control participants. This resulted in a total of 5248 person-days of data. Over 6 months, we collected 2 types of smartphone data: passive data on movement patterns with nearly 100,000 GPS data points per individual and active data through EMA capturing daily mood levels, including fatigue, irritability, depressed, and manic mood. Our study is limited to Android users due to operating system constraints.

RESULTS: Our findings revealed a significant negative correlation between normalized entropy (r=-0.353; P=.04) and weekly depressed mood as well as between location variance (r=-0.364; P=.03) and depressed mood. In participants with mood disorders, we observed bidirectional time-lagged associations. Specifically, changes in homestay were positively associated with fatigue (β=0.256; P=.03), depressed mood (β=0.235; P=.01), and irritability (β=0.149; P=.03). A decrease in location variance was significantly associated with higher depressed mood the following day (β=-0.015; P=.009). Conversely, an increase in depressed mood was significantly associated with reduced location variance the next day (β=-0.869; P<.001). These findings suggest a dynamic interplay between mood symptoms and mobility patterns.

CONCLUSIONS: This study demonstrates the potential of utilizing active EMA data to assess mood levels and passive GPS data to analyze mobility behaviors, with implications for managing disease progression in patients. Monitoring location variance and homestay can provide valuable insights into this process. The daily use of smartphones has proven to be a convenient method for monitoring patients’ conditions. Interventions should prioritize promoting physical movement while discouraging prolonged periods of staying at home.

PMID:39642364 | DOI:10.2196/55635