Optimizing polymyxin B exposure in carbapenem-resistant organism Hospital-Acquired Pneumonia: a retrospective observational study

Optimizing polymyxin B exposure in carbapenem-resistant organism Hospital-Acquired Pneumonia: a retrospective observational study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimizing polymyxin B exposure in carbapenem-resistant organism Hospital-Acquired Pneumonia: a retrospective observational study Mengru Xiong, Xiaoting Xu, Linlin Hu, Jie He, Hui Chen, Wenhan Hu, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7249423/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background The area under the concentration-time curve over 24 hours (AUC 0-24h ) is a critical pharmacokinetic parameter influencing the clinical efficacy of polymyxin B (PMB). However, due to substantial population heterogeneity among critically ill patients, the correlation between the AUC 0-24h of PMB and clinical treatment success, as well as the optimal therapeutic threshold remains inadequately elucidated. Objectives This study aimed to investigate the relationship between PMB AUC 0-24h and clinical efficacy in patients with carbapenem-resistant hospital-acquired pneumonia (HAP), and to identify the optimal therapeutic AUC 0-24h range for PMB. Methods We conducted a retrospective observational study of carbapenem-resistant HAP patients receiving intravenous PMB with therapeutic drug monitoring (TDM). The plasma concentrations of PMB were determined using validated ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC–MS/MS). The primary outcome was 14-day clinical treatment success rates, the secondary outcomes included the incidence of AKI. Logistic regression analyses and restricted cubic spline analyses were employed to investigate the optimal therapeutic threshold of PMB in carbapenem-resistant HAP patients. Result A total of 138 patients were ultimately included in the final analysis, with the median age of 68 years, and 110(79.7%) patients were male. Clinical success was achieved in 63(45.7%) patients. The pathogen of infection in 77% of patients was Carbapenem-Resistant Acinetobacter baumannii (CRAB), and all pathogens isolated from the included patients were sensitive to PMB, with a minimum inhibitory concentration (MIC) ≤ 2mg/L. The median AUC 0 − 24h of PMB was 77.5 (55.6, 105.6) mg·h/L. In enrolled patients, an AUC 0 − 24h >77 mg·h/L enabled to predict the clinical treatment success, while AUC 0 − 24h >110 mg·h/L enabled to predict the AKI incidence. In the multivariate logistic regression model, AUC 0 − 24h 110 mg·h/L significantly increased AKI risk (OR: 0.33, 95% CI: 1.06–10.47; p = 0.043). Conclusion This study confirms that the AUC 0 − 24h of PMB is closely associated with both 14-day clinical treatment success rates and the incidence of AKI in patients with carbapenem-resistant HAP, with an optimal range from 77 to 110 mg·h/L. Therapeutic drug monitoring Carbapenem-resistant organisms Hospital acquired pneumonia Pharmacokinetics/pharmacodynamics Nephrotoxicity Intensive care Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Hospital-acquired pneumonia (HAP) represents a significant global public health challenge. In particular, HAP caused by carbapenem-resistant bacteria has exacerbated the complexity of treatment, intensified the burden on healthcare systems(1), and further increased in-hospital mortality rates among affected patients(2, 3). Antibiotic treatment strategies for carbapenem-resistant HAP are extremely limited(4, 5). Polymyxins B is a concentration-dependent antibiotic(6), demonstrates significant antimicrobial efficacy against carbapenem-resistant Gram-negative bacterial strains(7, 8). However, it exhibits significant nephrotoxicity at high concentrations(9, 10). Therefore, clinical use typically relies on TDM to guide dosage adjustments(11). Pharmacokinetic and pharmacodynamic (PK/PD) studies are crucial for optimizing antibiotic administration. International consensus guidelines on the optimal use of polymyxins(12) recommend the ideal AUC 0 − 24h target range is suggested to be between 50 mg·h/L and 100 mg·h/L based on previous studies(13) (14).The retrospective study revealed that the range of 50–100 mg·h/kg is not always effective in critically ill patients and their complex clinical settings(15). Therefore, this study primarily investigates the best AUC 0 − 24h target range of PMB associated with favorable clinical outcomes in patients with carbapenem-resistant HAP. Methods Study protocol and population This study was designed as a retrospective, single-center observational analysis performed within the Intensive Care Unit of Zhongda Hospital, affiliated with Southeast University. The study included patients with carbapenem-resistant HAP who received intravenous PMB treatment and underwent TDM between January 2020 and June 2024 and was approved by the Ethics Committee of Zhongda Hospital, Southeast University (approval number: 2023ZDSYLL296-P01) and waived informed consent due to its retrospective nature. Inclusion criteria for patients were as follows: (a) over 18 years old; (b) diagnosed with HAP during ICU admission; (c) microbiological evidence indicating carbapenem-resistant pathogenic bacteria; (d) receiving intravenous polymyxin B therapy for more than 3 days. Exclusion criteria included: (a) lack of TDM for PMB or incomplete steady-state blood concentration data; (b) Intravenous polymyxin B therapy is primarily indicated for infections in other body sites, such as the abdominal cavity, intracranial region, and skin and soft tissues and so on; (c) pathogenic bacteria are resistant to polymyxin B; (d) pregnant or lactating patients. According to European guidelines(7), HAP was clinically defined as pneumonia developing ≥ 48 hours after hospital admission, requiring fulfillment of all following criteria: (1) presence of at least two clinical manifestations: including body temperature > 38°C, leukocytosis > 12,000 cells/mL/leukopenia < 4,000 cells/mL, or purulent respiratory secretions; (2) radiographic evidence of new pulmonary infiltrates or progression of existing infiltrates; and (3) semi-quantitative or quantitative positivity in respiratory culture. Patient demographic and clinical data were extracted from the electronic medical records, encompassing age, sex, height, weight, date of admission, and preexisting comorbidities. The severity of disease at the time of patient enrollment was assessed using the Acute Physiology and Chronic Health Evaluation II (APACHE II) score and SOFA score. Clinical data collection included laboratory parameters, infection-related variables, and organ support modalities administered during polymyxin B therapy, such as mechanical ventilation, continuous renal replacement therapy, and extracorporeal membrane oxygenation. PMB administration and concentration Clinically, PMB is typically administered at a dosage of 50–100 mg every 12 hours, with each infusion lasting 1 hour. Some patients receive combined intravenous and nebulized polymyxin B therapy. For nebulization, 25–50 mg of PMB is diluted in 5 mL of sterile water for injection, and the solution is administered via a vibrating mesh nebulizer connected to the patient's ventilator inspiratory circuit. After achieving steady-state PMB blood concentrations (which is typically reached after 5 intravenous doses of PMB), blood samples were obtained at three predetermined intervals: immediately before dosing (trough concentration/C min ), 1-hour post-infusion (peak concentration/C max ), and 6-hours following administration (C 6h ). If there is a change in the dosage during treatment, the steady-state concentration timeline and relevant steady-state blood concentration data are recalculated starting from the time the dosage is adjusted. Blood samples for drug concentration analysis were collected at the specified time points, immediately centrifuged at 1500g for 10 minutes after collection. The supernatant was then stored at -80°C. Plasma concentrations of PMB were measured using validated UPLC–MS/MS in the hospital's pharmacology laboratory. The PMB plasma concentration is the sum of PMB 1 and PMB 2 peptide concentrations. Since PMB 1 and PMB 2 have similar structures, the total PMB concentration is calculated as follows: Total PMB concentration = (PMB 1 concentration / PMB 1 molecular weight) + (PMB 2 concentration / PMB 2 molecular weight) × total PMB molecular weight The pharmacokinetic profile was characterized by plotting concentration-time curves for C max , C min , and C 6h . Pharmacokinetic parameters, including AUC 0− 24h , were derived through noncompartmental analysis of polymyxin B using Phoenix WinNonlin® software (version 6.4). Additionally, the intravenous dosage, duration of PMB treatment, use of nebulized PMB as adjunctive therapy, and the use of other antibiotics (targeting the main pathogens of carbapenem-resistant HAP) during PMB therapy were recorded for each patient. The carbapenem susceptibility profiles of carbapenem-resistant organisms were assessed in accordance with the interpretive criteria established by the European Committee on Antimicrobial Susceptibility Testing (EUCAST) (16, 17). The EUCAST Clinical Breakpoints of PMB were sensitivity (S ≤ 2mg/L) and drug resistance (R > 2mg/L). Polymyxin-sensitive bacteria were identified using the VITEK-2 Compact system with VITEK cards (0.5–16 mg/L for colistin) (bioMérieux, France). Endpoints The primary outcome was clinical treatment success at 14 days. Success was defined as a composite of the patient alive, hemodynamic stability (systolic blood pressure more than 90 mm Hg without need for vasopressors support), improved or stable SOFA score (for baseline SOFA ≥ 3, we required that the score improve by at least 30%, and for baseline SOFA < 3, we required that the score remain the same or decrease), stable or improved ratio of partial pressure of arterial oxygen to fraction of expired oxygen. Patients who did not meet all the success criteria were classified as clinical failure(18). The secondary endpoints comprised: (1) acute kidney injury (AKI) incidence, defined as a serum creatinine elevation ≥ 0.3 mg/dL (26.5 µmol/L) or ≥ 50% from baseline on two consecutive measurements during polymyxin B therapy; (2) 28-day all-cause mortality; (3) ventilator-free days at day 28; (4) intensive care unit mortality; (5) hospital length of stay; and (6) ICU length of stay. AKI severity was further stratified according to the Kidney Disease: Improving Global Outcomes (KDIGO) classification system. Patients who were receiving CRRT at enrollment were excluded from the AKI analysis due to the difficulty in diagnosing PMB-associated AKI during treatment. Statistical analysis We utilized restricted cubic spline regression with three knot points to flexibly characterize the nonlinear relationships between the AUC 0 − 24h of PMB and clinical outcomes, including treatment success and AKI incidence. The optimal AUC 0 − 24h thresholds were determined at the points where the HR and its entire 95% CI exceeded 1.0, establishing the lower (for efficacy) and upper (for safety) bounds of the therapeutic window. Patients were categorized into three groups based on their AUC 0 − 24h levels, and multivariable logistic regression models were employed to compare clinical outcomes across these groups, with variance inflation factors (VIF) < 5 confirming the absence of significant multicollinearity among adjusted variables. We did several sensitivity analyses in different subgroups. Patients receiving continuous renal replacement therapy (CRRT) at enrollment were excluded from the acute kidney injury (AKI) analysis because their serum creatinine levels and urine output could not accurately reflect true renal function changes. Statistical analyses were executed with R statistical software (v4.5.0; R Foundation for Statistical Computing), while graphical representations were generated using Prism 10 (GraphPad Software Inc., CA, USA). The distributional characteristics of continuous variables were assessed through Shapiro-Wilk normality testing. Parametric data are presented as mean values with standard deviation (mean ± SD), whereas nonparametric data are reported as medians with interquartile ranges (median [IQR]). Comparisons of continuous variables were performed using an independent samples t-test for normally distributed data and the Kolmogorov-Smirnov non-parametric test for non-normally distributed data. The analysis of categorical variables was performed using either Pearson's chi-square test or Fisher's exact probability test, depending on the sample size and expected frequency distribution. Multivariable analyses were conducted using logistic regression or Cox proportional hazards models for outcome prediction. A two-tailed p-value of < 0.05 was considered statistically significant. Results Patients Characteristics From January 2020 to June 2024, we initially identified 258 intensive care unit (ICU) patients who received polymyxin B (PMB) therapy. After applying predefined exclusion criteria, 120 patients were eliminated, yielding a final cohort of 138 patients for comprehensive evaluation (Fig. 1 ). The study population had a median age of 68 (58, 75) years, with males predominating 110 (79.7%). Septic shock was present in 97 cases (70.3%). Regarding organ support modalities during PMB treatment, 45 patients (32.6%) required continuous renal replacement therapy (CRRT), while 14 (10.1%) received extracorporeal membrane oxygenation (ECMO) support.The most used combination therapies with PMB were tigecycline (42.8%). All pathogens isolated from the included patients were sensitive to PMB, with a minimum inhibitory concentration (MIC) ≤ 2mg/L. The predominant causative pathogens identified were carbapenem-resistant Acinetobacter baumannii (CRAB, 77.5%), with carbapenem-resistant Klebsiella pneumoniae (CRKP, 14.5%) and carbapenem-resistant Pseudomonas aeruginosa (CRPA, 11.6%) representing fewer common isolates, five patients had simultaneous infections with multiple bacterial species (Table 1 ). Table 1 Demographic characteristics of the included patients Variable Total(n = 138) Clinical success(n = 63) Clinical failure (n = 75) P Age (years) 68.0 (58.0, 75.0) 69.0 (60.0, 75.0) 67.0 (58.0, 75.0) 0.510 Male, n (%) 110 (79.7) 54 (85.7) 56 (74.7) 0.163 BMI (kg/m 2 ) 23.6 (± 3.5) 23.3 (± 3.7) 23.7 (± 3.4) 0.516 Weight (kg) 70.0 (60.0, 75.0) 70.0 (60.0, 75.0) 65.0 (60.0, 75.0) 0.709 APACHE II at admission 23.5 (± 6.8) 21.6 (± 6.4) 25.0 (± 6.8) 0.004 SOFA at admission 9.0 (7.0, 11.0) 8.0 (5.0, 9.0) 10.0 (8.0, 13.0) < 0.001 Septic shock 97 (70.3) 38 (60.3) 59 (78.7) 0.031 VIS 24hmax 15.4 (0.0, 39.8) 8.0 (0.0, 26.7) 20.0 (7.7, 48.3) 0.005 Comorbidities, n (%) Hypertension 73 (52.9) 30 (47.6) 43 (57.3) 0.333 Diabetes 40 (29.0) 17 (27.0) 23 (30.7) 0.774 Cerebrovascular disease 25 (18.1) 10 (15.9) 15 (20.0) 0.685 Coronary heart disease 15 (10.9) 7 (11.1) 8 (10.7) > 0.999 COPD 17 (12.3) 8 (12.7) 9 (12.0) > 0.999 Chronic kidney disease 9 (6.5) 1 (1.6) 8 (10.7) 0.071 Liver disease 7 (5.1) 1 (1.6) 6 (8.0) 0.187 Malignant tumor 15 (10.9) 8 (12.7) 7 (9.3) 0.720 MV, n (%) 131 (94.9) 58 (92.1) 73 (97.3) 0.310 CRRT, n (%) 45 (32.6) 8 (12.7) 37 (49.3) < 0.001 ECMO, n (%) 14 (10.1) 5 (7.9) 9 (12.0) 0.614 Baseline laboratory data White blood cells (×10 9 /L) 10.2 (6.7, 15.2) 10.2 (6.5, 13.8) 11.2 (7.2, 17.1) 0.567 Neutrophils proportion (%) 86.2 (79.2, 92.6) 84.7 (77.8, 91.0) 89.2 (81.0, 93.0) 0.080 PCT (ng/mL) 1.2 (0.2, 4.1) 0.5 (0.2, 1.7) 2.3 (0.4, 7.1) 0.001 Lymphocyte count (×10 9 /L) 0.7 (0.4, 1.2) 0.8 (0.5, 1.2) 0.6 (0.4, 1.1) 0.136 CRP (mg/L) 117.6 (63.9, 173.0) 91.6 (58.3, 134.1) 157.6 (76.1, 200.1) 0.001 Albumin (g/L) 32.3 (29.6, 35.1) 32.5 (30.1, 35.5) 32.0 (29.2, 34.1) 0.230 GFR (ml/min) 86.5 (47.0, 103.8) 92.8 (66.9, 106.1) 73.4 (42.7, 101.2) 0.037 Pulmonary-only infection, n (%) 18 (13.0) 9 (14.3) 9 (12.0) 0.886 Pathogen, n (%) CRAB 107 (77.5) 48 (76.2) 59 (78.7) 0.887 CRKP 20 (14.5) 8 (12.7) 12 (16.0) 0.760 CRPA 16 (11.6) 9 (14.3) 7 (9.3) 0.523 PMB treatment Nebulization, n (%) 55 (39.9) 25 (39.7) 30 (40.0) > 0.999 Treatment duration (days) 11.0 (7.0, 14.0) 12.0 (9.0, 15.0) 9.0 (7.0, 12.0) 0.001 Daily dose (mg/kg/day) 2.1 (1.7, 2.5) 2.1 (1.8, 2.5) 2.1 (1.7, 2.5) 0.884 Concomitant drugs, n (%) Tigecycline 59 (42.8) 19 (30.2) 40 (53.3) 0.010 Carbapenem 22 (15.9) 8 (12.7) 14 (18.7) 0.471 Sulbactam 20 (14.5) 9 (14.3) 11 (14.7) > 0.999 Amikacin 24 (17.4) 11 (17.5) 13 (17.3) > 0.999 Minocycline 22 (15.9) 12 (19.0) 10 (13.3) 0.497 Data are mean (± SD), n (%), or median (IQR). BMI = Body Mass Index; APACHE II = Acute Physiology and Chronic Health Evaluation II; SOFA = Sequential Organ Failure Assessment; VIS = Vasoactive-Inotropic Score; COPD = Chronic Obstructive Pulmonary Disease; MV = Mechanical Ventilation; CRRT = Continuous Renal Replacement Therapy; ECMO = Extracorporeal Membrane Oxygenation; GFR = Glomerular Filtration Rate; PCT = Procalcitonin; CRP = C-reactive protein; CRAB = Carbapenem resistant Acinetobacter baumannii; CRKP = Carbapenem-resistant Klebsiella pneumoniae; CRPA = Carbapenem-resistant Pseudomonas aeruginosa; PMB = Polymyxin B. The enrolled patients were divided into two groups based on the ultimate clinical treatment outcomes. Comparative analysis of baseline characteristics revealed significant differences in disease severity between treatment response groups. Patients achieving clinical success presented with markedly less severe illness, as reflected in their lower median APACHE II and SOFA scores compared to the treatment failure group. Other demographic and clinical parameters showed no statistically significant differences between groups (Table 1 ). The clinical success cohort demonstrated superior outcomes across multiple endpoints: 28-day all-cause mortality was reduced, ventilator-free days at day 28 were significantly increased, and ICU mortality was lower. (Table 2 ). Table 2 Clinical outcomes of the included patients Variable Total(n = 138) Clinical success(n = 63) Clinical failure (n = 75) P 28-day all-cause mortality, n (%) 63 (45.7) 7 (11.1) 56 (74.7) < 0.001 Ventilator-free days at 28 days (days) 0.0 (0.0, 11.0) 6.0 (0.0, 18.5) 0.0 (0.0, 1.0) < 0.001 In-ICU mortality, n (%) 45 (32.6) 5 (7.9) 40 (53.3) < 0.001 Length of stay (days) 35.0 (23.2, 59.8) 44.0 (32.0, 68.5) 27.0 (18.0, 46.0) < 0.001 Length of ICU stay (days) 29.0 (20.0, 47.8) 35.0 (26.0, 53.0) 23.0 (17.5, 38.0) < 0.001 PMB exposure and concentrations The median daily dose of PMB among enrolled patients was 2.1 (1.7, 2.5) mg/kg, with 55 (39.9%) patients receiving nebulized PMB therapy (Table 1 ). The median AUC 0 − 24h was 77.5 (55.6, 105.6) mg·h/L. Patients in the clinical treatment success group exhibited significantly higher levels in the plasma concentration of PMB compared to the clinical treatment failure group (Table S1 and Figure S1 ). The optimal AUC 0 − 24h target of PMB The restricted cubic spline analysis revealed a nonlinear relationship between clinical treatment success rate and the AUC 0 − 24h of PMB. Initially, treatment success rates increased with higher AUC 0 − 24h levels, when the AUC 0 − 24h of PMB reached a certain threshold, the degree of clinical benefit derived from further increases diminished. An AUC 0 − 24h of PMB exceeding 77 mg·h/L could significantly predict clinical treatment success (Fig. 2 ). The analysis of PMB-associated AKI included 102 patients, with an overall AKI incidence rate of 34.3%. The restricted cubic spline plot also demonstrated that the incidence of AKI increased with higher the AUC 0 − 24h of PMB levels. When the AUC 0 − 24h of PMB exceeded 110 mg·h/L, both the odds ratio (OR) and its 95% confidence interval (CI) for AKI incidence were > 1, indicating that AUC 0 − 24h of PMB above this threshold significantly increased the risk of AKI (Fig. 2 ). When the enrolled patients were stratified into three groups based on AUC cutoffs (lower: 77 mg·h/L; upper: 110 mg·h/L), we found that the 77–110 mg·h/L group had a significantly higher clinical treatment success rate than the 110 mg·h/L group (Figure S2). We further evaluated the clinical relevance of the 77–110 mg·h/L AUC 0 − 24h range in multivariable logistic regression models. The results demonstrated that compared to the reference 77–110 mg·h/L group, AUC 0 − 24h 110 mg·h/L significantly increased AKI risk (OR: 3.24, 95% CI: 1.06–10.47; p = 0.043) (Table 4 ). Table 3 The impact of the AUC 0-24h of PMB on 14-day clinical treatment success rates in patients with CRO-HAP using logistic regression model Characteristic OR 95% CI P AUC 0 − 24h = 77–110 mg·h/L AUC 0 − 24h 110 mg·h/L 1.19 0.41–3.55 0.746 Age 1.00 0.97–1.03 0.822 Male 0.68 0.25–1.78 0.437 BMI 0.99 0.88–1.11 0.856 SOFA at admission 0.78 0.68–0.89 < 0.001 VIS 24hmax 1.00 0.98–1.01 0.791 AUC 0 − 24h = Area under the 24-hour drug concentration-time curve of PMB; BMI = Body Mass Index; SOFA = Sequential Organ Failure Assessment; VIS = Vasoactive-Inotropic Score. Table 4 The impact of the AUC 0-24h of PMB on AKI incidence in patients with CRO-HAP using logistic regression model Characteristic OR 95% CI P AUC 0 − 24h = 77–110 mg·h/L AUC 0 − 24h 110 mg·h/L 3.24 1.06–10.47 0.043 Age 1.00 0.97–1.05 0.814 Male 0.63 0.18–2.07 0.458 SOFA at admission 1.16 0.98–1.37 0.093 VIS 24hmax 0.99 0.97–1.01 0.407 GFR 0.99 0.97–1.01 0.214 AUC 0 − 24h = Area under the 24-hour drug concentration-time curve of PMB; SOFA = Sequential Organ Failure Assessment; VIS = Vasoactive-Inotropic Score; GFR = Glomerular Filtration Rate. Sensitivity Analysis In sensitivity analyses restricting the sample to male patients, those with normal BMI (18.5–28 kg/m²), Septic shock cases, or pulmonary infections only, the association between AUC 77–110 mg·h/L and higher clinical treatment success remained statistically significant when compared to the AUC 110 mg·h/L group (Fig. 3 and Fig. 4 ). Discussion This study primarily identified an optimal PMB AUC 0 − 24h range of 77–110 mg·h/L for carbapenem-resistant HAP patients, which maximized clinical treatment success while minimizing AKI incidence. This therapeutic window was subsequently validated through adjusted multivariable regression analysis. The international consensus guidelines on the optimal use of polymyxins recommend the ideal AUC 0 − 24h target range is suggested to be between 50 mg·h/L and 100 mg·h/L, and a maintenance dose of PMB is 1.25–1.5 mg/kg every 12 hours(12). Monte Carlo simulations have determined that PMB dosing regimens of 2.5 mg/kg/day and 3.0 mg/kg/day can achieve steady-state AUC 0 − 24h values of at least 44.3 mg·h/L and 53.1 mg·h/L, respectively, in 90% of patients(20). In our study, the median PMB maintenance intravenous daily dose was 2.1 (1.7, 2.5) mg/kg/day, which is lower than the guideline-recommended dose. This reduction in dosage may reflect the more severe baseline conditions of our patients, with clinicians adjusting maintenance doses to mitigate the risk of nephrotoxicity. All patients in our cohort underwent therapeutic drug monitoring (TDM), with > 80% achieving PMB AUC 0 − 24h levels exceeding the international guideline threshold of 50 mg·h/L, effectively addressing potential underdosing concerns. Previous studies have confirmed that The AUC 0 − 24h of PMB is associated with both patient outcomes and the occurrence of AKI(19, 21). The 2019 international consensus guidelines for polymyxins(12) recommend targeting The AUC 0 − 24h of PMB within the range of 50 mg·h/L to 100 mg·h/L. The lower target limit of 50 mg·h/L was identified by Landersdorfer et al. in a murine thigh infection model of Klebsiella pneumoniae as a target that could significantly reduce bacterial burden(13). However, this target demonstrated weaker bactericidal effects in a murine lung infection model. In a real-world study on PMB treatment for CRO pneumonia patients, Tang et al. determined through ROC curve analysis that the optimal PK/PD index of PMB for predicting clinical treatment success was an AUC 0 − 24h cutoff of 66.9 mg·h/L(15), exceeding the guideline-recommended lower target of 50 mg·h/L. Yu et al. reported in a prospective, observational multicenter study that PMB therapy for intra-abdominal infections demonstrated significantly lower 14-day mortality when the AUC exceeded 76 mg·h/L(22). The correlation between AUC 0 − 24h and clinical outcomes may sometimes be obscured by the complex clinical characteristics of patients, such as bacterial resistance(23). Our findings further validate this observation, demonstrating a significant association between the AUC 0 − 24h of PMB and clinical efficacy in carbapenem-resistant HAP patients, but with a higher optimal lower threshold, and an even furth. The incidence of AKI in this study is consistent with previous research data(24–26). A meta-analysis on PMB-associated AKI found that an AUC 0 − 24h exceeding 100 mg·h/L led to drug-induced nephrotoxicity in over 40% of patients(14). Yang et al. confirmed that an AUC 0 − 24h exceeding 100 mg·h/L is a significant risk factor for drug-induced nephrotoxicity(19). In our study, the PMB AUC 0 − 24h threshold associated with AKI incidence was 110 mg·h/L, aligning closely with findings from prior studies and the upper limit recommended by international guidelines for PMB use. This study has several limitations. First, as a single-center, retrospective study with a relatively small sample size, the accuracy and generalizability of the results are limited. Second, due to missing data inherent in retrospective studies, we were unable to investigate the impact of other pharmacokinetic parameters of PMB on clinical outcomes. Third, we did not analyze variations of the PMB AUC 0 − 24h in different infection sites, causative pathogens, or combination therapy regimens. These factors may hold greater clinical relevance for guiding treatment but were constrained by our limited sample size. Fourth, in discussing the incidence of AKI, we excluded patients who were undergoing CRRT at enrollment to avoid confounding in the evaluation of AKI incidence. This exclusion may result in differences between the target populations for the upper and lower limits of the AUC 0 − 24h , necessitating cautious interpretation of the recommended AUC 0 − 24h target range. Conclusions In conclusion, this study confirms that the AUC 0 − 24h of PMB is closely associated with both 14-day clinical treatment success rates and the incidence of AKI in patients with carbapenem-resistant HAP, with an optimal range from 77 to 110 mg·h/L. Abbreviations AUC 0-24h Area under the concentration-time curve across 24 hours PMB Polymyxin B CRO Carbapenem-resistant organism HAP Hospital-acquired pneumonia TDM therapeutic drug monitoring MIC Minimum inhibitory concentration KDIGO Kidney disease improving global outcomes AKI Acute kidney injury PK Pharmacokinetics PD Pharmacodynamics APACHE II Acute physiology and chronic health evaluation SOFA Sequential organ failure assessment MV Mechanical ventilation ECMO Extracorporeal membrane oxygenation CRRT Continuous renal replacement therapy C min Trough concentration at steady state C max Peak concentration at steady state C 6h 6 hours concentration at steady state VIS 24hmax Maximum Vasoactive-Inotropic Score within 24 hours of enrollment GFR estimated glomerular filtration rate PCT Procalcitonin CRP C-reactive protein CRPA Carbapenem-resistant Pseudomonas aeruginosa CRAB Carbapenem-resistant Acinetobacter baumannii CRKP Carbapenem-resistant klebsiella pneumonia Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of Zhongda Hospital, Southeast University (2023ZDSYLL296-P01) and waived informed consent due to its retrospective nature. All procedures were performed in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Consent for publication Not applicable. Availability of data and materials The data that support the findings of this study are available from the corresponding author, [Y.H.], upon reasonable request. Competing interests All authors declare no competing interests. Funding Supported by the National Key Research and Development Program of China (2022YFC2304600), National Natural Science Foundation of China (82272235 and 81971812), Jiangsu Province Key Research and Development Program (Social Development) Special Project (BE2021734). Contributions M.X., X.X. and Y.H. conceived the study. L.H., J.H., Q.P., M.B. and S.Z. collected data for the work. M.X., X.X., H.C., W.H., H.W., and S.Y. performed data analysis. M.X., X.X., W.H., J.X., and Y.H. prepared the first draft of the manuscript. All authors were responsible for data interpretation, revised the manuscript critically, and approved the version submitted for publication. Corresponding author Correspondence to Yingzi Huang. Author information Author notes Mengru Xiong and Xiaoting Xu have contributed equally to the work. Authors and Affiliations 1. Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing 210009, China Mengru Xiong1, Xiaoting Xu, Qingyun Peng, Mingze Bi, Shijia Zhong, Wenhan Hu, Haofei Wang, Shuhe Yang, Jianfeng Xie, Yingzi Huang 2. Department of Pharmacy, Zhongda Hospital, Southeast University, School of Medicine, Southeast University, Nanjing 210009, China Linlin Hu, Jie He Acknowledgements The authors thank all the subjects for their participation in this study. 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Tacconelli E, Carrara E, Savoldi A, Harbarth S, Mendelson M, Monnet DL, et al.Discovery, research, and development of new antibiotics: the WHO priority list of antibiotic-resistant bacteria and tuberculosis. Lancet Infect Dis. 2018;18(3):318–27. Nang SC, Azad MAK, Velkov T, Zhou QT, Li J . Rescuing the Last-Line Polymyxins: Achievements and Challenges. Pharmacol Rev. 2021;73(2):679–728. Torres A, Niederman MS, Chastre J, Ewig S, Fernandez-Vandellos P, Hanberger H, et al.International ERS/ESICM/ESCMID/ALAT guidelines for the management of hospital-acquired pneumonia and ventilator-associated pneumonia: Guidelines for the management of hospital-acquired pneumonia (HAP)/ventilator-associated pneumonia (VAP) of the European Respiratory Society (ERS), European Society of Intensive Care Medicine (ESICM), European Society of Clinical Microbiology and Infectious Diseases (ESCMID) and Asociación Latinoamericana del Tórax (ALAT). Eur Respir J. 2017;50(3). Gales AC, Jones RN, Sader HS . Contemporary activity of colistin and polymyxin B against a worldwide collection of Gram-negative pathogens: results from the SENTRY Antimicrobial Surveillance Program (2006-09). J Antimicrob Chemother. 2011;66(9):2070–4. Zhang J, Hu Y, Shen X, Zhu X, Chen J, Dai H . Risk factors for nephrotoxicity associated with polymyxin B therapy in Chinese patients. Int J Clin Pharm. 2021;43(4):1109–15. Cai Y, Leck H, Tan RW, Teo JQ, Lim TP, Lee W, et al.Clinical Experience with High-Dose Polymyxin B against Carbapenem-Resistant Gram-Negative Bacterial Infections-A Cohort Study. Antibiotics (Basel). 2020;9(8). Liu X, Huang C, Bergen PJ, Li J, Zhang J, Chen Y, et al.Chinese consensus guidelines for therapeutic drug monitoring of polymyxin B, endorsed by the Infection and Chemotherapy Committee of the Shanghai Medical Association and the Therapeutic Drug Monitoring Committee of the Chinese Pharmacological Society. J Zhejiang Univ Sci B. 2023;24(2):130–42. Tsuji BT, Pogue JM, Zavascki AP, Paul M, Daikos GL, Forrest A, et al.International Consensus Guidelines for the Optimal Use of the Polymyxins: Endorsed by the American College of Clinical Pharmacy (ACCP), European Society of Clinical Microbiology and Infectious Diseases (ESCMID), Infectious Diseases Society of America (IDSA), International Society for Anti-infective Pharmacology (ISAP), Society of Critical Care Medicine (SCCM), and Society of Infectious Diseases Pharmacists (SIDP). Pharmacotherapy. 2019;39(1):10–39. Landersdorfer CB, Wang J, Wirth V, Chen K, Kaye KS, Tsuji BT, et al.Pharmacokinetics/pharmacodynamics of systemically administered polymyxin B against Klebsiella pneumoniae in mouse thigh and lung infection models. J Antimicrob Chemother. 2018;73(2):462–8. Lakota EA, Landersdorfer CB, Nation RL, Li J, Kaye KS, Rao GG, et al.Personalizing Polymyxin B Dosing Using an Adaptive Feedback Control Algorithm. Antimicrob Agents Chemother. 2018;62(7). Tang T, Li Y, Xu P, Zhong Y, Yang M, Ma W, et al.Optimization of polymyxin B regimens for the treatment of carbapenem-resistant organism nosocomial pneumonia: a real-world prospective study. Crit Care. 2023;27(1):164. Satlin MJ, Lewis JS, Weinstein MP, Patel J, Humphries RM, Kahlmeter G, et al.Clinical and Laboratory Standards Institute and European Committee on Antimicrobial Susceptibility Testing Position Statements on Polymyxin B and Colistin Clinical Breakpoints. Clin Infect Dis. 2020;71(9):e523–e9. Giske CG, Turnidge J, Cantón R, Kahlmeter G . Update from the European Committee on Antimicrobial Susceptibility Testing (EUCAST). J Clin Microbiol. 2022;60(3):e0027621. Paul M, Daikos GL, Durante-Mangoni E, Yahav D, Carmeli Y, Benattar YD, et al.Colistin alone versus colistin plus meropenem for treatment of severe infections caused by carbapenem-resistant Gram-negative bacteria: an open-label, randomised controlled trial. Lancet Infect Dis. 2018;18(4):391–400. Yang J, Liu S, Lu J, Sun T, Wang P, Zhang X . An area under the concentration-time curve threshold as a predictor of efficacy and nephrotoxicity for individualizing polymyxin B dosing in patients with carbapenem-resistant gram-negative bacteria. Crit Care. 2022;26(1):320. Sandri AM, Landersdorfer CB, Jacob J, Boniatti MM, Dalarosa MG, Falci DR, et al.Pharmacokinetics of polymyxin B in patients on continuous venovenous haemodialysis. J Antimicrob Chemother. 2013;68(3):674–7. Liu S, Wu Y, Qi S, Shao H, Feng M, Xing L, et al.Polymyxin B therapy based on therapeutic drug monitoring in carbapenem-resistant organisms sepsis: the PMB-CROS randomized clinical trial. Crit Care. 2023;27(1):232. Yu Z, Hu H, Liu X, Liu J, Yu L, Wei A, et al.Clinical outcomes and pharmacokinetics/pharmacodynamics of intravenous polymyxin B treatment for various site carbapenem-resistant gram-negative bacterial infections: a prospective observational multicenter study. Antimicrob Agents Chemother. 2025;69(4):e0185924. Wang P, Liu S, Qi G, Xu M, Sun T, Yang J . Evaluation of polymyxin B AUC/MIC ratio for dose optimization in patients with carbapenem-resistant Klebsiella pneumoniae infection. Front Microbiol. 2023;14:1226981. Wang P, Zhang Q, Zhu Z, Pei H, Feng M, Sun T, et al.Comparing the Population Pharmacokinetics of and Acute Kidney Injury Due to Polymyxin B in Chinese Patients with or without Renal Insufficiency. Antimicrob Agents Chemother. 2021;65(2). Chang K, Wang H, Zhao J, Yang X, Wu B, Sun W, et al.Risk factors for polymyxin B-associated acute kidney injury. Int J Infect Dis. 2022;117:37–44. Rigatto MH, Behle TF, Falci DR, Freitas T, Lopes NT, Nunes M, et al.Risk factors for acute kidney injury (AKI) in patients treated with polymyxin B and influence of AKI on mortality: a multicentre prospective cohort study. J Antimicrob Chemother. 2015;70(5):1552–7. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7249423","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":510133831,"identity":"fb08dfc5-97e1-40b4-b00b-33de5de06136","order_by":0,"name":"Mengru Xiong","email":"","orcid":"","institution":"Zhongda Hospital, Southeast University","correspondingAuthor":false,"prefix":"","firstName":"Mengru","middleName":"","lastName":"Xiong","suffix":""},{"id":510133832,"identity":"67bd7e8b-37f4-42e0-bfab-010fa9967574","order_by":1,"name":"Xiaoting Xu","email":"","orcid":"","institution":"Zhongda Hospital, Southeast 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University","correspondingAuthor":true,"prefix":"","firstName":"Yingzi","middleName":"","lastName":"Huang","suffix":""}],"badges":[],"createdAt":"2025-07-30 06:53:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7249423/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7249423/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91076429,"identity":"a54c5fed-7ff9-43e2-9b3e-e0e5b8703370","added_by":"auto","created_at":"2025-09-11 11:10:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":173415,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of patient enrollment.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7249423/v1/cd0a8c0e90bd1168ab138c2c.png"},{"id":91074033,"identity":"62075ea3-6bb4-4601-8e2b-2a03fb561ed4","added_by":"auto","created_at":"2025-09-11 11:02:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":66193,"visible":true,"origin":"","legend":"\u003cp\u003eRestricted cubic splines were utilized to evaluate the hypothesis of potential nonlinear relationships between the AUC\u003csub\u003e0-24h\u003c/sub\u003e of PMB and the 14-day clinical treatment success rates (A) and AKI incidence (B) in patients with CRO-HAP.\u0026nbsp;\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7249423/v1/4537e7d3a266a0adaf1ea549.png"},{"id":91074034,"identity":"6a82b852-b933-4ae4-a748-477a8e830dbe","added_by":"auto","created_at":"2025-09-11 11:02:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":226868,"visible":true,"origin":"","legend":"\u003cp\u003eSensitivity Analysis of the AUC\u003csub\u003e0-24h\u003c/sub\u003e of PMB on 14-day clinical treatment success rates. BMI = Body Mass Index. CRAB = Carbapenem-resistant Acinetobacter baumannii.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7249423/v1/3ca3e66353f5e400d49775ba.png"},{"id":91076430,"identity":"7e59d157-dce7-454b-b4bb-3b6fed41f89d","added_by":"auto","created_at":"2025-09-11 11:10:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":230199,"visible":true,"origin":"","legend":"\u003cp\u003eSensitivity Analysis of the AUC0-24h of PMB on AKI Incidence. BMI = Body Mass Index. CRAB = Carbapenem-resistant Acinetobacter baumannii.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7249423/v1/e0f0715fe4e1d83d635b2d0d.png"},{"id":91079808,"identity":"64609da2-0467-4b79-8559-b7682627ee1e","added_by":"auto","created_at":"2025-09-11 11:26:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1343759,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7249423/v1/658ff930-4c90-413e-a5c4-5616cf465075.pdf"},{"id":91074042,"identity":"316213cc-da6f-4502-8722-4b1eddb71b5e","added_by":"auto","created_at":"2025-09-11 11:02:02","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1744950,"visible":true,"origin":"","legend":"","description":"","filename":"supplementerymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-7249423/v1/948da14d94a9d5af37d68757.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Optimizing polymyxin B exposure in carbapenem-resistant organism Hospital-Acquired Pneumonia: a retrospective observational study","fulltext":[{"header":"Background","content":"\u003cp\u003eHospital-acquired pneumonia (HAP) represents a significant global public health challenge. In particular, HAP caused by carbapenem-resistant bacteria has exacerbated the complexity of treatment, intensified the burden on healthcare systems(1), and further increased in-hospital mortality rates among affected patients(2, 3).\u003c/p\u003e\u003cp\u003eAntibiotic treatment strategies for carbapenem-resistant HAP are extremely limited(4, 5). Polymyxins B is a concentration-dependent antibiotic(6), demonstrates significant antimicrobial efficacy against carbapenem-resistant Gram-negative bacterial strains(7, 8). However, it exhibits significant nephrotoxicity at high concentrations(9, 10). Therefore, clinical use typically relies on TDM to guide dosage adjustments(11).\u003c/p\u003e\u003cp\u003ePharmacokinetic and pharmacodynamic (PK/PD) studies are crucial for optimizing antibiotic administration. International consensus guidelines on the optimal use of polymyxins(12) recommend the ideal AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e target range is suggested to be between 50 mg\u0026middot;h/L and 100 mg\u0026middot;h/L based on previous studies(13) (14).The retrospective study revealed that the range of 50\u0026ndash;100 mg\u0026middot;h/kg is not always effective in critically ill patients and their complex clinical settings(15). Therefore, this study primarily investigates the best AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e target range of PMB associated with favorable clinical outcomes in patients with carbapenem-resistant HAP.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy protocol and population\u003c/b\u003e\u003c/p\u003e\u003cp\u003e This study was designed as a retrospective, single-center observational analysis performed within the Intensive Care Unit of Zhongda Hospital, affiliated with Southeast University. The study included patients with carbapenem-resistant HAP who received intravenous PMB treatment and underwent TDM between January 2020 and June 2024 and was approved by the Ethics Committee of Zhongda Hospital, Southeast University (approval number: 2023ZDSYLL296-P01) and waived informed consent due to its retrospective nature.\u003c/p\u003e\u003cp\u003eInclusion criteria for patients were as follows: (a) over 18 years old; (b) diagnosed with HAP during ICU admission; (c) microbiological evidence indicating carbapenem-resistant pathogenic bacteria; (d) receiving intravenous polymyxin B therapy for more than 3 days. Exclusion criteria included: (a) lack of TDM for PMB or incomplete steady-state blood concentration data; (b) Intravenous polymyxin B therapy is primarily indicated for infections in other body sites, such as the abdominal cavity, intracranial region, and skin and soft tissues and so on; (c) pathogenic bacteria are resistant to polymyxin B; (d) pregnant or lactating patients. According to European guidelines(7), HAP was clinically defined as pneumonia developing\u0026thinsp;\u0026ge;\u0026thinsp;48 hours after hospital admission, requiring fulfillment of all following criteria: (1) presence of at least two clinical manifestations: including body temperature\u0026thinsp;\u0026gt;\u0026thinsp;38\u0026deg;C, leukocytosis\u0026thinsp;\u0026gt;\u0026thinsp;12,000 cells/mL/leukopenia\u0026thinsp;\u0026lt;\u0026thinsp;4,000 cells/mL, or purulent respiratory secretions; (2) radiographic evidence of new pulmonary infiltrates or progression of existing infiltrates; and (3) semi-quantitative or quantitative positivity in respiratory culture.\u003c/p\u003e\u003cp\u003ePatient demographic and clinical data were extracted from the electronic medical records, encompassing age, sex, height, weight, date of admission, and preexisting comorbidities. The severity of disease at the time of patient enrollment was assessed using the Acute Physiology and Chronic Health Evaluation II (APACHE II) score and SOFA score. Clinical data collection included laboratory parameters, infection-related variables, and organ support modalities administered during polymyxin B therapy, such as mechanical ventilation, continuous renal replacement therapy, and extracorporeal membrane oxygenation.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePMB administration and concentration\u003c/b\u003e\u003c/p\u003e\u003cp\u003eClinically, PMB is typically administered at a dosage of 50\u0026ndash;100 mg every 12 hours, with each infusion lasting 1 hour. Some patients receive combined intravenous and nebulized polymyxin B therapy. For nebulization, 25\u0026ndash;50 mg of PMB is diluted in 5 mL of sterile water for injection, and the solution is administered via a vibrating mesh nebulizer connected to the patient's ventilator inspiratory circuit. After achieving steady-state PMB blood concentrations (which is typically reached after 5 intravenous doses of PMB), blood samples were obtained at three predetermined intervals: immediately before dosing (trough concentration/C\u003csub\u003emin\u003c/sub\u003e), 1-hour post-infusion (peak concentration/C\u003csub\u003emax\u003c/sub\u003e), and 6-hours following administration (C\u003csub\u003e6h\u003c/sub\u003e). If there is a change in the dosage during treatment, the steady-state concentration timeline and relevant steady-state blood concentration data are recalculated starting from the time the dosage is adjusted.\u003c/p\u003e\u003cp\u003eBlood samples for drug concentration analysis were collected at the specified time points, immediately centrifuged at 1500g for 10 minutes after collection. The supernatant was then stored at -80\u0026deg;C. Plasma concentrations of PMB were measured using validated UPLC\u0026ndash;MS/MS in the hospital's pharmacology laboratory. The PMB plasma concentration is the sum of PMB\u003csub\u003e1\u003c/sub\u003e and PMB\u003csub\u003e2\u003c/sub\u003e peptide concentrations. Since PMB\u003csub\u003e1\u003c/sub\u003e and PMB\u003csub\u003e2\u003c/sub\u003e have similar structures, the total PMB concentration is calculated as follows:\u003c/p\u003e\u003cp\u003eTotal PMB concentration = (PMB\u003csub\u003e1\u003c/sub\u003e concentration / PMB\u003csub\u003e1\u003c/sub\u003e molecular weight) + (PMB\u003csub\u003e2\u003c/sub\u003e concentration / PMB\u003csub\u003e2\u003c/sub\u003e molecular weight) \u0026times; total PMB molecular weight\u003c/p\u003e\u003cp\u003eThe pharmacokinetic profile was characterized by plotting concentration-time curves for C\u003csub\u003emax\u003c/sub\u003e, C\u003csub\u003emin\u003c/sub\u003e, and C\u003csub\u003e6h\u003c/sub\u003e. Pharmacokinetic parameters, including AUC\u003csub\u003e0\u0026minus;\u0026thinsp;24h\u003c/sub\u003e, were derived through noncompartmental analysis of polymyxin B using Phoenix WinNonlin\u0026reg; software (version 6.4). Additionally, the intravenous dosage, duration of PMB treatment, use of nebulized PMB as adjunctive therapy, and the use of other antibiotics (targeting the main pathogens of carbapenem-resistant HAP) during PMB therapy were recorded for each patient.\u003c/p\u003e\u003cp\u003e The carbapenem susceptibility profiles of carbapenem-resistant organisms were assessed in accordance with the interpretive criteria established by the European Committee on Antimicrobial Susceptibility Testing (EUCAST) (16, 17). The EUCAST Clinical Breakpoints of PMB were sensitivity (S\u0026thinsp;\u0026le;\u0026thinsp;2mg/L) and drug resistance (R\u0026thinsp;\u0026gt;\u0026thinsp;2mg/L). Polymyxin-sensitive bacteria were identified using the VITEK-2 Compact system with VITEK cards (0.5\u0026ndash;16 mg/L for colistin) (bioM\u0026eacute;rieux, France).\u003c/p\u003e\u003cp\u003e\u003cb\u003eEndpoints\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe primary outcome was clinical treatment success at 14 days. Success was defined as a composite of the patient alive, hemodynamic stability (systolic blood pressure more than 90 mm Hg without need for vasopressors support), improved or stable SOFA score (for baseline SOFA\u0026thinsp;\u0026ge;\u0026thinsp;3, we required that the score improve by at least 30%, and for baseline SOFA\u0026thinsp;\u0026lt;\u0026thinsp;3, we required that the score remain the same or decrease), stable or improved ratio of partial pressure of arterial oxygen to fraction of expired oxygen. Patients who did not meet all the success criteria were classified as clinical failure(18).\u003c/p\u003e\u003cp\u003eThe secondary endpoints comprised: (1) acute kidney injury (AKI) incidence, defined as a serum creatinine elevation\u0026thinsp;\u0026ge;\u0026thinsp;0.3 mg/dL (26.5 \u0026micro;mol/L) or \u0026ge;\u0026thinsp;50% from baseline on two consecutive measurements during polymyxin B therapy; (2) 28-day all-cause mortality; (3) ventilator-free days at day 28; (4) intensive care unit mortality; (5) hospital length of stay; and (6) ICU length of stay. AKI severity was further stratified according to the Kidney Disease: Improving Global Outcomes (KDIGO) classification system. Patients who were receiving CRRT at enrollment were excluded from the AKI analysis due to the difficulty in diagnosing PMB-associated AKI during treatment.\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eWe utilized restricted cubic spline regression with three knot points to flexibly characterize the nonlinear relationships between the AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e of PMB and clinical outcomes, including treatment success and AKI incidence. The optimal AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e thresholds were determined at the points where the HR and its entire 95% CI exceeded 1.0, establishing the lower (for efficacy) and upper (for safety) bounds of the therapeutic window. Patients were categorized into three groups based on their AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e levels, and multivariable logistic regression models were employed to compare clinical outcomes across these groups, with variance inflation factors (VIF)\u0026thinsp;\u0026lt;\u0026thinsp;5 confirming the absence of significant multicollinearity among adjusted variables. We did several sensitivity analyses in different subgroups. Patients receiving continuous renal replacement therapy (CRRT) at enrollment were excluded from the acute kidney injury (AKI) analysis because their serum creatinine levels and urine output could not accurately reflect true renal function changes.\u003c/p\u003e\u003cp\u003eStatistical analyses were executed with R statistical software (v4.5.0; R Foundation for Statistical Computing), while graphical representations were generated using Prism 10 (GraphPad Software Inc., CA, USA). The distributional characteristics of continuous variables were assessed through Shapiro-Wilk normality testing. Parametric data are presented as mean values with standard deviation (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD), whereas nonparametric data are reported as medians with interquartile ranges (median [IQR]). Comparisons of continuous variables were performed using an independent samples t-test for normally distributed data and the Kolmogorov-Smirnov non-parametric test for non-normally distributed data. The analysis of categorical variables was performed using either Pearson's chi-square test or Fisher's exact probability test, depending on the sample size and expected frequency distribution. Multivariable analyses were conducted using logistic regression or Cox proportional hazards models for outcome prediction. A two-tailed p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003ePatients Characteristics\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFrom January 2020 to June 2024, we initially identified 258 intensive care unit (ICU) patients who received polymyxin B (PMB) therapy. After applying predefined exclusion criteria, 120 patients were eliminated, yielding a final cohort of 138 patients for comprehensive evaluation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The study population had a median age of 68 (58, 75) years, with males predominating 110 (79.7%). Septic shock was present in 97 cases (70.3%). Regarding organ support modalities during PMB treatment, 45 patients (32.6%) required continuous renal replacement therapy (CRRT), while 14 (10.1%) received extracorporeal membrane oxygenation (ECMO) support.The most used combination therapies with PMB were tigecycline (42.8%). All pathogens isolated from the included patients were sensitive to PMB, with a minimum inhibitory concentration (MIC)\u0026thinsp;\u0026le;\u0026thinsp;2mg/L. The predominant causative pathogens identified were carbapenem-resistant \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e (CRAB, 77.5%), with carbapenem-resistant \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (CRKP, 14.5%) and carbapenem-resistant \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (CRPA, 11.6%) representing fewer common isolates, five patients had simultaneous infections with multiple bacterial species (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic characteristics of the included patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal(n\u0026thinsp;=\u0026thinsp;138)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eClinical success(n\u0026thinsp;=\u0026thinsp;63)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eClinical failure (n\u0026thinsp;=\u0026thinsp;75)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e68.0 (58.0, 75.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e69.0 (60.0, 75.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e67.0 (58.0, 75.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.510\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e110 (79.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e54 (85.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e56 (74.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.163\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e23.6 (\u0026plusmn;\u0026thinsp;3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23.3 (\u0026plusmn;\u0026thinsp;3.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e23.7 (\u0026plusmn;\u0026thinsp;3.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.516\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e70.0 (60.0, 75.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e70.0 (60.0, 75.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e65.0 (60.0, 75.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.709\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAPACHE II at admission\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e23.5 (\u0026plusmn;\u0026thinsp;6.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e21.6 (\u0026plusmn;\u0026thinsp;6.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25.0 (\u0026plusmn;\u0026thinsp;6.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSOFA at admission\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9.0 (7.0, 11.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8.0 (5.0, 9.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.0 (8.0, 13.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeptic shock\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e97 (70.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e38 (60.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e59 (78.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.031\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVIS\u003csub\u003e24hmax\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15.4 (0.0, 39.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8.0 (0.0, 26.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20.0 (7.7, 48.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComorbidities, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e73 (52.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30 (47.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e43 (57.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.333\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e40 (29.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17 (27.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e23 (30.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.774\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCerebrovascular\u0026nbsp;disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e25 (18.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10 (15.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15 (20.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.685\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoronary heart disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15 (10.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7 (11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8 (10.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCOPD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17 (12.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8 (12.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9 (12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic kidney disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9 (6.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8 (10.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.071\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiver disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7 (5.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6 (8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.187\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMalignant tumor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15 (10.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8 (12.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7 (9.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.720\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMV, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e131 (94.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e58 (92.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e73 (97.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.310\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRRT, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45 (32.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8 (12.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e37 (49.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eECMO, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14 (10.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5 (7.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9 (12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.614\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBaseline laboratory data\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite blood cells (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10.2 (6.7, 15.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.2 (6.5, 13.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11.2 (7.2, 17.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.567\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeutrophils proportion (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e86.2 (79.2, 92.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e84.7 (77.8, 91.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e89.2 (81.0, 93.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.080\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCT (ng/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.2 (0.2, 4.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.5 (0.2, 1.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.3 (0.4, 7.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLymphocyte count (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.7 (0.4, 1.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.8 (0.5, 1.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.6 (0.4, 1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.136\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRP (mg/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e117.6 (63.9, 173.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e91.6 (58.3, 134.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e157.6 (76.1, 200.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlbumin (g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32.3 (29.6, 35.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32.5 (30.1, 35.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32.0 (29.2, 34.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.230\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGFR (ml/min)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e86.5 (47.0, 103.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e92.8 (66.9, 106.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e73.4 (42.7, 101.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.037\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePulmonary-only infection, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18 (13.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9 (14.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9 (12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.886\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePathogen, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRAB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e107 (77.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e48 (76.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e59 (78.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.887\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRKP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20 (14.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8 (12.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12 (16.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.760\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRPA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16 (11.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9 (14.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7 (9.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.523\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePMB treatment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNebulization, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e55 (39.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25 (39.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30 (40.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment duration (days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11.0 (7.0, 14.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12.0 (9.0, 15.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.0 (7.0, 12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDaily dose (mg/kg/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.1 (1.7, 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.1 (1.8, 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.1 (1.7, 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.884\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConcomitant drugs, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTigecycline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e59 (42.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19 (30.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40 (53.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarbapenem\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22 (15.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8 (12.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14 (18.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.471\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSulbactam\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20 (14.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9 (14.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11 (14.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAmikacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e24 (17.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11 (17.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13 (17.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMinocycline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22 (15.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12 (19.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10 (13.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.497\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eData are mean (\u0026plusmn;\u0026thinsp;SD), n (%), or median (IQR). BMI\u0026thinsp;=\u0026thinsp;Body Mass Index; APACHE II\u0026thinsp;=\u0026thinsp;Acute Physiology and Chronic Health Evaluation II; SOFA\u0026thinsp;=\u0026thinsp;Sequential Organ Failure Assessment; VIS\u0026thinsp;=\u0026thinsp;Vasoactive-Inotropic Score; COPD\u0026thinsp;=\u0026thinsp;Chronic Obstructive Pulmonary Disease; MV\u0026thinsp;=\u0026thinsp;Mechanical Ventilation; CRRT\u0026thinsp;=\u0026thinsp;Continuous Renal Replacement Therapy; ECMO\u0026thinsp;=\u0026thinsp;Extracorporeal Membrane Oxygenation; GFR\u0026thinsp;=\u0026thinsp;Glomerular Filtration Rate; PCT\u0026thinsp;=\u0026thinsp;Procalcitonin; CRP\u0026thinsp;=\u0026thinsp;C-reactive protein; CRAB\u0026thinsp;=\u0026thinsp;Carbapenem resistant Acinetobacter baumannii; CRKP\u0026thinsp;=\u0026thinsp;Carbapenem-resistant Klebsiella pneumoniae; CRPA\u0026thinsp;=\u0026thinsp;Carbapenem-resistant Pseudomonas aeruginosa; PMB\u0026thinsp;=\u0026thinsp;Polymyxin B.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe enrolled patients were divided into two groups based on the ultimate clinical treatment outcomes. Comparative analysis of baseline characteristics revealed significant differences in disease severity between treatment response groups. Patients achieving clinical success presented with markedly less severe illness, as reflected in their lower median APACHE II and SOFA scores compared to the treatment failure group. Other demographic and clinical parameters showed no statistically significant differences between groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The clinical success cohort demonstrated superior outcomes across multiple endpoints: 28-day all-cause mortality was reduced, ventilator-free days at day 28 were significantly increased, and ICU mortality was lower. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical outcomes of the included patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal(n\u0026thinsp;=\u0026thinsp;138)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eClinical success(n\u0026thinsp;=\u0026thinsp;63)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eClinical failure (n\u0026thinsp;=\u0026thinsp;75)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e28-day all-cause mortality, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e63 (45.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7 (11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e56 (74.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVentilator-free days at 28 days (days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.0 (0.0, 11.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.0 (0.0, 18.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0 (0.0, 1.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIn-ICU mortality, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45 (32.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5 (7.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40 (53.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLength of stay (days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35.0 (23.2, 59.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e44.0 (32.0, 68.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e27.0 (18.0, 46.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLength of ICU stay (days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29.0 (20.0, 47.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35.0 (26.0, 53.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e23.0 (17.5, 38.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ePMB exposure and concentrations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe median daily dose of PMB among enrolled patients was 2.1 (1.7, 2.5) mg/kg, with 55 (39.9%) patients receiving nebulized PMB therapy (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The median AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e was 77.5 (55.6, 105.6) mg\u0026middot;h/L. Patients in the clinical treatment success group exhibited significantly higher levels in the plasma concentration of PMB compared to the clinical treatment failure group (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe optimal AUC\u003c/b\u003e\u003csub\u003e\u003cb\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/b\u003e\u003c/sub\u003e \u003cb\u003etarget of PMB\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe restricted cubic spline analysis revealed a nonlinear relationship between clinical treatment success rate and the AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e of PMB. Initially, treatment success rates increased with higher AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e levels, when the AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e of PMB reached a certain threshold, the degree of clinical benefit derived from further increases diminished. An AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e of PMB exceeding 77 mg\u0026middot;h/L could significantly predict clinical treatment success (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe analysis of PMB-associated AKI included 102 patients, with an overall AKI incidence rate of 34.3%. The restricted cubic spline plot also demonstrated that the incidence of AKI increased with higher the AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e of PMB levels. When the AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e of PMB exceeded 110 mg\u0026middot;h/L, both the odds ratio (OR) and its 95% confidence interval (CI) for AKI incidence were \u0026gt;\u0026thinsp;1, indicating that AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e of PMB above this threshold significantly increased the risk of AKI (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWhen the enrolled patients were stratified into three groups based on AUC cutoffs (lower: 77 mg\u0026middot;h/L; upper: 110 mg\u0026middot;h/L), we found that the 77\u0026ndash;110 mg\u0026middot;h/L group had a significantly higher clinical treatment success rate than the \u0026lt;\u0026thinsp;77 mg\u0026middot;h/L group, while its AKI incidence was markedly lower than the \u0026gt;\u0026thinsp;110 mg\u0026middot;h/L group (Figure S2).\u003c/p\u003e\u003cp\u003eWe further evaluated the clinical relevance of the 77\u0026ndash;110 mg\u0026middot;h/L AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e range in multivariable logistic regression models. The results demonstrated that compared to the reference 77\u0026ndash;110 mg\u0026middot;h/L group, AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e \u0026lt; 77 mg\u0026middot;h/L was an independent risk factor for reduced clinical treatment success (OR: 0.33, 95% CI: 0.13\u0026ndash;0.78; p\u0026thinsp;=\u0026thinsp;0.013) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). AUC\u0026thinsp;\u0026gt;\u0026thinsp;110 mg\u0026middot;h/L significantly increased AKI risk (OR: 3.24, 95% CI: 1.06\u0026ndash;10.47; p\u0026thinsp;=\u0026thinsp;0.043) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe impact of the AUC\u003csub\u003e0-24h\u003c/sub\u003e of PMB on 14-day clinical treatment success rates in patients with CRO-HAP using logistic regression model\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e = 77\u0026ndash;110 mg\u0026middot;h/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e \u0026lt; 77 mg\u0026middot;h/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.13\u0026ndash;0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e \u0026gt;110 mg\u0026middot;h/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.41\u0026ndash;3.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.746\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.97\u0026ndash;1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.822\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.25\u0026ndash;1.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.437\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.88\u0026ndash;1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.856\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSOFA at admission\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.68\u0026ndash;0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVIS\u003csub\u003e24hmax\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.98\u0026ndash;1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.791\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eAUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e = Area under the 24-hour drug concentration-time curve of PMB; BMI\u0026thinsp;=\u0026thinsp;Body Mass Index; SOFA\u0026thinsp;=\u0026thinsp;Sequential Organ Failure Assessment; VIS\u0026thinsp;=\u0026thinsp;Vasoactive-Inotropic Score.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe impact of the AUC\u003csub\u003e0-24h\u003c/sub\u003e of PMB on AKI incidence in patients with CRO-HAP using logistic regression model\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e = 77\u0026ndash;110 mg\u0026middot;h/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e \u0026lt; 77 mg\u0026middot;h/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.37\u0026ndash;3.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.826\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e \u0026gt;110 mg\u0026middot;h/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.06\u0026ndash;10.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.043\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.97\u0026ndash;1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.814\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.18\u0026ndash;2.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.458\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSOFA at admission\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.98\u0026ndash;1.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.093\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVIS\u003csub\u003e24hmax\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.97\u0026ndash;1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.407\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGFR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.97\u0026ndash;1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.214\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eAUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e = Area under the 24-hour drug concentration-time curve of PMB; SOFA\u0026thinsp;=\u0026thinsp;Sequential Organ Failure Assessment; VIS\u0026thinsp;=\u0026thinsp;Vasoactive-Inotropic Score; GFR\u0026thinsp;=\u0026thinsp;Glomerular Filtration Rate.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSensitivity Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn sensitivity analyses restricting the sample to male patients, those with normal BMI (18.5\u0026ndash;28 kg/m\u0026sup2;), Septic shock cases, or pulmonary infections only, the association between AUC 77\u0026ndash;110 mg\u0026middot;h/L and higher clinical treatment success remained statistically significant when compared to the AUC\u0026thinsp;\u0026lt;\u0026thinsp;77 mg\u0026middot;h/L group. Furthermore, in the normal BMI subgroup (18.5\u0026ndash;28 kg/m\u0026sup2;), the 77\u0026ndash;110 mg\u0026middot;h/L AUC range remained significantly associated with lower AKI risk compared to the \u0026gt;\u0026thinsp;110 mg\u0026middot;h/L group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study primarily identified an optimal PMB AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e range of 77\u0026ndash;110 mg\u0026middot;h/L for carbapenem-resistant HAP patients, which maximized clinical treatment success while minimizing AKI incidence. This therapeutic window was subsequently validated through adjusted multivariable regression analysis.\u003c/p\u003e\u003cp\u003eThe international consensus guidelines on the optimal use of polymyxins recommend the ideal AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e target range is suggested to be between 50 mg\u0026middot;h/L and 100 mg\u0026middot;h/L, and a maintenance dose of PMB is 1.25\u0026ndash;1.5 mg/kg every 12 hours(12). Monte Carlo simulations have determined that PMB dosing regimens of 2.5 mg/kg/day and 3.0 mg/kg/day can achieve steady-state AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e values of at least 44.3 mg\u0026middot;h/L and 53.1 mg\u0026middot;h/L, respectively, in 90% of patients(20). In our study, the median PMB maintenance intravenous daily dose was 2.1 (1.7, 2.5) mg/kg/day, which is lower than the guideline-recommended dose. This reduction in dosage may reflect the more severe baseline conditions of our patients, with clinicians adjusting maintenance doses to mitigate the risk of nephrotoxicity. All patients in our cohort underwent therapeutic drug monitoring (TDM), with \u0026gt;\u0026thinsp;80% achieving PMB AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e levels exceeding the international guideline threshold of 50 mg\u0026middot;h/L, effectively addressing potential underdosing concerns.\u003c/p\u003e\u003cp\u003ePrevious studies have confirmed that The AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e of PMB is associated with both patient outcomes and the occurrence of AKI(19, 21). The 2019 international consensus guidelines for polymyxins(12) recommend targeting The AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e of PMB within the range of 50 mg\u0026middot;h/L to 100 mg\u0026middot;h/L. The lower target limit of 50 mg\u0026middot;h/L was identified by Landersdorfer et al. in a murine thigh infection model of Klebsiella pneumoniae as a target that could significantly reduce bacterial burden(13). However, this target demonstrated weaker bactericidal effects in a murine lung infection model. In a real-world study on PMB treatment for CRO pneumonia patients, Tang et al. determined through ROC curve analysis that the optimal PK/PD index of PMB for predicting clinical treatment success was an AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e cutoff of 66.9 mg\u0026middot;h/L(15), exceeding the guideline-recommended lower target of 50 mg\u0026middot;h/L. Yu et al. reported in a prospective, observational multicenter study that PMB therapy for intra-abdominal infections demonstrated significantly lower 14-day mortality when the AUC exceeded 76 mg\u0026middot;h/L(22). The correlation between AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e and clinical outcomes may sometimes be obscured by the complex clinical characteristics of patients, such as bacterial resistance(23). Our findings further validate this observation, demonstrating a significant association between the AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e of PMB and clinical efficacy in carbapenem-resistant HAP patients, but with a higher optimal lower threshold, and an even furth.\u003c/p\u003e\u003cp\u003eThe incidence of AKI in this study is consistent with previous research data(24\u0026ndash;26). A meta-analysis on PMB-associated AKI found that an AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e exceeding 100 mg\u0026middot;h/L led to drug-induced nephrotoxicity in over 40% of patients(14). Yang et al. confirmed that an AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e exceeding 100 mg\u0026middot;h/L is a significant risk factor for drug-induced nephrotoxicity(19). In our study, the PMB AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e threshold associated with AKI incidence was 110 mg\u0026middot;h/L, aligning closely with findings from prior studies and the upper limit recommended by international guidelines for PMB use.\u003c/p\u003e\u003cp\u003eThis study has several limitations. First, as a single-center, retrospective study with a relatively small sample size, the accuracy and generalizability of the results are limited. Second, due to missing data inherent in retrospective studies, we were unable to investigate the impact of other pharmacokinetic parameters of PMB on clinical outcomes. Third, we did not analyze variations of the PMB AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e in different infection sites, causative pathogens, or combination therapy regimens. These factors may hold greater clinical relevance for guiding treatment but were constrained by our limited sample size. Fourth, in discussing the incidence of AKI, we excluded patients who were undergoing CRRT at enrollment to avoid confounding in the evaluation of AKI incidence. This exclusion may result in differences between the target populations for the upper and lower limits of the AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e, necessitating cautious interpretation of the recommended AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e target range.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, this study confirms that the AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e of PMB is closely associated with both 14-day clinical treatment success rates and the incidence of AKI in patients with carbapenem-resistant HAP, with an optimal range from 77 to 110 mg\u0026middot;h/L.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAUC\u003csub\u003e0-24h\u003c/sub\u003e\u0026nbsp; \u0026nbsp;Area under the concentration-time curve across 24 hours\u003c/p\u003e\n\u003cp\u003ePMB \u0026nbsp; Polymyxin B\u003c/p\u003e\n\u003cp\u003eCRO \u0026nbsp; Carbapenem-resistant organism\u003c/p\u003e\n\u003cp\u003eHAP Hospital-acquired pneumonia\u003c/p\u003e\n\u003cp\u003eTDM \u0026nbsp; therapeutic drug monitoring\u003c/p\u003e\n\u003cp\u003eMIC \u0026nbsp; Minimum inhibitory concentration\u003c/p\u003e\n\u003cp\u003eKDIGO \u0026nbsp; Kidney disease improving global outcomes\u003c/p\u003e\n\u003cp\u003eAKI \u0026nbsp; Acute kidney injury\u003c/p\u003e\n\u003cp\u003ePK \u0026nbsp; Pharmacokinetics\u003c/p\u003e\n\u003cp\u003ePD \u0026nbsp; Pharmacodynamics\u003c/p\u003e\n\u003cp\u003eAPACHE II \u0026nbsp; Acute physiology and chronic health evaluation\u003c/p\u003e\n\u003cp\u003eSOFA \u0026nbsp; \u0026nbsp;Sequential organ failure assessment\u003c/p\u003e\n\u003cp\u003eMV Mechanical ventilation\u003c/p\u003e\n\u003cp\u003eECMO \u0026nbsp; Extracorporeal membrane oxygenation\u003c/p\u003e\n\u003cp\u003eCRRT \u0026nbsp; Continuous renal replacement therapy\u003c/p\u003e\n\u003cp\u003eC\u003csub\u003emin\u003c/sub\u003e\u0026nbsp; \u0026nbsp;Trough concentration at steady state\u003c/p\u003e\n\u003cp\u003eC\u003csub\u003emax\u003c/sub\u003e\u0026nbsp; \u0026nbsp;Peak concentration at steady state\u003c/p\u003e\n\u003cp\u003eC\u003csub\u003e6h\u003c/sub\u003e\u0026nbsp; \u0026nbsp;6 hours concentration at steady state\u003c/p\u003e\n\u003cp\u003eVIS\u003csub\u003e24hmax\u003c/sub\u003e\u0026nbsp; \u0026nbsp; Maximum Vasoactive-Inotropic Score within 24 hours of enrollment\u003c/p\u003e\n\u003cp\u003eGFR \u0026nbsp; estimated glomerular filtration rate\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePCT \u0026nbsp; Procalcitonin\u003c/p\u003e\n\u003cp\u003eCRP \u0026nbsp; C-reactive protein\u003c/p\u003e\n\u003cp\u003eCRPA \u0026nbsp; Carbapenem-resistant Pseudomonas aeruginosa\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCRAB \u0026nbsp; Carbapenem-resistant Acinetobacter baumannii\u003c/p\u003e\n\u003cp\u003eCRKP \u0026nbsp; \u0026nbsp;Carbapenem-resistant klebsiella pneumonia\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThis study was approved by\u0026nbsp;the Ethics Committee of Zhongda Hospital, Southeast University\u0026nbsp;(2023ZDSYLL296-P01) and\u0026nbsp;waived informed consent due to its retrospective nature.\u0026nbsp;All procedures were performed in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author, [Y.H.], upon reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eAll authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eSupported by the National Key Research and Development Program of China (2022YFC2304600), National Natural Science Foundation of China (82272235 and 81971812), Jiangsu Province Key Research and Development Program (Social Development) Special Project (BE2021734).\u003c/p\u003e\n\u003cp\u003eContributions\u003c/p\u003e\n\u003cp\u003eM.X., X.X. and Y.H. conceived the study. L.H., J.H., Q.P., M.B. and S.Z. collected data for the work. M.X., X.X., H.C., W.H., H.W., and S.Y. performed data analysis. M.X., X.X., W.H., J.X., and Y.H. prepared the first draft of the manuscript. All authors were responsible for data interpretation, revised the manuscript critically, and approved the version submitted for publication.\u003c/p\u003e\n\u003cp\u003eCorresponding author\u003c/p\u003e\n\u003cp\u003eCorrespondence to Yingzi Huang.\u003c/p\u003e\n\u003cp\u003eAuthor information\u003c/p\u003e\n\u003cp\u003eAuthor notes\u003c/p\u003e\n\u003cp\u003eMengru Xiong and Xiaoting Xu have contributed equally to the work.\u003c/p\u003e\n\u003cp\u003eAuthors and Affiliations\u003c/p\u003e\n\u003cp\u003e1. Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing 210009, China\u003c/p\u003e\n\u003cp\u003eMengru Xiong1, Xiaoting Xu, Qingyun Peng, Mingze Bi, Shijia Zhong, Wenhan Hu, Haofei Wang, Shuhe Yang, Jianfeng Xie, Yingzi Huang\u003c/p\u003e\n\u003cp\u003e2. Department of Pharmacy, Zhongda Hospital, Southeast University, School of Medicine, Southeast University, Nanjing 210009, China\u003c/p\u003e\n\u003cp\u003eLinlin Hu, Jie He\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors thank all the subjects for their participation in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCassini A, H\u0026ouml;gberg LD, Plachouras D, Quattrocchi A, Hoxha A, Simonsen GS, et al.Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysis. Lancet Infect Dis. 2019;19(1):56\u0026ndash;66.\u003c/li\u003e\n\u003cli\u003eSu CH, Chien LJ, Fang CT, Chang SC\u003cstrong\u003e. \u003c/strong\u003eExcess mortality and long-term disability from healthcare-associated carbapenem-resistant Acinetobacter baumannii infections: A nationwide population-based matched cohort study. PLoS One. 2023;18(9):e0291059.\u003c/li\u003e\n\u003cli\u003eLemos EV, de la Hoz FP, Einarson TR, McGhan WF, Quevedo E, Casta\u0026ntilde;eda C, et al.Carbapenem resistance and mortality in patients with Acinetobacter baumannii infection: systematic review and meta-analysis. Clin Microbiol Infect. 2014;20(5):416\u0026ndash;23.\u003c/li\u003e\n\u003cli\u003eBassetti M, Kollef MH, Poulakou G\u003cstrong\u003e. \u003c/strong\u003ePrinciples of antimicrobial stewardship for bacterial and fungal infections in ICU. Intensive Care Med. 2017;43(12):1894\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eTacconelli E, Carrara E, Savoldi A, Harbarth S, Mendelson M, Monnet DL, et al.Discovery, research, and development of new antibiotics: the WHO priority list of antibiotic-resistant bacteria and tuberculosis. Lancet Infect Dis. 2018;18(3):318\u0026ndash;27.\u003c/li\u003e\n\u003cli\u003eNang SC, Azad MAK, Velkov T, Zhou QT, Li J\u003cstrong\u003e. \u003c/strong\u003eRescuing the Last-Line Polymyxins: Achievements and Challenges. Pharmacol Rev. 2021;73(2):679\u0026ndash;728.\u003c/li\u003e\n\u003cli\u003eTorres A, Niederman MS, Chastre J, Ewig S, Fernandez-Vandellos P, Hanberger H, et al.International ERS/ESICM/ESCMID/ALAT guidelines for the management of hospital-acquired pneumonia and ventilator-associated pneumonia: Guidelines for the management of hospital-acquired pneumonia (HAP)/ventilator-associated pneumonia (VAP) of the European Respiratory Society (ERS), European Society of Intensive Care Medicine (ESICM), European Society of Clinical Microbiology and Infectious Diseases (ESCMID) and Asociaci\u0026oacute;n Latinoamericana del T\u0026oacute;rax (ALAT). Eur Respir J. 2017;50(3).\u003c/li\u003e\n\u003cli\u003eGales AC, Jones RN, Sader HS\u003cstrong\u003e. \u003c/strong\u003eContemporary activity of colistin and polymyxin B against a worldwide collection of Gram-negative pathogens: results from the SENTRY Antimicrobial Surveillance Program (2006-09). J Antimicrob Chemother. 2011;66(9):2070\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eZhang J, Hu Y, Shen X, Zhu X, Chen J, Dai H\u003cstrong\u003e. \u003c/strong\u003eRisk factors for nephrotoxicity associated with polymyxin B therapy in Chinese patients. Int J Clin Pharm. 2021;43(4):1109\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eCai Y, Leck H, Tan RW, Teo JQ, Lim TP, Lee W, et al.Clinical Experience with High-Dose Polymyxin B against Carbapenem-Resistant Gram-Negative Bacterial Infections-A Cohort Study. Antibiotics (Basel). 2020;9(8).\u003c/li\u003e\n\u003cli\u003eLiu X, Huang C, Bergen PJ, Li J, Zhang J, Chen Y, et al.Chinese consensus guidelines for therapeutic drug monitoring of polymyxin B, endorsed by the Infection and Chemotherapy Committee of the Shanghai Medical Association and the Therapeutic Drug Monitoring Committee of the Chinese Pharmacological Society. J Zhejiang Univ Sci B. 2023;24(2):130\u0026ndash;42.\u003c/li\u003e\n\u003cli\u003eTsuji BT, Pogue JM, Zavascki AP, Paul M, Daikos GL, Forrest A, et al.International Consensus Guidelines for the Optimal Use of the Polymyxins: Endorsed by the American College of Clinical Pharmacy (ACCP), European Society of Clinical Microbiology and Infectious Diseases (ESCMID), Infectious Diseases Society of America (IDSA), International Society for Anti-infective Pharmacology (ISAP), Society of Critical Care Medicine (SCCM), and Society of Infectious Diseases Pharmacists (SIDP). Pharmacotherapy. 2019;39(1):10\u0026ndash;39.\u003c/li\u003e\n\u003cli\u003eLandersdorfer CB, Wang J, Wirth V, Chen K, Kaye KS, Tsuji BT, et al.Pharmacokinetics/pharmacodynamics of systemically administered polymyxin B against Klebsiella pneumoniae in mouse thigh and lung infection models. J Antimicrob Chemother. 2018;73(2):462\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eLakota EA, Landersdorfer CB, Nation RL, Li J, Kaye KS, Rao GG, et al.Personalizing Polymyxin B Dosing Using an Adaptive Feedback Control Algorithm. Antimicrob Agents Chemother. 2018;62(7).\u003c/li\u003e\n\u003cli\u003eTang T, Li Y, Xu P, Zhong Y, Yang M, Ma W, et al.Optimization of polymyxin B regimens for the treatment of carbapenem-resistant organism nosocomial pneumonia: a real-world prospective study. Crit Care. 2023;27(1):164.\u003c/li\u003e\n\u003cli\u003eSatlin MJ, Lewis JS, Weinstein MP, Patel J, Humphries RM, Kahlmeter G, et al.Clinical and Laboratory Standards Institute and European Committee on Antimicrobial Susceptibility Testing Position Statements on Polymyxin B and Colistin Clinical Breakpoints. Clin Infect Dis. 2020;71(9):e523\u0026ndash;e9.\u003c/li\u003e\n\u003cli\u003eGiske CG, Turnidge J, Cant\u0026oacute;n R, Kahlmeter G\u003cstrong\u003e. \u003c/strong\u003eUpdate from the European Committee on Antimicrobial Susceptibility Testing (EUCAST). J Clin Microbiol. 2022;60(3):e0027621.\u003c/li\u003e\n\u003cli\u003ePaul M, Daikos GL, Durante-Mangoni E, Yahav D, Carmeli Y, Benattar YD, et al.Colistin alone versus colistin plus meropenem for treatment of severe infections caused by carbapenem-resistant Gram-negative bacteria: an open-label, randomised controlled trial. Lancet Infect Dis. 2018;18(4):391\u0026ndash;400.\u003c/li\u003e\n\u003cli\u003eYang J, Liu S, Lu J, Sun T, Wang P, Zhang X\u003cstrong\u003e. \u003c/strong\u003eAn area under the concentration-time curve threshold as a predictor of efficacy and nephrotoxicity for individualizing polymyxin B dosing in patients with carbapenem-resistant gram-negative bacteria. Crit Care. 2022;26(1):320.\u003c/li\u003e\n\u003cli\u003eSandri AM, Landersdorfer CB, Jacob J, Boniatti MM, Dalarosa MG, Falci DR, et al.Pharmacokinetics of polymyxin B in patients on continuous venovenous haemodialysis. J Antimicrob Chemother. 2013;68(3):674\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eLiu S, Wu Y, Qi S, Shao H, Feng M, Xing L, et al.Polymyxin B therapy based on therapeutic drug monitoring in carbapenem-resistant organisms sepsis: the PMB-CROS randomized clinical trial. Crit Care. 2023;27(1):232.\u003c/li\u003e\n\u003cli\u003eYu Z, Hu H, Liu X, Liu J, Yu L, Wei A, et al.Clinical outcomes and pharmacokinetics/pharmacodynamics of intravenous polymyxin B treatment for various site carbapenem-resistant gram-negative bacterial infections: a prospective observational multicenter study. Antimicrob Agents Chemother. 2025;69(4):e0185924.\u003c/li\u003e\n\u003cli\u003eWang P, Liu S, Qi G, Xu M, Sun T, Yang J\u003cstrong\u003e. \u003c/strong\u003eEvaluation of polymyxin B AUC/MIC ratio for dose optimization in patients with carbapenem-resistant Klebsiella pneumoniae infection. Front Microbiol. 2023;14:1226981.\u003c/li\u003e\n\u003cli\u003eWang P, Zhang Q, Zhu Z, Pei H, Feng M, Sun T, et al.Comparing the Population Pharmacokinetics of and Acute Kidney Injury Due to Polymyxin B in Chinese Patients with or without Renal Insufficiency. Antimicrob Agents Chemother. 2021;65(2).\u003c/li\u003e\n\u003cli\u003eChang K, Wang H, Zhao J, Yang X, Wu B, Sun W, et al.Risk factors for polymyxin B-associated acute kidney injury. Int J Infect Dis. 2022;117:37\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eRigatto MH, Behle TF, Falci DR, Freitas T, Lopes NT, Nunes M, et al.Risk factors for acute kidney injury (AKI) in patients treated with polymyxin B and influence of AKI on mortality: a multicentre prospective cohort study. J Antimicrob Chemother. 2015;70(5):1552\u0026ndash;7.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Therapeutic drug monitoring, Carbapenem-resistant organisms, Hospital acquired pneumonia, Pharmacokinetics/pharmacodynamics, Nephrotoxicity, Intensive care","lastPublishedDoi":"10.21203/rs.3.rs-7249423/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7249423/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThe area under the concentration-time curve over 24 hours (AUC\u003csub\u003e0-24h\u003c/sub\u003e) is a critical pharmacokinetic parameter influencing the clinical efficacy of polymyxin B (PMB). However, due to substantial population heterogeneity among critically ill patients, the correlation between the AUC\u003csub\u003e0-24h\u003c/sub\u003e of PMB and clinical treatment success, as well as the optimal therapeutic threshold remains inadequately elucidated.\u003c/p\u003e\u003ch2\u003eObjectives\u003c/h2\u003e\u003cp\u003eThis study aimed to investigate the relationship between PMB AUC\u003csub\u003e0-24h\u003c/sub\u003e and clinical efficacy in patients with carbapenem-resistant hospital-acquired pneumonia (HAP), and to identify the optimal therapeutic AUC\u003csub\u003e0-24h\u003c/sub\u003e range for PMB.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe conducted a retrospective observational study of carbapenem-resistant HAP patients receiving intravenous PMB with therapeutic drug monitoring (TDM). The plasma concentrations of PMB were determined using validated ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC\u0026ndash;MS/MS). The primary outcome was 14-day clinical treatment success rates, the secondary outcomes included the incidence of AKI. Logistic regression analyses and restricted cubic spline analyses were employed to investigate the optimal therapeutic threshold of PMB in carbapenem-resistant HAP patients.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e\u003cp\u003eA total of 138 patients were ultimately included in the final analysis, with the median age of 68 years, and 110(79.7%) patients were male. Clinical success was achieved in 63(45.7%) patients. The pathogen of infection in 77% of patients was Carbapenem-Resistant Acinetobacter baumannii (CRAB), and all pathogens isolated from the included patients were sensitive to PMB, with a minimum inhibitory concentration (MIC)\u0026thinsp;\u0026le;\u0026thinsp;2mg/L. The median AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e of PMB was 77.5 (55.6, 105.6) mg\u0026middot;h/L. In enrolled patients, an AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e \u0026gt;77 mg\u0026middot;h/L enabled to predict the clinical treatment success, while AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e \u0026gt;110 mg\u0026middot;h/L enabled to predict the AKI incidence. In the multivariate logistic regression model, AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e \u0026lt; 77 mg\u0026middot;h/L was an independent risk factor for reduced clinical treatment success (OR: 0.33, 95% CI: 0.13\u0026ndash;0.78; p\u0026thinsp;=\u0026thinsp;0.013). AUC\u0026thinsp;\u0026gt;\u0026thinsp;110 mg\u0026middot;h/L significantly increased AKI risk (OR: 0.33, 95% CI: 1.06\u0026ndash;10.47; p\u0026thinsp;=\u0026thinsp;0.043).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThis study confirms that the AUC\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;24h\u003c/sub\u003e of PMB is closely associated with both 14-day clinical treatment success rates and the incidence of AKI in patients with carbapenem-resistant HAP, with an optimal range from 77 to 110 mg\u0026middot;h/L.\u003c/p\u003e","manuscriptTitle":"Optimizing polymyxin B exposure in carbapenem-resistant organism Hospital-Acquired Pneumonia: a retrospective observational study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-11 11:01:57","doi":"10.21203/rs.3.rs-7249423/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-09-04T06:28:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-28T06:21:51+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-06T07:29:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-06T03:55:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-08-06T03:52:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ec7cf04b-b043-4ec2-a6e3-02300137e988","owner":[],"postedDate":"September 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-11T11:01:57+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-11 11:01:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7249423","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7249423","identity":"rs-7249423","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}