Prafulla Kumar Swain

Antimicrobial drug prescribing patterns for community-acquired pneumonia in hospitalized patients: A retrospective pilot study from New Delhi, India

Objective: The objective of this study was to determine patterns and frequency of antimicrobial drug use among hospitalized patients with community-acquired pneumonia (CAP). Methodology: A retrospective 5 years (April 2007–March 2012) detailed medical record review of patients diagnosed with CAP and discharged to home from Non-Intensive Care Unit respiratory medicine wards of two public hospitals in Delhi. Results: A total of 261 medical records were analyzed. Over the 5 years, 82.0% (2007–08), 78.6% (2008–09), 59.5% (2009–10), 64.7% (2010–11), and 67.8% (2011–12) patients were prescribed two antimicrobials. In the last two study years, the proportion of patients receiving three antimicrobials increased (from 2.0% to 26.5% and 28.8%), while the proportion receiving monotherapy decreased (from 16.0% to 8.8% and 3.4%). In accordance with guidelines, beta-lactams and macrolides were the two most frequently prescribed antimicrobials (34.1%). However, newer generation beta-lactams were prescribed. A total of 37 patients were prescribed beta-lactam-tazobactam combination preparations. Overall, beta-lactams constituted more than 40% of prescriptions while macrolides were the second most prescribed class. Cephalosporin prescriptions significantly increased (P < 0.01) and penicillin prescriptions significantly decreased over study periods. The prescription of fluoroquinolones also decreased (21.5–6.0%, P < 0.01) and aminoglycoside prescription ranged from 9.7% to 16.4%, over 5 years. Reasons for prescribing three antimicrobials, use of aminoglycosides, or higher-end/reserve antibiotics were not mentioned in the medical records. There were no hospital-specific guidelines for doctors to follow in the treatment of CAP. Conclusions: These findings suggest the need for implementing antimicrobial treatment guidelines. Adequate documentation and monitoring of antibiotic use for feedback are also lacking. An antimicrobial stewardship program may offer the most comprehensive solution for appropriate use of antimicrobials.

A Multistate Markov Model Based on CD4 Cell Count for HIV/AIDS Patients on Antiretroviral Therapy (ART)

Abstract: The main purpose of this study is to assess the impact of Antiretroviral Therapy (ART) by using a multistate Markov model to estimate transition intensities and transition probabilities among various states (transient as well as absorbing) of the AIDS patients. A total of 580 AIDS patients were included in this study who are undergoing Antiretroviral Therapy treatment in the ART centre in New Delhi during the period of April 2004 to April 2011. The patients are classified in different states on the basis of their available CD4 cell counts. The authors also estimated the mean sojourn time and total length of stay in each state before absorption, and also examined the effects of explanatory variables (i.e Age, Sex, Mode of transmission) on the rates of transition using Cox’s proportional hazard model.

On the assessment of various factors effecting the improvement in CD4 count of aids patients undergoing antiretroviral therapy using generalized Poisson regression

An important marker for identifying the progression of human immunodeficiency virus (HIV) infection in an individual is the CD4 cell count. Antiretroviral therapy (ART) is a treatment for HIV/AIDS (AIDS, acquired immune-deficiency syndrome) which prolongs and improves the lives of patients by improving the CD4 cell count and strengthen the immune system. This strengthening of the immune system in terms of CD4 count, not only depends on various biological factors, but also other behavioral factors. Previous studies have shown the effect of CD4 count on the mortality, but nobody has attempted to study the factors which are likely to influence the improvement in CD4 count of patients diagnosed of AIDS and undergoing ART. In this paper, we use Poisson regression model (GPR) for exploring the effect of various socio-demographic covariates such as age, gender, geographical location, and drug usage on the improvement in the CD4 count of AIDS patients. However, if the CD4 count data suffers from under or overdispersion, we use GPR model and compare it with negative binomial distribution. Finally, the model is applied for the analysis of data on patients undergoing the ART in the Ram Manohar Lohia Hospital, Delhi, India. The data exhibited overdispersion and hence, GPR model provided the best fit.