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    <title>Canon Journal of Medicine</title>
    <link>https://www.canonjm.com/</link>
    <description>Canon Journal of Medicine</description>
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    <pubDate>Sat, 05 Apr 2025 00:00:00 +0330</pubDate>
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      <title>Application of Machine Learning Models for Predicting COVID-19 Mortality: A Retrospective Cohort Study Using Random Forest Algorithm</title>
      <link>https://www.canonjm.com/article_218208.html</link>
      <description>Background: The COVID-19 pandemic has posed immense challenges to healthcare systems worldwide, making it critical to identify predictors of patient mortality. Machine learning algorithms have shown great promise in predicting outcomes for COVID-19 patients based on clinical and laboratory data. This study aimed to evaluate the performance of three machine learning models&amp;amp;mdash;Random Forest, Support Vector Machine (SVM), and Logistic Regression&amp;amp;mdash;in predicting mortality among COVID-19 patients using clinical and laboratory data.Methods: A retrospective cohort study was conducted on 2,500 COVID-19 patients admitted to three major hospitals in Tehran, Iran, between 2020 and 2021. Demographic, clinical, and laboratory data were collected. Machine learning models were trained to predict mortality, and their performance was evaluated using the area under the curve (AUC), sensitivity, specificity, and positive predictive value (PPV). Model validation was performed using 10-fold cross-validation and an 80-20 train-test split to ensure robustness and generalizability.Results: The Random Forest model outperformed both SVM and Logistic Regression with an AUC of 83.3%, sensitivity of 63.0%, and specificity of 90.5%. Important predictors of mortality included age, gender, comorbidities (such as diabetes, ischemic heart disease, and cancer), ICU admission, and laboratory markers (e.g., ALT, white blood cell count, and creatinine levels).Conclusion: The Random Forest algorithm demonstrated superior predictive performance compared to SVM and Logistic Regression in predicting mortality among COVID-19 patients. These findings suggest that machine learning models, particularly Random Forest, can be instrumental in identifying high-risk patients and supporting clinical decision-making.</description>
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    <item>
      <title>A Step Toward Faster, Fairer, and More Flexible Publishing at Canon Journal of Medicine</title>
      <link>https://www.canonjm.com/article_222394.html</link>
      <description>The Canon Journal of Medicine (CJM) is transitioning to a continuous publication model starting June 2025. This strategic shift aims to address challenges posed by variable submission volumes and enhance the timely dissemination of medical research. Under the new model, articles will be published online immediately after peer review and final formatting, eliminating delays associated with quarterly issue compilation. Core values such as rigorous peer review, open access, ethical publishing, and no fees remain unchanged. This transition promotes faster visibility for authors, immediate access for readers, and sustained journal activity, aligning CJM with the evolving demands of scientific communication.</description>
    </item>
    <item>
      <title>The Prevalence of Postcode Stress Among Nurses: A Systematic Review and Meta-Analysis Protocol</title>
      <link>https://www.canonjm.com/article_224993.html</link>
      <description>Background: Postcode stress is a significant concern among nurses in high-stakes environments like emergencies and intensive care units. This stress arises from the emotional and psychological burden of performing cardiopulmonary resuscitation (CPR), especially when outcomes are unfavorable. Despite its recognized impact on nurses' mental health and patient care quality, empirical research does not quantify its prevalence and identify contributing factors. This study aims to conduct a systematic review and meta-analysis to determine the prevalence of postcode stress among nurses, providing a comprehensive understanding of this phenomenon to inform effective interventions and support mechanisms.Methods: A thorough search was conducted across various online databases. Studies were deemed eligible for inclusion if they examined postcode stress within nursing practice utilizing validated instruments, irrespective of the academic status, gender, country, setting, ethnicity, race, or limitations of the studies. Two reviewers independently undertook data extraction and quality assessment, following the PRISMA guidelines. Discussion: &amp;amp;nbsp;Post-resuscitation stress, or "postcode stress," significantly impacts critical care nurses involved in failed CPR attempts. This emotional burden can lead to moderate to severe stress levels and symptoms like post-traumatic stress disorder, affecting mental health and job satisfaction. Key factors include high-stakes settings, emotional investment in patient care, and perceived responsibility. Like structured debriefing sessions, institutional support alleviates these adverse effects, highlighting the need for supportive work environments. Positive coping strategies and regular stress assessments can enhance nurses' well-being and improve patient care outcomes.Systematic review registration: PROSPERO CRD42025646495. This protocol follows the PRISMA-P guidelines for reporting systematic reviews.</description>
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    <item>
      <title>The Prevalence of Moral Sensitivity Among Nurses: A Systematic Review and Meta-Analysis Protocol</title>
      <link>https://www.canonjm.com/article_236610.html</link>
      <description>Background:Moral sensitivity is crucial in nursing ethics, significantly impacting patient care and decision-making. By recognizing ethical dilemmas, nurses provide compassionate, patient-centered care that improves outcomes. This review explores the levels of moral sensitivity among nurses and factors influencing its role, aiming to enhance ethical decision-making and standards in nursing.&#13;
Methods:This systematic review will follow the Joanna Briggs Institute methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive search will be conducted across multiple databases, including PubMed, Web of Science, Scopus, PsycINFO, Embase, and CINAHL, from January 1995 to April 2025. The search will not be restricted by study design or language. Studies on moral sensitivity scores in nursing practice, their levels, and the factors influencing them will be considered. The evidence synthesis will incorporate qualitative and quantitative analyses, with the results examined using descriptive statistics and thematic synthesis. The Theoretical Domains Framework will be utilised to categorise the factors influencing moral sensitivity.&#13;
Discussion:This study highlights the significance of moral sensitivity in nurses for ethical decision-making and patient care. Findings will reveal factors influencing moral sensitivity in nursing and showcase strengths and gaps in practices and education. Ultimately, the data will inform targeted interventions and educational strategies aimed at enhancing moral sensitivity and improving patient outcomes.&#13;
Systematic review registration:PROSPERO CRD420251010641. This protocol follows the PRISMA-P guidelines for reporting systematic reviews.</description>
    </item>
    <item>
      <title>From Empathy to Evidence: Moral Sensitivity in Iranian Nursing Students &amp;mdash; A Systematic Review and Meta-Analysis</title>
      <link>https://www.canonjm.com/article_238245.html</link>
      <description>Background: Moral sensitivity is a key component of ethical nursing practice, enabling nurses to recognize and address ethical challenges in patient care. Although several Iranian studies have examined nursing students&amp;amp;rsquo; moral sensitivity, their findings remain inconsistent. This systematic review and meta-analysis aimed to estimate the overall level of moral sensitivity among Iranian undergraduate nursing students.Methods: A systematic search was conducted in PubMed, Scopus, Web of Science, CINAHL, SID, and Google Scholar from inception to February 8, 2025, using terms related to &amp;amp;ldquo;moral sensitivity&amp;amp;rdquo; and &amp;amp;ldquo;nursing students.&amp;amp;rdquo; The primary measurement instrument was L&amp;amp;uuml;tz&amp;amp;eacute;n&amp;amp;rsquo;s Moral Sensitivity Questionnaire (MSQ). Results: The meta-analysis pooled findings from multiple studies on Iranian undergraduate nursing students. The pooled mean moral sensitivity score was 61.33 (95% CI: 53.35&amp;amp;ndash;69.31), indicating a moderate level. Subgroup analysis showed no significant differences by gender or risk of bias. High heterogeneity was observed (I&amp;amp;sup2; = 100%). After adjusting for publication bias, the mean increased to 85.44. Moral sensitivity was highest in rule-based domains and lowest in moral meaning and benevolence.Conclusion: Iranian nursing students demonstrate moderate moral sensitivity. While they can identify ethical conflicts, they face challenges in moral reasoning and benevolence. In clinical care, enhancing moral sensitivity is crucial for safer, patient-centred care through improved recognition of ethical issues, respect for privacy, equitable practice, and timely advocacy. These findings suggest the need for integrating longitudinal ethics education and interdisciplinary ethics rounds into nursing curricula to strengthen moral judgment and decision-making.</description>
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    <item>
      <title>The Future of Neurosurgery: How Artificial Intelligence (AI) is Changing the Game, A Narrative Review</title>
      <link>https://www.canonjm.com/article_238246.html</link>
      <description>The use of Artificial Intelligence in neurosurgery has gained significant attention in recent years. This review explores the current state and future potential of AI applications in neurosurgery, focusing on areas such as neuro-oncology, epilepsy, spine, and functional surgery. AI algorithms and technologies can support neurosurgeons in preoperative planning, intraoperative guidance, and postoperative evaluation. The benefits of AI in neurosurgery include improved accuracy of preoperative planning, increased efficiency during surgery, and enhanced patient outcomes. However, integrating AI in neurosurgery also poses technical, ethical, and regulatory challenges. Developing robust and reliable AI algorithms that adhere to regulatory and ethical standards is crucial for the successful integration of AI in neurosurgery. The need for transparency and accountability in AI systems is also an important consideration, particularly in medical applications. In conclusion, the increased utilization and integration of AI in neurosurgery has the potential to significantly improve patient outcomes and the therapeutic efficacy of neurosurgical procedures. Further research and development are needed to address the challenges associated with the use of AI in medical practice and to fully realize the benefits of AI in neurosurgery.</description>
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    <item>
      <title>Acute Wernicke&amp;rsquo;s Encephalopathy in a Chronic Alcohol User: Clinical Presentation, MRI Findings, and Treatment Response</title>
      <link>https://www.canonjm.com/article_238247.html</link>
      <description>This case report is about a 37-year-old man who came to the emergency room with the chief complaint of a decrease in level of consciousness. According to the history given by his family, he had a heavy alcohol consumption (about one liter per day) for the past four years. In Neurological exams, he showed signs of ataxia (loss of coordination), strabismus because of sixth cranial nerve damage. Based on clinical signs and MRI findings (showing signal changes in the periaqueductal region and mammillary bodies), the diagnosis of Wernicke&amp;amp;rsquo;s Encephalopathy (WE) was confirmed, with no evidence of progression to Korsakoff Syndrome (WKS). The patient was being treated with sodium valproate because of a seizure disorder. The treatment protocol was high-dose thiamine, B-complex vitamin injection, and changing sodium valproate to levetiracetam due to liver involvement. Although there were relative improvements after the treatment, sixth nerve damage was still present in the patient and needed much longer follow-ups.</description>
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    <item>
      <title>Corpus Callosum Morphology among Children&amp;rsquo;s With Seizure: a comparative study</title>
      <link>https://www.canonjm.com/article_238248.html</link>
      <description>Background: This study aimed to evaluate the morphological and quantitative changes in the corpus callosum in children aged 1 to 16 years with a history of seizures and to compare these findings with a control group of healthy children.Methods: In this case-control study 42 pediatric patients diagnosed with seizures and 25 healthy controls were included. Magnetic Resonance Imaging (T1-weighted MRI) was used to obtain detailed measurements of the corpus callosum, focusing on its length, width, and thickness across the anterior, middle, and posterior regions (genu, B1-4, and splenium). Results: 67 children in the aged between 1-16 years were included in the study. The results showed that the overall length and width of the corpus callosum were not significantly different between the two groups. But the thickness of B1 region in patients with seizures was significantly higher than the control group (p=0.029). Other thickness areas did not show significant differences. Statistical analysis showed that some differences such as the thickness of the B1 region deviate from the normal distribution, but for other differences, no significant difference was observed between the groups.Conclusions: The study's findings indicate that seizures in children may be associated with specific morphological alterations in the corpus callosum. These changes could potentially serve as biomarkers for understanding the neurological impact of seizures and guiding therapeutic interventions. Further research is needed to elucidate the mechanisms behind these alterations and their clinical significance.</description>
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    <item>
      <title>Clear Cell Renal Cell Carcinoma with A Tumor Thrombus in the Proximal Ureter: A Case Report</title>
      <link>https://www.canonjm.com/article_238249.html</link>
      <description>Background: Renal cell carcinoma (RCC) holds the distinction of being the most prevalent cancer of the kidney in adults. Although invasion of surrounding tissue is a common phenomenon in RCC, the spread within the lumen of the collecting system and the ureters is rarely encountered. It may be essential to consider including urinary tract extension in the TNM staging.Case presentation: We present the case of a 57 years old male, with no smoking history and no previous medical conditions, presenting with painless gross hematuria. The patient's CT scan revealed a heterogeneous mass in the left kidney with central necrotic areas. The tumor was found to have spread to the left pelvis and ureter, reaching a distance of 7.5 cm from the ureteropelvic junction. No evidence of left renal vein and IVC involvement was found. Later on, he underwent a radical nephrectomy. An atypical pattern of RCC dissemination was observed, with a tumor protrusion into the renal sinus fat, renal pelvis, and a tumor thrombus extending to the ureter. The histological examination showed a grade 4 clear cell renal cell carcinoma with 10% sarcomatoid features.Conclusion: It may be of significance to consider the inclusion of urinary tract extension in RCC when determining the TNM staging.</description>
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