The Impact of Antibiotics Administration on Mortality for Time in Sepsis and Septic Shock Patients including Possible Reasons for Delayed Administration in Malaysia
Abstract
:1. Introduction
2. Results
2.1. Audit on the Time Interval
2.2. Compliance with the Surviving Sepsis Campaign
2.3. Association between Antibiotic Administration Timings and Mortality Rate
3. Discussion
4. Materials and Methods
4.1. Study Design and Setting
4.2. Data Definitions
4.3. Study Population
4.4. Data Collection
4.5. Statistical Analysis
4.6. Outcome Measurement
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Patterson, B. How Important is the Timing of Antibiotics for Surviving Sepsis? Infectious Disease Advisor. 1 May 2018. Available online: https://www.infectiousdiseaseadvisor.com/home/topics/sepsis/how-important-is-the-timing-of-antibiotics-for-surviving-sepsis/ (accessed on 27 July 2022).
- Rhodes, A.; Evans, L.E.; Alhazzani, W.; Levy, M.M.; Antonelli, M.; Ferrer, R.; Kumar, A.; Sevransky, J.E.; Sprung, C.L.; Nunnally, M.E.; et al. Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock. Crit. Care Med. 2017, 45, 486–552. [Google Scholar] [CrossRef] [PubMed]
- Seymour, C.W.; Rosengart, M.R. Septic shock: Advances in diagnosis and treatment. JAMA 2015, 314, 708–717. [Google Scholar] [CrossRef] [PubMed]
- Angus, D.C.; van der Poll, T. Severe sepsis and septic shock. N. Engl. J. Med. 2013, 369, 2063. [Google Scholar] [CrossRef] [PubMed]
- Sterling, S.A.; Miller, W.R.; Pryor, J.; Puskarich, M.A.; Jones, A.E. The Impact of Timing of Antibiotics on Outcomes in Severe Sepsis and Septic Shock: A Systematic Review and Meta-analysis. Crit. Care Med. 2015, 43, 1907–1915. [Google Scholar] [CrossRef] [PubMed]
- Kumar, A.; Roberts, D.; Wood, K.E.; Light, B.; Parrillo, J.E.; Sharma, S.; Suppes, R.; Feinstein, D.; Zanotti, S.; Taiberg, L.; et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit. Care Med. 2006, 34, 1589–1596. [Google Scholar] [CrossRef] [PubMed]
- Liu, V.X.; Fielding-Singh, V.; Greene, J.D.; Baker, J.M.; Iwashyna, T.J.; Bhattacharya, J.; Escobar, G.J. The Timing of Early Antibiotics and Hospital Mortality in Sepsis. Am. J. Respir. Crit. Care Med. 2017, 96, 856–863. [Google Scholar] [CrossRef] [PubMed]
- Bloos, F.; Rüddel, H.; Thomas-Rüddel, D.; Schwarzkopf, D.; Pausch, C.; Harbarth, S.; Schreiber, T.; Gründling, M.; Marshall, J.; Simon, P.; et al. Effect of a multifaceted educational intervention for anti-infectious measures on sepsis mortality: A cluster randomized trial. Intensiv. Care Med. 2017, 43, 1602–1612. [Google Scholar] [CrossRef] [PubMed]
- Abe, T.; Kushimoto, S.; Tokuda, Y.; Phillips, G.S.; Rhodes, A.; Sugiyama, T.; Komori, A.; Iriyama, H.; Ogura, H. Implementation of earlier antibiotic administration in patients with severe sepsis and septic shock in Japan: A descriptive analysis of a prospective observational study. Crit. Care 2019, 23, 360. [Google Scholar] [CrossRef] [PubMed]
- Singer, M.; Deutschman, C.S.; Seymour, C.W.; Shankar-Hari, M.; Annane, D.; Bauer, M.; Bellomo, R.; Bernard, G.R.; Chiche, J.-D.; Coopersmith, C.M.; et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016, 315, 801–810. [Google Scholar] [CrossRef] [PubMed]
- Bone, R.C.; Balk, R.A.; Cerra, F.B.; Dellinger, R.P.; Fein, A.M.; Knaus, W.A.; Schein, R.M.H.; Sibbald, W.J. Definitions for Sepsis and Organ Failure and Guidelines for the Use of Innovative Therapies in Sepsis. Chest 1992, 101, 1644–1655. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Characteristics | No. (%) of Patients |
---|---|
Age | |
<55 years | 39 (50.0) |
≥55 years | 39 (50.0) |
Gender | |
Male | 46 (59.0) |
Female | 32 (41.0) |
Ethnicity | |
Malay | 48 (61.5) |
Chinese | 18 (23.1) |
Indian | 12 (15.4) |
With underlying Chronic Illness | |
No | 35 (44.9) |
Yes | 43 (55.1) |
Mortality after 48 h | |
No | 47 (60.3) |
Yes | 31 (39.7) |
Medication administered within 1 h from order time | |
No | 40 (51.3) |
Yes | 38 (48.7) |
Potential cause of not delivering drug within 1 h | |
Awaiting culture | 22 (46.8) |
Delay in sending the order | 19 (40.4) |
No stat (immediate) dose is given | 5 (10.6) |
Procedure ongoing | 1 (2.1) |
The potential source of not delivering drug within 1 h | |
Nursing | 22 (47.8) |
Supporting staff | 18 (39.1) |
Physician | 6 (13.0) |
Diagnosis | |
Occult sepsis | 44 (56.4) |
Known sepsis | 34 (43.6) |
Order status | |
Usual order | 31 (39.7) |
Stat and usual order | 47 (60.3) |
After-office-hours order | |
No | 49 (62.8) |
Yes | 29 (37.2) |
Source of drug stock | |
Pharmacy | 58 (74.4) |
ICU | 20 (25.6) |
Administered drug category | |
Piperacillin–Tazobactam | 39 (50.0) |
Meropenem | 26 (33.3) |
Others | 13 (16.7) |
Time taken for mediation delivery, median (IQR) | 1 h 42 min (3 h 17 min) |
Variables | Survived N (%) | Died N (%) | p-Value |
---|---|---|---|
Age category | 0.817 | ||
<55 years | 23 (59.0%) | 16 (41.0%) | |
≥55 years | 24 (61.5%) | 15 (38.5%) | |
Gender | 0.044 * | ||
Male | 32 (69.6) | 14 (30.4) | |
Female | 15 (46.9) | 17 (53.1) | |
Ethnicity | 0.064 | ||
Malay | 24 (50.0) | 24 (50.0) | |
Chinese | 14 (77.8) | 4 (22.2) | |
Indian | 9 (75.0) | 3 (25.0) | |
With underlying Chronic Illness | 0.374 | ||
No | 23 (65.7) | 12 (34.3) | |
Yes | 24 (55.8) | 19 (44.2) | |
Medication administered within 1 h from order time | 0.018 * | ||
No | 19 (47.5) | 21 (52.5) | |
Yes | 28 (73.7) | 10 (26.3) | |
After-office-hours order | 0.480 | ||
No | 31 (63.3) | 18 (36.7) | |
Yes | 16 (55.2) | 13 (44.8) | |
Diagnosis | 0.820 | ||
Occult sepsis | 27 (61.4) | 17 (38.6) | |
Known sepsis | 20 (58.8) | 14 (41.2) | |
Type of infections | 0.542 | ||
CLABSI | 24 (68.6) | 11 (31.4) | |
CAUTI | 3 (100.0) | 0 (0.0) | |
SSI | 4 (66.7) | 2 (33.3) | |
VAP | 16 (47.1) | 18 (52.9) | |
Order status | <0.001 * | ||
Usual order | 27 (87.1) | 4 (12.9) | |
Stat and usual order | 20 (42.6) | 27 (57.4) | |
Source of drug stock | 0.302 | ||
Pharmacy | 33 (56.9) | 25 (43.1) | |
ICU | 14 (70.0) | 6 (30.0) | |
SOFA Score | 0.202 | ||
Score 0 to 6 | 9 (100.0) | 0 (0.0) | |
Score 7 to 9 | 12 (100.0) | 0 (0.0) | |
Score 10 to 12 | 25 (86.2) | 4 (13.8) | |
Score 13 to 14 | 1 (14.3) | 6 (85.7) | |
Score 15 | 0 (0.0) | 17 (100.0) | |
Score 16 to 24 | 0 (0.0) | 4 (100.0) | |
Administered drug category | 0.706 | ||
Tazosin | 25 (64.1) | 39 (50.0) | |
Meropenem | 14 (53.8) | 26 (33.3) | |
Others | 8 (61.5) | 13 (16.7) | |
Inotropic support | 0.031 * | ||
No | 2 (100.0) | 0 (0.0) | |
Yes | 45 (59.2) | 31 (40.8) | |
Artificial ventilation | 0.240 | ||
HFMO2 | 1 (100.0) | 0 (0.0) | |
CPAP | 13 (76.5) | 4 (23.5) | |
SIMV | 28 (77.8) | 8 (22.2) | |
BILEVEL | 5 (20.8) | 19 (79.2) |
Variables | Crude OR | (95% CI) | p-Value a | Adj. OR | (95% CI) | p-Value b | |
---|---|---|---|---|---|---|---|
Age category | <55 years | 1.00 (ref.) | 0.817 | 1.00 (ref.) | 0.525 | ||
≥55 years | 1.13 | (0.45, 2.76) | 1.50 | (0.43, 5.22) | |||
Gender | Male | 1.00 (ref.) | 0.046 | 1.00 (ref.) | 0.187 | ||
Female | 0.39 | (0.15, 0.98) | 0.41 | (0.11, 1.54) | |||
Ethnicity | Malay | 1.00 (ref.) | 0.072 | 1.00 (ref.) | 0.244 | ||
Chinese | 3.00 | (0.72, 12.46) | 3.06 | (0.47, 20.15) | |||
Indian | 0.86 | (0.15, 4.76) | 1.18 | (0.13, 11.08) | |||
With underlying Chronic Illness | No | 1.00 (ref.) | 0.375 | 1.00 (ref.) | 0.711 | ||
Yes | 0.66 | (0.26, 1.66) | 0.79 | (0.17, 4.05) | |||
Medication administered within 1 h from order time | No | 1.00 (ref.) | 0.020 | 1.00 (ref.) | 0.015 | ||
Yes | 3.10 | (1.19, 8.02) | 5.79 | (1.41, 23.78) | |||
After-office-hours order | No | 1.00 (ref.) | 0.481 | 1.00 (ref.) | 0.826 | ||
Yes | 0.72 | (0.28, 1.82) | 0.87 | (0.24, 3.09) | |||
Diagnosis | No | 1.00 (ref.) | 0.820 | 1.00 (ref.) | 0.808 | ||
Yes | 0.90 | (0.36, 2.24) | 1.17 | (0.34, 4.02) | |||
Order status | Usual order | 1.00 (ref.) | <0.001 | 1.00 (ref.) | 0.001 | ||
Stat and usual order | 0.11 | (0.03, 0.36) | 0.08 | (0.02, 0.35) | |||
Source of drug stock | Pharmacy | 1.00 (ref.) | 0.305 | 1.00 (ref.) | 0.817 | ||
ICU | 1.77 | (0.60, 5.25) | 0.83 | (0.17, 4.08) | |||
Administered drug category | Tazosin | 1.00 (ref.) | 0.707 | 1.00 (ref.) | 0.619 | ||
Meropenem | 1.37 | (0.35, 5.33) | 0.62 | (0.10, 4.03) | |||
Others | 0.90 | (0.25, 3.27) | 0.74 | (0.13, 4.16) |
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Arulappen, A.L.; Danial, M.; Ng, L.W.; Teoh, J.C. The Impact of Antibiotics Administration on Mortality for Time in Sepsis and Septic Shock Patients including Possible Reasons for Delayed Administration in Malaysia. Antibiotics 2022, 11, 1202. https://doi.org/10.3390/antibiotics11091202
Arulappen AL, Danial M, Ng LW, Teoh JC. The Impact of Antibiotics Administration on Mortality for Time in Sepsis and Septic Shock Patients including Possible Reasons for Delayed Administration in Malaysia. Antibiotics. 2022; 11(9):1202. https://doi.org/10.3390/antibiotics11091202
Chicago/Turabian StyleArulappen, Ann L., Monica Danial, Ling Wei Ng, and Jui Chang Teoh. 2022. "The Impact of Antibiotics Administration on Mortality for Time in Sepsis and Septic Shock Patients including Possible Reasons for Delayed Administration in Malaysia" Antibiotics 11, no. 9: 1202. https://doi.org/10.3390/antibiotics11091202
APA StyleArulappen, A. L., Danial, M., Ng, L. W., & Teoh, J. C. (2022). The Impact of Antibiotics Administration on Mortality for Time in Sepsis and Septic Shock Patients including Possible Reasons for Delayed Administration in Malaysia. Antibiotics, 11(9), 1202. https://doi.org/10.3390/antibiotics11091202