| Literature DB >> 34223116 |
Nam Nguyen-Hoang1, Quynh Thi Huong Bui1,2.
Abstract
OBJECTIVES: To assess the appropriateness of empirical antimicrobial therapy for sepsis and septic shock and determine factors associated with patient treatment outcomes at a Vietnamese national hospital.Entities:
Year: 2021 PMID: 34223116 PMCID: PMC8210270 DOI: 10.1093/jacamr/dlab048
Source DB: PubMed Journal: JAC Antimicrob Resist ISSN: 2632-1823
Demographic characteristics of the study population
| Characteristics | Frequency | Percentage |
|---|---|---|
| Age, median (IQR) | 70 (58–82) | |
| ≥65 years old | 88 | 65.7 |
| <65 years old | 46 | 34.3 |
| Gender | ||
| male | 66 | 49.3 |
| female | 68 | 50.7 |
| Initial eGFR | ||
| ≥60 mL/min/1.73 m2 | 41 | 31.3 |
| <60 mL/min/1.73 m2 | 90 | 68.7 |
| Department of treatment | ||
| ICU | 18 | 13.4 |
| infectious diseases department | 70 | 52.2 |
| others | 46 | 34.4 |
| Presence of septic shock | ||
| no | 114 | 85.1 |
| yes | 20 | 14.9 |
| Site of infection | ||
| unknown | 30 | 22.4 |
| urinary | 38 | 28.4 |
| intra-abdominal | 26 | 19.4 |
| respiratory | 22 | 16.4 |
| skin and soft tissue | 16 | 11.9 |
| others | 2 | 1.5 |
| Positive culture | ||
| yes | 73 | 57.0 |
| no | 55 | 43.0 |
| Blood culture | ||
| positive | 53 | 44.5 |
| negative | 66 | 5.5 |
| Number of organisms isolated from blood | ||
| 0 | 66 | 55.5 |
| 1 | 49 | 41.2 |
| ≥2 | 4 | 3.7 |
Three patients did not have laboratory tests related to serum creatinine, thus we could calculate eGFR values of only the 131 remaining patients.
The cultures (blood and other cultures) were only collected from 128 patients.
The blood cultures were only collected from 119 patients.
Figure 1.Suspected microbiological pathogens in 134 patients with sepsis and/or septic shock.
Patterns of antimicrobial use in treatment of sepsis and/or septic shock
| Antibiotics | Frequency | Percentage cases prescribed |
|---|---|---|
| β-lactam | ||
| ceftriaxone | 58 | 43.3 |
| imipenem/cilastatin | 43 | 32.1 |
| meropenem | 25 | 18.7 |
| cefoperazone/sulbactam | 18 | 13.4 |
| piperacillin/tazobactam | 6 | 4.5 |
| others | 18 | 13.4 |
| Fluoroquinolone | ||
| levofloxacin | 51 | 38.1 |
| ciprofloxacin | 33 | 24.6 |
| others | 5 | 3.7 |
| Glycopeptide | ||
| teicoplanin | 21 | 15.7 |
| vancomycin | 12 | 9.0 |
| Aminoglycoside | ||
| netilmicin | 12 | 9.0 |
| amikacin | 5 | 3.7 |
| Polymyxin | ||
| colistin | 15 | 11.2 |
| Antifungal | ||
| fluconazole | 10 | 7.5 |
| 5-nitroimidazole | ||
| metronidazole | 9 | 6.7 |
| Others | 14 | 10.4 |
Other β-lactam: ampicillin/sulbactam, amoxicillin/clavulanic acid, cefaclor, cefuroxime, cefixime, ceftazidime, ertapenem and doripenem.
Other fluoroquinolone: moxifloxacin and norfloxacin.
Other classes: fosfomycin, linezolid, clindamycin, azithromycin and tigecycline.
Appropriateness of empirical antimicrobial therapy
| Level of appropriateness | Frequency | Percentage |
|---|---|---|
| Antimicrobial agent | 73 | 56.6 |
| Dosage | 31 | 42.5 |
| Route of administration | 61 | 83.6 |
| Overall appropriateness | 30 | 23.3 |
Factors related to treatment outcomes
| Factors | Treatment success, | Treatment failure, |
|
|---|---|---|---|
| Age | |||
| ≥65 years old | 66 (75.0) | 22 (25.0) | 0.042 |
| <65 years old | 42 (91.3) | 4 (8.7) | |
| Gender | |||
| male | 49 (74.2) | 17 (25.8) | 0.107 |
| female | 59 (86.8) | 9 (13.2) | |
| Initial eGFR | |||
| ≥60 mL/min/1.73 m2 | 36 (87.8) | 5 (12.2) | 0.213 |
| <60 mL/min/1.73 m2 | 69 (76.7) | 21 (23.3) | |
| Department of treatment | |||
| ICU | 2 (11.1) | 16 (88.9) | <0.001 |
| infectious diseases department | 69 (98.6) | 1 (1.4) | |
| others | 37 (80.4) | 9 (19.6) | |
| Presence of septic shock | |||
| no | 103 (90.4) | 11 (9.6) | <0.001 |
| yes | 5 (25.0) | 15 (75.0) | |
| Site of infection | |||
| unknown | 27 (90.0) | 3 (10.0) | <0.001 |
| urinary | 35 (92.1) | 3 (7.9) | |
| intra-abdominal | 21 (80.8) | 5 (19.2) | |
| respiratory | 9 (40.9) | 13 (59.1) | |
| skin and soft tissue | 14 (87.5) | 2 (12.5) | |
| Blood culturee | |||
| positive | 42 (79.2) | 11 (20.8) | 0.739 |
| negative | 55 (83.3) | 11 (16.7) | |
| Appropriate empirical antimicrobial agents | |||
| yes | 58 (79.5) | 15 (20.5) | 0.874 |
| no | 46 (82.1) | 10 (17.9) | |
| Appropriate dosage (in 73 patients who received appropriate antibiotic agents) | |||
| yes | 30 (96.8) | 1 (3.2) | 0.004 |
| no | 28 (66.7) | 14 (33.3) | |
| Overall | |||
| appropriate | 29 (96.7) | 1 (3.3) | 0.023 |
| inappropriate | 75 (75.8) | 24 (24.2) | |
Based on χ2 test and/or Fisher’s exact test.
Statistically significant at 95% CI.
Three patients did not have laboratory tests related to serum creatinine, thus we could calculate eGFR values of only the 131 remaining patients.
Two patients with sepsis that originated from other sites of infection were excluded from the analysis.
The blood cultures were only collected from 119 patients.
Empirical antimicrobial therapy were assessed in 129 patients whose microbiological tests were not available at the time of administering antibiotics; 5 other patients were prescribed targeted antimicrobial therapy.
The five best predictive models for sepsis/septic shock treatment outcome selected by the BMA technique
| Predictors | Probability (%) | Regression coefficient | ||||
|---|---|---|---|---|---|---|
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | ||
| Intercept | −18.6 | −1.3 | 19.2 | −18.6 | −2.5 | |
| Age | 0.0 | — | — | — | — | — |
| Gender | 3.6 | |||||
| male | — | — | — | −1.2 | — | |
| eGFR | 0.0 | |||||
| <60 mL/min/1.73 m2 | — | — | — | — | — | |
| Department of treatment | 100.0 | |||||
| infectious diseases department | 22.4 | 5.6 | 22.8 | 23.0 | 6.5 | |
| others | 20.3 | 3.3 | 20.4 | 20.4 | 3.8 | |
| Site of infection | 0.0 | |||||
| urinary tract | — | — | — | — | — | |
| intra-abdominal | — | — | — | — | — | |
| respiratory tract | — | — | — | — | — | |
| skin and soft tissue | — | — | — | — | — | |
| Presence of septic shock | 83.1 | |||||
| yes | −2.8 | −2.6 | — | — | — | |
| Blood culture | 0.0 | |||||
| positive | — | — | — | — | — | |
| Overall appropriate empirical antibiotic | 66.9 | |||||
| yes | 18.6 | — | 19.2 | 19.2 | — | |
| Number of variables | 3 | 2 | 2 | 3 | 1 | |
| BIC | −446.9 | −445.7 | −443.5 | −441.5 | −441.5 | |
| Posterior probability (%) | 53.6 | 29.6 | 9.8 | 3.6 | 3.5 | |
Reference group: ICU.
Reference group: unknown source.
Bayesian information criterion (BIC) or Schwarz information criterion is a criterion for model selection among a finite set of models; the model with the lowest BIC is preferred.