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Universa Medicina
Published by Universitas Trisakti
ISSN : 19073062     EISSN : 24072230     DOI : -
Core Subject : Health, Science,
Health Professions Immunology & microbiology Medicine & Pharmacology Public Health
Universa Medicina (univ.med) is a four-monthly medical journal that publishes new research findings on a wide variety of topics of importance to biomedical science and clinical practice. Universa Medicina Online contains both the current issue and an online archive that can be accessed through browsing, advanced searching, or collections by disease or topic
Arjuna Subject : -
Articles 595 Documents
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Higher uric acid serum levels are associated with sarcopenia among elderly in a community health center Farista, A. Deza; Rivianti, Nur; Bahar, Erial; Permata, Mega; Reagan, Muhammad; Indah, Crisnah; Artini, Ika
Universa Medicina Vol. 44 No. 3 (2025)
Publisher : Faculty of Medicine, Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18051/UnivMed.2025.v44.335-344

Abstract

BackgroundAs people age, skeletal muscle mass and strength decrease, leading to sarcopenia, diagnosed through calf circumference, muscle mass, strength, and physical performance. Uric acid (UA), with both pro-oxidant and antioxidant properties, is an indicator of oxidative stress and may contribute to sarcopenia. This study aimed to determine the correlation between serum uric acid levels and sarcopenia in elderly in a community health center. MethodsA cross-sectional study was conducted involving 42 subjects aged ≥60 years, consisting of 37 female and 5 male participants. We applied Asian Working Group for Sarcopenia (AWGS) 2019 criteria to define sarcopenia. Muscle mass was measured using skeletal muscle index (SMI) based on bioimpedance analysis (BIA). Handgrip strength (HGS), physical performance, calf circumference, and blood test data were collected. A backward regression analysis was performed to investigate the relationship between UA and SMI, HGS, physical performance, and calf circumference after adjusting for gender, smoking history, upper arm circumference, and body mass index.Results After adjusting for potential confounding variables, uric acid remained significantly associated with muscle strength (β=0.326; p=0.023) and calf circumference (β=0.264; p=0.010), but not with muscle mass (β=0.046; p=0.727) or physical performance (β=–0.171; p=0.279).ConclusionThere is a significant correlation between uric acid levels and muscle strength, physical performance, and calf circumference in sarcopenia among the elderly in the community health center. Higher uric acid serum levels might slow down the progression of sarcopenia.
Effect of cross-running polypropylene intradermal suture technique on keloid scar: a single-blind randomized controlled trial Wihastyoko, Herman Yosef Limpat; Rinhastyanti, Edith Sumaregita; Arviansyah, Arviansyah; Siswanto, Yudi; Agustina, Wilma; Sintaningrum, Elisabeth Prajanti
Universa Medicina Vol. 45 No. 1 (2026): Aheaf Of Print
Publisher : Faculty of Medicine, Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18051/UnivMed.2026.v45.4-12

Abstract

BACKGROUNDKeloids are abnormal scars that present a therapeutic challenge. Various treatment modalities have been developed, including surgical excision. While cross-running intradermal sutures were previously created using absorbable polyglycolic acid, this study introduces a modification using a non-absorbable material. Therefore, this study aimed to evaluate the effect of the cross-running polypropylene intradermal suture (CR-PIS) technique compared to the simple interrupted suture technique on keloid repair. METHODSThis was a randomized controlled trial with a post-test-only design involving 30 male and female keloid patients aged 20-50 years. Participants were randomized into the treatment group (n=15) and the control group (n=15). Wound assessment using the Vancouver Scar Scale (VSS), Manchester Scar Scale (MSS), and Patient and Observer Scar Assessment Scale (POSAS) was performed at 3, 6, and 9 months after surgery. Differences in VSS, MSS, and POSAS scores between the CR-PIS group and the simple knot group were analyzed using the Mann-Whitney U test. RESULTSStatistical analysis revealed a significant difference between the simple knot and CR-PIS groups (p<0.05). The median scores for each assessment (VSS, MSS, and POSAS) decreased significantly at 3, 6, and 9 months, with the control group's values being higher than those in the CR-PIS group (p<0.05). These results indicate that the control group developed moderate scars, whereas the treatment group exhibited good scars. CONCLUSIONSThe CR-PIS is more effective than the simple knot technique in improving keloid scars, as shown by changes in wound appearance, morphological function, topography, and patient and evaluator assessments.
Clinical significance of pre-operative prognostic nutritional index in predicting survival in patients with renal cell carcinoma Utama, Eldo Taufila Putra; Danarto, Raden
Universa Medicina Vol. 44 No. 3 (2025)
Publisher : Faculty of Medicine, Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18051/UnivMed.2025.v44.345-351

Abstract

BackgroundRenal cell carcinoma (RCC) is a prevalent urologic malignancy with heterogeneous outcomes even after surgery. Conventional prognostic factors are insufficient to capture host-related influences on survival. The prognostic nutritional index (PNI), derived from serum albumin and lymphocyte count, reflects nutritional and immunological status and has emerged as a potential prognostic biomarker. The objective of this study was to determine preoperative PNI in predicting survival outcomes of RCC patients.MethodsThis was a retrospective cohort study involving 107 RCC patients who underwent radical or partial nephrectomy. Patients were categorized into normal and low PNI. Associations between PNI and clinicopathological features were assessed, while survival outcomes were evaluated using Kaplan–Meier analysis and Cox proportional hazards regression.ResultsPatients’ mean age was 53.1 ± 13.5 years, and 58.9% of the patients were male. Clear cell carcinoma was the most common histological type (69.2%). Low PNI was significantly associated with older age (p=0.04), metastatic disease (p<0.001), and advanced tumor stage (p=0.014). Kaplan–Meier analysis demonstrated significantly poorer survival in the low-PNI group (p<0.001). In the multivariate Cox model, PNI remained the strongest independent predictor of overall survival (HR = 0.29, 95% CI: 0.13–0.67, p=0.003), while metastasis also retained independent significance (HR = 2.04, 95% CI: 1.06–3.93, p=0.031).ConclusionThe PNI is an independent, simple, and cost-effective prognostic factor for overall survival in RCC. Incorporating PNI into preoperative risk stratification may enhance clinical decision-making. Therefore, PNI could be used as an effective prognostic indicator in RCC.
Machine learning models for predicting 48-hour mortality in acute intracerebral hemorrhagic stroke Kemaladina, Intan; Syahrul, Syahrul; Abidin, Taufik Fuadi; Musadir, Nasrul; Imran, Imran
Universa Medicina Vol. 45 No. 1 (2026): Aheaf Of Print
Publisher : Faculty of Medicine, Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18051/UnivMed.2026.v45.13-26

Abstract

BACKGROUNDIdentifying patients with intracerebral hemorrhagic (ICH) at high risk of mortality is crucial for timely intervention. Machine learning (ML) offers novel methodologies for precise predictive models for ICH.  Therefore, the aim of this study was to develop an ML-based predictive model for 48-hour mortality in patients with acute hemorrhagic stroke.  METHODSA cross-sectional study was conducted using secondary data from 657 patients diagnosed with acute ICH. Demographic, clinical, laboratory, and radiological variables were extracted from medical records. Data preprocessing included cleaning, normalization, and class balancing using the Synthetic Minority Oversampling Technique (SMOTE). Three supervised algorithms—Random Forest, Decision Tree, and Gaussian Naïve Bayes—were developed and evaluated using stratified 5-fold cross-validation. Model performance was assessed using accuracy, sensitivity, specificity, precision, recall, F1-score, and AUC. RESULTSRandom Forest achieved the best overall performance for predicting 48-hour mortality, with an accuracy of 84.77%, F1-score of 84.63%, and AUC of 80.51, outperforming Decision Tree (AUC 61.12) and Gaussian Naïve Bayes (AUC 82.94). Random Forest most accurately identified >48-hour survival, with high sensitivity (93.5%) and PPV (92.9%), while Naïve Bayes provided the most reliable positive classification for this category (PPV 99.0; specificity 94.2%). For ≤24-hour mortality, Naïve Bayes showed the best detection performance (sensitivity 85.4%; NPV 98.7%).  CONCLUSIONSMachine learning, particularly the Random Forest algorithm, enables reliable prediction of 48-hour mortality in patients with acute ICH using basic clinical and radiological data available at admission. The model offers practical potential for early risk stratification in emergency and critical care settings.
Microbiota as a reservoir of antibiotic resistance genes: relevance and urgency Maddela, Naga Raju
Universa Medicina Vol. 45 No. 1 (2026): Aheaf Of Print
Publisher : Faculty of Medicine, Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18051/UnivMed.2026.v45.1-3

Abstract

'Antimicrobial resistance' (AMR) is one of the top threats to global public health and developments.

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