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Introduction: Methicillin-resistant Staphylococcus aureus (MRSA) infections are a serious threat to public health. Vancomycin (VAN) remains the primary treatment for these infections, and achieving the recommended area under the curve (AUC) target has been linked to improved clinical outcomes. The current VAN therapeutic monitoring guidelines recommend a loading dose (LD) of 20–35 mg/kg to rapidly attain targeted VAN exposures within 24 h of therapy. However, there is a paucity of data describing the impact of VAN LD on day 1 area under the curve (AUC0–24). This study aims to employ pharmacokinetic (PK) equations to calculate and describe the AUC0–24 following a VAN LD of 20 mg/kg. Methods: This was a retrospective study of adult patients who were loaded with VAN 20 mg/kg, received ≥ 48 h of treatment, and had two consecutive serum VAN levels collected within 24 h. Linear, non-trapezoidal PK equations and two post-infusion VAN levels were used to calculate AUC0–24. Therapeutic AUC0–24 was defined as 400–600 mg/l*h. Results: Among 123 included patients, the median age was 46 years (IQR 36, 62), 54% (67/123) of the patients had a body mass index (BMI) ≥ 30 kg/m2 and 27% (33/123) were admitted to the intensive care unit (ICU). Following a LD of 20 mg/kg, 50% (61/123) of the patients met the therapeutic AUC0–24, while 22% (27/123) of the patients were subtherapeutic, and 28% (35/123) were supratherapeutic. Compared with patients who achieved therapeutic AUC0–24, patients with subtherapeutic AUC0–24 were more likely to be younger (44 vs. 37 years old) and have a BMI ≥ 30 kg/m2 (67 vs. 52%). In contrast, patients with supratherapeutic AUC0–24 were more likely to be older (64 vs. 44 years old) and to have chronic kidney disease diagnosis (23 vs. 7%) when compared to patients who achieved a therapeutic AUC0–24. Conclusions: Only 50% of patients achieve the target AUC0-24 following a VAN 20 mg/kg LD, with younger, heavier patients underexposed and older patients with renal impairment overexposed, suggesting that different dosing strategies are needed for these populations. [ABSTRACT FROM AUTHOR]

Background: Guidelines support area-under-the-curve (AUC) monitoring for vancomycin dosing which may lower overall doses and reduce acute kidney injury (AKI). Objective: The aim of this study was to compare incidence of AKI across 3 vancomycin dosing modalities: AUC-targeted Bayesian pharmacokinetic software, AUC-targeted empiric dosing nomogram, and trough-guided dosing using clinical pharmacists' judgment. Methods: This retrospective study included adult patients with a pharmacy dosing consult who received ≥1 dose of vancomycin and ≥1 serum vancomycin level documented between January 1, 2018, and December 31, 2019. Patients with baseline serum creatinine ≥2 mg/dL, weight ≥100 kg, receiving renal replacement therapy, AKI prior to vancomycin therapy, or vancomycin ordered only for surgical prophylaxis were excluded. The primary analysis was incidence of AKI adjusted for baseline serum creatinine, age, and intensive care unit admission. A secondary outcome was adjusted incidence of an abnormal trough value (<10 or >20 μg/mL). Results: The study included 3459 encounters. Incidence of AKI was 21% for Bayesian software (n = 659), 22% for the nomogram (n = 303), and 32% for trough-guided dosing (n = 2497). Compared with trough-guided dosing, incidence of AKI was lower in the Bayesian (adjusted odds ratio [OR] = 0.72, 95% confidence interval [CI]: 0.58-0.89) and the nomogram (adjusted OR = 0.71, 95% CI: 0.53-0.95) groups. Compared with trough-guided dosing, abnormal trough values were less common in the Bayesian group (adjusted OR = 0.83, 95% CI: 0.69-0.98). Conclusion and Relevance: Study results suggest that use of AUC-guided Bayesian software reduces the incidence of AKI and abnormal trough values compared with trough-guided dosing. [ABSTRACT FROM AUTHOR]

Beta‐lactam therapeutic drug monitoring (TDM) can improve precision dosing and clinical outcomes in critically ill patients, but has not been implemented widely in the United States. Mayo Clinic recently implemented a beta‐lactam TDM program. This single‐center experience forms the basis of the manuscript which outlines practical considerations involved with beta‐lactam TDM implementation, including the pharmacist's role as a leader. Our implementation effort focused on three primary domains. First, we aimed to ensure a supportive organizational infrastructure. Early leadership engagement by the pharmacist‐led core team facilitated advocacy for the clinical need, allocation of resources, and assay development. Second, core clinical workflows were developed that addressed the preferred patient population for use, desirable pharmacokinetic and pharmacodynamic targets, and the preferred sampling strategy. Clinical tools to guide pharmacists in interpreting the results (e.g., pharmacokinetics calculator) and documenting decisions were developed. Third, stakeholders were offered repeated exposure to evidence and expertise to facilitate understanding and application of the new practice. This act of 'individual internalization' seems to be uniquely important to beta‐lactam TDM implementation compared with the implementation of other antimicrobial TDM programs. Educational strategies and supportive materials that were developed were focused on providing substantive and varied information tailored to the stakeholders' role in the process. For pharmacists, this included both clinical and operational considerations. A continuous improvement plan to support management of the process was instituted to address necessary updates and changes that inevitably emerged. In summary, the described approach to implementation of a pharmacist‐led beta‐lactam TDM program could be used as a roadmap to aid other institutions that aim to develop such a program. [ABSTRACT FROM AUTHOR]

Background: Free online adaptive vancomycin dosing calculators are available to estimate area under the concentration-time curve (AUC), but the accuracy of predicting vancomycin AUC using these calculators compared with using a 2-point pharmacokinetic approach has not been described. Objective: To evaluate the accuracy of calculator-predicted AUC (cpAUC) using 4 free online calculators compared with reference AUC (rAUC), and to assess pharmacists' impressions of the ease of use. Methods: Vancomycin AUC was estimated using (1) the reference method via the Sawchuk-Zaske method and linear-logarithmic trapezoidal rule using 2 steady-state postdistributional vancomycin serum concentrations and (2) 4 free online vancomycin dosing calculators including ClinCalc, VancoPK, TDMx, and DMC. Accuracy was calculated by dividing cpAUC by rAUC. Ease of cpAUC estimation was determined by using a 10-point Likert scale. Results: All 4 calculators had a median cpAUC accuracy ranging from 89% to 110%. Concordance between cpAUC and rAUC determinations of AUC <400 and > 600 mg·h/L occurred 63.3% to 71.4% and 74.5% to 78.6% of the time, respectively. Pharmacist investigators agreed that ClinCalc and VancoPK calculators were easiest to use. Conclusion and Relevance: cpAUC accuracy varied among the 4 calculators, but all consistently identified patients with an rAUC <400 mg·h/L and an rAUC > 600 mg·h/L at comparable frequencies. All 4 calculators demonstrated some imprecision based on their wide 95% CIs and potential inaccuracies in predicting an rAUC <400 mg·h/L or an rAUC > 600 mg·h/L. Clin Calc and VancoPK were most user friendly based on our pharmacists' impressions. [ABSTRACT FROM AUTHOR]

The most recent consensus guidelines for dosing and monitoring vancomycin recommended the use of area‐under‐the‐curve with Bayesian estimation for therapeutic monitoring. As this is a modern concept in the practice of clinical pharmacy, the main objective of this review is to introduce the fundamentals of Bayesian estimation and its mathematical application as it relates to vancomycin therapeutic drug monitoring. In addition, we aim to identify pharmacokinetic (PK) software programs that incorporate Bayesian estimation for vancomycin dosing and to describe the PK models utilized in those software programs for the adult population. Twelve software programs that utilize Bayesian estimation were identified, which included: Adult and Pediatric Kinetics, Best Dose, ClinCalc, DoseMeRx, ID‐ODS, InsightRx, MwPharm++, NextDose, PrecisePK, TDMx, Tucuxi, and VancoCalc. The software programs varied in the population PK models used as the Bayesian a priori. With the presence of various vancomycin Bayesian software programs, it is important to choose those that utilize PK models reflective of the specific patient population. [ABSTRACT FROM AUTHOR]

Introduction: The latest vancomycin therapeutic drug monitoring guidelines for serious MRSA infections have made a pivotal change in dosing, switching from targeting trough levels to AUC dosing. Because of these new recommendations, antimicrobial stewardship programs across the country are tasked with implementing AUC based dosing. Objectives: To assess plans for institutional adoption of vancomycin AUC dosing programs and perceptions of currently used programs in hospitals across the US. Methods: An electronic survey was distributed to members of the American College of Clinical Pharmacy IDprn Listserv and American Society of Health-System Pharmacists between May and June 2020 to assess current institutional vancomycin dosing. Institutional program use and multiple software user parameters were analyzed using descriptive statistics. Results: Two hundred two pharmacists responded to the survey with the majority practicing in institutions with 251-500 beds. Most respondents have yet to implement AUC dosing (142/202, 70.3%) with many of them planning to do so in the next year (81/142, 57.0%). Of those that already implemented AUC dosing programs, purchased Bayesian software (23/60, 38.3%) and homemade software (21/60, 35.0%) were the 2 methods most frequently utilized. Purchased Bayesian software users were more likely to recommend their software to other institutions and ranked user friendliness higher compared to non-purchased software. Conclusion: Most respondents have not made the switch to vancomycin AUC dosing, but there is a growing interest with many institutions looking to adopt a program within the next year. [ABSTRACT FROM AUTHOR]

Several guidelines advise to monitor therapeutic LMWH therapy with peak anti-Xa concentrations in renal insufficiency with subsequent dose adjustments. A better understanding of the clinical association between peak anti-Xa concentrations and clinical outcomes is mandatory, because misunderstanding this association could lead to erroneous, and potentially even harmful, LMWH dose adjustments We reviewed the evidence of the widely applied therapeutic window for anti-Xa peak concentrations and report on the evidence for pharmacokinetic dose reduction in renal insufficiency, limitations of peak and trough anti-Xa concentration monitoring. The added value of peak anti-Xa monitoring in patients with renal insufficiency, receiving a dose reduced for pharmacokinetic changes, is not supported by data. Enoxaparin and nadroparin should be adjusted to 50–65% and 75–85% of the original dose for patients with a creatinine clearance (CrCL) of <30 ml/min and 30–60 ml/min, respectively. Tinzaparin should be adjusted to around 50% of the original dose for patients with a CrCL of <30 ml/min. In case anti-Xa monitoring is applied, trough concentration anti-Xa monitoring is preferred over peak monitoring, aiming at a maximum concentration of 0.4 IU/mL for once-daily dosed tinzaparin and 0.5 IU/mL for twice-daily dosed enoxaparin and nadroparin. [ABSTRACT FROM AUTHOR]

Background: New guidance recommends area under the curve/minimum inhibitory concentration (AUC/MIC) instead of trough-based monitoring for vancomycin therapy. While this transition has demonstrated improved safety and efficacy in large, tertiary centers, this has not been assessed in the primary hospital setting. Objective: The primary objectives were to evaluate the efficacy and safety of AUC/MIC monitoring in inpatient veterans treated with intravenous vancomycin for ≥72 hours compared to a historical cohort of trough-based monitoring. Methods: This was a retrospective, quasi-experimental study over 2 five-month study periods. Efficacy was evaluated by comparing clinical failure rates as defined by a persistent fever, clinical deterioration, or escalation of gram-positive therapy. Safety was determined by the incidence of acute kidney injury (AKI) defined by an acute increase in serum creatinine ≥0.3 mg/dL over 48 hours. Results: 25 patients met the criteria in the before group and 19 in the after group. Efficacy was equivalent between groups; no patients exhibited clinical failure of vancomycin therapy. In the before group, 2 patients (8%) met defined criteria for AKI, while none in the after group experienced AKI (P = 0.21). Total vancomycin exposure was similar between groups (P = 0.56). Conclusion: AUC-based monitoring was equally efficacious as trough-based monitoring with similarly low rates of AKI. [ABSTRACT FROM AUTHOR]

The recently released revised vancomycin consensus guideline endorsed area under the concentration‐time curve (AUC) guided monitoring. Means to AUC‐guided monitoring include pharmacokinetic (PK) equations and Bayesian software programs, with the latter approach being preferable. We aimed to evaluate the predictive performance of these two methods when monitoring using troughs or peaks and troughs at varying single or mixed dosing intervals (DIs), and evaluate the significance of satisfying underlying assumptions of steady‐state and model transferability. Methods included developing a vancomycin population PK model and conducting model‐informed precision dosing clinical trial simulations. A one‐compartment PK model with linear elimination, exponential between‐subject variability, and mixed (additive and proportional) residual error model resulted in the best model fit. Conducted simulations demonstrated that Bayesian‐guided AUC can, potentially, outperform that of equation‐based AUC predictions depending on the quality of model diagnostics and met assumptions. Ideally, Bayesian‐guided AUC predictive performance using a trough from the first DI was equivalent to that of PK equations using two measurements (peak and trough) from the fifth DI. Model transferability diagnostics can guide the selection of Bayesian priors but are not strong indicators of predictive performance. Mixed versus single fourth and/or fifth DI sampling seems indifferent. This study illustrated cases associated with the most reliable AUC predictions and showed that only proper Bayesian‐guided monitoring is always faster and more reliable than equations‐guided monitoring in pre‐steady‐state DIs in the absence of a loading dose. This supports rapid Bayesian monitoring using data as sparse and early as a trough at the first DI. [ABSTRACT FROM AUTHOR]

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Background It is unclear which vancomycin area under the curve (AUC) values are most associated with risk for acute kidney injury (AKI). Methods This retrospective cohort study was undertaken to determine if vancomycin AUC >550 is associated with a higher rate of AKI than an AUC <550. Patients treated with vancomycin for at least 4 days at the VA St. Louis Health Care System from 1/1/2016 to 9/31/2018 were included. The primary outcome was AKI (defined as an increase in serum creatinine by 0.3 mg/dL or 50% from baseline). Secondary outcomes included length of stay, readmission in 30 days, and mortality in 30 days. A bivariate analysis was used to determine other potential factors affecting AKI rate, with significant variables (P  < .2) to be included in the multivariate logistic regression analysis to determine independent risk for AKI. Results Two hundred patients were included in the analysis; 100 patients with an AUC ≥550 and 100 with an AUC <550. Only mean vancomycin dose (1722.50 mg vs 2361.25 mg; P  < .05), mean AUC (465.88 vs 696.45; P  < .05), and peak SCr (1.22 mg/dL vs 1.48 mg/dL; P  = .015) were significantly different between groups (AUC <550 vs AUC ≥550, respectively). AKI occurred in 42% (42/100) of patients with AUC ≥550 compared with 2% (2/100) of patients with AUC <550 (P  < .05). Secondary outcomes were not different between the groups. In the bivariate analysis, age ≥70, CrCl <50 mL/min, and AUC ≥550 (odds ratio, 49.5; 95% CI, 10.1–242.3; P  < .05) were found to be independently associated with risk for developing AKI. Conclusions Patients with a vancomycin AUC ≥550 were found to have a significantly higher rate of AKI compared with those with an AUC <550. [ABSTRACT FROM AUTHOR]

Published vancomycin dosing recommendations for patients receiving maintenance hemodialysis were not designed to meet newly recommended 24‐hour area under the curve/minimum inhibitory concentration (AUC24h/MIC) pharmacokinetic/pharmacodynamic targets. The aims of this study were to predict pharmacokinetic/pharmacodynamic target attainment rates with a commonly used vancomycin regimen and to design a new dosing scheme incorporating therapeutic drug monitoring (TDM) to maximize target attainment in patients receiving vancomycin and hemodialysis with high‐ or low‐flux hemodialyzers. Vancomycin pharmacokinetic‐ and dialysis‐specific parameters were incorporated into Monte Carlo simulations (MCS). A commonly used vancomycin regimen was modeled to determine its likelihood of attaining AUC24h/MIC targets for 1 week of thrice‐weekly hemodialysis treatments. MCS was then used to develop optimal initial vancomycin dosing for patients receiving intradialytic or postdialytic vancomycin administration with either high‐ or low‐flux hemodialyzers. Finally, a new MCS model incorporating TDM was built to further optimize the probability of pharmacokinetic/pharmacodynamic target attainment. Traditional vancomycin dosing methods are unlikely to meet AUC24h/MIC targets. Vancomycin doses necessary to attain AUC24h/MIC targets are significantly influenced by hemodialyzer permeability and whether vancomycin is administered intradialytically or after hemodialysis. Depending on dialyzer type and whether vancomycin is administered during or after hemodialysis, loading doses of 25 to 35 mg/kg followed by maintenance doses of 7.5 to 15 mg/kg are necessary to reach minimum AUC24h/MIC targets in 90% of virtual patients. For a 3‐day interdialytic period, a 30% higher maintenance dose is required to maintain target attainment. Dosing based on a single vancomycin serum concentration obtained prior to the second dialysis session greatly enhances the probability of target attainment. [ABSTRACT FROM AUTHOR]

Background: A vancomycin target of area under the curve to minimum inhibitory concentration (AUC:MIC) ratio ≥400 is recommended for treatment of methicillin-resistant Staphylococcus aureus (MRSA) bacteremia. Objective: To evaluate vancomycin total daily dose (TDD) achieving trough targets versus a calculated strategy achieving AUC targets based on body mass index (BMI). Methods: A retrospective cohort study was performed within a large hospital network. Patients with MRSA bacteremia were eligible if they received vancomycin with a steady-state trough (15-20 mg/L). Cockcroft-Gault was used to estimate creatinine clearance, calculating vancomycin clearance and AUC. Patients were stratified by BMI (less than/greater than 30 kg/m2). The primary outcome was vancomycin TDD for the trough-based strategy compared with an AUC-dosing strategy. Results: A total of 119 patients were included, including 51 (42.9%) and 68 (57.1%) patients with high- and low-BMI, respectively. The TDD for trough-based dosing (2390.76 ± 1224.59 mg) differed significantly from AUC-based dosing (1985.07 ± 616.18 mg) across the cohort (P = 0.0014). For patients with high BMI, there was a significant difference (P < 0.0001) in TDD between trough (2637.25 ± 1327.89 mg) versus AUC (1918.71 ± 625.89 mg) strategies. No difference in TDD between dosing strategies was observed among low-BMI patients. Across all patients, 46 (38.7%) experienced acute kidney injury (AKI); high-BMI patients experienced higher rates of AKI compared with low-BMI patients (54.9 vs 26.5%; P = 0.002). Conclusions and Relevance: An AUC-based dosing strategy may reduce vancomycin TDD required for MRSA bacteremia compared with trough-based dosing, particularly for patients with higher BMI. [ABSTRACT FROM AUTHOR]

Purpose: This Position Paper aims to review and discuss the available data on therapeutic drug monitoring (TDM) of antibacterials, antifungals and antivirals in critically ill adult patients in the intensive care unit (ICU). This Position Paper also provides a practical guide on how TDM can be applied in routine clinical practice to improve therapeutic outcomes in critically ill adult patients.Methods: Literature review and analysis were performed by Panel Members nominated by the endorsing organisations, European Society of Intensive Care Medicine (ESICM), Pharmacokinetic/Pharmacodynamic and Critically Ill Patient Study Groups of European Society of Clinical Microbiology and Infectious Diseases (ESCMID), International Association for Therapeutic Drug Monitoring and Clinical Toxicology (IATDMCT) and International Society of Antimicrobial Chemotherapy (ISAC). Panel members made recommendations for whether TDM should be applied clinically for different antimicrobials/classes.Results: TDM-guided dosing has been shown to be clinically beneficial for aminoglycosides, voriconazole and ribavirin. For most common antibiotics and antifungals in the ICU, a clear therapeutic range has been established, and for these agents, routine TDM in critically ill patients appears meritorious. For the antivirals, research is needed to identify therapeutic targets and determine whether antiviral TDM is indeed meritorious in this patient population. The Panel Members recommend routine TDM to be performed for aminoglycosides, beta-lactam antibiotics, linezolid, teicoplanin, vancomycin and voriconazole in critically ill patients.Conclusion: Although TDM should be the standard of care for most antimicrobials in every ICU, important barriers need to be addressed before routine TDM can be widely employed worldwide. [ABSTRACT FROM AUTHOR]

The article offers information related to medical industry. Topics include that Measles virus infection cause loss of immune memory that can be reconstituted by reexposure to pathogens; and a case study of a 55-year-old resident with a 2-week history of fever and confirmation of a severe acute hepatitis and liver failure caused by Leishmaniasis.

Background: Various pharmacokinetic (PK) equations and software have been developed to individualize vancomycin dosing. However, the benefit of using any PK information to guide vancomycin dosing has not been fully elucidated. Objective: To appraise available evidence on the effectiveness and safety of individualized vancomycin dosing via PK tools. Methods: PubMed, EMBASE, the Cochrane Library, and 2 Chinese literature databases were searched through August 1, 2019. Randomized controlled trials (RCTs) and cohort studies that reported the PK and clinical outcomes of individualized vancomycin dosing versus empirical dosing were included. Pooled risk ratios (RRs) and mean differences were calculated for dichotomous and continuous outcomes, respectively. Results: A total of 21 studies involving 4346 patients were finally included, of which 3 were RCTs and 18 were cohort studies. Meta-analysis revealed that PK-guided vancomycin dosing significantly increased the attainment of target trough concentration (RR = 1.59; 95% CI = 1.49-1.70) and decreased the incidence of nephrotoxicity (RR = 0.57; 95% CI = 0.46-0.71). Additionally, the available evidence showed that target area under the curve/minimum inhibitory concentration attainment rate and time to target concentration could improve. However, the evidence on clinical outcomes was scarce, and no significant differences were detected in clinical response rate, microbiological eradication rate, mortality, and length of hospital stay between PK-guided vancomycin dosing and empirical dosing strategies. Conclusion and Relevance: Individualized vancomycin dosing via PK tools significantly increases the attainment of target trough concentration and decreases the incidence of nephrotoxicity. Evidence on clinical effectiveness was limited and showed no significant benefit. Further well-designed studies are warranted to assess its clinical effectiveness and inform routine care. [ABSTRACT FROM AUTHOR]

We observed poor uptake of vancomycin AUC monitoring with the use of first-order PK analytic equations, with only 25% of regimens meeting criteria having AUC monitoring performed. Our institutional vancomycin monitoring guidelines recommend AUC monitoring for patients with severe MRSA infections, excluding patients on hemodialysis, those with unstable/acutely changing renal function, or if lab draws must be limited. [Extracted from the article]

Objectives: In the absence of consensus, the present meta-analysis was performed to determine an optimal dosing regimen of vancomycin for neonates.Methods: A 'meta-model' with 4894 concentrations from 1631 neonates was built using NONMEM, and Monte Carlo simulations were performed to design an optimal intermittent infusion, aiming to reach a target AUC0-24 of 400 mg·h/L at steady-state in at least 80% of neonates.Results: A two-compartment model best fitted the data. Current weight, postmenstrual age (PMA) and serum creatinine were the significant covariates for CL. After model validation, simulations showed that a loading dose (25 mg/kg) and a maintenance dose (15 mg/kg q12h if <35 weeks PMA and 15 mg/kg q8h if ≥35 weeks PMA) achieved the AUC0-24 target earlier than a standard 'Blue Book' dosage regimen in >89% of the treated patients.Conclusions: The results of a population meta-analysis of vancomycin data have been used to develop a new dosing regimen for neonatal use and to assist in the design of the model-based, multinational European trial, NeoVanc. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to assess the impact of area under the curve (AUC)-based vancomycin monitoring on pharmacist-initiated dose adjustments after transitioning from a trough-only to an AUC-based monitoring method at our institution. Methods: A retrospective cohort study of patients treated with vancomycin for complicated methicillin-resistant Staphylococcus aureus (MRSA) infection between November 2013 and December 2016 was conducted. The frequency of pharmacist-initiated dose adjustments was assessed for patients monitored via trough-only and AUC-based approaches for trough ranges: 10 to 14.9 mg/L and 15 to 20 mg/L. Results: Fifty patients were included: 36 in the trough-based monitoring and 14 in the AUC-based-monitoring group. The vancomycin dose was increased in 71.4% of patients when troughs were 10 to 14.9 mg/L when a trough-only approach was used and in only 25% of patients when using AUC estimation (P =.048). In the AUC group, the dose was increased only when AUC/minimum inhibitory concentration (MIC) <400; unchanged regimens had an estimated AUC/MIC ≥400. The AUC-based monitoring did not significantly increase the frequency of dose reductions when trough concentrations were 15 to 20 mg/L (AUC: 33.3% vs trough: 4.6%; P =.107). Conclusions: The AUC-based monitoring resulted in fewer patients with dose adjustments when trough levels were 10 to 14.9 mg/L. The AUC-based monitoring has the potential to reduce unnecessary vancomycin exposure and warrants further investigation. [ABSTRACT FROM AUTHOR]