Ida Fitriana

The off-label use of human over-the-counter (OTC) medications in veterinary medicine is a common but potentially hazardous practice, particularly in regions where access to veterinary-approved drugs is limited. While some OTC agents, such as diphenhydramine or melatonin, may offer therapeutic benefits under veterinary supervision, many others pose significant risks due to species-specific differences in drug metabolism, narrow safety margins, and the presence of toxic excipients such as xylitol, pseudoephedrine, or acetaminophen. This literature review examines the rationale behind such practices, the most commonly used OTC drug classes, and the associated pharmacological and toxicological risks. It also highlights critical considerations in clinical decision-making, including appropriate dosing, contraindications, and alternative treatment options. Additionally, the role of veterinary pharmacists, interprofessional collaboration, and pharmacovigilance systems are discussed as essential components in mitigating risks and promoting safe usage. The review emphasizes the importance of client education and the need for veterinarians to rely on species-specific products whenever available. Ultimately, the off-label use of OTC medications in animals should be approached with caution, guided by evidence-based practice, and employed only when clinically justified and accompanied by rigorous safety monitoring.

Background and Aim: Animal antimicrobials must be studied to determine if they have the same types, norms of use, and resistance patterns as those used in humans. This study aimed to facilitate the analysis of data on the use of antimicrobials in veterinary medicine and to aid in developing a strategy to prevent the emergence of antimicrobial resistance (AMR) in humans and animals. Materials and Methods: Data were obtained through a survey of 101 veterinarians working in animal clinics and independent practice in five regencies of Yogyakarta province. Results: Both of the antibiotics, antiparasitic (78.6%) and, antiseptic and disinfectant (68.0%), and antifungal (31.1%) were the most frequently used types of antimicrobials, while antivirals were the least used (9.7%). The most often treated animals with antimicrobials are pets (37%), followed by large and small livestock (30%), poultry (15%), and exotic animals (14%). Of the respondents, 89% were aware of the factors contributing to AMR, but only 47% monitored developments and expanded their understanding of AMR. The most common antibiotic classes were penicillin (71), tetracyclines (50), sulfonamides (41), fluoroquinolones (31), and aminoglycosides (27). Conclusion: All antimicrobials used in the animal health sector are also used in human medicine, which requires special consideration. This cross-use of antibiotics was a crucial factor in determining the cause of the spread of AMR between humans and animals. Keywords: animal health, antimicrobial use, Yogyakarta.

Background and Aim: Enrofloxacin and tylosin can be combined into an antibiotic formulation which is expected to have a broader range of antibacterial activity against various infections in broilers. Validation method analysis of the levels of these two active compounds needs to be done for future use in pharmacokinetic or residual studies. The present study aims to determine a suitable validation method of isocratic high-performance liquid chromatography (HPLC) to measure the concentration of antibiotic combinations in the broiler liver, kidney, and muscles. Materials and Methods: The combination of enrofloxacin and tylosin in the liver, kidney, and muscle was validated by HPLC method to find the procedures, processes, equipment, and systems used, consistently provides the appropriate results. The chromatography system consisted of an Octadecyl-silica column of 5 μm in diameter and 150 mm in length with a mobile phase of a mixture of 0.05 M monobasic sodium phosphate (pH 2.5) and acetonitrile (65:35 v/v). The solution was detected at a wavelength of 280 nm, 30°C, a flow rate of 1 mL/min, and an injection volume of 20 μL. The combination antibiotics powder was produced from PT Tekad Mandiri Citra, Bandung, Indonesia, and broiler tissues obtained from day-old chick broilers maintained for 30 days with free antibiotic feed. Results: Validation of a combination solution of enrofloxacin and tylosin shows the linearity values of enrofloxacin and tylosin in the liver, kidney, and muscles as r2=0.9988, r2=0.9999, r2=0.9997, r2=0.9989, r2=0.9978, and r2=0.9962. The accuracy and precision values of enrofloxacin in the liver, kidney, and muscles were 5.53, 6.23, and 6.93, respectively. The values of accuracy and precision of tylosin in the liver, kidney, and muscles were 10.43, 4.63, and 7.16%, respectively. The retention times for enrofloxacin and tylosin were 1.945-2.000 min and 4.175-4.342 min. The limit of detection (LOD) and limit of quantity (LOQ) values for enrofloxacin were 3.03 and 10.1 μg/g, respectively. In contrast, the LOD and LOQ values for tylosin were 9.05 and 30.17 μg/g, respectively. Conclusion: The value of linearity, accuracy, precision, specificity, and sensitivity of the combined solution of enrofloxacin and tylosin showed promising results.

Background and Aim: Chicken meat needs in Indonesia increase every year, farmers use feed supplements to improve broiler performance. The purpose of this study was to evaluate moringa leaf extract on the performance and morphology of broiler gut.Materials and Methods: Fifty Day Old Chickens (DOC) were divided into 5 treatment groups. The treatment groups were: groups with the addition of vitachick (V), treated 10% Moringa extract of drinking water (M1), 15 % Moringa extract of drinking water (M2), 30 % Moringa extract of drinking water (M3), and control of drinking water without drugs (C). Weight and feed data are taken daily to calculate Feed Conversion Ratio (FCR) and Average Daily Gain values ( ADG). The treatment was carried out for 12 days. On the 13th day, the chicken is discharged and then the intestine is taken for Hematoxylin-eosin staining. Data on body weight, feed consumption and drinking water were analyzed by Anova.Results: The FCR value of group treated with 30 % Moringa extract of drinking water has a more efficient value than the control group and other treatments. Based on statistical analysis, body weight of the group treated with of 10 %, 30 % Moringa extract and Vitachick® which were compared with controls differed significantly (P <0.05). The best performance index of group with treated of 30 % Moringa extract of drinking water was 346.28. Moringa extract improves the morphology of chicken intestine.Conclusion: Based on these data it can be concluded that the addition of Moringa extract in drinking water for 12 days can be used as an alternative feed supplement by improving intestinal performance and morphology.

Medicines are widely used to prevent or cure illness. One of the medicines which often used to relieve stomach pain is a medicines that contains digestive enzymes. This type of medicines is much needed by hospitals and other health institutions. Hospitals and other health institutions should ensure the availability of medications for patients. This situation forces health institutions to deal with the uncertainty of medicine usage. Hospitals as one of the health institutions have some challenges. One of the challenges that must be faced is to ensure the availability of medicines for patients. The ability to predict can help ensure medicines availability in hospital. In this study will presents the forecasting model using Long Term Short Memory (LSTM) method to predict the need for medicines that contain digestive enzymes in the hospital. This method is chosen because it is known to have a high accuracy to predict stationary data. One of the methods used in input identification for the LSTM method is by using the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF). The results of this study indicate that the use of LSTM method suitable for time series forecasting in historical dataset, with 12.733 Root Mean Square Error (RMSE) value.

Medicine Inventory Management by ABC-VED Analysis in the Pharmacy Store of Veterinary Hospital, Yogyakarta, Indonesia

Registration system is one of the most important elements in an organization or institution that involves the presence of customers and one by one services. Nowadays, with the development of technology, services process in an institution become more effective and efficient. One of the institutions that require the development of this technology, in the form of hospital information management system, is the veterinary hospital. The conventional system has many shortcomings include allowing an error in writing the patient data also the patient registration recaps is less effective and more time consuming. Therefore, a prototype of RSH management information system was made as an ilustration in the design of hospital information management system. The focus of this study is the patient registration system which use First In First Out (FIFO) algorithms where the patient who came first to the hospital is the one who enrolled first.

The medicine is a tool for patients either human or animal to treat or prevent disease. One of the medicines which often used to help prevent infections is an antiseptic medicine. Povidone-iodine is an antiseptic and disinfectant medicine that is extensively used by hospital and other health care. A health care institution such as pharmacies or hospitals must ensure the availability of medicines for patients. These things make the pharmaceutical dealing with the uncertainty of the medicine needed. Veterinary hospital as a health service provider has several challenges. One of the challenges is it must ensure the availability of the medicine needed at all time. The predictive capability of the amount of medicine usage can assist for managing the availability of medicines in veterinary hospitals. This study analyses and presents a forecasting model using ARIMA method to predict an antiseptic povidone-iodine usage at Prof. Soeparwi Veterinary Hospital. ARIMA method was selected because the method can be used in fitting forecasting models when there is a non-stationary time series and the method has capability to correct for local trend in data. Results of this study is ARIMA (1,0,1) was selected as a suitable model to represent historical dataset.