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1. EFFECT OF MORINGA (Moringa oleifera) LEAF FLOUR ETHANOL EXTRACT ON REDUCTION OF BLOOD GLUCOSE IN MALE WISTAR STRAIN RATS INDUCED BY ALLOXAN

Author

Ditya Ananda Safira, Susianti, Dyah Wulan Sumekar Rengganis Wardani, and Jhons Fatriyadi Suwandi

Subjects
diabetes, tepung daun kelor, moringa oleifera, Medicine
Abstract

This study is to determine the effect of giving ethanol extract of moringa leaf flour (Moringa oleifera) on reducing blood glucose levels of alloxan-induced Wistar Rattus norvegicus male rats. Using a true experimental design with a randomized pre and post control group approach. The sample used consisted of 35 male Wistar white rats. Data collection using simple random sampling technique. Paired t test gives the results of p

Published
2024
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2. Acute Kidney Injury Prediction Model Using Cystatin-C, Beta-2 Microglobulin, and Neutrophil Gelatinase-Associated Lipocalin Biomarker in Sepsis Patients

Author

Susianti H, Asmoro AA, Sujarwoto, Jaya W, Sutanto H, Kusdijanto AY, Kuwoyo KP, Hananto K, and Khrisna MB

Subjects
machine learning, sepsis, aki, cystatin c, beta-2 microglobulin, ngal, Diseases of the genitourinary system. Urology, RC870-923
Abstract

Hani Susianti,1 Aswoco Andyk Asmoro,2 Sujarwoto,3 Wiwi Jaya,2 Heri Sutanto,4 Amanda Yuanita Kusdijanto,1 Kevin Putro Kuwoyo,1 Kristian Hananto,5 Matthew Brian Khrisna1 1Clinical Pathology Department, Faculty of Medicine Brawijaya University/Saiful Anwar General Hospital, Malang, Indonesia; 2Anesthesiology and Intensive Therapy Department, Faculty of Medicine Brawijaya University/Saiful Anwar General Hospital, Malang, Indonesia; 3Faculty of Public Administration, Brawijaya University, Malang, Indonesia; 4Internal Medicine Department, Faculty of Medicine Brawijaya University/Saiful Anwar General Hospital, Malang, Indonesia; 5Faculty of Medicine, Brawijaya University, Malang, IndonesiaCorrespondence: Hani Susianti, Clinical Pathology Department, Medicine Faculty of Universitas Brawijaya/Dr. Saiful Anwar General Hospital, Malang, Indonesia, Email hanisusianti.fk@ub.ac.idIntroduction: AKI is a frequent complication in sepsis patients and is estimated to occur in almost half of patients with severe sepsis. However, there is currently no effective therapy for AKI in sepsis. Therefore, the therapeutic approach is focused on prevention. Based on this, there is an opportunity to examine a panel of biomarker models for predicting AKI.Material and Methods: This prospective cohort study analysed the differences in Cystatin C, Beta-2 Microglobulin, and NGAL levels in sepsis patients with AKI and sepsis patients without AKI. The biomarker modelling of AKI prediction was done using machine learning, namely Orange Data Mining. In this study, 130 samples were analysed by machine learning. The parameters used to obtain the biomarker panel were 23 laboratory examination parameters.Results: This study used SVM and the Naïve Bayes model of machine learning. The SVM model’s sensitivity, specificity, NPV, and PPV were 50%, 94.4%, 71.4%, and 87.5%, respectively. For the Naïve Bayes model, the sensitivity, specificity, NPV, and PPV were 83.3%, 77.8%, 87.5%, and 71.4%, respectively.Discussion: This study’s SVM machine learning model has higher AUC and specificity but lower sensitivity. The Naïve Bayes model had better sensitivity; it can be used to predict AKI in sepsis patients.Conclusion: The Naïve Bayes machine learning model in this study is useful for predicting AKI in sepsis patients.Keywords: machine learning, sepsis, AKI, Cystatin C, Beta-2 Microglobulin, NGAL

Published
2024

3. New hybrid radio-fluorescent probes [131I]-BPF-01 and [131I]-BPF-02 for visualisation of cancer cells: Synthesis and preliminary in vitro and ex vivo evaluations

Author

Hendris Wongso, Ahmad Kurniawan, Alfian M. Forentin, Veronika Y. Susilo, Yanuar Setiadi, Isa Mahendra, Muhamad B. Febrian, Aziiz M. Rosdianto, Iwan Setiawan, Hanna Goenawan, Susianti Susianti, Unang Supratman, Eva M. Widyasari, Teguh H.A. Wibawa, Maula E. Sriyani, Iim Halimah, and Ronny Lesmana

Subjects
Fluorescent, Hybrid radio-fluorescent, Solid cancers, Imaging, Image-guided surgery, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

We synthesised and biologically evaluated two new hybrid probes [131I]BPF-01 and [131I]BPF-02 which were built from three structural entities: benzothiazole-phenyl, fluorescein isothiocyanate (FITC), and iodine-131. These probes were designed for potential applications in assisting surgical procedures of solid cancers. The cytotoxicity study demonstrated that fluorescent probes BPF-01 (31.23 μg/mL) and BPF-02 (250 μg/mL) were relatively not toxic to normal immortalized human keratinocytes (HaCaT) cells, as indicated by the percentage of cell survival above 50 %. Furthermore, both probes displayed low to moderate anticancer activity against the breast cancer cells (MDA-MB-231) and prostate cancer cells (LNCaP and DU-145). The probe BPF-01 apparently showed an accumulation in the tumour tissues, as suggested by ex vivo fluorescence examinations. In addition, the cellular uptake study suggests that hybrid probe [131I]-BPF-01 was potentially accumulated in the MCF-7 cell line with the highest uptake of 16.11 ± 1.52 % after 2 h of incubation, approximately 50-fold higher than the accumulation of iodine-131 (control). The magnetic bead assay suggests that [131I]-BPF-02 and [131I]-BPF-02 showed a promising capability to interact with translocator protein 18 kDa (TSPO). Moreover, the computational data showed that the binding scores for ligands 7–8, BPF-01 and BPF-02, and [131I]-BPF-01 and [131I]-BPF-02 in the TSPO were considerably high. Accordingly, fluorescent probes BPF-01 and BPF-02, and hybrid probes [131I]BPF-01 and [131I]BPF-02 can be further developed for targeting cancer cells during intraoperative tumour surgery.

Published
2023
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4. Optical Coherence Tomography Angiography Findings in Ocular Toxoplasmosis with Multiple Recurrences

Author

Sofia O, Wahyudi INSA, Fitri LE, Prayitnaningsih S, and Susianti H

Subjects
ocular toxoplasmosis, retinochoroiditis, recurrent, optical coherence tomography angiography, Medicine (General), R5-920
Abstract

Ovi Sofia,1,2 I Nyoman Surya Ari Wahyudi,3 Loeki Enggar Fitri,4 Seskoati Prayitnaningsih,2 Hani Susianti5 1Doctoral Program in Medical Science, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; 2Department of Ophthalmology, Faculty of Medicine, Universitas Brawijaya, Dr. Saiful Anwar General Hospital, Malang, Indonesia; 3Residency Training Program, Department of Ophthalmology, Faculty of Medicine, Universitas Brawijaya, Dr. Saiful Anwar General Hospital, Malang, Indonesia; 4Department of Clinical Parasitology, Faculty of Medicine, Universitas Brawijaya, Dr. Saiful Anwar General Hospital, Malang, Indonesia; 5Department of Clinical Pathology, Faculty of Medicine, Universitas Brawijaya, Dr. Saiful Anwar General Hospital, Malang, IndonesiaCorrespondence: Loeki Enggar Fitri, Department of Clinical Parasitology, Faculty of Medicine, Universitas Brawijaya, Dr. Saiful Anwar General Hospital, Malang, Indonesia, Email lukief@ub.ac.idAbstract: Ocular toxoplasmosis is the most common cause of posterior uveitis that is caused by Toxoplasma gondii infection. Humans can be infected congenitally or postnatally. The typical lesion of ocular toxoplasmosis is focal necrotizing retinitis with overlying vitritis, which lead to hyperpigmented retinochoroidal scar at resolution of lesion. Macula involvement can cause substantial visual impairment. The high incidence of disease reactivation may lead to greater risk of vision loss. Optical coherence tomography angiography (OCTA) is a non-invasive imaging method to visualize the vascular and density perfusion of the retina and choroid, which cannot be obtained by conventional Optical Coherence Tomography (OCT). In this case report, we present two cases of active ocular toxoplasmosis with multiple recurrences to study pathological changes in retinal and choroidal microvasculature. The findings reveal the involvement of all of the retinal layers in the choroid, with distinct changes in the deep retinal layer.Keywords: ocular toxoplasmosis, retinochoroiditis, recurrent, optical coherence tomography angiography

Published
2023

7. Nutmeg extract potentially alters characteristics of white adipose tissue in rats

Author

Ronny Lesmana, Melisa Siannoto, Gaga I. Nugraha, Hanna Goenawan, Astrid K. Feinisa, Yuni S. Pratiwi, Fifi Veronica, Vita M. Tarawan, Susianti Susianti, and Unang Supratman

Subjects
browning, nutmeg, obesity, PGC‐1α, UCP1, UCP3, Veterinary medicine, SF600-1100
Abstract

Abstract Background Browning of white adipose tissue (WAT) is a promising approach to obesity treatment. During browning, WAT transforms into beige adipose tissue through stimulation of the peroxisome proliferator activated receptor γ (PPARγ). Nutmeg, one of the Indonesian herbs, reportedly has dual roles as a PPARα/γ partial agonist. Even though nutmeg has been traditionally used in body weight reduction, there is limited information regarding the potential role of nutmeg in browning of WAT. Objectives In this study, we explored the effect of nutmeg seed extract (NuSE) as a potential inductor of WAT browning. Methods Twelve male Wistar rats, 5–6 weeks old, were divided into control and nutmeg groups. The rats in nutmeg group were given NuSE for 12 weeks by oral gavage. After 12 weeks, the rat's inguinal WAT and brown adipose tissue (BAT) were collected, weighed and stored at − 80°C until use. Results We observed that even though NuSE did not reduce the final body weight, it significantly reduced body weight gain. NuSE also increased protein levels of peroxisome proliferator activated receptor γ coactivator 1α (PGC‐1α) and uncoupling protein 3 (UCP3) significantly and tended to increase UCP2 and UCP1 levels. Furthermore, NuSE induced macroscopic and microscopic morphological changes of inguinal WAT, marked by significantly increased adipocyte numbers and decreased adipocyte size. Conclusions Even though NuSE did not increase UCP1 significantly, it potentially alters inguinal WAT characteristics and leads to browning through PGC‐1α and UCP3 induction. However, UCP3’s specific mechanism in WAT browning remains unclear. Our findings could contribute to obesity treatment in the future.

Published
2021
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8. The Effect of Nutmeg Seed (M. fragrans) Extracts Induces Apoptosis in Melanoma Maligna Cell’s (B16-F10)

Author

Susianti Susianti, Ronny Lesmana, Supriatno Salam, Euis Julaeha, Yuni Susanti Pratiwi, Nova Sylviana, Hanna Goenawan, Ahmad Kurniawan, and Unang Supratman

Subjects
Medicine (General), R5-920
Abstract

BACKGROUND: Nutmeg (Myristica fragrans H.), one of native plants of Maluku Indonesia, has long been used as traditional medicines especially to treat tumors, externally to treat skin infections. M. fragrans also has important biological activities as anticancer. However, antimelanoma activity of M. fragrans remains unknown. The aim of this study is to compare M. fragrans extracts as anticancer on melanoma B16-F10 cells by inducing apoptosis. METHODS: M. fragrans seed was extracted with ethanol then fractionated with n-hexane, ethyl acetate, and n-butanol. B16-F10 melanoma cells were cultured and treated with various doses and tested using resazurin reduction assay. Apoptosis signalling via caspase-3 was measured by using western blot. RESULTS: The extract and fractions of M. fragrans reduced viability of cells with IC50 value for ethanol extract 21.83 µg/mL, ethyl acetate fraction 21.66 µg/mL, n-hexane fraction 47.53 µg/mL, and n-butanol fraction >1,000 µg/mL. The active fraction of ethyl acetate induced apoptosis via caspase-3 proteins similar with cisplatin as positive control in B16-F10 cells at 10 hours treatment. CONCLUSION: Taken together, M. fragrans ethyl acetate fraction has the highest IC50 than n-hexane and n-butanol fractions that significantly inhibited B16-F10 cell proliferation by inducing apoptosis via caspase-3. It provides the insight that it has the most potential activity as a chemopreventive agent for addressing melanoma skin cancer. KEYWORDS: M. fragrans, apoptosis, fraction, melanoma

Published
2021
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9. Pengaruh Ekstrak Kulit Manggis (Garcinia mangostana L.) TERHADAP Testis Tikus Putih yang Diberi Paparan Gelombang Elektromagnetik Handphone

Author

Muhartono Muhartono, Andrian Rivanda, Anggraeni Janar Wulan, and Susianti Susianti

Subjects
antioxidants, electromagnetic wave, handphone, mangosteen peel, testicle, Medicine, Medicine (General), R5-920
Abstract

Mobile phone electromagnetic waves will induce elevated reactive oxygen species (ROS) that may cause testicle histopathological changes. Resolving this condition, the antioxidants contained in mangosteen peel are needed. This study was to determine the effects of ethanol extract from mangosteen peel (Garcinia mangostana L.) in order to repair testicle histopathological changes, specifically spermatozoa and spermatogenic cells on Sprague dawley strain white male rats (Rattus norvegicus) that had been exposed by handphone electromagnetic waves. This study were used 25 Sprague dawley strain white male rats with 200-300 gram body weight, then the samples were divided into 5 groups which consist of Control Group 1 (K1) with no treatments were given in rats, Control 2 (K2) were given Nacl 0,9 % and mobile phone electromagnetic waves exposures. The Treatment group (P1), (P2), and (P3) were given ethanol extract from mangosteen peel with multilevel dosage of 50, 100, 200 mg / kgBW and exposure to mobile phone electromagnetic wave for 3 hours per day along for 28 days. The result of this study showed mean of sperm cells on K1=173.75±SD 16.978, K2=101.75±7.455 SD, P1=148.50±SD 10.149, 10.247 P2=162.50± SD, P3=180.75 7.365 ± SD and mean of spermatogenic cells on K1=306.75±SD 11.955, K2= 157.00±7.303 SD, P1=243.50±SD 21.672 10.340 P2=266.75±SD P3=294.75±13.150 SD. One Way Anova test (p

Published
2017
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11. Pengaruh Ekstrak Jintan Hitam (Nigella Sativa L.) terhadap Gambaran Histopatologi Hepar, Paru, dan Testis Tikus Putih (Rattus Norvegicus) yang Diinduksi Gentamisin

Author

Susianti

Subjects
Education (General), L7-991, Science (General), Q1-390
Abstract

DOWNLOAD Gentamisin merupakan salah satu antibiotik dari golongan aminoglikosida yang sering digunakan karena harganya relatif lebih terjangkau dan efektif. Namun gentamisin memiliki efek samping terhadap berbagai organ. Efek toksik gentamisin berbagai organ dapat dinetralisir oleh antioksidan yang terdapat dalam ekstrak tanaman obat. Penelitian ini bertujuan untuk mengetahui pengaruh ekstrak jintan hitam (Nigella sativa L.) terhadap berbagai organ diantaranya hepar, paru dan testis tikus putih (Rattus norvegicus) yang diinduksi gentamisin.Penelitian menggunakan 25 ekor tikus putih jantan galur Sprague dawley. Tikus secara acak dibagi menjadi 5 kelompok yaitu K1 (aquadest), K2 (gentamisin intraperitoneal/ip 80 mg/KgBB), K3 (gentamisin ip 80 mg/KgBB+ ekstrak jinten hitam 500 mg/KgBB), K4 (gentamisin ip 80 mg/KgBB+ ekstrak jinten hitam 1000 mg/KgBB) dan K5 (gentamisin ip 80 mg/KgBB+ ekstrak jinten hitam 1500 mg/KgBB). Gentamisin diberikan selama 8 hari dan ekstrak jintan hitam selama 10 hari, lalu tikus diterminasi. Gambaran histopatologi hati, paru dan testis tikus dengan pewarnaan hematoksilin eosin diamati dibawah mikroskop dan dilakukan analisis data. Dari hasil penelitian ini dapat disimpulkan bahwa terdapat pengaruh pemberian ekstrak jintan hitam (Nigella sativa L.) terhadap gambaran histopatologi hepar, paru dantestis tikus putih (Rattus norvegicus) yang diinduksi gentamisin. Kata Kunci: Gentamisin, hepar, Nigella sativa L., paru, testis

Published
2015
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12. PENGARUH MINYAK GORENG BEKAS YANG DIMURNIKAN DENGAN BUAH MENGKUDU (Morinda citrifotia) TERHADAP GAMBARAN HISTOPATOLOGI HEPAR DAN JANTUNG TIKUS

Author

Susianti Susanti

Subjects
minyak goreng bekas, mengkudu, Morinda citrifotia, hepar, jantung, used cooking oil, noni fruit, Morinda citrifolia, liver, heart, Medicine (General), R5-920
Abstract

Pemanasan minyak goreng secara berulang-ulang akan menyebabkan pembentukan radikalbebas. Metode pemurnian minyak goreng bekas dapat dilakukan dengan penambahanantioksidan ke dalam minyak. Salah satu tanaman yang kaya antioksidan adalah mengkudu.Tujuan dalam penelitian ini adalah untuk mengetahui pengaruh minyak goreng bekai yangdimurnikan dengan buah mengkudu (Morinda Citrifotia,) terhadap gambaran histopatologihepar dan jantung (miokardium dan arteri koronaria) tikus.Sampel penelitian sebanyak 20 ekor yang dipilih secara acak dibagi dalam 4 kelompok dandiberi perlakuan selama 1 bulan. Kl (kontrol) diberikan aquadest 1Oprl/gram BB,K2 diberikan1Opl/gram BB minyak goreng bekas penggorengan lele 3 jam, K3 diberikan 1gprl/gram BBminyak goreng bekas penggorengan lele 6 jam, dan K4 diberikan regenerasi minyak gorengbekas penggorengan lele 6 jam dengan buah mengkudu sebanyak 1Opl/gram BB.Pemberian minyak goreng bekas yang dimurnikan dengan buah mengkudu (Morinda citrifotia)menurunkan jumlah kerusakan hepatosit, menurunkan,jumlah persentase inTiltrasi lemak padasel otot jantung dan menurunkan ketebalan arteri koronaria tikus wistar jantan.ABSTRACTHeating cooking oil repeatly will result formation of free radicals. Purifying used cooking oil canbe done by giving antioxidant to the oil. Noni fruit is one of the ptant that be rich of antioxidants.The aim of this research is to investigate the effect of used cooking oit which purified by nonifruit to liver and heaft (myocardium and caronary artery) histopathology appearance heart ofrat.ln this study, 20 male Wistar rats divided randomly into 4 groups and given treatment for 4weeks. Kl (control) is given aquadest), K2 (given used cooking oit with 3 hours heating 10 mLlgram BW), K3 (given used cooking oil with 6 hours heating 10 ml/gram BW), K4 (given usedcooking oilwith 6 hours of heating which purified by nonifruit 10 mugram BW).Giving used coaking oil which purified by noni fruit decrease fhe damage of hepatocyte,decreased the fatty infiltration percentage in myocardium and decreased the thickness ofcoronary artery.

Published
2014
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16. Lower serum BDNF as a predictor of post-stroke cognitive impairment in acute ischemic stroke patients [version 2; peer review: 1 approved, 1 not approved]

Author

Ismail Setyopranoto, Astuti Prodjohardjono, Sri Sutarni, Noor Alia Susianti, Muhammad Hardhantyo, and Amelia Nur Vidyanti

Subjects
Research Article, Articles, serum BDNF, predictor, post-stroke cognitive impairment, acute ischemic stroke
Abstract

Background Reduced level of serum brain-derived neurotrophic factor (BDNF) in acute stroke patients is associated with poor outcomes. We aimed to identify the role of serum BDNF level as a predictor for post-stroke cognitive impairment (PSCI). Methods This was a prospective study. We recruited acute ischemic stroke patients in Dr. Sardjito General Hospital Yogyakarta, Indonesia followed them up for 90 days (3 months). Serum BDNF was collected at day 5 and day 30 of stroke onset and measured by enzyme-linked immunosorbent assay (ELISA). Montreal Cognitive Assessment (MoCA) was used to measure the cognitive function at 90 days of follow up. Receiver operating characteristic (ROC) curve was conducted to measure the cut-off point of the BDNF level. Factors independently associated with PSCI were analyzed by using stepwise regression. Results Among 89 patients recruited, 60 patients (67.41%) developed PSCI. The mean age of PSCI and non-PSCI patients was 62.7 ± 9.5 and 57.5 ± 8.7, respectively (p = 0.01). Patients with dyslipidemia were less likely to develop PSCI (OR 0.10, 95%CI 0.02-0.51, p < 0.05). In addition, patients with day 5-serum BDNF level < 23.29 ng/mL were five times more likely to develop PSCI compared with their counterparts (OR 5.15, 95%CI 1.26-21.09, p < 0.05). Conclusions Among acute ischemic stroke patients, those with serum BDNF

Published
2024
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17. Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author

Steinmetz, Jaimie D, Seeher, Katrin Maria, Schiess, Nicoline, Nichols, Emma, Cao, Bochen, Servili, Chiara, Cavallera, Vanessa, Cousin, Ewerton, Hagins, Hailey, Moberg, Madeline E, Mehlman, Max L, Abate, Yohannes Habtegiorgis, Abbas, Jaffar, Abbasi, Madineh Akram, Abbasian, Mohammadreza, Abbastabar, Hedayat, Abdelmasseh, Michael, Abdollahi, Mohammad, Abdollahi, Mozhan, Abdollahifar, Mohammad-Amin, Abd-Rabu, Rami, Abdulah, Deldar Morad, Abdullahi, Auwal, Abedi, Aidin, Abedi, Vida, Abeldańo Zuńiga, Roberto Ariel, Abidi, Hassan, Abiodun, Olumide, Aboagye, Richard Gyan, Abolhassani, Hassan, Aboyans, Victor, Abrha, Woldu Aberhe, Abualhasan, Ahmed, Abu-Gharbieh, Eman, Aburuz, Salahdein, Adamu, Lawan Hassan, Addo, Isaac Yeboah, Adebayo, Oladimeji M, Adekanmbi, Victor, Adekiya, Tayo Alex, Adikusuma, Wirawan, Adnani, Qorinah Estiningtyas Sakilah, Adra, Saryia, Afework, Tsion, Afolabi, Aanuoluwapo Adeyimika, Afraz, Ali, Afzal, Saira, Aghamiri, Shahin, Agodi, Antonella, Agyemang-Duah, Williams, Ahinkorah, Bright Opoku, Ahmad, Aqeel, Ahmad, Danish, Ahmad, Sajjad, Ahmadzade, Amir Mahmoud, Ahmed, Ali, Ahmed, Ayman, Ahmed, Haroon, Ahmed, Jivan Qasim, Ahmed, Luai A, Ahmed, Muktar Beshir, Ahmed, Syed Anees, Ajami, Marjan, Aji, Budi, Ajumobi, Olufemi, Akade, Seyed Esma'il, Akbari, Morteza, Akbarialiabad, Hossein, Akhlaghi, Shiva, Akinosoglou, Karolina, Akinyemi, Rufus Olusola, Akonde, Maxwell, Al Hasan, Syed Mahfuz, Alahdab, Fares, AL-Ahdal, Tareq Mohammed Ali, Al-amer, Rasmieh Mustafa, Albashtawy, Mohammed, AlBataineh, Mohammad T, Aldawsari, Khalifah A, Alemi, Hediyeh, Alemi, Sharifullah, Algammal, Abdelazeem M, Al-Gheethi, Adel Ali Saeed, Alhalaiqa, Fadwa Alhalaiqa Naji, Alhassan, Robert Kaba, Ali, Abid, Ali, Endale Alemayehu, Ali, Liaqat, Ali, Mohammed Usman, Ali, Musa Mohammed, Ali, Rafat, Ali, Shahid, Ali, Syed Shujait Shujait, Ali, Zahid, Alif, Sheikh Mohammad, Alimohamadi, Yousef, Aliyi, Ahmednur Adem, Aljofan, Mohamad, Aljunid, Syed Mohamed, Alladi, Suvarna, Almazan, Joseph Uy, Almustanyir, Sami, Al-Omari, Basem, Alqahtani, Jaber S, Alqasmi, Ibrahim, Alqutaibi, Ahmed Yaseen, Al-Shahi Salman, Rustam, Altaany, Zaid, Al-Tawfiq, Jaffar A, Altirkawi, Khalid A, Alvis-Guzman, Nelson, Al-Worafi, Yaser Mohammed, Aly, Hany, Aly, Safwat, Alzoubi, Karem H, Amani, Reza, Amindarolzarbi, Alireza, Amiri, Sohrab, Amirzade-Iranaq, Mohammad Hosein, Amu, Hubert, Amugsi, Dickson A, Amusa, Ganiyu Adeniyi, Amzat, Jimoh, Ancuceanu, Robert, Anderlini, Deanna, Anderson, David B, Andrei, Catalina Liliana, Androudi, Sofia, Angappan, Dhanalakshmi, Angesom, Teklit W, Anil, Abhishek, Ansari-Moghaddam, Alireza, Anwer, Razique, Arafat, Mosab, Aravkin, Aleksandr Y, Areda, Demelash, Ariffin, Hany, Arifin, Hidayat, Arkew, Mesay, Ärnlöv, Johan, Arooj, Mahwish, Artamonov, Anton A, Artanti, Kurnia Dwi, Aruleba, Raphael Taiwo, Asadi-Pooya, Ali A, Asena, Tilahun Ferede, Asghari-Jafarabadi, Mohammad, Ashraf, Muhammad, Ashraf, Tahira, Atalell, Kendalem Asmare, Athari, Seyyed Shamsadin, Atinafu, Bantalem Tilaye Tilaye, Atorkey, Prince, Atout, Maha Moh'd Wahbi, Atreya, Alok, Aujayeb, Avinash, Avan, Abolfazl, Ayala Quintanilla, Beatriz Paulina, Ayatollahi, Haleh, Ayinde, Olatunde O, Ayyoubzadeh, Seyed Mohammad, Azadnajafabad, Sina, Azizi, Zahra, Azizian, Khalil, Azzam, Ahmed Y, Babaei, Mahsa, Badar, Muhammad, Badiye, Ashish D, Baghdadi, Soroush, Bagherieh, Sara, Bai, Ruhai, Baig, Atif Amin, Balakrishnan, Senthilkumar, Balalla, Shivanthi, Baltatu, Ovidiu Constantin, Banach, Maciej, Bandyopadhyay, Soham, Banerjee, Indrajit, Baran, Mehmet Firat, Barboza, Miguel A, Barchitta, Martina, Bardhan, Mainak, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrow, Amadou, Bashash, Davood, Bashiri, Hamideh, Bashiru, Hameed Akande, Basiru, Afisu, Basso, João Diogo, Basu, Sanjay, Batiha, Abdul-Monim Mohammad, Batra, Kavita, Baune, Bernhard T, Bedi, Neeraj, Begde, Ahmet, Begum, Tahmina, Behnam, Babak, Behnoush, Amir Hossein, Beiranvand, Maryam, Béjot, Yannick, Bekele, Alehegn, Belete, Melaku Ashagrie, Belgaumi, Uzma Iqbal, Bemanalizadeh, Maryam, Bender, Rose G, Benfor, Bright, Bennett, Derrick A, Bensenor, Isabela M, Berice, Betyna, Bettencourt, Paulo J G, Beyene, Kebede A, Bhadra, Abhishek, Bhagat, Devidas S, Bhangdia, Kayleigh, Bhardwaj, Nikha, Bhardwaj, Pankaj, Bhargava, Ashish, Bhaskar, Sonu, Bhat, Ajay Nagesh, Bhat, Vivek, Bhatti, Gurjit Kaur, Bhatti, Jasvinder Singh, Bhatti, Rajbir, Bijani, Ali, Bikbov, Boris, Bilalaga, Mariah Malak, Biswas, Atanu, Bitaraf, Saeid, Bitra, Veera R, Bjørge, Tone, Bodolica, Virginia, Bodunrin, Aadam Olalekan, Boloor, Archith, Braithwaite, Dejana, Brayne, Carol, Brenner, Hermann, Briko, Andrey, Bringas Vega, Maria L, Brown, Julie, Budke, Christine M, Buonsenso, Danilo, Burkart, Katrin, Burns, Richard A, Bustanji, Yasser, Butt, Muhammad Hammad, Butt, Nadeem Shafique, Butt, Zahid A, Cabral, Lucas Scotta, Caetano dos Santos, Florentino Luciano, Calina, Daniela, Campos-Nonato, Ismael R, Cao, Chao, Carabin, Hélène, Cárdenas, Rosario, Carreras, Giulia, Carvalho, Andre F, Castańeda-Orjuela, Carlos A, Casulli, Adriano, Catalá-López, Ferrán, Catapano, Alberico L, Caye, Arthur, Cegolon, Luca, Cenderadewi, Muthia, Cerin, Ester, Chacón-Uscamaita, Pamela R, Chan, Jeffrey Shi Kai, Chanie, Gashaw Sisay, Charan, Jaykaran, Chattu, Vijay Kumar, Chekol Abebe, Endeshaw, Chen, Hui, Chen, Jianqi, Chi, Gerald, Chichagi, Fatemeh, Chidambaram, Saravana Babu, Chimoriya, Ritesh, Ching, Patrick R, Chitheer, Abdulaal, Chong, Yuen Yu, Chopra, Hitesh, Choudhari, Sonali Gajanan, Chowdhury, Enayet Karim, Chowdhury, Rajiv, Christensen, Hanne, Chu, Dinh-Toi, Chukwu, Isaac Sunday, Chung, Eric, Coberly, Kaleb, Columbus, Alyssa, Comachio, Josielli, Conde, Joao, Cortesi, Paolo Angelo, Costa, Vera Marisa, Couto, Rosa A S, Criqui, Michael H, Cruz-Martins, Natália, Dabbagh Ohadi, Mohammad Amin, Dadana, Sriharsha, Dadras, Omid, Dai, Xiaochen, Dai, Zhaoli, D'Amico, Emanuele, Danawi, Hadi A, Dandona, Lalit, Dandona, Rakhi, Darwish, Amira Hamed, Das, 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Tabatabaei, Seyyed Mohammad, Tabatabai, Shima, Tabish, Mohammad, Taheri, Majid, Tahvildari, Azin, Tajbakhsh, Ardeshir, Tampa, Mircea, Tamuzi, Jacques JL Lukenze, Tan, Ker-Kan, Tang, Haosu, Tareke, Minale, Tarigan, Ingan Ukur, Tat, Nathan Y, Tat, Vivian Y, Tavakoli Oliaee, Razieh, Tavangar, Seyed Mohammad, Tavasol, Arian, Tefera, Yibekal Manaye, Tehrani-Banihashemi, Arash, Temesgen, Worku Animaw, Temsah, Mohamad-Hani, Teramoto, Masayuki, Tesfaye, Amensisa Hailu, Tesfaye, Edosa Geta, Tesler, Riki, Thakali, Ocean, Thangaraju, Pugazhenthan, Thapa, Rajshree, Thapar, Rekha, Thomas, Nikhil Kenny, Thrift, Amanda G, Ticoalu, Jansje Henny Vera, Tillawi, Tala, Toghroli, Razie, Tonelli, Marcello, Tovani-Palone, Marcos Roberto, Traini, Eugenio, Tran, Nghia Minh, Tran, Ngoc-Ha, Tran, Phu Van, Tromans, Samuel Joseph, Truelsen, Thomas Clement, Truyen, Thien Tan Tri Tai, Tsatsakis, Aristidis, Tsegay, Guesh Mebrahtom, Tsermpini, Evangelia Eirini, Tualeka, Abdul Rohim, Tufa, Derara Girma, Ubah, Chukwudi S, Udoakang, Aniefiok John, Ulhaq, Inam, Umair, Muhammad, Umakanthan, Srikanth, Umapathi, Krishna Kishore, Unim, Brigid, Unnikrishnan, Bhaskaran, Vaithinathan, Asokan Govindaraj, Vakilian, Alireza, Valadan Tahbaz, Sahel, Valizadeh, Rohollah, Van den Eynde, Jef, Vart, Priya, Varthya, Shoban Babu, Vasankari, Tommi Juhani, Vaziri, Siavash, Vellingiri, Balachandar, Venketasubramanian, Narayanaswamy, Verras, Georgios-Ioannis, Vervoort, Dominique, Villafańe, Jorge Hugo, Villani, Leonardo, Vinueza Veloz, Andres Fernando, Viskadourou, Maria, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Volovat, Simona Ruxandra, Vu, Loc Tri, Vujcic, Isidora S, Wagaye, Birhanu, Waheed, Yasir, Wahood, Waseem, Walde, Mandaras Tariku, Wang, Fang, Wang, Shu, Wang, Yanzhong, Wang, Yuan-Pang, Waqas, Muhammad, Waris, Abdul, Weerakoon, Kosala Gayan, Weintraub, Robert G, Weldemariam, Abrha Hailay, Westerman, Ronny, Whisnant, Joanna L, Wickramasinghe, Dakshitha Praneeth, Wickramasinghe, Nuwan Darshana, Willekens, Barbara, Wilner, Lauren B, Winkler, Andrea Sylvia, Wolfe, Charles D A, Wu, Ai-Min, Wulf Hanson, Sarah, Xu, Suowen, Xu, Xiaoyue, Yadollahpour, Ali, Yaghoubi, Sajad, Yahya, Galal, Yamagishi, Kazumasa, Yang, Lin, Yano, Yuichiro, Yao, Yao, Yehualashet, Sisay Shewasinad, Yeshaneh, Alex, Yesiltepe, Metin, Yi, Siyan, Yiğit, Arzu, Yiğit, Vahit, Yon, Dong Keon, Yonemoto, Naohiro, You, Yuyi, Younis, Mustafa Z, Yu, Chuanhua, Yusuf, Hadiza, Zadey, Siddhesh, Zahedi, Mohammad, Zakham, Fathiah, Zaki, Nazar, Zali, Alireza, Zamagni, Giulia, Zand, Ramin, Zandieh, Ghazal G Z, Zangiabadian, Moein, Zarghami, Amin, Zastrozhin, Mikhail Sergeevich, Zeariya, Mohammed G M, Zegeye, Zelalem Banjaw, Zeukeng, Francis, Zhai, Chunxia, Zhang, Chen, Zhang, Haijun, Zhang, Yunquan, Zhang, Zhi-Jiang, Zhao, Hanqing, Zhao, Yang, Zheng, Peng, Zhou, Hengxing, Zhu, Bin, Zhumagaliuly, Abzal, Zielińska, Magdalena, Zikarg, Yossef Teshome, Zoladl, Mohammad, Murray, Christopher J L, Ong, Kanyin Liane, Feigin, Valery L, Vos, Theo, and Dua, Tarun

Published
2024
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21. Zinc chloride may regulate hematopoietic stem cell aging and pro-inflammatory cytokines in systemic lupus erythematosus [version 1; peer review: awaiting peer review]

Author

Hani Susianti, Achmad Arrizal, Bakhtiar Yusuf Habibi, Friska Supriyanto, Matthew Brian Khrisna, Kusworini Handono, Cesarius Singgih Wahono, Perdana Aditya Rahman, Mirza Zaka Pratama, and Syahrul Chilmi

Subjects
Research Article, Articles, systemic lupus erythematosus, zinc chloride, aging, pro-inflammatory cytokines, hematopoietic stem cells
Abstract

Background: The immune cells of patients with systemic lupus erythematosus (SLE) age earlier than those of normal subjects. However, the senescence of circulating hematopoietic stem cells (HSCs) in patients with SLE is not well understood, and it is unclear whether zinc treatment can regulate the senescence and proinflammatory cytokine production of HSCs in these patients. Methods: Clinical data were collected on 38 patients with SLE and 35 healthy controls (HCs), and the complete blood count, circulating HSC number, and p16 (a senescence marker) expression in the peripheral blood of these participants were analyzed via flow cytometry. Pooled circulating HSCs were isolated using leukapheresis. The effects of zinc chloride exposure on the pooled HSCs of each group were determined in vitro. Levels of the proinflammatory cytokines IL-6 and IL17, regulatory cytokine TGF-β, p16, and regulator T-cells (Tregs) were evaluated 72 h after incubation with 50 or 100 µM zinc chloride. Results: The number of circulating HSCs did not differ between the two groups (p=0.1685). The expression of p16 in HSCs was higher in the SLE group than in the HC group (p = 0.0043), and patients with SLE exhibited higher levels of IL-6, IL-17, and p16 in pooled HSCs (p =0.0025, p Conclusions: Circulating HSCs in SLE are more aged and produce more proinflammatory cytokines. Zinc chloride treatment might prevent immunoaging and inhibit proinflammatory cytokine–producing cells in patients with SLE.

Published
2023
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22. The implication of interleukin-2 on the expression of CD56 bright, CD56 dim, and interferon-γ in patients with systemic lupus erythematosus [version 1; peer review: awaiting peer review]

Author

Dwi Soelistyoningsih, Hani Susianti, Handono Kalim, Kusworini Handono, and Jonny Karunia Fajar

Subjects
Research Article, Articles, systemic lupus erythematosus, interleukin – 2, natural killer cells, CD56bright, CD56dim, interferon – γ
Abstract

Background: Interleukin-2 (IL-2) stimulation had been reported as having a beneficial impact to the expression of CD56 bright, CD56 dim, and interferon-γ (IFN-γ) in the case of immunological dysfunction diseases. However, in the case of systemic lupus erythematosus (SLE), the role of IL-2 had never been investigated. The objective of this study was to assess the impact of IL-2 on the expression of CD56 bright, CD56 dim, and IFN-γ in SLE patients. Methods: An experimental study was conducted by involving peripheral blood mononuclear cells isolated from six SLE patients. The study consisted of four groups based on IL-2 stimulation: D0 (0U/ml), D1 (50U/ml), D2 (150U/ml), and D3 (250U/ml); and they were then cultured for 72 hours. The levels of CD56 bright and CD56 dim were measured by FACSMelody TM, while the levels of IFN-γ were measured using ELISA. Results: In group D0, D1, D2, and D3; the levels of CD56 bright were 57.27±37.27, 241.16±64.41, 256.94±50.95, and 259.37±36.44 x1000 cells/mm3 respectively. Moreover, the levels of CD56 dim were 812.85±167.37, 631.98±129.90, 616.42±157.97, and 615.90±155.57 x1000 cells/mm3 respectively. On the other hand, the levels of IFN-γ were 24.01±2.56, 26.09±4.79, 30.11±5.34, and 32.43±7.14 pg/ml respectively. Our analysis elucidated that the administration of IL-2 provided potential impact to the levels of CD56 bright, but not to the levels of CD56 dim and IFN-γ. Our findings indicated that the increased dosage of IL-2 resulted in a more significant impact on CD56 bright. Conclusions: Our study clarifies that IL-2 provides a beneficial impact on CD56 bright expression in SLE patients.

Published
2023
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23. Association of the CD28 markers with the disease activity in systemic lupus erythematosus patients [version 1; peer review: awaiting peer review]

Author

Mirza Zaka Pratama, Kusworini Handono, Handono Kalim, and Hani Susianti

Subjects
Research Article, Articles, Systemic Lupus Erythematosus, CD28 markers, disease monitoring
Abstract

Background: Systemic Lupus Erythematosus (SLE) is a complex autoimmune disease with diverse manifestations and unpredictable activity. CD28 markers, particularly sCD28, is a promising biomarker for evaluating SLE disease activity. This study aimed to investigate the significance of CD28 markers in evaluating disease activity in SLE and the role of sCD28 in various clinical manifestations. Methods: A total of 40 female subjects, aged between 18 and 45 years, who fulfilled the 2019 EULAR/ACR classification criteria for SLE were recruited in this study. Twenty healthy matched individuals were also recruited as control. Comprehensive data on demographic information, clinical manifestations, laboratory test findings, and treatment history were collected from all participants. The Indonesian version of SLEDAI-2K score was utilized to assess disease activity, categorizing patients into active SLE and lupus low disease activity (LLDAS). Collected data were analyzed on SPSS for Windows version 25.0. Results: Patients with SLE in LLDAS category had significantly lower SLEDAI scores (1.8 ± 1.4 vs 11.7 ± 4.9, p+CD28 + cells (5.7 ± 4.1%) and the highest sCD28 concentration (26.2 ± 11.3 ng/ml) compared to other groups. Moreover, sCD28 concentration demonstrated a moderate positive correlation with SLE disease activity. In most cases, higher sCD28 concentrations were associated with clinical manifestations, particularly in neuropsychiatric lupus (OR 7.1 [1.8 – 67.9], p=0.047), nephritis (OR 14.5 [1.6 – 131.9], p=0.017), and mucocutaneous manifestations (OR 3.4 [1.9 – 12.8], p=0.035). Conclusions: Our study establishes the link between CD28 markers and disease activity, including certain clinical manifestations in SLE. We suggest that CD28 has a potential role in predicting disease activity. However, further research through longitudinal studies is required to strengthen these findings.

Published
2023
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24. Synergistic effect of the combination of Chrysanthemum cinerariifolium (Trev.) and doxorubicin in inhibiting PI3K and Cyclin D in oral squamous cell carcinoma: in vitro study [version 1; peer review: awaiting peer review]

Author

Anik Listiyana, Yuanita Lely Rachmawati, Hani Susianti, Nurdiana Nurdiana, Hidayat Sujuti, Roihatul Mutiah, and Agustina Tri Endharti

Subjects
Research Article, Articles, Chrysanthemum cinerariifolium (Trev.), Cyclin D, doxorubicin, IC50, OSCC, PI3K
Abstract

Background: The most common type of lips and oral cavity cancer is oral squamous cell carcinoma (OSCC). Doxorubicin (DX) is commonly used as a chemotherapy drug, but its use is limited due to risk factors and drug resistance. Chrysanthemum cinerariifolium (Trev.) (CC) has potential as an anticancer agent. Combining the plant extract and chemotherapy drug might prevent OSCC proliferation by inhibiting PI3K and cyclin D protein. Therefore, the present study aimed to determine the synergistic effect of the combination of C. cinerariifolium (Trev.) and doxorubicin in inhibiting PI3K and Cyclin D protein. Methods: Human oral squamous carcinoma cell lines SCC-9 were used in this study. A cytotoxicity assay was performed to obtain the IC 50 value of CC ethanol extract and DX on the SCC-9 cell line. Synergism evaluation of the combination CC and DX was analyzed using CompuSyn software. ELISA and the immunofluorescent assay were performed to determine the level of PI3K and cyclin D in the SCC-9 cell line after being treated with IC 50 value of CC, IC 50 value of DX and three combinations of CC and DX [7/8 IC 50 CC + 1/8 IC 50 DX (dose 1), 6/8 IC 50 CC + 2/8 IC 50 DX (dose 2), and 4/8 IC 50 CC + 4/8 IC 50 DX (dose 3). Results: CC stem ethanol extract and DX inhibited the proliferation of SCC-9 cell lines with the IC 50 value of 133.4 µg/mL and 288.3 nM, respectively. The combination of CC and DX at dose 2 (6/8 IC 50 CC + 2/8 IC 50 DX) exhibited a high decrease in PI3K and cyclin D expression. Conclusions: The combination of C. cinerariifolium and doxorubicin synergistically declined OSCC proliferation by inhibiting PI3K and cyclin D expression.

Published
2023
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26. Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author

Steinmetz, J, Seeher, K, Schiess, N, Nichols, E, Cao, B, Servili, C, Cavallera, V, Cousin, E, Hagins, H, Moberg, M, Mehlman, M, Abate, Y, Abbas, J, Abbasi, M, Abbasian, M, Abbastabar, H, Abdelmasseh, M, Abdollahi, M, Abdollahifar, M, Abd-Rabu, R, Abdulah, D, Abdullahi, A, Abedi, A, Abedi, V, Abeldano Zuniga, R, Abidi, H, Abiodun, O, Aboagye, R, Abolhassani, H, Aboyans, V, Abrha, W, Abualhasan, A, Abu-Gharbieh, E, Aburuz, S, Adamu, L, Addo, I, Adebayo, O, Adekanmbi, V, Adekiya, T, Adikusuma, W, Adnani, Q, Adra, S, Afework, T, Afolabi, A, Afraz, A, Afzal, S, Aghamiri, S, Agodi, A, Agyemang-Duah, W, Ahinkorah, B, Ahmad, A, Ahmad, D, Ahmad, S, Ahmadzade, A, Ahmed, A, Ahmed, H, Ahmed, J, Ahmed, L, Ahmed, M, Ahmed, S, Ajami, M, Aji, B, Ajumobi, O, Akade, S, Akbari, M, Akbarialiabad, H, Akhlaghi, S, Akinosoglou, K, Akinyemi, R, Akonde, M, Al Hasan, S, Alahdab, F, Al-Ahdal, T, Al-Amer, R, Albashtawy, M, Albataineh, M, Aldawsari, K, Alemi, H, Alemi, S, Algammal, A, Al-Gheethi, A, Alhalaiqa, F, Alhassan, R, Ali, A, Ali, E, Ali, L, Ali, M, Ali, R, Ali, S, Shujait Ali, S, Ali, Z, Alif, S, Alimohamadi, Y, Aliyi, A, Aljofan, M, Aljunid, S, Alladi, S, Almazan, J, Almustanyir, S, Al-Omari, B, Alqahtani, J, Alqasmi, I, Alqutaibi, A, Al-Shahi Salman, R, Altaany, Z, Al-Tawfiq, J, Altirkawi, K, Alvis-Guzman, N, Al-Worafi, Y, Aly, H, Aly, S, Alzoubi, K, Amani, R, Amindarolzarbi, A, Amiri, S, Amirzade-Iranaq, M, Amu, H, Amugsi, D, Amusa, G, Amzat, J, Ancuceanu, R, Anderlini, D, Anderson, D, Andrei, C, Androudi, S, Angappan, D, Angesom, T, Anil, A, Ansari-Moghaddam, A, Anwer, R, Arafat, M, Aravkin, A, Areda, D, Ariffin, H, Arifin, H, Arkew, M, Arnlov, J, Arooj, M, Artamonov, A, Artanti, K, Aruleba, R, Asadi-Pooya, A, Asena, T, Asghari-Jafarabadi, M, Ashraf, M, Ashraf, T, Atalell, K, Athari, S, Atinafu, B, Atorkey, P, Atout, M, Atreya, A, Aujayeb, A, Avan, A, Ayala Quintanilla, B, Ayatollahi, H, Ayinde, O, Mohammad Ayyoubzadeh, S, Azadnajafabad, S, Azizi, Z, Azizian, K, Azzam, A, Babaei, M, Badar, M, Badiye, A, Baghdadi, S, Bagherieh, S, Bai, R, Baig, A, Balakrishnan, S, Balalla, S, Baltatu, O, Banach, M, Bandyopadhyay, S, Banerjee, I, Baran, M, Barboza, M, Barchitta, M, Bardhan, M, Barker-Collo, S, Barnighausen, T, Barrow, A, Bashash, D, Bashiri, H, Bashiru, H, Basiru, A, Basso, J, Basu, S, Batiha, A, Batra, K, Baune, B, Bedi, N, Begde, A, Begum, T, Behnam, B, Behnoush, A, Beiranvand, M, Bejot, Y, Bekele, A, Belete, M, Belgaumi, U, Bemanalizadeh, M, Bender, R, Benfor, B, Bennett, D, Bensenor, I, Berice, B, Bettencourt, P, Beyene, K, Bhadra, A, Bhagat, D, Bhangdia, K, Bhardwaj, N, Bhardwaj, P, Bhargava, A, Bhaskar, S, Bhat, A, Bhat, V, Bhatti, G, Bhatti, J, Bhatti, R, Bijani, A, Bikbov, B, Bilalaga, M, Biswas, A, Bitaraf, S, Bitra, V, Bjorge, T, Bodolica, V, Bodunrin, A, Boloor, A, Braithwaite, D, Brayne, C, Brenner, H, Briko, A, Bringas Vega, M, Brown, J, Budke, C, Buonsenso, D, Burkart, K, Burns, R, Bustanji, Y, Butt, M, Butt, N, Butt, Z, Cabral, L, dos Santos, F, Calina, D, Campos-Nonato, I, Cao, C, Carabin, H, Cardenas, R, Carreras, G, Carvalho, A, Castaneda-Orjuela, C, Casulli, A, Catala-Lopez, F, Catapano, A, Caye, A, Cegolon, L, Cenderadewi, M, Cerin, E, Chacon-Uscamaita, P, Chan, J, Chanie, G, Charan, J, Chattu, V, Chekol Abebe, E, Chen, H, Chen, J, Chi, G, Chichagi, F, Chidambaram, S, Chimoriya, R, Ching, P, Chitheer, A, Chong, Y, Chopra, H, Choudhari, S, Chowdhury, E, Chowdhury, R, Christensen, H, Chu, D, Chukwu, I, Chung, E, Coberly, K, Columbus, A, Comachio, J, Conde, J, Cortesi, P, Costa, V, Couto, R, Criqui, M, Cruz-Martins, N, Dabbagh Ohadi, M, Dadana, S, Dadras, O, Dai, X, Dai, Z, D'Amico, E, Danawi, H, Dandona, L, Dandona, R, Darwish, A, Das, S, Dascalu, A, Dash, N, Dashti, M, De la Hoz, F, de la Torre-Luque, A, De Leo, D, Dean, F, Dehghan, A, Dejene, H, Demant, D, Demetriades, A, Demissie, S, Deng, X, Desai, H, Devanbu, V, Dhama, K, Dharmaratne, S, Dhimal, M, Dias da Silva, D, Diaz, D, Dibas, M, Ding, D, Dinu, M, Dirac, M, Diress, M, Do, T, Doan, K, Dodangeh, M, Doheim, M, Dokova, K, Dongarwar, D, Dsouza, H, Dube, J, Duraisamy, S, Durojaiye, O, Dutta, S, Dziedzic, A, Edinur, H, Eissazade, N, Ekholuenetale, M, Ekundayo, T, El Nahas, N, El Sayed, I, Elahi Najafi, M, Elbarazi, I, Elemam, N, Elgar, F, Elgendy, I, Elhabashy, H, Elhadi, M, Elilo, L, Ellenbogen, R, Elmeligy, O, Elmonem, M, Elshaer, M, Elsohaby, I, Emamverdi, M, Emeto, T, Endres, M, Esezobor, C, Eskandarieh, S, Fadaei, A, Fagbamigbe, A, Fahim, A, Faramarzi, A, Fares, J, Farjoud Kouhanjani, M, Faro, A, Farzadfar, F, Fatehizadeh, A, Fathi, M, Fathi, S, Fatima, S, Feizkhah, A, Fereshtehnejad, S, Ferrari, A, Ferreira, N, Fetensa, G, Firouraghi, N, Fischer, F, Fonseca, A, Force, L, Fornari, A, Foroutan, B, Fukumoto, T, Gadanya, M, Gaidhane, A, Galali, Y, Galehdar, N, Gan, Q, Gandhi, A, Ganesan, B, Gardner, W, Garg, N, Gau, S, Gautam, R, Gebre, T, Gebrehiwot, M, Gebremeskel, G, Gebreslassie, H, Getacher, L, Ghaderi Yazdi, B, Ghadirian, F, Ghaffarpasand, F, Ghanbari, R, Ghasemi, M, Ghazy, R, Ghimire, S, Gholami, A, Gholamrezanezhad, A, Ghotbi, E, Ghozy, S, Gialluisi, A, Gill, P, Glasstetter, L, Gnedovskaya, E, Golchin, A, Golechha, M, Goleij, P, Golinelli, D, Gomes-Neto, M, Goulart, A, Goyal, A, Gray, R, Grivna, M, Guadie, H, Guan, B, Guarducci, G, Guicciardi, S, Gunawardane, D, Guo, H, Gupta, B, Gupta, R, Gupta, S, Gupta, V, Gutierrez, R, Habibzadeh, F, Hachinski, V, Haddadi, R, Hadei, M, Hadi, N, Haep, N, Haile, T, Haj-Mirzaian, A, Hall, B, Halwani, R, Hameed, S, Hamiduzzaman, M, Hammoud, A, Han, H, Hanifi, N, Hankey, G, Hannan, M, Hao, J, Harapan, H, Hareru, H, Hargono, A, Harlianto, N, Haro, J, Hartman, N, Hasaballah, A, Hasan, F, Hasani, H, Hasanian, M, Hassan, A, Hassan, S, Hassanipour, S, Hassankhani, H, Hassen, M, Haubold, J, Hay, S, Hayat, K, Hegazy, M, Heidari, G, Heidari, M, Heidari-Soureshjani, R, Hesami, H, Hezam, K, Hiraike, Y, Hoffman, H, Holla, R, Hopf, K, Horita, N, Hossain, M, Hossain, S, Hosseinzadeh, H, Hosseinzadeh, M, Hostiuc, S, Hu, C, Huang, J, Huda, M, Hussain, J, Hussein, N, Huynh, H, Hwang, B, Ibitoye, S, Ilaghi, M, Ilesanmi, O, Ilic, I, Ilic, M, Immurana, M, Iravanpour, F, Islam, S, Ismail, F, Iso, H, Isola, G, Iwagami, M, Iwu, C, Iyer, M, Jaan, A, Jacob, L, Jadidi-Niaragh, F, Jafari, M, Jafarinia, M, Jafarzadeh, A, Jahankhani, K, Jahanmehr, N, Jahrami, H, Jaiswal, A, Jakovljevic, M, Jamora, R, Jana, S, Javadi, N, Javed, S, Javeed, S, Jayapal, S, Jayaram, S, Jiang, H, Johnson, C, Johnson, W, Jokar, M, Jonas, J, Joseph, A, Joseph, N, Joshua, C, Jurisson, M, Kabir, A, Kabir, Z, Kabito, G, Kadashetti, V, Kafi, F, Kalani, R, Kalantar, F, Kaliyadan, F, Kamath, A, Kamath, S, Kanchan, T, Kandel, A, Kandel, H, Kanmodi, K, Karajizadeh, M, Karami, J, Karanth, S, Karaye, I, Karch, A, Karimi, A, Karimi, H, Karimi Behnagh, A, Kasraei, H, Kassebaum, N, Kauppila, J, Kaur, H, Kaur, N, Kayode, G, Kazemi, F, Keikavoosi-Arani, L, Keller, C, Keykhaei, M, Khadembashiri, M, Khader, Y, Khafaie, 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A., Guo H., Gupta B., Gupta R., Gupta S., Gupta V. B., Gupta V. K., Gutierrez R. A., Habibzadeh F., Hachinski V., Haddadi R., Hadei M., Hadi N. R., Haep N., Haile T. G., Haj-Mirzaian A., Hall B. J., Halwani R., Hameed S., Hamiduzzaman M., Hammoud A., Han H., Hanifi N., Hankey G. J., Hannan M. A., Hao J., Harapan H., Hareru H. E., Hargono A., Harlianto N. I., Haro J. M., Hartman N. N., Hasaballah A. I., Hasan F., Hasani H., Hasanian M., Hassan A., Hassan S., Hassanipour S., Hassankhani H., Hassen M. B., Haubold J., Hay S. I., Hayat K., Hegazy M. I., Heidari G., Heidari M., Heidari-Soureshjani R., Hesami H., Hezam K., Hiraike Y., Hoffman H. J., Holla R., Hopf K. P., Horita N., Hossain M. M., Hossain M. B., Hossain S., Hosseinzadeh H., Hosseinzadeh M., Hostiuc S., Hu C., Huang J., Huda M. N., Hussain J., Hussein N. R., Huynh H. -H., Hwang B. -F., Ibitoye S. E., Ilaghi M., Ilesanmi O. S., Ilic I. M., Ilic M. D., Immurana M., Iravanpour F., Islam S. M. S., Ismail F., Iso H., Isola G., Iwagami M., Iwu C. C. D., Iyer M., Jaan A., Jacob L., Jadidi-Niaragh F., Jafari M., Jafarinia M., Jafarzadeh A., Jahankhani K., Jahanmehr N., Jahrami H., Jaiswal A., Jakovljevic M., Jamora R. D. G., Jana S., Javadi N., Javed S., Javeed S., Jayapal S. K., Jayaram S., Jiang H., Johnson C. O., Johnson W. D., Jokar M., Jonas J. B., Joseph A., Joseph N., Joshua C. E., Jurisson M., Kabir A., Kabir Z., Kabito G. G., Kadashetti V., Kafi F., Kalani R., Kalantar F., Kaliyadan F., Kamath A., Kamath S., Kanchan T., Kandel A., Kandel H., Kanmodi K. K., Karajizadeh M., Karami J., Karanth S. D., Karaye I. M., Karch A., Karimi A., Karimi H., Karimi Behnagh A., Kasraei H., Kassebaum N. J., Kauppila J. H., Kaur H., Kaur N., Kayode G. A., Kazemi F., Keikavoosi-Arani L., Keller C., Keykhaei M., Khadembashiri M. A., Khader Y. S., Khafaie M. A., Khajuria H., Khalaji A., Khamesipour F., Khammarnia M., Khan M., Khan M. A. B., Khan Y. H., Suheb M. Z. K., Khanmohammadi S., Khanna T., Khatab K., Khatatbeh H., Khatatbeh M. M., Khateri S., Khatib M. N., Khayat Kashani H. R., Khonji M. S., Khorashadizadeh F., Khormali M., Khubchandani J., Kian S., Kim G., Kim J., Kim M. S., Kim Y. J., Kimokoti R. W., Kisa A., Kisa S., Kivimaki M., Kochhar S., Kolahi A. -A., Koly K. N., Kompani F., Koroshetz W. J., Kosen S., Kourosh Arami M., Koyanagi A., Kravchenko M. A., Krishan K., Krishnamoorthy V., Defo B. K., Kuddus M. A., Kumar A., Kumar G. A., Kumar M., Kumar N., Kumsa N. B., Kundu S., Kurniasari M. D., Kusuma D., Kuttikkattu A., Kyu H. H., La Vecchia C., Ladan M. A., Lahariya C., Laksono T., Lal D. K., Lallukka T., Lam J., Lami F. H., Landires I., Langguth B., Lasrado S., Latief K., Latifinaibin K., Lau K. M. -M., Laurens M. B., Lawal B. K., Le L. K. D., Le T. T. T., Ledda C., Lee M., Lee S. -W., Lee S. W., Lee W. -C., Lee Y. H., Leonardi M., Lerango T. L., Li M. -C., Li W., Ligade V. S., Lim S. S., Linehan C., Liu C., Liu J., Liu W., Lo C. -H., Lo W. D., Lobo S. W., Logroscino G., Lopes G., Lopukhov P. D., Lorenzovici L., Lorkowski S., Loureiro J. A., Lubinda J., Lucchetti G., Saute R. L., Ma Z. F., Mabrok M., Machoy M., Madadizadeh F., El Razek M. M. A., Maghazachi A. A., Maghbouli N., Mahjoub S., Mahmoudi M., Majeed A., Malagon-Rojas J. N., Malakan Rad E., Malhotra K., Malik A. A., Malik I., Mallhi T. H., Malta D. C., Manilal A., Mansouri V., Mansournia M. A., Marasini B. P., Marateb H. R., Maroufi S. F., Martinez-Raga J., Martini S., Martins-Melo F. R., Martorell M., Marz W., Marzo R. R., Massano J., Mathangasinghe Y., Mathews E., Maude R. J., Maugeri A., Maulik P. K., Mayeli M., Mazaheri M., McAlinden C., McGrath J. J., Meena J. K., Mehndiratta M. M., Mendez-Lopez M. A. M., Mendoza W., Mendoza-Cano O., Menezes R. G., Merati M., Meretoja A., Merkin A., Mersha A. M., Mestrovic T., Mi T., Miazgowski T., Michalek I. M., Mihretie E. T., Minh L. H. N., Mirfakhraie R., Mirica A., Mirrakhimov E. M., Mirzaei M., Misganaw A., Misra S., Mithra P., Mizana B. A., Mohamadkhani A., Mohamed N. S., Mohammadi E., Mohammadi H., Mohammadi S., Mohammadshahi M., Mohammed M., Mohammed S., Mohan S., Mojiri-Forushani H., Moka N., Mokdad A. H., Molinaro S., Moller H., Monasta L., Moniruzzaman M., Montazeri F., Moradi M., Moradi Y., Moradi-Lakeh M., Moraga P., Morovatdar N., Morrison S. D., Mosapour A., Mosser J. F., Mossialos E., Motaghinejad M., Mousavi P., Ehsan Mousavi S., Mubarik S., Muccioli L., Mughal F., Mukoro G. D., Mulita A., Mulita F., Musaigwa F., Mustafa A., Mustafa G., Muthu S., Nagarajan A. J., Naghavi P., Naik G. R., Nainu F., Nair T. S., Najmuldeen H. H. R., Nakhostin Ansari N., Nambi G., Namdar Areshtanab H., Nargus S., Nascimento B. R., Naser A. Y., Nashwan A. J. J., Nasoori H., Nasreldein A., Natto Z. S., Nauman J., Nayak B. P., Nazri-Panjaki A., Negaresh M., Negash H., Negoi I., Negoi R. I., Negru S. M., Nejadghaderi S. A., Nematollahi M. H., Nesbit O. D., Newton C. R. J., Nguyen D. H., Nguyen H. T. H., Nguyen H. Q., Nguyen N. -T. T., Nguyen P. T., Nguyen V. T., Niazi R. K., Nikolouzakis T. K., Niranjan V., Nnyanzi L. A., Noman E. A., Noroozi N., Norrving B., Noubiap J. J., Nri-Ezedi C. A., Ntaios G., Nunez-Samudio V., Nurrika D., Oancea B., Odetokun I. A., O'Donnell M. J., Ogunsakin R. E., Oguta J. O., Oh I. -H., Okati-Aliabad H., Okeke S. R., Okekunle A. P., Okonji O. C., Okwute P. G., Olagunju A. T., Olaiya M. T., Olana M. D., Olatubi M. I., Oliveira G. M. M., Olufadewa I. I., Olusanya B. O., Bali A. O., Ong S., Onwujekwe O. E., Ordak M., Orji A. U., Ortega-Altamirano D. V., Osuagwu U. L., Otstavnov N., Otstavnov S. S., Ouyahia A., Owolabi M. O., Mahesh Padukudru P. A., Pacheco-Barrios K., Padubidri J. R., Pal P. K., Palange P. N., Palladino C., Palladino R., Palma-Alvarez R. F., Pan F., Panagiotakos D., Panda-Jonas S., Pandey A., Pandian J. D., Pangaribuan H. U., Pantazopoulos I., Pardhan S., Parija P. P., Parikh R. R., Park S., Parthasarathi A., Pashaei A., Patel J., Patil S., Patoulias D., Pawar S., Pedersini P., Pensato U., Pereira D. M., Pereira J., Pereira M. O., Peres M. F. P., Perico N., Perna S., Petcu I. -R., Petermann-Rocha F. E., Pham H. T., Phillips M. R., Pinilla-Monsalve G. D., Piradov M. A., Plotnikov E., Poddighe D., Polat B., Poluru R., Pond C. D., Poudel G. R., Pouramini A., Pourbagher-Shahri A. M., Pourfridoni M., Pourtaheri N., Prakash P. Y., Prakash S., Prakash V., Prates E. J. S., Pritchett N., Purnobasuki H., Qasim N. H., Qattea I., Qian G., Radhakrishnan V., Raee P., Shahraki H. R., Rafique I., Raggi A., Raghav P. R., Rahati M. M., Rahim F., Rahimi Z., Rahimifard M., Rahman M. O., Rahman M. H. U., Rahman M., Rahman M. A., Rahmani A. M., Rahmani S., Youshanlouei H. R., Rahmati M., Raj Moolambally S., Rajabpour-Sanati A., Ramadan H., Ramasamy S. K., Ramasubramani P., Ramazanu S., Rancic N., Rao I. R., Rao S. J., Rapaka D., Rashedi V., Rashid A. M., Rashidi M. -M., Rashidi Alavijeh M., Rasouli-Saravani A., Rawaf S., Razo C., Redwan E. M. M., Bana A. R., Remuzzi G., Rezaei N., Rezaeian M., Rhee T. G., Riad A., Robinson S. R., Rodrigues M., Rodriguez J. A. B., Roever L., Rogowski E. L. B., Romoli M., Ronfani L., Roy P., Pramanik K. R., Rubagotti E., Ruiz M. A., Russ T. C., Sunnerhagen K. S., Saad A. M. A., Saadatian Z., Saber K., SaberiKamarposhti M., Sacco S., Saddik B., Sadeghi E., Sadeghian S., Saeed U., Safdarian M., Safi S. Z., Sagar R., Sagoe D., Saheb Sharif-Askari F. S., Saheb Sharif-Askari N., Sahebkar A., Sahoo S. S., Sahraian M. A., Sajedi S. A., Sakshaug J. W., Saleh M. A., Salehi Omran H., Salem M. R., Salimi S., Samadi Kafil H., Samadzadeh S., Samargandy S., Samodra Y. L., Samuel V. P., Samy A. M., Sanadgol N., Sanjeev R. K., Sanmarchi F., Santomauro D. F., Santri I. N., Santric-Milicevic M. M., Saravanan A., Sarveazad A., Satpathy M., Saylan M., Sayyah M., Scarmeas N., Schlaich M. P., Schuermans A., Schwarzinger M., Schwebel D. C., Selvaraj S., Sendekie A. K., Sengupta P., Senthilkumaran S., Serban D., Sergindo M. T., Sethi Y., SeyedAlinaghi S., Seylani A., Shabani M., Shabany M., Shafie M., Shahabi S., Shahbandi A., Shahid S., Shahraki-Sanavi F., Shahsavari H. R., Shahwan M. J., Shaikh M. A., Shaji K. S., Sham S., Shama A. T. T., Shamim M. A., Shams-Beyranvand M., Shamsi M. A., Shanawaz M., Sharath M., Sharfaei S., Sharifan A., Sharma M., Sharma R., Shashamo B. B., Shayan M., Sheikhi R. A., Shekhar S., Shen J., Shenoy S. M., Shetty P. H., Shiferaw D. S., Shigematsu M., Shiri R., Shittu A., Shivakumar K. M., Shokri F., Shool S., Shorofi S. A., Shrestha S., Siankam Tankwanchi A. B., Siddig E. E., Sigfusdottir I. D., Silva J. P., Silva L. M. L. R., Sinaei E., Singh B. B., Singh G., Singh P., Singh S., Sirota S. B., Sivakumar S., Sohag A. A. M., Solanki R., Soleimani H., Solikhah S., Solomon Y., Song S., Song Y., Sotoudeh H., Spartalis M., Stark B. A., Starnes J. R., Starodubova A. V., Stein D. J., Steiner T. J., Stovner L. J., Suleman M., Abdulkader R. S., Sultana A., Sun J., Sunkersing D., Sunny A., Susianti H., Swain C. K., Szeto M. D., Tabares-Seisdedos R., Tabatabaei S. M., Tabatabai S., Tabish M., Taheri M., Tahvildari A., Tajbakhsh A., Tampa M., Lukenze Tamuzi J. J. L., Tan K. -K., Tang H., Tareke M., Tarigan I. U., Tat N. Y., Tat V. Y., Tavakoli Oliaee R., Tavangar S. M., Tavasol A., Tefera Y. M., Tehrani-Banihashemi A., Temesgen W. A., Temsah M. -H., Teramoto M., Tesfaye A. H., Tesfaye E. G., Tesler R., Thakali O., Thangaraju P., Thapa R., Thapar R., Thomas N. K., Thrift A. G., Ticoalu J. H. V., Tillawi T., Toghroli R., Tonelli M., Tovani-Palone M. R., Traini E., Tran N. M., Tran N. -H., Van Tran P., Tromans S. J., Truelsen T. C., Truyen T. T. T. T., Tsatsakis A., Tsegay G. M., Tsermpini E. E., Tualeka A. R., Tufa D. G., Ubah C. S., Udoakang A. J., Ulhaq I., Umair M., Umakanthan S., Umapathi K. K., Unim B., Unnikrishnan B., Vaithinathan A. G., Vakilian A., Tahbaz S. V., Valizadeh R., Van den Eynde J., Vart P., Varthya S. B., Vasankari T. J., Vaziri S., Vellingiri B., Venketasubramanian N., Verras G. -I., Vervoort D., Villafane J. H., Villani L., Veloz A. F. V., Viskadourou M., Vladimirov S. K., Vlassov V., Volovat S. R., Vu L. T., Vujcic I. S., Wagaye B., Waheed Y., Wahood W., Walde M. T., Wang F., Wang S., Wang Y., Wang Y. -P., Waqas M., Waris A., Weerakoon K. G., Weintraub R. G., Weldemariam A. H., Westerman R., Whisnant J. L., Wickramasinghe D. P., Wickramasinghe N. D., Willekens B., Wilner L. B., Winkler A. S., Wolfe C. D. A., Wu A. -M., Wulf Hanson S., Xu S., Xu X., Yadollahpour A., Yaghoubi S., Yahya G., Yamagishi K., Yang L., Yano Y., Yao Y., Yehualashet S. S., Yeshaneh A., Yesiltepe M., Yi S., Yigit A., Yigit V., Yon D. K., Yonemoto N., You Y., Younis M. Z., Yu C., Yusuf H., Zadey S., Zahedi M., Zakham F., Zaki N., Zali A., Zamagni G., Zand R., Zandieh G. G. Z., Zangiabadian M., Zarghami A., Zastrozhin M. S., Zeariya M. G. M., Zegeye Z. B., Zeukeng F., Zhai C., Zhang C., Zhang H., Zhang Y., Zhang Z. -J., Zhao H., Zhao Y., Zheng P., Zhou H., Zhu B., Zhumagaliuly A., Zielinska M., Zikarg Y. T., Zoladl M., Murray C. J. L., Ong K. L., Feigin V. L., Vos T., and Dua T.

Abstract

Background: Disorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021. Methods: We estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous s

Published
2024

28. Evaluation of microRNA‐10a and microRNA‐210 as Biomarkers in Sepsis Patients With Acute Kidney Injury.

Author

Susianti, Hani, Sutrisnani, Catur Suci, Santosa, I.P. Adi, Febrianto, Wahyu, Kusdjianto, Amanda Yuanita, Kuwoyo, Kevin Putro, Riyu, Elita, and Kershaw, David B.

Subjects
*CROSS-sectional method, *RESEARCH funding, *DATA analysis, *RECEIVER operating characteristic curves, *CREATININE, *SURVIVAL rate, *EARLY medical intervention, *MICRORNA, *KRUSKAL-Wallis Test, *ACUTE kidney failure, *REVERSE transcriptase polymerase chain reaction, *DESCRIPTIVE statistics, *MANN Whitney U Test, *SERUM, *SEPSIS, *CASE-control method, *STATISTICS, *UREA, *COMPARATIVE studies, *CONFIDENCE intervals, *EARLY diagnosis, *BIOMARKERS, *SENSITIVITY & specificity (Statistics), *KIDNEYS, *DISEASE complications
Abstract

Background: Sepsis‐associated acute kidney injury (AKI) is a condition that increases in‐hospital mortality and the risk of progression to CKD. The current method of detecting AKI, which relies on increased serum creatinine levels or a decrease in urine output, has low sensitivity. Early diagnosis and appropriate intervention in AKI can lead to improved patient outcomes. Several low molecular weight proteins and microRNAs detected in AKI are considered early biomarkers of AKI, such as miR‐10a‐5p and miR‐210‐3p. Method: A cross‐sectional study was conducted among 62 participants, consisting of 26 sepsis patients with AKI, 26 sepsis patients without AKI, and 10 healthy controls. AKI was determined according to KDIGO criteria. MicroRNA expression was analyzed using reverse transcription quantitative polymerase chain reaction (RT‐qPCR). Statistical analysis was obtained using the Kruskal–Wallis test, Spearman's correlation coefficient, and ROC curve analysis. Result: The median miR‐10a‐5p expression of the healthy controls versus sepsis with AKI versus sepsis without AKI groups was 10.38 (5.50–33.82) versus 10.32 (3.32–31.53) versus 9.76 (0.32–97.36), while the median miR‐210‐3p expression was 0.20 (0.03–0.41) versus 0.38 (0.04–1.24) versus 0.29 (0.06–1.67), respectively, with p = 0.721 for miR‐10a‐5p and p = 0.013 for miR‐210‐3 p. A significant increase in miR‐210‐3p expression was found in the sepsis with AKI compared to the healthy controls (p = 0.013) and sepsis without AKI (p = 0.034). miR‐210‐3p significantly correlated with creatinine and urea serum level (p < 0.05); miR‐10a‐5p did not have a significant correlation. The sensitivity and specificity of miR‐10a‐5p were 61.5% and 47.2%, and miR‐210‐3p were 84.6% and 63.9% for determining AKI. Conclusion: The study's findings revealed a significant increase in miR‐210‐3p expression in sepsis patients with AKI, indicating its potential as a promising biomarker for determining AKI. This discovery demonstrates that the diagnostic performance of miR‐210‐3p surpasses that of miR‐10a‐5p, providing a more accurate biomarker for diagnosing AKI in sepsis patients. [ABSTRACT FROM AUTHOR]

Published
2024
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33. Lower serum BDNF as a predictor of post-stroke cognitive impairment in acute ischemic stroke patients [version 1; peer review: 1 approved, 1 not approved]

Author

Ismail Setyopranoto, Astuti Prodjohardjono, Sri Sutarni, Noor Alia Susianti, Muhammad Hardhantyo, and Amelia Nur Vidyanti

Subjects
Research Article, Articles, serum BDNF, predictor, post-stroke cognitive impairment, acute ischemic stroke
Abstract

Background: Reduced level of serum BDNF in acute stroke patients is associated with poor outcomes. We aimed to identify the role of serum BDNF level as a predictor for post-stroke cognitive impairment (PSCI). Methods: This was a prospective study. We recruited acute ischemic stroke patients in Dr. Sardjito General Hospital Yogyakarta, Indonesia followed them up for 90 days (3 months). Serum BDNF was collected at day 5 and day 30 of stroke onset and measured by ELISA. Montreal Cognitive Assessment (MoCA) was used to measure the cognitive function at 90 days of follow up. ROC curve was conducted to measure the cut-off point of the BDNF level. Factors independently associated with PSCI were analyzed by using stepwise regression. Results: Among 89 patients recruited, 60 patients (67.41%) developed PSCI. The mean age of PSCI and non-PSCI patients was 62.7 ± 9.5 and 57.5 ± 8.7, respectively (p = 0.01). Patients with dyslipidemia were less likely to develop PSCI (OR 0.19, 95%CI 0.06–0.56, p < 0.05). In addition, patients with day 5-serum BDNF level < 23.29 ng/mL were five times more likely to develop PSCI compared with their counterparts (OR 5.02, 95%CI 1.67–15.04, p < 0.05). Conclusion s: Among acute ischemic stroke patients, those with serum BDNF

Published
2022
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36. Diagnostic Performance of IL-1β and C-Reactive Protein in Childhood Tuberculosis.

Author

Iskandar, Agustin, Halim, Desyi, Susianti, Hani, Olivianto, Ery, and Aprilia, Andrea

Subjects
C-reactive protein, TUBERCULOSIS, MEDICAL care, MEDICAL personnel, BIOMARKERS
Abstract

Interleukin (IL)-1γ, a proinflammatory cytokine produced by phagocytes infected with Mycobacterium tuberculosis, is known for its stability in storage, which ensures consistent measurement in clinical settings. This stability, along with its unaffected levels by age, sex, or lung disease severity, makes IL-1γ a promising biomarker in tuberculosis (TB). This study aims to evaluate the diagnostic performance of IL-1γ and C-reactive protein (CRP) in childhood TB. cross-sectional study was conducted on 77 children with suspected TB at Saiful Anwar Hospital. The inclusion criteria were based on the 2016 technical guidelines for TB. IL-1γ levels were measured using Elisa, while CRP was assessed via immunoturbidimetry. A significant difference in mean IL-1γ levels was observed between the TB and non-TB groups (p = 0.028). However, IL-1γ showed a weak correlation with the TB group (r = 0.251, p = 0.027). The area under the curve (AUC) for IL-1γ was 0.671 (p = 0.028) with 52.5% sensitivity, 83.3% specificity, 91.1% positive predictive value (PPV), 34.8% negative predictive value (NPV), and 59.7% accuracy at a cut-off of 6.1 pg/mL. CRP levels showed no significant correlation or difference between the groups. The combination of IL-1γ and CRP yielded an AUC of 0.669 (p = 0.031), with 41.5% sensitivity, 75% specificity, 84.4% PPV, 28.1% NPV, and 49.3% accuracy. Although IL-1γ shows moderate diagnostic performance and CRP alone or combined with IL-1γ has limited utility in diagnosing childhood TB, IL-1γ still holds potential as a biomarker. Its high positive predictive value (PPV) indicates strong reliability in confirming TB, making it a valuable tool in a broader diagnostic or monitoring of childhood TB. [ABSTRACT FROM AUTHOR]

Published
2024
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37. The role of endothelial microparticles in children with asthma: Does it promote atherosclerosis progress? [version 1; peer review: 2 not approved]

Author

Lisa Adhia Garina, Bambang Supriyatno, Faisal Yunus, Ina Susianti Timan, Bambang Hermani, Aria Kekalih, Cissy B. Kartasasmita, and Suhendro Suwarto

Subjects
Research Article, Articles, asthma, children, endothelial dysfunction, microparticles
Abstract

Background: Asthma is a chronic inflammatory airway disease that has been linked to enhanced risks for atherosclerosis. The impact of asthma on cardiovascular disease risk in children is less well established. Asthma is defined by a history of respiratory symptoms and accompanied by airflow limitation, with heterogeneous clinical manifestations, and variability in the intensity of airway inflammation and remodeling. Endothelial microparticles (EMP) are biomarkers of endothelial dysfunction in several chronic diseases. Endothelial microparticles initiate an event of atherosclerotic plaque formation. Our study aimed to evaluate the role of endothelial microparticles in children with asthma. Methods: A cross-sectional study was performed on a total of 50 children with asthma aged seven‒17 years. Children with asthma exacerbations, infections, and steroid use were excluded. Endothelial microparticles were measured with beads, and the fluorescence signal was measured using a flow cytometer. Pro-inflammatory cytokines were measured by enzyme-linked immunosorbent assay (ELISA) method. Results: Based on the results from 50 asthmatic children, it was found that most children had a normal nutritional status, intermittent, and allergic asthma. The results of this study also showed that the circulation of asthmatic children found that the mean levels (µL) of CD31+/CD62E+, CD31+/CD62E-, and CD62E+/CD31- were 2,392.99 ± 7,787.94; 922.14 ± 1,554.03; 198.97 ± 387.68, with the average ratio of CD31+/CD62E+, which was ≤1.0 and identifies apoptosis. Path analysis results found that IL-6, TNF-α, and CD31+/CD62E- EMP played a role in peak expiratory flow rate (%PEFR, p = 0.02; p = 0.003; p = 0.04) in children with allergic asthma. Conclusions: Endothelial microparticles play a role on peak expiratory flow rate (PEFR) in children with allergic asthma. Further study is needed to investigate the role of these biomarkers and their correlation with pro-inflammatory cytokines in the mechanism of atherosclerosis progression.

Published
2022
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38. The association between FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a among chronic granulocytic leukemia patients treated with imatinib mesylate [version 3; peer review: 2 approved]

Author

Shinta Oktya Wardhani, Hani Susianti, Puji Rahayu, Yuyun Prabowowati Yueniwati, and Jonny Karunia Fajar

Subjects
Research Article, Articles, chronic granulocytic leukemia, FOXO3a, FOXO3a rs4946936 gene polymorphism
Abstract

Background: The gene FOXO3a has been elucidated to govern the development of chronic granulocytic leukemia (CGL). Moreover, it has been suggested that the levels of FOXO3a in circulation are affected by the FOXO3a rs4946936 gene polymorphism. However, no study has assessed the correlation between the FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a. The objective of this study was to assess the association between the FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a in CGL patients treated with imatinib mesylate. Methods: A cross-sectional study was conducted from February 2019 to February 2020. The genotyping of FOXO3a rs4946936 gene polymorphism was conducted using PCR-RFLP, and the levels of FOXO3a were assessed using ELISA. The association between the FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a were assessed using multiple logistic regression. Results: A total of 60 CGL patients were assessed in our study. Among them, the CC, CT, and TT genotypes of the FOXO3a rs4946936 gene polymorphism were 35.0%, 48.3%, and 16.7% respectively. Our calculation revealed that elevated levels of FOXO3a were found in CGL patients with the CC genotype of the FOXO3a rs4946936 gene polymorphism. While we failed to clarify the association between either the CT or the TT genotype of FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a. Conclusion: Our study identifies that the CC genotype of the FOXO3a rs4946936 gene polymorphism affects the elevated levels of FOXO3a in CGL patients treated with imatinib mesylate.

Published
2022
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39. Performance of the T cell senescence markers in predicting the active disease of systemic lupus erythematosus [version 1; peer review: 1 approved, 1 approved with reservations, 1 not approved]

Author

Kusworini Handono, Mirza Zaka Pratama, Radiyati Umi Partan, Hani Susianti, Nimas Eka Firdaningrum, Siti Roziah Ria Famuji, Ade Wildan Rizky Fachry, Norma Hanifah Sumarta, and Handono Kalim

Subjects
Research Article, Articles, immunosenescence, systemic lupus erythematosus, disease activity, senescence markers
Abstract

Background: Accelerated immunosenescence has been observed in several autoimmune diseases, including systemic lupus erythematosus (SLE). T cell senescence plays an essential role in the destruction of organs in SLE patients. This study aimed to identify the ability of immunosenescence markers to predict SLE disease activity. Methods: Overall, 61 SLE patients and 60 healthy subjects were enrolled in this cross-sectional study. The Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) score assessed disease activity. Senescence surface markers of CD4 and CD8 T lymphocytes were measured by flow cytometry (CD4/CD8 ratio, CD28 null, CD57, CD45 isoforms [CD45RA and CD45RO], and KLRG1). Enzyme-linked immunosorbent assay (ELISA) was used to measure the serum cytokines (IFNγ and IL-2) and cytomegalovirus (CMV) serology. Complement and anti-dsDNA levels were also evaluated as the comparator for predicting active disease in SLE. Logistic regression models were used to identify the independent predictive factors for active SLE status. Performance of the senescence markers in predicting active disease in SLE was analyzed by receiver operating characteristic (ROC) curve as the area under curve (AUC). Results: SLE patients with active disease had significantly higher CD8 +CD28 null, CD8 +CD57 +, CD8 +CD45RA +, CD8 +CD45RO +, and CD8 +KLRG1 + percentages with lower CD4/CD8 ratio than healthy subjects and SLE patients with inactive disease. The highest AUC and sensitivity were seen in CD8 +CD28 null (AUC 0.801 [0.662-0.940], sensitivity 91.9%, cut off >6.85%) with comparable results to serum complement and anti-dsDNA in predicting active disease. Multivariate analysis showed that CD4/CD8 ratio, CD8 +CD28 null, and C3 had significantly increased OR for active SLE. Combination models of CD4/CD8 ratio, CD8 +CD28 null, and C3 yielded the best results for predicting the active SLE (AUC 0.923 [0.848-0.997], sensitivity 81.2%, specificity 84.0%, LR+ 5.08 and LR- 0.22). Conclusions: Our findings demonstrated that combining immunosenescence markers, including CD4/CD8 ratio and CD8+CD28null with C3 levels could increase the odds of predicting active disease in SLE.

Published
2022
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40. The association between FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a among chronic granulocytic leukemia patients treated with imatinib mesylate [version 2; peer review: 1 approved, 1 approved with reservations]

Author

Shinta Oktya Wardhani, Hani Susianti, Puji Rahayu, Yuyun Prabowowati Yueniwati, and Jonny Karunia Fajar

Subjects
Research Article, Articles, chronic granulocytic leukemia, FOXO3a, FOXO3a rs4946936 gene polymorphism
Abstract

Background: The gene FOXO3a has been elucidated to govern the development of chronic granulocytic leukemia (CGL). Moreover, it has been suggested that the levels of FOXO3a in circulation are affected by the FOXO3a rs4946936 gene polymorphism. However, no study has assessed the correlation between the FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a. The objective of this study was to assess the association between the FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a in CGL patients treated with imatinib mesylate. Methods: A cross-sectional study was conducted from February 2019 to February 2020. The genotyping of FOXO3a rs4946936 gene polymorphism was conducted using PCR-RFLP, and the levels of FOXO3a were assessed using ELISA. The association between the FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a were assessed using multiple logistic regression. Results: A total of 60 CGL patients were assessed in our study. Among them, the CC, CT, and TT genotypes of the FOXO3a rs4946936 gene polymorphism were 35.0%, 48.3%, and 16.7% respectively. Our calculation revealed that elevated levels of FOXO3a were found in CGL patients with the CC genotype of the FOXO3a rs4946936 gene polymorphism. While we failed to clarify the association between either the CT or the TT genotype of FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a. Conclusion: Our study identifies that the CC genotype of the FOXO3a rs4946936 gene polymorphism affects the elevated levels of FOXO3a in CGL patients treated with imatinib mesylate.

Published
2022
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41. Steroid Compounds of Manihot Esculenta Crantz Var. Sao Pedro Petro (Tuber) and Their Cytotoxic Effects on Melanoma Cancer Cells (B16-F10)

Author

Widiastuti, Diana, primary, Warnasih, Siti, additional, Mulyati, Ade Heri, additional, Sutanto, Sutanto, additional, Triastinurmiatiningsih, Triastinurmiatiningsih, additional, Sinaga, Siska Elisahbet, additional, Salam, Supriatno, additional, Harneti, Desi, additional, Lesmana, Ronny, additional, Supratman, Unang, additional, Susianti, Susianti, additional, Agustine, Dine, additional, Herlina, Eka, additional, and Mulyani, Rahmaniar, additional

Published
2024
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46. Serological Profiles of Systemic Lupus Erythematosus in Humanized Mice and Pristane-Induced Lupus Models

Author

Syahrul Chilmi, Dimas Ikhsan Airlangga, Hani Susianti, Kusworini Handono, Syahrul Chilmi, Dimas Ikhsan Airlangga, Hani Susianti, and Kusworini Handono

Abstract

Highlights:1. This study compared the serological markers of pristane-induced mice to humanized mouse models of lupus achieved by transplanting stem cells from lupus patients, which is a novel method in Indonesia.2. This study will allow for more accurate research into the pathophysiology of the disease and the development of new lupus treatment strategies. Abstract More studies related to systemic lupus erythematosus (SLE) therapy are urgently needed because of the current insufficiency in treatment effectiveness. However, due to ethical limitations, researchers use experimental animals as a substitute for conducting studies on humans. Models commonly used to study lupus include the pristane-induced mouse model and the recently developed humanized mouse model. The second model involves implanting human immune cells into immunodeficient mice. This study compared the serologic profiles of lupus antibodies, the antinuclear antibodies (ANA) and anti-double stranded DNA (anti-dsDNA), in both mouse models. The aim was to determine which one is more promising for use as a lupus animal model. Thirty BALB/c mice (Mus musculus) were used as subjects and divided into three groups: K1, K2, and K3. K1 served as the control group, consisting of healthy mice that received a placebo. The K2 mice were intraperitoneally injected with 0.5 cc of pristane. The K3 mice were transplanted with stem cell cultures from SLE patients, resulting in humanized mice with immune deficiencies. The mice were observed for 16 weeks, during which the ANA and anti-dsDNA levels in their serum were obtained for analysis using the Kruskal-Wallis test (p<0.05). The comparison revealed differences in the average ANA and anti-dsDNA levels among the three groups. K3 had the highest ANA and anti-dsDNA levels, followed by K1 and K2. The Kruskal-Wallis test indicated that the differences were not significant in the mean levels of ANA (p=0.156) and anti-dsDNA (p=0.061). In conclusion, the humanized mouse mode

Published
2024

47. Acute Kidney Injury Prediction Model Using Cystatin-C, Beta-2 Microglobulin, and Neutrophil Gelatinase-Associated Lipocalin Biomarker in Sepsis Patients

Author

Susianti,Hani, Asmoro,Aswoco, Sujarwoto, Jaya,Wiwi, Sutanto,Heri, Kusdijanto,Amanda, Kuwoyo,Kevin, Hananto,Kristian, Khrisna,Matthew, Susianti,Hani, Asmoro,Aswoco, Sujarwoto, Jaya,Wiwi, Sutanto,Heri, Kusdijanto,Amanda, Kuwoyo,Kevin, Hananto,Kristian, and Khrisna,Matthew

Abstract

Hani Susianti,1 Aswoco Andyk Asmoro,2 Sujarwoto,3 Wiwi Jaya,2 Heri Sutanto,4 Amanda Yuanita Kusdijanto,1 Kevin Putro Kuwoyo,1 Kristian Hananto,5 Matthew Brian Khrisna1 1Clinical Pathology Department, Faculty of Medicine Brawijaya University/Saiful Anwar General Hospital, Malang, Indonesia; 2Anesthesiology and Intensive Therapy Department, Faculty of Medicine Brawijaya University/Saiful Anwar General Hospital, Malang, Indonesia; 3Faculty of Public Administration, Brawijaya University, Malang, Indonesia; 4Internal Medicine Department, Faculty of Medicine Brawijaya University/Saiful Anwar General Hospital, Malang, Indonesia; 5Faculty of Medicine, Brawijaya University, Malang, IndonesiaCorrespondence: Hani Susianti, Clinical Pathology Department, Medicine Faculty of Universitas Brawijaya/Dr. Saiful Anwar General Hospital, Malang, Indonesia, Email hanisusianti.fk@ub.ac.idIntroduction: AKI is a frequent complication in sepsis patients and is estimated to occur in almost half of patients with severe sepsis. However, there is currently no effective therapy for AKI in sepsis. Therefore, the therapeutic approach is focused on prevention. Based on this, there is an opportunity to examine a panel of biomarker models for predicting AKI.Material and Methods: This prospective cohort study analysed the differences in Cystatin C, Beta-2 Microglobulin, and NGAL levels in sepsis patients with AKI and sepsis patients without AKI. The biomarker modelling of AKI prediction was done using machine learning, namely Orange Data Mining. In this study, 130 samples were analysed by machine learning. The parameters used to obtain the biomarker panel were 23 laboratory examination parameters.Results: This study used SVM and the Naïve Bayes model of machine learning. The SVM model’s sensitivity, specificity, NPV, and PPV were 50%, 94.4%, 71.4%, and 87.5%, respectively. For the Naïve Bayes model, the sensitivity, specificity, NPV, and PPV were 83.3%, 77.8%, 87.5%, and 71.4%, respectively.Discus

Published
2024

48. Peran Guru Kristen Sebagai Penuntun: Sebuah Kajian Teologis Efesus 4:11-16 Dalam Konteks Pendidikan Kristen [The Role of Christian Teachers as Guides: A Theological Study of Ephesians 4:11-16 in the Context of Christian Education]

Author

Zega, Sri Susianti, Tarigan, Musa Sinar, Zega, Sri Susianti, and Tarigan, Musa Sinar

Abstract

The role of teacher as a guide is very significant in teaching, especially to equip students to know God through Christian education. Teachers guide the students to understand knowledge, attitudes, skills, and spirituality based on Biblical principles. But in reality, teachers do not teach the Bible principles in learning, teachers do not guide the students, and have lack of knowledge of the Bible. Teachers should have understood the significance of guiding students based on the Bible. Hence, the purpose of writing this article is to present the significant role of teachers as a guide through the theological study based on Ephesians 4:11-16 for the context of Christian education with literature study as the research method. Teachers must guide students based on the truth of God's Word, through imitating Jesus as the Great Shepherd. Christian teachers’ role as guide do not only stop at knowledge in academic learning, but to be an impact for students to be a part of service to God and to build others up as members of the body of Christ. Christian teachers must guide students to achieve, namely: the unity of the faith in Christ as God and Savior in true knowledge, thorough maturity, and growth in accordance with the fullness of Christ and to ensure to be not tossed around by the waves of false teaching that ignore The Lord. This article concludes that the teacher's role as guide is one form for equipping students to grow more mature in Christ. The author suggests that Christian teachers understand that teachers are God's calling to reveal God's truth to students so that their lives base on Bible teaching, and Christian teachers must understand the students' needs to know God and grow spiritually to become more like Christ.BAHASA INDONESIA ABSTRACT: Peran guru sebagai pembimbing sangat penting dalam pengajaran, terutama untuk memperlengkapi murid-murid mengenal Tuhan melalui pendidikan Kristen. Guru membimbing murid untuk memahami pengetahuan, sikap, keterampilan, dan k

Published
2024

49. The association between FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a among chronic granulocytic leukemia patients treated with imatinib mesylate [version 1; peer review: 2 approved with reservations]

Author

Shinta Oktya Wardhani, Hani Susianti, Puji Rahayu, Yuyun Prabowowati Yueniwati, and Jonny Karunia Fajar

Subjects
Research Article, Articles, chronic granulocytic leukemia, FOXO3a, FOXO3a rs4946936 gene polymorphism
Abstract

Background: The gene FOXO3a has been elucidated to govern the development of chronic granulocytic leukemia (CGL). Moreover, it has been suggested that the levels of FOXO3a in circulation are affected by the FOXO3a rs4946936 gene polymorphism. However, no study has assessed the correlation between the FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a. The objective of this study was to assess the association between the FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a in CGL patients treated with imatinib mesylate. Methods: A cross-sectional study was conducted from February 2019 to February 2020. The genotyping of FOXO3a rs4946936 gene polymorphism was conducted using PCR-RFLP, and the levels of FOXO3a were assessed using ELISA. The association between the FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a were assessed using multiple logistic regression. Results: A total of 60 CGL patients were assessed in our study. Among them, the CC, CT, and TT genotypes of the FOXO3a rs4946936 gene polymorphism were 35.0%, 48.3%, and 16.7% respectively. Our calculation revealed that elevated levels of FOXO3a were found in CGL patients with the CC genotype of the FOXO3a rs4946936 gene polymorphism. While we failed to clarify the association between either the CT or the TT genotype of FOXO3a rs4946936 gene polymorphism and the levels of FOXO3a. Conclusion: Our study identifies that the CC genotype of the FOXO3a rs4946936 gene polymorphism affects the elevated levels of FOXO3a in CGL patients treated with imatinib mesylate.

Published
2021
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50. Pengetahuan Berhubungan dengan Kepatuhan ODHA dalam Menjalani Terapi Anti Retro Viral

Author

Susianti Susianti, Dyah Wulan Sumekar Rengganis Wardani, and Irawan Budi Waskito

Subjects
Earth-Surface Processes
Abstract

Kepatuhan merupakan gambaran perilaku pasien dalam konsumsi obat yang benar pada dosis, waktu dan frekuensinya. Kepatuhan yang tinggi sangat diperlukan untuk terapi Antiretroviral (ARV) pada penderita HIV/AIDS. Ketidakpatuhan pengobatan ARV menyebabkan meningkatnya progresivitas penyakit, transmisi HIV dan resistensi ARV. Hal ini dipengaruhi oleh pengetahuan tentang terapi ARV. Tujuan penelitian ini menganalisis hubungan pengetahuan dengan kepatuhan ODHA dalam menjalani terapi ARV. Penelitian ini menggunakan jenis penelitian kuantitatif analitik observasional dengan pendekatan cross sectional. Penelitian ini dilakukan bulan Januari 2023 di Klinik VCT Mahoni RSUD Demang Sepulau Raya Lampung Tengah. Variabel independen adalah pengetahuan dan variabel dependen adalah kepatuhan minum obat ARV. Populasi dalam penelitian adalah penderita HIV AIDS yang tercatat mendapatkan pelayanan ARV berjumlah 115 orang. Sampel dalam penelitian ini berjumlah 93 orang. Instrumen penelitian menggunakan kuesioner, yang sudah dilakukan validitas dan reliabilitas. Pengolahan data melalui tahapan editing, coding, tabulating, entry dan cleaning. Analisis data berupa univariat dan bivariat menggunakan uji Chi-Square. Hasil dari penelitian mendapatkan responden menjalani terapi ARV patuh tinggi sebanyak 60,2%, pengetahuan tinggi sebanyak 74,2%. Analisis mendapatkan terdapat hubungan pengetahuan (p value=0,002 dan OR=4,9) dengan kepatuhan ODHA dalam menjalani terapi ARV.

Published
2023
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