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Analogue of ampicillin, is a semisynthetic antibiotic with essentially the all patients who present agar (Biokar®) were prepared and sterilized according to the manufacturers’ instructions. Another drug and may not reflect the rates.

Chronic bronchitis and colds is important to avoid patients at risk will not treat a viral infection such as the flu or a common cold. Do not start, stop, or change the.

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The bone amoxicillin-clavulanic acid concentrations from Grimer et al.

(54) were approximately 2 to 3 times lower than those from our study, whereas Adam et al.

(1) reported clavulanic acid concentrations about 10 times higher than those obtained in our study (Fig. This pronounced difference (20- to 30-fold for averages) for clavulanic acid calls for standardized methods of sample preparation, drug analysis, and PK evaluation. The concentrations of amoxicillin and clavulanic acid showed a high correlation in cortical bone ( r = 0.90; observed data) and cancellous bone ( r = 0.95; Fig.

This suggests that both drugs were stable and that sample preparation and


analysis were precise and reproducible.

The concentrations in cortical and cancellous bone were correlated for both drugs ( r = 0.75). (54) and indicates that the equilibration rates between cortical bone and serum and between cancellous bone and serum were probably similar.

Consequently, the equilibration half-lives for both types of bone were assumed to be the same in the final model. Short equilibration half-lives between bone and serum were estimated for both drugs (Table 1; Fig. This suggests that concentrations above the PK-PD breakpoints were reached within less than 30 min after the end of a 30-min infusion. As serum and bone concentrations are decreasing after the end of a short-term infusion, these fast equilibration half-lives suggest from a PK point of view that the surgery should start within the first 30 min after the end of a 30-min infusion.

As the breakpoints reported here are based on PK-PD targets for the treatment of infections and as these targets were derived on the basis of the plasma or serum concentrations, PK-PD targets for surgical prophylaxis need to be established and our simulation results should be interpreted conservatively.

The determination of total antibiotic concentrations in bone homogenate, as reported in virtually all studies on bone penetration published to date (36), has several limitations.

Bone tissue consists of an organic matrix (30 to 35% of total bone mass) and an inorganic matrix (65 to 70%) (14, 25, 48).

The organic matrix mainly consists of collagen fibrils, glycoproteins, proteoglycans, extracellular fluid (25), and bone cells (1 to 2% of the total bone mass) (14). The inorganic matrix is formed by hydroxyapatite crystals (calcium phosphate) deposited within the organic matrix (14). Neither antibiotics nor bacteria are expected to distribute homogeneously in bone. No techniques for the separation of bone samples into extracellular fluid, hydroxyapatite, collagen fibrils, and bone cells are currently available. In addition, only the unbound fraction of drug is considered to be microbiologically active, and the extent of binding in bone is not known. Binding experiments suggest that beta-lactams do not bind (or bind only to a minor extent) to bone powder or hydroxyapatite crystals (1, 55).

Beta-lactams likely distribute mainly within the vascular and extracellular fluid spaces in bone (17, 26, 34, 41). They pass the capillary walls of blood vessels located in the Haversian and Volkmann canals in bone, diffuse into the interstitial fluid space, and likely distribute in the lacunocanalicular system (Table 4, scenarios B and C) (15, 34). Furthermore, bacteria are not expected to distribute into the inorganic matrix or collagen fibrils but mainly distribute in the interstitial and extracellular fluid spaces (scenarios B and C). Therefore, scenarios B and C in Table 4 seem to be the most likely, and the breakpoints reported in Table 2 appear to be conservative (i.e., low) estimates, if the bacteria do not distribute intracellularly and do not reside in sequestered areas. As it is not known how drug and bacteria distribute within bone, Table 4 lists potential breakpoints for a dose of 2,000/200 mg amoxicillin-clavulanic acid q6h for various distribution scenarios.

The most realistic potential scenario might be scenario B or a scenario in which amoxicillin distributes in interstitial fluid plus part of the total bone fluid outside the interstitial space (a mix of scenarios B and C). As total bone fluid likely includes fluid in small pores of the hydroxyapatite crystals from which interstitial fluid markers (e.g., sucrose) are excluded (45), distribution throughout total bone fluid (scenario C) seems less likely. aureus to enter


survive in osteoblasts (31, 35) was suggested to be a possible reason for relapses of osteomyelitis (Table 4, scenario D).

As beta-lactams are not expected to penetrate cells well, an intracellular bone infection might relapse (38).

In any case, when bacteria reside in a part of the bone which is inaccessible to amoxicillin, treatment failure or relapse seems likely. The volumes described in Table 4 refer to those in healthy bone.

In patients with acute osteomyelitis, it has been suggested that the blood supply to the bone is increased, capillary permeability is higher, and potentially greater antibiotic concentrations reach bone (34).

In osteomyelitic canine bone, the volume of distribution of cefazolin was increased to 0.572 ml per ml bone, whereas in uninfected bone, it was 0.0662 ml per ml bone (17). The results of few PK studies with patients with osteomyelitis are available.

In patients with chronic osteomyelitis, dead bone (a location where bacteria may be sequestered) which is not reached by the blood circulation is often present.

Beta-lactams most likely cannot penetrate into sequestered areas, and therefore, surgical debridement, in addition to antibiotic therapy, is necessary.

Another limitation of our analysis is that the target for beta-lactams in bone is unknown.

Data on the efficacies of


and other beta-lactams for the treatment of osteomyelitis are sparse. Therefore, the present analysis could not apply reverse engineering to determine the PK-PD target, as was done previously (9, 37). To consider a wide range of potential target values, we reported the results for fT > MIC targets of at least 30%, 50%, 70%, or 100% (Tables 2 and 3). Should a future study determine that amoxicillin needs to achieve a free concentration of greater than 4? the MIC for 50% of the time, for example, one can directly calculate the breakpoints on the basis of the results of our analysis by dividing our breakpoint (on the basis of fT > 1 ? MIC ) by 4, since amoxicillin displays linear PK after intravenous administration. Although beta-lactams likely distribute mainly in the interstitial space in bone and the bacteria residing there might encounter concentrations similar to those that they would encounter in plasma, the time course of the concentration in bone is different from that in serum. For the beta-lactam target fT > MIC , the shape of


concentration-time curve affects the PTA, unless the drug is given by continuous infusion. Simulations with our model confirmed that fT > MIC depends on the equilibration half-life between serum and bone, even for dosing at steady state.

For single doses, such as for perioperative prophylaxis, the equilibration half-life has an even greater impact.

Therefore, it is important to determine the half-life of equilibration by modeling and to derive breakpoints on the basis of the concentration-time profiles in bone.

However, clinical trials are needed to determine the PK-PD target for bone.

Like virtually all studies of drug bone penetration whose findings have been published, we had one bone sample per patient.

The collection of multiple bone samples is not feasible in joint replacement studies. In contrast to previous studies, we applied population PK analysis in which all data from all patients were considered simultaneously.

In addition, a full Bayesian analysis, which is the latest method for data analysis and which is particularly valuable for use with sparse data, was applied.

Our analysis considered between-patient variability and the PK in both serum and bone and therefore provides information in addition to the comparison of bone concentrations to MICs usually applied.

The latter method was also applied to amoxicillin bone penetration studies (3, 24, 36, 54) and was recently criticized by Mouton et al.

(47) as “meaningless,” and they also considered its use to be “potentially harmful in patient care.” Despite the activity of amoxicillin-clavulanic acid against pathogens commonly encountered in bone infections (28), its PK profile and PK-PD breakpoints in bone have not been determined by population PK and Monte Carlo simulations.

used population PK and Monte Carlo simulations to analyze the penetration of levofloxacin into the prostate (21) and epithelial lining fluid (20).

We used these techniques, which consider the full time course of tissue and serum concentrations and their BSVs, to estimate the extent and rate of bone penetration and to evaluate the PK-PD profile. Even though the data


sparse, the estimates from NONMEM and S-ADAPT were comparable (Table 1).

Given the limitations pointed out above, the PK-PD breakpoints (Table 2) predicted by population PK and Monte Carlo simulations compared favorably to the MICs for clinically relevant pathogens. Amoxicillin achieved PTA expectation values of >90% against MSSA in bone and serum for 30-min infusions of 2,000/200 mg amoxicillin-clavulanic acid q4h and q6h and for both an fT > MIC of ?30% and an fT > MIC of ?50% (Table 3).

The susceptibility patterns of the local hospital should be used to determine if amoxicillin-clavulanic acid is a promising choice for the treatment of bone infections.

In conclusion, the median ratios of the AUC for bone/AUC for serum were 20% (80% prediction interval for BSV, 16% to 25%) for cortical bone and 18% (80% prediction interval for BSV, 11% to 29%) for cancellous bone for amoxicillin and 15% (80% prediction interval for BSV, 11% to 21%) for cortical bone and 10% (80% prediction interval for BSV, 5.1% to 21%) for cancellous bone for clavulanic acid.

Equilibration between serum and bone was rapid for both drugs.

For dosing q4h, amoxicillin achieved robust (?90%) PTAs for MICs of ?12 mg/liter in serum and 2 to 3 mg/liter in cortical and cancellous bone for the nearly maximal kill target ( fT > MIC , ?50%).

Amoxicillin achieved PTA expectation values of >90% against MSSA for both targets in


and serum for 30-min infusions of 2,000/200 mg amoxicillin-clavulanic acid q4h and q6h ( fT > MIC , ?50%). The PTA expectation values were slightly lower for S. As the PK-PD target in bone will need to be established in future studies, we considered a wide range of PK-PD targets, and our simulation results should be interpreted conservatively.

Antibiotics save lives, but antibiotics can have negative effects. When patients have bacterial infections, we want to treat them to prevent complications of the bacterial infection, but not treat them for an excessive duration.

So we have a Goldilocks problem — we want antibiotic duration to be just right — neither too short or too long. Some clinical conditions have adequate research to define


Goldilocks duration.

Community acquired pneumonia only requires


days of antibiotics, if the patient is clinically stable at three days. We know that five days is sufficient, so if we give antibiotics for 7 or 10 days, the patient gets exposed to unnecessary antibiotics. We have learned antibiotic duration without the teaching (and guidelines) having an evidence base. So a new movement suggests that we should tell patients to stop the antibiotics when they feel better.

The concept of an antibiotic course ignores the fact that patients may respond differently to the same antibiotic, depending on diverse patient and disease factors. Currently, we largely ignore this fact and instead make indication specific recommendations for antibiotic duration that are based on poor evidence.

This situation is changing in hospital practice, where biomarkers of treatment response such as procalcitonin can guide when to stop antibiotic treatment.

Outside hospital, where repeated testing may not be feasible, patients might be best advised to stop treatment when they feel better, in direct contradiction of WHO advice.

Of note, a recent clinical trial found that using fever resolution to guide stopping antibiotics in community acquired pneumonia halved the average duration of antibiotic treatment without affecting clinical success. So this interesting


got published in the British Medical Journal.

But does subjectivity get us to the Goldilocks duration?

So this article argues against the BMJ opinion piece: Why you really should take your full course of antibiotics.

So, knowing what you now know, do you think stopping a course of antibiotics when you feel better as opposed to completing the course is a good idea?

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