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Journal of Antibiotics Research

ISSN: 2574-5980

Open Access
Research Article
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A Retrospective Study in DUE and ATC/DDD Evaluation of Antibiotics in Specific Departments of a Tertiary Care Hospital

Received Date: August 29, 2023 Accepted Date: August 29, 2023 Published Date: August 30, 2023

Copyright: © 2023 KV Surya Teja. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

In the pre-anesthesia era, the anguish of planned surgical maneuver was dreadful and the experience of actual procedure “utterly speechless torture”. Although, the concept of pain relief and even total insensibility was not unfamiliar to medical profession, some of the “Big Giants in Medicine” believed “knife and pain as inseparable” and the efforts to relieve or prevent pain “in vain”. In such a situation the anesthesia,one of the greatest boons of science for mankind, “burst like a revolution on medical profession”. Despite hostility from religious sect, professional colleagues and civil societies the pioneers in discovery of anesthesia stood firm, unshaken by the negative criticism. Although the fate of the active contestant of “Ether Controversy” was mournful,their untiring and dedicated struggle to relieve the sufferings of mankind can never be underscored. Renowned Arab surgeon Ibn al Quff (1232-1286 AD) was the first to suggest anesthesia as independent speciality. However, it took almost 700 years for his dream to come true.

Background:Large numbers of nations are associated with utilization of anti-toxins regardless of remedy (OTC medications). This DDD/ATC value contributes to improved antibiotic use quality. The principal objective is to direct improvement of sane medication use of strategies and to give a standard technique for information for future evaluation.

Aim and Objective:This study aims to examine the drug use and ATC/DDD evaluation of antibiotics in specific departments of a tertiary care hospital in a retrospective fashion. To sort the case reports of patients in light of socioeconomics, we likewise recognized the most regularly involved anti-infection agents in various sicknesses and divisions, alongside examining drug use designs in view of WHO rules, assessing therapy diagrams in view of course of organization, and furthermore researching the significance of units of estimation in measuring anti-toxins utilizing ATC/DDD methodology.

Methods:During our ward participation of inpatient departments from September 2017 to December 2019, data would be reviewed within six months from treatment charts, prescriptions, and case sheets of in-patients admitted to specific departments like General Medicine, General Surgery, and Orthopaedics. It was a cross-sectional, retrospective, and observational study on inpatients at Government General Hospital, Kadapa.

Results:In this review, a sum of 900 subjects treated with anti-toxins were incorporated. There were 499 female subjects (55.5%) and 401 male subjects (44.5%). The average number of drugs prescribed per encounter (2%), the percentage of drugs with generic names (96%), the percentage of drugs prescribed from the essential drug list (100%), and the percentage of drugs prescribed as antibiotics (100%) were all found in this study

Conclusion:In this study, antibiotics were used for six months in a tertiary care hospital. Both the percentage of antibiotic use and the DDD/100 bed-days were used to calculate antibiotic use. In the study, penicillin, a broad-spectrum cephalosporin, was used more. The fact that generic prescribing is declining demonstrates the need to examine and enhance all of these parameters in order to provide the patient with quality and rational treatment.

Keywords: Antibiotics; Atc/Ddd Value; Drug Utilisation Evaluation (Due); Rational Drug Use; Irrational Drug Use

Introduction

Antibiotics are used to treat only bacterial infections. Usually, an antibiotic is a substance that inhibits and kills the growth of other microorganisms. Many countries are involved in the usage of antibiotics and they are the largest single group of drugs purchased for the development of antibiotics [1]. The greater the use of antibiotics, whether appropriate or not, exerts selective pressure by reducing the reproductive success of microorganisms and, here, by speeding up the development of antimicrobial resistance (AMR) [2]. Drug utilisation is defined by the WHO as the “marketing, distribution, prescription, and use of drug in society, with special emphasis on the resulting medical, social, and economic consequences” [3]. Studies on drug usage evaluation serve as a tool to assess the quality of therapeutic care and evaluate drug usage and play an important role in improving drug dispensing policies in tertiary care hospitals at each and every level to promote the rational use of antibiotics [4]. The drug usage pattern is being studied to analyse the present scenario and the development of drug usage at various levels of the healthcare system [5].

The Anatomical Therapeutic Chemical (ATC) code is a tool to express drug utilisation research in order to improve the quality of drug use. DDD is appropriate for drugs that have already been provided with an ATC code. These parameters are useful for evaluating drug utilization at every level of the healthcare system [6]. To assess the units of measurement used to quantify antibiotic use and discussions about the interpretation of these units are rarely presented in the scientific literature.

DDDper1000persons per day = N×M×Q×1000/DDD×P×T

Where

  • Prescriptions refers to the number of prescriptions generated or dispensed (N),
  • Mass is the dose in, e.g., milligrams or grams (M),
  • Quantity refers to the pack size (Q),
  • DDD is the figure assigned in the WHO guidelines (check dose units),
  • Population is the sample size reflected (P); the calculation is multiplied by 1000 toconvert the population size to “per 1000 population”,
  • Time is the number of days of the study duration (days) [7, 8].
  • The ultimate goal is to guide the development of rational-use drug policies and to provide a standard method of data for future assessment [9]. Rational drug use is a quality healthcare service, particularly in the use of antibiotics and also its usage that is cost-effective with increasing drug toxicity, clinical therapeutic effects, and minimising the occurrence of resistance [10]. Irrational use of medicine is the use of too many medicines per patient (polypharmacy), inappropriate use of antibiotics, inadequate dosage for non-bacterial infections, failure to prescribe under clinical guidelines, inappropriate self-medication, and also overuse of prescribed medicines [11]. Hence, the current study was conducted to assess the Drug utilization and ATC/DDD evaluation of antibiotics in specific departments of a tertiary care hospital: a retrospective study in Government General Hospital (GGH) – Kadapa, Andhra Pradesh [12].

    Aim

    The purpose of this study is to conduct a retrospective investigation into the drug utilisation and ATC/DDD evaluation of antibiotics in specific departments of a tertiary care hospital and to evaluate the drug utilisation and ATC/DDD evaluation of antibiotics in specific departments of a tertiary care hospital.

    The key objectives of the study:

  • To categorise the case patients based on demographics.

  • To identify the most commonly used antibiotics in different diseases and departments.
  • To analyse drug utilisation patterns based on WHO guidelines.
  • To evaluate treatment charts based on route of administration.
  • To Classify commonly used antibiotics by using ATC/DDD
  • To investigate the importance of units of measurement in quantifying antibiotics using ATC/DDDD methodology.
  • Methodology
    Source of Data

    Data was be collected from treatment charts, prescriptions, and case sheets of the in-patients who are admitted to specific departments such as General Medicine, General Surgery, and Orthopaedics during our ward participation of inpatients departments from September 2017–December 2019.

    Study Design and Study Period

    It was a retrospective, observational, cross-sectional type of study was conducted on the in-patients at Government General Hospital, Kadapa.

    Sample Size

    The total sample size was about 900 patients.

    Inclusion Criteria

    1. The study included if the subject satisfies the following criteria:

    2. Patients admitted to the in-patient unit, regardless of gende

    3. Patients who had undergone antibiotic treatment between the ages of 20 and 80

    4. Patients admitted in the specific department such as General Medicine, General surgery and Orthopaedics.

    5. Antibiotics available in the G.G.H Essential Drug List

    6. Antibiotics are prescribed in different drug dosage forms.

    All patients who are prescribed at least one antibiotic and are admitted to specific departments such as General Medicine, General Surgery, and Orthopaedics

    Exclusion Criteria:The study excluded the following people:

    1. Patients who are allergic to antibiotics

    2. Paediatric population

    Method of Collection of Data

  • Annexure-I (Patient Data Collection Form)
  • Annexure-II (Treatment Regimen)
  • Annexure-III (Laboratory Investigations)
  • Statistical Analysis

    All the data of recruited subjects was entered into a Microsoft excel spreadsheet then Descriptive statistics like mean, standard deviation was used to assess the different demographic parameters. We assigned an ATC code to the antibiotic use and calculation of DDD/100 bed-days themost commonly used antimicrobials were classified using the ATC Classification system, and drug utilisation was measured as DDD/100 bed-days. In the ATC Classification system, drugs are divided into different groups according to the organ or system on which they act and their chemical, pharmacological, and therapeutic properties.

    Results

    A total of 900 samples were collected from December 2020 to May 2021 in a period of 6 months, among them 300 samples were collected from 2017 medical record department,300 samples were collected from 2018 medical record department and 300 samples were collected from 2019 medical record department.

    Most commonly used antibiotics in general medicine for common diseases are pneumonia, pancreatitis, thrombocytopenia, malaria, CKD, tuberculosis, PUD, COPD, liver cirrhosis, epilepsy, jaundice, bronchial asthma, hepatomegaly, ALD, PID, Takayasis arteritis, endocarditis, cad,oedema, typhoid fever, uti, parkinsons, gastritis, stroke, jaundice, gastroenteritis, seizures, asthma, anaemia, cholecystitis, hypoalbuminemia. The most commonly used antibiotics are ceftriaxone, amoxicillin with clavulanic acid, ampicillin, piperacillin with tazobactam, cefperazone with salbactam, cefotaxime, cefixime, amikacin, streptomycin, gentamicin, doxycycline, azithromycin, ciprofloxacin, levofloxacin, ofloxacin, norfloxacin, gatifloxacin, metronidazole, cotrimoxazole (sulphamethoxazole + trimethoprim), nitrofurantoin. (Shown in table 4)

    Most commonly used antibiotics in general surgery for common diseases are appendectomy, hernia, IBD, varicose veins, trauma ulcer, necrosing fasciitis, synovitis, pancreatitis, cellulitis. The most commonly used antibiotics are ceftriaxone, gentamicin, amoxicillin with clavulanic acid, ampicillin, piperacillin with tazobactam. (Shown in table 5).

    Most commonly used antibiotics in orthopaedics for common diseases are rheumatoid arthritis, osteoarthritis, arthralgia, low backpain, hip fracture, fractures, tennis elbow. The most commonly used antibiotics are ceftriaxone, gentamicin, amoxicillin with clavulanic acid, doxycycline, piperacillin with tazobactam, ciprofloxacin. (Shown in table 6).

    The WHO assigned DDD was mentioned in the table number. Our study results were below the standard DDD, which indicates rational prescribing. All the antibiotics used in In-patient were found to be rational. The observed value of commonly used antibiotics in General Medicine were ceftriaxone (0.11), Amoxicillin and potassium clavulanate/ clavulanic acid(0.12), Ampicillin (0.06), Piperacillin with tazobactam (0.032),Cefperazone with salbactam (0.005), Cefotaxime (0), Cefixime (0.12), Amikacin (0.001), Streptomycin (0.003), Gentamicin (0.02), Doxycycline (0.426), Azithromycin (0.426), Ciprofloxacin (0.006), Levofloxacin (0.095), Ofloxacin (0.18), Norfloxacin (0.002), Metronidazole (0.001), Cotrimoxazole (0.16), Nitrofurantoin (0.007). (Shown in table 7).

    The WHO assigned DDD was mentioned in the table number. Our study results were below the standard DDD, which indicates rational prescribing. All the antibiotics used in In-patient were found to be rational. The observed value of commonly used antibiotics in General Surgery were Ceftriaxone (0.065), Amoxicillin with potassium clavulanate/ clavulanic acid (0.32), Piperacillin with tazobactam (0.005), Ampicillin (0.005), Gentamicin (0.081), Ciprofloxacin (0.020). (Shown in table 8)

    The WHO assigned DDD was mentioned in the table number. Our study results were below the standard DDD, which indicates rational prescribing. All the antibiotics used in In-patient were found to be rational. The observed value of commonly used antibiotics in Orthopaedics were Ceftriaxone (0.03), Amoxicillin with potassium clavulanate/ clavulanic acid (0.058), Piperacillin with tazobactam (0.0086), Doxycycline (0.58), Gentamicin (0.17), Ciprofloxacin (0.011). In this Moderate usage of antibiotics had more ATC/DDD value of antibiotics. (Shown in table 9).

    Discussion

    Our clinical study was conducted on the drug utilisation and ATC/DDD evaluation of antibiotics in specific departments of a tertiary care hospital. It was found that slightly more female patients were admitted to the various departments in the hospital when compared to male patients. Prescribed drugs by generic names would make it easier for the hospital to have control over its regulatory stock and also lower the cost of treatment. Most patients were involved in IV therapy only

    In this study, we concluded that, according to WHO standards, every drug must be prescribed with a generic name. to avoid this type of confusion between different classes of drugs with nearly similar brand names while dispensing and also to decrease the cost of therapy which is similar to the study of Kanishk Kala et.al., in 2019 [3]. Some key indicators, such as the number of drugs prescribed under generic names and the number of drugs on the essential medicine list, should always be close and also mentioned depending on the clinical needs of the patients which is similar to the study of Ajaya kumar sahoo et.al., in 2020 [4]. In a majority of the 900 cases, a majority of the drugs were purely prescribed based on their generic names (97.33%) which is similar to Nilay Solanki et.al. in 2019 [5]. In this study, the prescribing frequency of antibiotics per prescription is mostly one (40.33%) or two (26.11%) was Ceftriaxone and Amoxycillin and potassium clavulanate / clavulanic acid were the most commonly prescribed medications in the general medicine, general surgery, and orthopaedics departments respectively were found to be effective for treating infections both empirically and prophylactically. which is similar to R. Suraj et.al., in 2008 [7].

    Conclusion

    This study reports the use of antibiotics in a tertiary care hospital for six months. Antibiotic usage was calculated in both the percentage of antibiotic use and DDD/100 bed-days. ATC-DDD system which is accepted globally can be used in antibiotic usage studies for better expression and possible cross comparisonacross similar studies. The use of antibiotics usually broad-spectrum cephalosporins, pencillins was high in the study. A high average number of drugs per prescription along with high use of injections was noted. Generic prescribing is less this shows that all these parameters should be checked and improved to provide quality and rational treatment to the patient.

    Conflicts of Interest

    Nil

    1 KNS Karthik, Konda Ravi Kumar (2017) retrospective study on usage of different antibiotics: world journal of pharmaceutical and medical research 3: 251-4.
    2 Nebyu Daniel Amaha, Dawit G. Weldemariam et al. (2014 to 2018) Antibiotic consumption study in two hospitals in Asmara from using WHO’sdefined daily dose (DDD) methodology: PLOS ONE.
    3 Kanishk Kala, Rupinder Kaur Sodhi et al. (2019) Drug Utilization Evaluation of Antibiotics in District Hospital Baurari Tehri Uttarakhand: International Journal of Pharmacy and Biological Sciences, IJPBS 9: 01-8.
    4 Ajaya Kumar Sahoo1, Dhyuti Gupta July-September (2020) Retrospective Analysis of Drug Prescription Statistics in a Tertiary Care Center in India: Recommendations for Promoting Prudent Utilization of drugs: Journal of Research in Pharmacy Practice 9.
    5 Solanki N Patel (2019) Drug Utilization Pattern and Drug Interaction Study of Antibiotics Prescribed to Orthopaedic Patients in Private Hospital: Arch Pharma Pract 10: 114-7.
    6 Suhena R Patel, Amit M Shah (2016) Evaluation of drug utilization pattern of antimicrobials using ATC/DDD system in intensive care unit of a tertiary-care teaching hospital: International Journal of Medical Science and Public Health 5.
    7 R Suraj, Rejitha Gopinath (2008) Study to Assess the Value of ATC/DDD Methodology in Quantifying Antibiotic Use at a Tertiary CareTeaching Hospital: Indian Journal of Hospital Pharmacy 45: 121-5.
    8 Samantha Hollingworth, Therése Kairuz (2021) Measuring Medicine Use: Applying ATC/DDD Methodology to Real-World Data: Pharmacy 9: 60.
    9 Samantha Hollingworth, Therése Kairuz (2021) Measuring Medicine Use: Applying ATC/DDD Methodology to Real-World Data: Pharmacy 9: 60.
    10 Sintiya regimulya, sri oktavia (2021) A Review: Rational Drug Use of Antibiotics in Patients with Urinary Tract Infection at Hospitals in Indonesia: IOSR Journal of Pharmacy 11: 01-9.
    11 Shahzar Khan, Shah Faisal (2021) Irrational use of antibiotics as major cause of drug resistance in developing and developed countries: Innovative Scientific Information & Services Network, Bioscience Research 18: 2292-300
    12 Kanishk Kala, Rupinder Kaur Sodhi (September 2017) Drug Utilization Evalauation of Antibiotics in Dh Uttarakashi: IOSR Journal Of Pharmacy 7: 01-5.

    Journal of Antibiotics Research

    Tables at a glance
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    Table 1
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    Table 2
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    Table 3
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    Table 4
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    Table 5
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    Table 6
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    Table 7
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    Table 8
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    Table 9
    Figures at a glance
    image-icon
    Figure 1
    image-icon
    Figure 2
    image-icon
    Figure 3
    Figure 1: Gender wise Distribution
    In this study, a total of 900 subjects treated with antibiotics were included. Among them 401 subjects were males (44.5%) and 499 subjects were females (55.5%). (Shown in figure 1)
    Figure 2: Age group Categorization
    This study included 900 patients and out of them most of the patients was observed from the age group between 21-30 years (23%), next from the age group 31-40 years (22.9%), next from the age group 41-50 years (19.9%), next from the age group 51-60 years (17.7%), next from the age group 61-70 years (10.7%) and the age group 71-80 years (5.8%) (Shown in figure 2)
    Figure 3: Based on Number of Antibiotics per Prescription
    In this study, the antibiotics per prescription per patient of 1 antibiotic 295 (32.8%), 2 antibiotics 385 (42.7%), 3 antibiotics are 167 (18.6%) and 4 number of antibiotics per prescription per patient are 53 (5.9%). (Shown in figure 3).

    S. No

    Route of administration

    Total

    Percentage

    1

    ORAL

    531

    59 %

    2

    IV

    807

    89.7%

    Table 1: Based on Route of Administration
    In this study reveals the oral route usage of drugs was59% (531)and the Iv route usage of drugs was 89.7% (807) (shown in the table 1).

    S.No

    Department

    Average length of stay

    1

    General medicine

    3.5 days

    2

    Orthopedics

    4 days

    3

    General surgery

    5 days

    Table 2: Based on average length of stay in hospital
    In this study the average length of stay in hospital, the General Medicine Department was 3.5 days, orthopaedics was 4 days and General Surgery was 5 days.(Shown in table 2)

    WHO Core Prescribing Indicators

    Value

    The average number of drugs per encounter

    2

    Percentage encounter prescribed injections

    59 %

    Percentage of drugs with generic names

    96 %

    Percentage of drugs prescribed in the essential drug list

    100 %

    Percentage encounter prescribed antibiotics

    100 %

    Table 3: WHO Core Prescribing Indicators
    In this Study the average number of drugs per encounter (2), Percentage encounter prescribed injections (59%), Percentage of drugs with generic names (96%), percentage of drugs prescribed in the essential drug list (100%), Percentage encounter prescribed antibiotics (100%). (Shown in table 3).

    Department

    Disease

    Drugs

    General Medicine 300(100%)

    Pneumonia 15(5%)
    Pancreatitis 9(3%)
    Thrombocytopenia 18(6%)
    Malaria 18(6%)
    CKD 12(4%)
    TB 15(5%)
    Pud 15(5%)
    COPD 21(7%)
    Liver Cirrhosis 9(3%)
    Epilepsy 6(2%)
    Jaundice 12(4%)
    Bronchial Asthma 12(4%)
    Hepatomegaly 6(2%)
    ALD 12(4%)
    PID3(1%)
    Takayasis Arteritis 3(1%)
    Endocarditis 3(1%)
    Cad 3 (1%)
    Oedema 9(3%)
    Typhoid Fever 27(9%)
    Uti 15(5%)
    Parkinsons 9(3%)
    Gastritis 9(3%)
    Stroke 3(1%)
    Jaundice 6(2%)
    Gastroenteritis 12(4%)
    Seizures 6(2%)
    Asthma 6(2%)
    Anaemia 3(1%)
    Cholicystitis 3(1%)
    Hypoalbumunimia 3(1%)

    Amoxicillin 63(50%)
    Ampicillin 24(19%)
    Piperacillin 39(30%)
    Tazobactam 39(100%)
    Clavulanic acid 63(80.7%)
    Salbactam 15(19.2%)
    Cefperazone 15(7.69%)
    Cefotaxime 3(1.5%)
    Ceftriaxone 165(84.6%)
    Cefixime 12(6.15%)
    Amikacin 3(25%)
    Streptomycin 3(25%)
    Gentamicin 6(50%)
    Doxycycline 42(100%)
    Azithromycin 42(100%)
    Ciprofloxacin 12(20%)
    Levofloxacin 9(15%)
    Ofloxacin 18(13.33%)
    Norfloxacin 15(25%)
    Gatifloxacin 6(10%)
    Metronidazole 48(100%)
    Co-trimoxazole 27(100%)
    Nitrofurantoin 15(100%)

    Table 4: Commonly Used antibiotics in different disease and department of general Medicine

    Department

    Diseases

    Drugs

    General Surgery 300 (100%)

    Appendectomy 30(10%)
    Hernia 11(3.66%)
    IBD 32(10.66%)
    Varicose Veins 24(8%)
    Trauma Ulcer 57(19%)
    Necrosing Fascitis 36(12%)
    Synovitis 35(11.66%)
    Pancreatitis 31(10.33%)
    Cellulitis 44(14.66%)

    Ceftriaxone 129(100%)
    Gentamicin 24(100%)
    Amoxicillin 76(71.6%)
    Amipicillin 14(13.2%)
    Piperacillin 16(15.1%)
    Tazobactem 16(16%)
    Clavulanic Acid 76(76%)

    Table 5: Commonly Used antibiotics in different disease and department of general surgery

    Department

    Diseases

    Drugs

    Orthopedics 300 (100%)

    Rheumatoid Arthritis 74(24.6%)
    Osteoarthritis 53(17.66%)
    Arthralgia 37(12.33%)
    Low Back Pain 70(23.3%)
    Hip Fracture 26(8.66%)
    Fractures 29(9.66%)
    Tennis Elbow 11(3.66%)

    Ceftriaxone 69(100%)
    Gentamicin 51(100%)
    Amoxicillin 96(100%)
    Doxycycline 57(100%)
    Tazobactem 57(100%)
    Clavulanic Acid 32(32%)
    Ciprofloxacin 4(4%)

    Table 6: Commonly Used antibiotics in different disease and department of orthopaedics

    S. No

    Antibiotics

    ATC Code

    DDD Value/ 1000 Inhabitants (mg)

    WHO Code (g)

    1.  

    Ceftriaxone

    J01dd04

    0.11

    2

    1.  

    Amoxicillin With Clavulanic Acid

    J01cr02

    0.12

    1.5

    1.  

    Ampicillin

    J01ca01

    0.06

    2

    1.  

    Piperacillin With Tazobactam

    J01cr05

    0.0032

    14

    1.  

    Cefperazone With Sulbactam

    J01dd62

    0.005

    4

    1.  

    Cefotaxime

    J01dd01

    0

    4

    1.  

    Cefixime

    J01dd08

    0.12

    0.4

    1.  

    Amikacin

    J01gb06

    0.001

    1

    1.  

    Streptomycin

    J01ga01

    0.003

    1

    1.  

    Gentamicin

    J01gb03

    0.02

    0.24

    1.  

    Doxycycline

    J01aa02

    0.426

    0.1

    1.  

    Azithromycin

    J01fa10

    0.426

    0.3

    1.  

    Ciprofloxacin

    J01ma02

    0.006

    1

    1.  

    Levofloxacin

    J01ma12

    0.095

    0.24

    1.  

    Ofloxacin

    J01ma01

    0.18

    0.4

    1.  

    Norfloxacin

    J01ma06

    0.002

    0.8

    1.  

    Metronidazole

    J01xd01

    0.001

    1.5

    1.  

    Cotrimoxazole (Sulphamethoxazole + Trimethoprim)

    J01ee01

    0.16

    1.06

    1.  

    Nitrofurantoin

    J01xe01

    0.007

    0.2

    Table 7: DDD value of commonly used antibiotics at General Medicine

    S. No

    Antibiotics

    Atc Code

    Ddd Value/ 1000 Inhabitants

    Who Ddd Value (G)

    1.  

    Ceftriaxone

    J01dd04

    0.065

    2

    1.  

    Amoxicillin With Clavulanic Acid

    J01cr02

    0.32

    1.5

    1.  

    Piperacillin With Tazobactam

    J01cr05

    0.005

    14

    1.  

    Ampicillin

    J01ca01

    0.005

    2

    1.  

    Gentamicin

    J01gb03

    0.081

    0.24

    1.  

    Ciprofloxacin

    J01ma02

    0.020

    1

    Table 8: DDD value of commonly used antibiotics at General Surgery

    S. No

    Antibiotics

    ATC Code

    DDD Value/ 1000 inhabitants

    WHO DDD Value (g)

    1.  

    Ceftriaxone

    J01DD04

    0.03

    2

    1.  

    Amoxicillin With Clavulanic Acid

    J01CR02

    0.058

    1.5

    1.  

    Piperacillin With Tazobactam

    J01CR05

    0.0086

    14

    1.  

    Doxycycline

    J01AA02

    0.58

    0.1

    1.  

    Gentamicin

    J01GB03

    0.17

    0.24

    1.  

    Ciprofloxacin

    J01MA02

    0.011

    1

    Table 9: DDD value of commonly used antibiotics at Orthopaedics

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