Literature DB >> 27493799

Determinants of Deescalation Failure in Critically Ill Patients with Sepsis: A Prospective Cohort Study.

Nawal Salahuddin1, Lama Amer2, Mini Joseph3, Alya El Hazmi4, Hassan Hawa4, Khalid Maghrabi1.   

Abstract

Introduction. Deescalation refers to either discontinuation or a step-down of antimicrobials. Despite strong recommendations in the Surviving Sepsis Guidelines (2012) to deescalate, actual practices can vary. Our objective was to identify variables that are associated with deescalation failure. Methods. In this prospective study of patients with sepsis/septic shock, patients were categorized into 4 groups based on antibiotic administration: no change in antibiotics, deescalation, escalation (where antibiotics were changed to those with a broader spectrum of antimicrobial coverage), or mixed changes (where both escalation to a broader spectrum of coverage and discontinuation of antibiotics were carried out). Results. 395 patients were studied; mean APACHE II score was 24 ± 7.8. Antimicrobial deescalation occurred in 189 (48%) patients; no changes were made in 156 (39%) patients. On multivariate regression analysis, failure to deescalate was significantly predicted by hematologic malignancy OR 3.3 (95% CI 1.4-7.4) p < 0.004, fungal sepsis OR 2.7 (95% CI 1.2-5.8) p = 0.011, multidrug resistance OR 2.9 (95% CI 1.4-6.0) p = 0.003, baseline serum procalcitonin OR 1.01 (95% CI 1.003-1.016) p = 0.002, and SAPS II scores OR 1.01 (95% CI 1.004-1.02) p = 0.006. Conclusions. Current deescalation practices reflect physician reluctance when dealing with complicated, sicker patients or with drug-resistance or fungal sepsis. Integrating an antibiotic stewardship program may increase physician confidence and provide support towards increasing deescalation rates.

Entities:  

Year:  2016        PMID: 27493799      PMCID: PMC4963586          DOI: 10.1155/2016/6794861

Source DB:  PubMed          Journal:  Crit Care Res Pract        ISSN: 2090-1305


1. Introduction

Early administration of broad-spectrum, empiric antimicrobial therapy reduces mortality and improves outcomes in patients with severe sepsis and septic shock. However, broad-spectrum therapy favors the emergence of drug-resistance and adds excessively to the costs of care. Deescalation refers to a strategy whereby clinicians either discontinue or change to a narrower spectrum antimicrobial drug and is usually carried out after culture results become available. The objective of this study was to identify variables associated with deescalation failure.

2. Methods

This study is reported following the STROBE statement checklist for observational studies [1].

2.1. Ethics, Consent, and Permissions

The institutional Office of Research Affairs (ORA) and ORA Research Ethics Committee approved the study methods (RAC number 2131108). The Research Ethics Committee waived patient consent based on the study design. The study was performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. No individual patient data is presented.

2.2. Study Design and Setting

In this prospective, cohort study we reviewed consecutive adult (>14 years) patients admitted to the intensive care unit (ICU) with a diagnosis of sepsis or septic shock. The period of study was from 1st January 2013 to 1st January 2014. Patients who were not for resuscitation (DNR) or were expected to die within 48 hours were excluded.

2.3. Operational Definitions

Antibiotic therapy was considered appropriate based on in vitro sensitivity on culture. On day 7 after ICU admission, we categorized patients into four groups based on antibiotic administration: no change in antibiotics, deescalation (defined as stopping or changing to a narrower spectrum antibiotic), escalation (where antibiotics were changed to those with a broader spectrum of antimicrobial coverage), or mixed changes (where both escalation to a broader spectrum of coverage and discontinuation of antibiotics were carried out).

2.4. Statistical Analysis

Continuous data was tested for normality; measures of central tendency were reported as means ± standard deviations (SD) and compared using Student's t-test for normally distributed variables and reported as medians (interquartile range, IQR) and compared using the Mann-Whitney U test for skewed data. Categorical variables were compared using the χ 2 test or the Fisher Exact test for n < 5. Logistic regression analysis was performed to determine the predictive ability of variables for antibiotic deescalation. Univariate and multivariate techniques were used, and, for multivariate regression, a backward mode with a threshold 0.10 was used for elimination. Multivariate associations were reported as odds ratios, Exp(B) with 95% confidence intervals. A two-sided p value of < 0.05 was considered as statistically significant. All analyses were carried out using IBM SPSS version 22.0.

3. Results

Three hundred and ninety-five patients were included in the study; 194 (49%) were female, mean age of 52.4 ± 12 years; mean APACHE II and SAPS II scores were 24 ± 7.8 and 45 ± 19.7. Three hundred and thirty-three (84.3%) patients were admitted from within the hospital, 58 (14.7%) were admitted from the emergency department, and 4 (1%) came as interhospital transfers via MEDEVAC. Two hundred and forty-eight patients (62.8%) were admitted after regular working hours (4:30 pm to 7:30 am); of these, 214 (86%) came from in-hospital wards, 30 (12%) from the emergency department, and 4 (2%) as transfers. Only 195 (49.3%) of the total 395 patients had positive cultures. Nosocomial acquisition of sepsis was confirmed in 105 [75%] of 139 culture-positive patients admitted “after-hours” and in 50 [89%] inpatients of 56 culture-positive patients admitted during “regular” hours. Patients with hematologic malignancy comprised 106 (26.8%) of the admissions; detailed patient characteristics are shown in Table 1.
Table 1

Characteristics of patients.

Patient characteristics n = 395
APACHE II score24 ± 7.8

Serum procalcitonin3.9 (IQR 25% 1.1, 75% 18.4)

Admission during working hours147 (37%)
Admission after working hours248 (63%)

Vasopressors at 72 hours236 (60%)

Comorbid illnesses
 Malignancy86 (22%)
  Metastatic cancer26 (7%)
  Hematologic malignancy35 (9%)
 Acute respiratory failure67 (17%)
 Chronic renal failure64 (16%)
 Dialysis dependent42 (11%)
 Cirrhosis62 (16%)
 Chronic diseases 235 (59%)

No microbial growth on admission cultures200 (51%)

Source of sepsis
 BSI83 (42%)
 Respiratory72 (37%)
 Urinary tract27 (14%)
 Peritonitis 11 (5%)
 Surgical site10 (5%)

Multidrug resistant organisms41 (21%)

Fungal organisms36 (18%)

Initial antimicrobial therapy appropriate112 (57%)

ICU length of stay (days)6 (IQR 39)

ICU mortality74 (18.7%)

28-day mortality114 (28.9%)

∗ refers to chronic medical illnesses, that is, type 2 diabetes mellitus, coronary artery disease, and hypertension.

Empiric antibiotics were a combination of vancomycin, 292 patients (74%), and carbapenem, 277 patients (70%), with colistin, 70 patients (18%), aminoglycosides, 37 (9%), and quinolones, 64 (16%), used in addition. Empiric caspofungin was added in 47 (12%) patients. Most frequent empiric antibiotic regimen used was vancomycin + carbapenem, 193 (49%), followed by vancomycin + extended-spectrum penicillin/β-lactamase inhibitor, 131 (33%), and vancomycin and aminoglycosides or quinolones, 71 (18%). Cultures were positive in 195 (49.4%) patients and 200 (50.6%) remained culture negative. Please refer to Table 2 for frequencies of all isolates.
Table 2

Frequencies of all microbial isolates.

Organisms isolatedNumber
Enterobacteriaceae 57 (29.2%)

Pseudomonas aeruginosa 53 (27.1%)

GPC 21 (10.7%)

Fungal 25 (12.8%)
Candida albicans 11 (5.6%)
Candida non-albicans 13 (6.6%)
Aspergillus 1

Stenotrophomonas maltophilia 8 (4%)

MRSA 7 (3.5%)

Acinetobacter baumannii 7 (3.5%)

VRE 5 (2.5%)

Viruses # 3 (1.5%)

Miscellaneous ∧∧ 9 (16%)

⋆ Out of 195 positive cultures;  ∗ includes Escherichia coli, Klebsiella, Enterobacter, Citrobacter koseri, and Proteus mirabilis; ∧ includes Streptococcus sp. and methicillin-sensitive Staphylococcus aureus; # includes MERS-corona, parainfluenza, and influenza; ∧∧ includes Alcaligenes xylosoxidans, Vibrio cholerae, Mycobacterium tuberculosis, and Nocardia.

Empiric therapy was appropriate in 57% cases. The median ICU length of stay was 6 days (IQR 4–43) with a 28-day survival rate of 71% (281 patients). Antimicrobial deescalation was carried out in 189 (48%) patients; in 156 (39%) patients no changes in the antimicrobial regimen were made; 42 (11%) patients had their antimicrobial coverage escalated and in 8 (2%) patients mixed changes were made. Please refer to Table 3 for differences in patient characteristics by final antibiotic grouping.
Table 3

Differences in patient characteristics by final antibiotic grouping.

Deescalation (n = 189)No change (n = 156)Escalation (n = 42)Mixed changes (n = 8) p value
SAPS II48 ± 19.541 ± 1947 ± 18.544 ± 23.70.007
Admission procalcitonin2.3(IQR 0.7–7.4)7.9(IQR 2–33.6)4.6(IQR 1.1–11.1)11.1(IQR 7–15.3)0.007
No growth86 (45.5%)102 (65.3%)12 (28.5%)0<0.001
Single site of sepsis60 (31.7%)35 (22.4%)22 (52.3%)3 (37.5%)0.002
MDR organism12 (6.3%)22 (14.1%)5 (11.9%)2 (25%)0.05
Fungal sepsis11 (5.8%)15 (9.6%)8 (19%)2 (25%)0.019
ICU length of stay6.5(IQR 4.2–44)5.5(IQR 4–17)5(IQR 4–36.5)7.5(IQR 5–33.2)0.003
ICU mortality28 (14.8%)38 (24.4%)6 (14.3%)2 (25%)0.11
In a comparison of patients that were deescalated compared to patients “not deescalated” (combination of groups with escalation, no changes, or both escalation and deescalation, i.e., mixed changes), rates of malignancy, multidrug resistant (MDR) organisms, fungal sepsis, chronic organ failure (renal, liver), baseline APACHE II, SAPS II, and serum procalcitonin were significantly different. Deescalation rates were not significantly different between patients with positive cultures and those with negative cultures or single versus multiple positive culture sites or when the patient continued to be vasopressor-dependent. Deescalation was associated with a significantly lower ICU mortality compared to patients not deescalated, 27 out of 188 patients (14.3%) versus 47 out of 207 patients (22.7%).

3.1. Univariate Outcome Data

On univariate regression analysis failure to deescalate was significantly predicted by APACHE II and SAPS II scores, OR 1.02 (95% CI 1.002–1.05, p = 0.037) and OR 1.01 (95% CI 1.005–1.02, p = 0.004), baseline serum procalcitonin OR 1.01 (95% CI 1.003–1.016, p = 0.003), hematologic malignancy OR 2.85 (95% CI 1.3–6.2, p = 0.009), isolation of MDR organisms OR 2.39 (95% CI 1.18–4.8, p = 0.015), and fungal sepsis OR 2.21 (95% CI 1.05–4.62, p = 0.035).

3.2. Multivariate Analysis

After adjusting for covariates, serum procalcitonin, OR 1.01 (95% CI 1.004–1.016) p = 0.002, SAPS II scores OR 1.01 (95% CI 1.004–1.02), p = 0.006, hematologic malignancy OR 3.3 (95% CI 1.4–7.4) p < 0.004, fungal sepsis OR 2.7 (95% CI 1.2–5.8) p = 0.011, and MDR isolates OR 2.9 (95% CI 1.4–6.0) p = 0.003 remained significant predictors for no deescalation. Please refer to Table 4 showing multivariate regression analysis to indicate variables associated with no deescalation of antimicrobials.
Table 4

Multivariate regression analysis to indicate variables associated with no deescalation of antimicrobials.

Wald statisticExp(B)95% CI for Exp(B) p value
LowerUpper
Hematologic malignancy8.313.301.467.440.004
Admission procalcitonin 9.731.011.0041.0160.002
Fungal sepsis6.502.701.255.800.011
MDR organisms isolated8.582.941.436.070.003
SAPS II score7.591.011.0041.0260.006

4. Discussion

In this prospective study of critically ill, septic patients antimicrobial deescalation was carried out in less than half of all patients, with higher baseline procalcitonin levels, greater organ dysfunction scores, comorbid hematologic malignancy, isolation of drug-resistant bacteria, and fungal organisms identified as independent predictors of failure to deescalate. The morbidity and costs of continued broad-spectrum antimicrobials and the safety of deescalation are now well established in the medical literature. A deescalation strategy has not been shown to be harmful in patients with varied immune statuses or systemic or limited infections or in fungal septicemia [7, 11, 12, 16–25] and in fact may even exert a protective effect as reported by Lee et al. [11] and Garnacho-Montero et al. [9]. Please see Table 5 for a summary of recent studies on antibiotic deescalation.
Table 5

Summary of studies on antibiotic deescalation.

Study typeSettingPatientsDeescalation rateAssociation with outcomesFactors associated with no deescalation
Rello et al., 2004 [2]Prospective, observationalMedical-surgical ICU with VAP11531.4%Not reportedNonfermenting Gram-negative bacillus (2.7% versus 49.3%), late-onset pneumonia (12.5% versus 40.7%), p < 0.05

Eachempati  et al., 2009 [3]ObservationalSurgical ICU with VAP13855%No difference in recurrent pneumonia rate or mortality, 34% versus 42%Not reported

De Waele et al., 2010 [4]RetrospectiveSurgical ICU11342%No difference in mortality rate (7% versus 21%, p 0.12)Negative cultures, colonization with multiresistant Gram-negative organisms

Hibbard et al., 2010 [5]RetrospectiveSurgical ICU, VAP811 antibiotic days78%–59%No change in resistance ratesNot reported

Morel et al., 2010 [6]RetrospectiveMixed ICU11645%Recurrent infection (19% versus 5%, p  0.01)Inadequate empiric antibiotic and initial therapy not containing aminoglycoside

Gonzalez et al., 2013 [7]RetrospectiveMedical ICU22951%No differences in mortality, length of stay, antibiotic duration, mechanical ventilation, ICU-acquired infection, or drug-resistant bacteria Inadequacy of initial antibiotic therapy (OR = 0.1, 0.0 to 0.1, p < 0.001), multidrug resistant bacteria (OR = 0.2, 0.1 to 0.7, p = 0.006)

Duchêne et al., 2013 [8]RetrospectiveUrosepsis8046%Not reportedShock, renal abscess, obstructive uropathy, bacterial resistance

Garnacho-Montero et al., 2014 [9]Prospective, observationalMedical 71234.9%Deescalation protective for mortality (OR 0.54; 95% CI 0.33-0.89)Not reported

Carugati et al., 2015 [10]Secondary analysis of CAP databaseMedical with CAP26163.2%No association with mortalityMore severe presentation

Lee et al., 2015 [11]RetrospectiveCommunity-onset monomicrobial Enterobacteriaceae (CoME) bacteremia18945.5%Deescalation strategy was protective for mortality (OR 0.37, p 0.04)Not reported

Madaras-Kelly et al., 2016 [12]RetrospectiveHCAP in VA system931928.3%Not reportedDeescalation associated with initial broad-spectrum therapy (OR 1.5, 95% CI 1.4–1.5), collection of respiratory tract cultures (OR 1.1, 95% CI 1.0–1.2), care in higher complexity facilities (OR 1.3, 95% CI 1.1–1.6)

Falguera et al., 2010 [13]RCTCommunity-acquired pneumonia177, deescalation by urinary antigen resultsHigher cost (p 0.28), reduced adverse events (9% versus 18%, p 0.12), lower exposure to broad-spectrum antimicrobials (154.4 versus 183.3 daily doses per 100 patient days)

Kim et al.,  2012 [14]RCTMedical ICU, hospital-acquired pneumonia109No differences in ICU stay or mortality rates, higher risk of MRSA with deescalation; HR 3.84; 95% CI 1.06–13.91

Leone et al., 2014 [15]Multicenter, RCTSevere sepsis60Deescalation resulted in prolonged duration of ICU stay; mean difference 3.4 (95% CI −1.7–8.5); no effect on mortality Not reported

ICU: intensive care unit; VAP: ventilator-associated pneumonia; CAP: community-acquired pneumonia; HCAP: healthcare associated pneumonia; HR: hazard ratio; OR: odds ratio.

Despite reports of benefit, deescalation remains variably practiced with rates from 10 to 60% [26]. Please refer to Table 5. In our cohort of multidisciplinary critically ill patients with sepsis and shock, antimicrobial deescalation was carried out in 48% patients, which is comparable to that reported by other investigators. The real question then is when are physicians less likely to deescalate? Recent studies have shown that antibiotic deescalation becomes less likely with severe, complicated infections and drug-resistance and when initial antibiotic therapy is inadequate. Please refer to Table 5. In our study, deescalation failure was predicted by the isolation of drug-resistant bacteria and fungal organisms, greater severity of illness as demonstrated by higher initial organ dysfunction scores, underlying hematologic malignancy, and a procalcitonin level that may suggest a greater bacterial load. What then appears to be a common theme here is that physicians are uncomfortable deescalating antimicrobials when faced with sicker patients with a higher possibility of complications. Antimicrobial stewardship is a strategy that employs availability of either an infectious disease specialist and/or a clinical pharmacist to assist in decision-making at the bedside. Stewardship programs have been shown to successfully reduce resistance patterns, reduce antibiotic usage, and reduce costs without increasing adverse outcomes [27-34]. Our study confirms the results of others that there is a real need for and potential benefits of implementing antimicrobial stewardship programs across all areas where broad-spectrum antimicrobials are utilized. Whether they are specialty driven or pharmacy-led should be tailored to the resources available to individual centers. This study's strengths are its large numbers of patients and the generalizability of our results to other ICUs. We have a varied case-mix from our surgical and medical ICUs with causative organisms that are similar to those isolated from most ICUs. The limitation of our results is that this is a single-center study. Assisting the stewardship model is a recent publication from de Jong and colleagues [35] where, in a controlled trial in 15 Netherland hospitals, ICU admissions were randomized to usual care versus antibiotic deescalation once procalcitonin levels decreased by 80% or more of its peak value or to 0.5 μg/L or lower. Mortality was significantly lower in the procalcitonin-guided group, between-group absolute difference 5.4% (95% CI 1.2–9.5, p = 0.0122). Therefore, procalcitonin absolute levels and patterns may assist bedside decision-making incorporated into an antibiotic stewardship program.

5. Conclusions

Current deescalation practices reflect physician reluctance when dealing with complicated, sicker patients or with drug-resistance or fungal sepsis. Integrating an antibiotic stewardship program may increase physician confidence and provide support towards increasing deescalation rates.
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Authors:  M Carugati; F Franzetti; T Wiemken; R R Kelley; R Kelly; P Peyrani; F Blasi; J Ramirez; S Aliberti
Journal:  Clin Microbiol Infect       Date:  2015-06-23       Impact factor: 8.067

Review 2.  Antibiotic de-escalation in the ICU: how is it best done?

Authors:  Jose Garnacho-Montero; Ana Escoresca-Ortega; Esperanza Fernández-Delgado
Journal:  Curr Opin Infect Dis       Date:  2015-04       Impact factor: 4.915

3.  De-escalation from micafungin is a cost-effective alternative to traditional escalation from fluconazole in the treatment of patients with systemic Candida infections.

Authors:  Robert G Masterton; Montserrat Casamayor; Primrose Musingarimi; Anke van Engen; Raymund Zinck; Olatunji Odufowora-Sita; Isaac A O Odeyemi
Journal:  J Med Econ       Date:  2013-09-25       Impact factor: 2.448

4.  Antifungal de-escalation was not associated with adverse outcome in critically ill patients treated for invasive candidiasis: post hoc analyses of the AmarCAND2 study data.

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5.  De-escalation of antimicrobial treatment in neutropenic patients with severe sepsis: results from an observational study.

Authors:  Djamel Mokart; Géraldine Slehofer; Jérôme Lambert; Antoine Sannini; Laurent Chow-Chine; Jean-Paul Brun; Pierre Berger; Ségolène Duran; Marion Faucher; Jean-Louis Blache; Colombe Saillard; Norbert Vey; Marc Leone
Journal:  Intensive Care Med       Date:  2014-01       Impact factor: 17.440

6.  Prospective, randomised study to compare empirical treatment versus targeted treatment on the basis of the urine antigen results in hospitalised patients with community-acquired pneumonia.

Authors:  M Falguera; A Ruiz-González; J A Schoenenberger; C Touzón; I Gázquez; C Galindo; J M Porcel
Journal:  Thorax       Date:  2009-08-23       Impact factor: 9.139

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Authors:  Evelien de Jong; Jos A van Oers; Albertus Beishuizen; Piet Vos; Wytze J Vermeijden; Lenneke E Haas; Bert G Loef; Tom Dormans; Gertrude C van Melsen; Yvette C Kluiters; Hans Kemperman; Maarten J van den Elsen; Jeroen A Schouten; Jörn O Streefkerk; Hans G Krabbe; Hans Kieft; Georg H Kluge; Veerle C van Dam; Joost van Pelt; Laura Bormans; Martine Bokelman Otten; Auke C Reidinga; Henrik Endeman; Jos W Twisk; Ewoudt M W van de Garde; Anne Marie G A de Smet; Jozef Kesecioglu; Armand R Girbes; Maarten W Nijsten; Dylan W de Lange
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8.  De-escalation after empirical meropenem treatment in the intensive care unit: fiction or reality?

Authors:  Jan J De Waele; Mariska Ravyts; Pieter Depuydt; Stijn I Blot; Johan Decruyenaere; Dirk Vogelaers
Journal:  J Crit Care       Date:  2010-01-15       Impact factor: 3.425

9.  Impact of a Multimodal Antimicrobial Stewardship Program on Pseudomonas aeruginosa Susceptibility and Antimicrobial Use in the Intensive Care Unit Setting.

Authors:  Douglas Slain; Arif R Sarwari; Karen O Petros; Richard L McKnight; Renee B Sager; Charles J Mullett; Alison Wilson; John G Thomas; Kathryn Moffett; H Carlton Palmer; Harakh V Dedhia
Journal:  Crit Care Res Pract       Date:  2011-05-19

10.  De-escalation as part of a global strategy of empiric antibiotherapy management. A retrospective study in a medico-surgical intensive care unit.

Authors:  Jérôme Morel; Julie Casoetto; Richard Jospé; Gérald Aubert; Raphael Terrana; Alain Dumont; Serge Molliex; Christian Auboyer
Journal:  Crit Care       Date:  2010-12-17       Impact factor: 9.097

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