2015-42-4_6
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This document discusses a study investigating hospital-acquired pneumonia (HAP) and the association between HAP and chronic comorbidities. The study included 213 HAP patients and found the most common pathogens were Streptococcus spp. for early-onset pneumonia and Acinetobacter spp. for late-onset pneumonia. Antibiotics like quinolones, cephalosporins and carbapenems were most commonly used but showed high resistance rates. Higher Chronic Disease Scores, older age, cancer, and mechanical ventilation were associated with worse treatment outcomes.
2015-42-4_6
- 1. Investigation on hospital-acquired pneumonia and the association between hospital-acquired pneumonia and chronic comorbidity at the Department of General Internal Medicine, University Medical Center Hochiminh City MT. Nguyen1 , TD. Dang Nguyen1* 1 Department of Clinical Pharmacy, Faculty of Pharmacy, University of Medicine and Pharmacy, Hochiminh City, Vietnam Abstract Hospital-acquired pneumonia (HAP) is the most common cause of death among nosocomial infections. Controlling for risk factors, especially comorbid conditions plays an important role in the prevention and management of HAP. The Chronic Disease Score (CDS) has been widely used as a tool for comorbidity measurement of chronic diseases. However, little is known about the use of CDS in estimating the impact of comorbidity on infectious conditions. This descriptive cross-sectional study aims at describing the charateristics of HAP patients, the use of antibiotics and identifying the association between chronic comorbidities using CDS and treatment outcome among patients with HAP. The study population included 213 patients diagnosed with HAP admitted to the Department of General Internal Medicine, University Medical Center Hochiminh city from October 1st 2014 to March 31st 2015. The mean CDS score was 4.9, ranging from 0 to 15. The most common pathogen associated with early-onset pneumonia (NP) is Streptococcus spp. whereas Acinetobacter spp. is the most common pathogen found in late-onset NP. Third generation cephalosporins and quinolones were markedly resistant. The combination of two antibiotics accounted for 65.3% of cases treated with antibiotic empiric therapy. Multivariable logistic regression analysis identified that cancer (OR = 4.95; 95% CI 1.46-16.76), CDS score (OR = 0.832; 95% CI 0.71 - 0.97), age from 45 to 64 (OR = 14.09; 95% CI 6.77 - 21.96), age 65 and above (OR = 15.13; 95% CI 7.87-15.92) and mechanical ventilation (OR = 5.05; 95% CI 1.23 - 20.60) were associated with failure in treatment outcome. Keyword: chronic disease score, comorbidity, hospital-acquired pneumonia 1. INTRODUCTION Hospital-acquired pneumonia (HAP) isthesecondmostcommonnosocomialinfection and is associated with high morbidity and mortality. HAP carries a crude mortality rate of 30% to 70%, increases hospital stay by an average of 7 to 9 days and produces an excess cost of more than $40,000 per patient1 . Antibiotic resistance among major pathogens ofHAPhasbecomeaglobalchallenge.Inrecent reports on nosocomial infection in Vietnam, Klebsiella spp. was found to be resistant to third generation cephalosporins (90%) and vancomycin resistance in Staphylococcus aureus resistance to vancomycin was also reported2,3,4 . In addition to the rational use of anti- biotics, controlling for risk factors, especially comorbid conditions plays an important role in the prevention and management of HAP. Several tools for comorbidity measurement have been developed using hospital administrative or pharmacy databases. The Chronic Disease Score (CDS), a pharmacy-based indicator, has been widely used as an effective tool to measure comorbid conditions of chronic diseases. CDS *Corresponding author: E-mail: dtrangpharm@yahoo.com, trang.dnd@umc.edu.vn Original Article Mahidol Univ J Pharm Sci 2015; 42 (4), 195-202
- 2. MT. Nguyen et al. 196 has been validated for use as a predictor of physician-rated disease status, self-rated health status, hospitalization, and mortality5,6 . However, little is known about the use of CDS in estimating the impact of comorbidity on infectious conditions. This study aims at providing updated information on the use of antibiotic therapy on the treatment of HAP and identifying the association between chronic comorbidities using CDS and treatment outcome among patients with HAP. 2. MATERIALAND METHODS 2.1. Study population Data was obtained from all patients aged 18 and over with diagnosis of HAP at discharge at the Department of General Internal Medicine, University Medical Center Hochiminh City between October 1st 2014 and March 31st 2015. Exclusion criteria included pregnancy, immunodeficiency and fungal pneumonia. A total number of 213 medical profiles of patients that met the selection criteria were taken into analysis. 2.2. Methods A descriptive cross-sectional study was conducted to provide descriptive information on the characteristics, risk factor, comorbidities and antimicrobial treatment of HAP patients. Microbiologic diagnosis was provided by the Department of Microbiology, University Medical center. Sensitivity to antibiotics was determined using disk diffusion test based on the protocol of Clinical and Laboratory Standards Institute (CLSI, 2014). Multivariable logistic regression was used to identify factors statistically associated with treatment outcome (success/failure). All statistical analysis was performed using SPSS 22.0 software package. 3. RESULTS Characteristics of the population Patients aged 65 and above accounted for 74.2% of the study population whereas only 7.5% were youger than 45 years old. The majority of cases were early-onset (66.2 %), diagnosed on day 4.5 ± 2.9 from admission. The average length of stay was 13 days. 169 patients had at least one risk factors (79.3%), ranging from 1 to 4. Of the factors observed, the use of H2 blockers, proton pump inhibitors (PPIs) or antacids accounted for 68.1%. Nasogastric intubation (19.7%), hemoglobin below 10 g/dl (18.8%) and mechanical ventilation (18.3%) were among the leading factors previously reported to be associated with HAP. The most frequent comorbid chronic diseases included hypertension (55.4%), lung diseases (29.1%), diabetes mellitus (28.6%) and cardiovascular diseases (27.7%). Physical examination and laboratory investigations Confusion (16%), hypotension (25.4%), tachycardia (33.8%) and tachypnea (6.1%) were symptoms remarkedly observed in the study population. 29 patients (13.6%) had an initial SpO2 less than 90%, mainly due to comorbid pulmonary diseases. Chronic diseases scores and comorbidities (CDS) The mean CDS score of the study population was 4.9 ± 3.4, ranging from 0 to 15. Mean CDS were significantly different among 3 age groups (<45; 45-64; >=65). Mean CDS were higher in women (5.3 ± 3.2) than in men (4.5 ± 3.4). However, the difference was not statistically significant. Almost HAP hospital profiles were observed with comorbidities (94.8%), ranging from 1 to 5. The mean number of comorbid diseases were 2.2 ± 1.1. Hypertension (55.4%), other lung diseases (29.1%), diabetes mellitus (28.6%) and other cardiovascular diseases (27.7%) were the most common group of comorbid diseases recorded. Baseline characteristics, CDS and laboratory findings of the study population are presented in Table 1.
- 3. 197Investigation on hospital-acquired pneumonia and the association between hospital-acquired pneumonia and chronic comorbidity at the Department of General Internal Medicine, University Medical Center Hochiminh City Variables Values † Male (%) 48.8 Age (years) 77 (16-98) Early-onset NP (%) 66.2 Length of stay (days) 13 (2-100) Risk factor (%) 79.3 H2 blocker, PPIs or antacid therapy 68.1 Nasogastric intubation 19.7 Haemoglobin <10 g/dl 18.8 Mechanical ventilation 18.3 Smoking 10.8 Malnutrition 8.0 Chest surgery 0.9 Comorbidity (%) 94.8 Hypertension 55.4 Lung diseases 29.1 Diabetes mellitus 28.6 Other cardiovascular diseases* 27.7 Chronic kidney disease 18.3 Cerebrovascular disease 16.4 Liver disease 16.4 Peptic ulcer disease 15.5 Malignancy 12.7 Alzheimer 1.9 Number of comorbidities 2.2 ± 1.1 CDS 4.9 ± 3.4 SpO2, % 94 SpO2 < 90%, n (%) 29 (13.6) Haemoglobin, g/dl 11.82 ± 2.148 Haematocrit, % 35.39 ± 6.446 Platelets, /10-9 litter 271.65 ± 122.745 Leucocytes, /10-9 litter 11.69 C-reactive protein, mg/l 335 Glucose, mg/dl 120 Serum creatinine, mg/dl 0.88 Urea, mg/dl 36 Table 1. Baseline characteristics, CDS and laboratory findings of the study population * include ischaemic heart disease, heart failure † Values outside reference range were in bold
- 4. MT. Nguyen et al. 198 ● Bacterial pathogens Of 213 hospital profiles analyzed, antimicrobial testing was indicated in 151 cases (70.9%) and 77 cases were found with positive test results. Specimens tested included sputum (74.0%), bronchoalveolar lavage fluid (13.0%) and blood (13.0%). There were no significant differences in the total numbers of pathogen found in early- onset and late-onset HAPcases but the distribution varied among the two pneumonia categories. Streptococcus spp. (16.2%) was the most common pathogen in early-onset NP while Acinetobacter spp was the most common pathogen (14.0%) in late-onset cases (Table 2). All the patients infected with S. aureus in this study also had comorbid diabetes mellitus. Microorganisms Early-onset NP Late-onset NP Total Gram-positive microorganisms, n (%) Streptococcus spp. 16 (16.2) 9 (9.1) 25 (25.3) Staphylococcus aureus 2 (2.0) 2 (2.0) 4 (4.0) Staphylococcus coagulase (-) - 2 (2.0) 2 (2.0) Gram-negative microorganisms, n (%) Acinetobacter spp. 8 (8.1) 14 (14.0) 22 (22.2) Klebsiella spp. 5 (5.1) 7 (7.1) 12 (12.2) Pseudomonas aeruginosa 6 (6.1) 7 (7.1) 13 (13.1) Escherichia coli 5 (5.1) 5 (5.0) 10 (10.1) Table 2. Distribution of microorganisms isolated from patients with HAP in the study population ● Antibiotic resistance P. aeruginosa showed high resistance rates to quinolones and meropenem (46.2% and 77.0%, respectively).Antibiotics that remained highly effective to P. aeruginosae were colistin (100% sensitive) and piperacillin/tazobactam (92.3% sensitive). Resistance rates of Acineto- bacter spp. to commonly used antibiotic were above 40.0%; colistin, imipenem and cefoperazon/ sulbactam still remained effective to Acinetobacter spp. ESBL-producers exhibited low susceptibility tofirst-lineantibioticssuchasmeropenem(12.5%), piperacillin/tazobactam (22.2%) (Appendix). Antibiotic therapy in treatment of hospital- acquired pneumonia Antibiotics were indicated to all 213 cases in the study population with a total of 642 antibiotics. The average duration of antimicrobial treatment was 11 days. Figure 1 shows the distribution of patients based on the number of antibiotics administered, table 3 enlists the frequency and proportion of each antibiotic group. The most frequently prescribed anti- biotics, which represented 76.7% of all antibiotic prescriptions, were quinolones (37.3%), carbapenems (21.3%) and third-generation cephalosporins (18.2%). Only 9 out of 213 patients received aminoglycosides (1.4%), possibly due to the advanced age and decline in renal function of the study population. Thirdgenerationcephalosporins(11.3%) and quinolones (9.4%) were the most commonly antibiotics empirically used in cases of mono- therapy. The combination of two antibiotics was indicated in 139 cases (65.3%) including quinolone plus cephalosporin (28.2%) and quinolone plus carbapenem (17.8%). Only 15 patients (7.0%) were administered with three antibiotics.
- 5. 199Investigation on hospital-acquired pneumonia and the association between hospital-acquired pneumonia and chronic comorbidity at the Department of General Internal Medicine, University Medical Center Hochiminh City Figure 1. Distribution of the study population based on the number of antibiotics administered Association between chronic comorbidities and other risk factors with treatment outcome There were 148 cases (69.5%) with successful treatment outcome. The association between treatment outcome (success/failure) with chronic comorbidities (type of comorbidity, number of comorbidities, chronic disease score) and other factors including age, sex, previously reported risk factors, onset of HAP, number of antibiotics administered was identi- fied by multivariable logistic regression. Result from the analysis showed that cancer (OR = 4.95; 95% CI 1.46-16.76), CDS score (OR = 0.832; 95% CI 0.71 - 0.97), age from 45 to 64 (OR = 14.09; 95% CI 6.77 - 21.96), age 65 and above (OR = 15.13; 95% CI 7.87-15.92) and mechanical ventilation (OR = 5.05; 95% CI 1.23-20.60) were associated with failure in treatment outcome. 3. DISCUSSION The mean length of stay observed in the study population was 13 days. The mean length of stay of unsuccessful cases tended to be shorter than successful cases due to the fact that patients usually requested to be transferred Table 3. Frequency and proportion of prescribed antibiotics Antibiotic group Frequency Proportion β-lactam Penicillin 15 2.3% Antipseudomonal Penicillin 35 5.4% Cephalosporin 117 18.2% Carbapenem 137 21.3% Aminoglycoside 9 1.4% Quinolone 239 37.3% Glycopeptide 31 4.9% Others 59 9.2% Total 642 100%
- 6. MT. Nguyen et al. 200 to another hospital as soon as progressive deterioration was noted. Treatment outcome of HAP varied considerably in different studies according to the characteristics of the study population. Mortality rate is frequently used to evaluate treatment outcome of severe infectious diseases in many studies7,8 . In this study, since almost patients requested to be discharged or transferred to another hospital when deterioration was noted, the true mortality rate could not be recorded through hospital profiles. Treatment outcome recorded was the conclusion at discharge by physicians. The use of PPIs or drugs that can change gastric pH was found to be the predominant risk factor of HAP in this study (68.1%). In University Medical Center, the majority of postoperative or long-stay inpatients were administered H2 blockers, antacids or PPIs to prevent stress-induced gastrointestinal bleeding. The association between the increase in gastric pH and the incidence of HAP has been reported in several studies. A recent review on HAP and its management by Natalie Schellack also confirms medicines that result in an increase in the gastric pH as a pharmacological risk factor associated with HAP and ventilator-associated pneumonia9 . Findings from this study were similar to those reported in some previous studies worldwide. According to Magret M, bacteremic pneumonia episodes were more frequent in patients with prolonged mechanical ventilation and independent risk factors for mortality7 . A survey by Craven DE also confirmed that mechanically ventilated patients have higher incidence of pneumonia and mortality than non-ventilated patients10 . Data from a study by Tumbarello M showed old age to be independently associated with ICU mortality in patient with Pseudomonas pneumonia8 while a study by Burgos J. found that age above 50 years was a risk factor for respiratory failure in pneumococcal pneumonia11 . Although the impact of cancer on pneumonia has not been adequately studied, some reports noted that nearly 15% of cancer patients experienced acute respiratory failure requiring admission to the intensive care unit, where their mortality rate was about 50%12 . N. Shimazaki and colleagues also reported that underlying malignancy was a factor that affected the efficacy of vancomycin therapy on MRSA pneumonia13 . Although the sample size was not large enough to detect a statistical significance, the data analysis suggested that patients with chronic diseases of kidney, liver, lung, heart, diabetes mellitus or with risk factors such as smoking, using H2 blockers, PPIs or antacids, feeding through nasogastric tube and having haemoglobin <10 g/dl were more likely to get failure in treatment of HAP. However, quite opposite to initial predictions, CDS was inversely related to treatment outcome. Even though the use of Chronic Disease Score has not been reported in pneumonia, the use of Charlson Comorbidity Index (CCI) in previous studies showed a strong and positive relation between the two factors. According to Librero, length of stay significantly rose with each level of the CCI and in-hospital mortality rate in patients with higher scores increased by 4 times compared to patients without comorbidities14 . In a survey by Lensen, comorbidity was found to contribute to death in patients with Staphylococcus aureus bacteremia. The CCI is a good predictor of mortality in this population15 . The calculation of CDS was based on medications used during hospitalization. Since physicians generally focus on antibiotic therapy and discontinue unessential medicines during exacerbations of infection, the CDS score may not accurately reflect the comorbidities of the study population. Results from the study revealed that the majority of the study population was found with chronic comorbid conditions. Cancer, mechanical ventilation, age 45 and above were found to be significantly associated with failure in overall outcome. Isolated pathogens exhibited high resistance against third generation cephalosporins and quinolones. Reduced susceptibility to aminoglycosides, carbapenems and antipseudomonal penicillins were also reported. Colistin still showed efficacy on gram negative bacteria, whereas vancomycin and linezolid were still effective on gram positive
- 7. 201Investigation on hospital-acquired pneumonia and the association between hospital-acquired pneumonia and chronic comorbidity at the Department of General Internal Medicine, University Medical Center Hochiminh City bacteria. Quinolones, carbapenems and third generation cephalosporins were the most frequently prescribed antibiotics (accounted for 41.1%, 23.5% and 20.0%, respectively). Combination of two antibiotics was commonly chosen as initial empiric therapy (65.3%). In addition to an adequate and timely antibiotic therapy, controlling for comorbid chronic conditions should be taken into consideration in managing infectious diseases including HAP. Mechanical ventilation should be carefully indicated based on risk/benefit assessment. Noninvasive ventilation should be considered if possible. Since there was no guideline on prevention and management of HAPat University Medical Center when data was collected, findings from the study suggested that in order to improve the outcome of HAP, a standard treatment guideline should be developed based on local microbiological patterns. Further studies should be conducted on larger population to determine the association between comorbidity and treatment outcome as well as the possibility of using CDS as a predictive score in infectious diseases. 4. ACKNOWLEDGEMENT We would like to thank Division of Respiratory Medicine, Department of General Internal Medicine, University Medical Center Hochiminh City for the support in collecting data for the study. REFERENCES 1. American Thoracic Society, Infectious Diseases Society of America. Guidelines for the management of adults with hospital- acquired, ventilator-associated, and health care-associated pneumonia. Am J Respir Crit Care Med. 2003; 171(4): 388-416. 2. Nguyen TB, Nga CM, Tran TTN, Vu TKC, Nguyen SMT, Vu BC, Huynh MT. First choice of antibiotics in the treating of nosocomial infection in some hospitals in Ho Chi Minh city. Y Hoc TP Ho Chi Minh. 2012; 16(1): 206-214. 3. Nguyen TTH, Cam NP, Le HD, Le Thi Hong Lan, Tran Tuyet Hanh. Epidermiological characteristics of nosocomical infection in newborn intensive care unit – Children’s Hospital 1. Y Hoc TP Ho Chi Minh. 2011; 15(3): 122- 128. 4. Nguyen TP, Ngo TB.Analysis of bacteriology of nosocomial pneumonia after abdominal operation at intensive care unit of Binh Dan hospital.YHoc TPHo Chi Minh. 2013; 17(1): 88-96. 5. Von Korff M, Wagner EH, Saunders K. A chronic disease score from automated pharmacy data. J Clin Epidemiol. 1992; 45(2): 197-203. 6. Yurkovich M, Avina-Zubieta JA, Thomas J, Gorenchtein M, Lacaille D. A systematic review identifies valid comorbidity indices derived from administrative health data. J Clin Epidemiol. 2015; 68(1): 3-14. 7. Magret M, Lisboa T, et al. Bacteremia is an independent risk factor for mortality in nosocomial pneumonia: a prospective and observational multicenter study. Crit Care. 2011; 15(1): R62. 8. Tumbarello M, De Pascale G, et al. Clinical outcomes of Pseudomonas aeruginosa pneumonia in intensive care unit patients. Intensive Care Med. 2013; 39(4): 682-692. 9. Schellac N, Schellac G, Omoding R. Chronic obstructive pulmonary disease: an update. S Afr Pharm J. 2015; 82(6):24-2 10. Craven DE, Steger KA. Nosocomial pneumonia in mechanically ventilated adult patients: epidemiology and prevention in 1996. Semin Respir Infect. 1996; 11(1): 32-53. 11. Burgos J, Lujan M, et al. Risk factors for respiratory failure in pneumococcal pneumonia: the importance of pneumococcal serotypes. Eur Respir J. 2014; 43(2):, 545- 553. 12. Azoulay E, Schlemmer B. Diagnostic strategy in cancer patients with acute respiratory failure. Intensive Care Med. 2006; 32(6): 808-822. 13. Shimazaki N, Hayashi H, Umeda K, Aoyama T, Iida H, Matsumoto Y. Clinical factors affecting the efficacy of vancomycin in methicillin-resistant Staphylococcus aureus pneumonia. Int J Clin Pharmacol Ther. 2010; 48(8): 534-541.
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