Escherichia coli urinary tract infection (UTI) among elderly patients in general practice. Data on urine culture came from urine samples performed in general practice and sent to hospitals in the Capital Region of Denmark, and prescription data came from a nationwide prescription database. The study population consisted of patients with UTI episodes  caused by E. coli that received a concurrent antibiotic prescription against UTI from 2012 to 2017. We used a case-control design. Cases were UTI episodes caused by mecillinam, trimethoprim, nitrofurantoin or multi-resistant E. coli and controls were UTI episodes caused by E. coli not displaying the respective resistance pattern. We analyzed whether exposure to antibiotics in a period of 8–90 days prior to the UTI episode affected the risk of antibiotic resistant uropathogenic E coli. The analyses were adjusted for age, sex, hospital admission and nursing home status. The odds of resistance to all of the four antibiotics increased significantly after exposure to antibiotics within 90 days prior to the UTI episode. In general, mecillinam showed the lowest increase in the odds for selection of resistance. The results indicate that mecillinam is a favorable antibiotic choice in terms of selection of resistance.We investigated whether prior use of antibiotics affects the risk of mecillinam/trimethoprim/nitrofurantoin/multi-resistant  Escherichia coli and infections are often treated empirically. However, a high rate of antimicrobial resistance is increasingly causing treatment failure [Antimicrobial resistance (AMR) is a major threat to global health  and incr failure .Prior studies have shown associations between antibiotic use and AMR at both the individual level ,6,7 and E. coli based on person-specific data. Nitrofurantoin and trimethoprim are second line choices in case of penicillin allergy, and both are frequently used in other European countries as a first line treatment. In Denmark, the resistance rate of the three agents for E. coli in urine samples from general practices differs: mecillinam 4.9%, trimethoprim 21% and nitrofurantoin 0.8% [In Denmark, pivmecillinam (the prodrug of mecillinam) is first line treatment for UTI in general practice and, to our knowledge, no studies have examined the association between prior antibiotic use and risk of UTI caused by mecillinam resistant oin 0.8% .The elderly population is highly relevant to the study in relation to AMR as it is a high antibiotic-exposure population ,13,14. TE. coli in UTI among elderly patients in general practice.To avoid unnecessary antibiotic use and at the same time limit the risk of treatment failure, it is important for the GP to be able to identify individuals at high risk of AMR. We set out to investigate whether prior outpatient exposure to antibiotics affects the risk of mecillinam/trimethoprim/nitrofurantoin/multi-resistant E. coli, submitted to the Departments of Clinical Microbiology (DCM) in hospitals at the Capital Region of Copenhagen from 2012 to 2017, combined with data on antibiotic prescriptions. The study only included urine samples with significant growth of E. coli and susceptibility testing to one or more of the following antibiotics: mecillinam, nitrofurantoin or trimethoprim. In order to exclude episodes of asymptomatic bacteriuria (ASB), we only included urine samples where a UTI treatment had been redeemed within two days before and five days after the date the urine sample was taken (hereafter referred to as a UTI episode). UTI treatments were defined as prescription of the following antibiotics available for UTI treatment in Denmark: pivmecillinam, trimethoprim, nitrofurantoin, sulfamethizole, ciprofloxacin, pivampicillin and amoxicillin. A UTI episode was included in the analysis if a full exposure period was available, i.e., there was at least a 90-day interval between two UTI episodes. This series of case-control studies use data on all urine samples from elderly people (aged ≥ 65 years) in general practice with significant growth of Data on the urine samples (mainly midstream urine samples and urine sampled via catheter) were extracted from the two DCMs’ laboratory information systems. Data included sampling date and culture results, including susceptibility testing results.Antibiotic exposure data were retrieved from the Danish National Prescription Registry (DNPR). This registry contains individual level information on all prescriptions redeemed at a pharmacy since 1995 and has high validity and completeness . In DenmData on hospital admission history were collected from the Danish national patient registry. This registry contains administrative data on all contacts in the secondary health care sector, such as date of admission, type of admission and diagnoses related to the admission. Data on age and sex were provided by Statistics Denmark. The different data sources were linked by the unique 10-digit personal identification number.E. coli was defined as minimum 1000 CFU/mL. Bacterial species identification was based on phenotypical and biochemical characteristics and possibly confirmed using Matrix-Assisted Laser Desorption-Ionization time of flight mass spectrometry. Susceptibility testing was performed using EUCAST disk diffusion methodology and breakpoints [Urinalysis was performed according to European guidelines . Urine sakpoints . For triFour parallel case-control analyses were performed, one for each type of resistance. This means that for each analysis all UTI episodes were classified as either case or control depending on the result of the susceptibility report. The four outcomes were resistance to mecillinam, trimethoprim, nitrofurantoin, and multi-resistance, the latter defined as resistance to all three agents at the same time.E. coli. All remaining UTI episodes, i.e., samples with significant growth of E. coli susceptible to mecillinam or trimethoprim or nitrofurantoin or all three simultaneously, were defined as the corresponding controls. If more than one E. coli isolate was identified in a urine sample, resistance overruled susceptibility.Cases were defined as UTI episodes with significant growth of mecillinam or trimethoprim or nitrofurantoin or multi-resistant Outpatient antibiotic exposure was defined as a prescription of an antibiotic agent according to the Anatomical Therapeutic Chemical Classification System, ATC code J01: antibiotics for systematic use and P01AB01: metronidazole. The exposure to prior antibiotic use was measured from eight days before the sampling date of the urine sample to 90 days before the sample date. Exposure in the 0–7 days prior to the sample date was not included in the exposure as this most likely reflects treatment failure.Prior antibiotic exposure was measured in the following ways: (1) total exposure ). Number of prescriptions were categorized as no prescriptions, 1 prescription, 2 prescriptions or ≥3 prescriptions. DDD was grouped as no exposure and three equally large groups of exposure constructed as follows: >0–33.3 percentile, >33.3–66.6 percentile and >66.6 percentile. All specific numbers are provided as footnotes in the tables; (2) Time since last prescription ; and (3) exposure to different specific types of antibiotics .For the covariate hospital admission both the number of hospital admissions and the number of days admitted to hospital in the exposure period were collected. Only full-day admissions were included. The number of hospital admissions were grouped as 0 admissions, 1 admission, and >1 admission within the exposure period. The number of days admitted to hospital were grouped as 0 days, 1–7 days, and >7 days. Furthermore, the number of admissions and the number of days of admissions related to infectious diseases were calculated based on the recorded diagnosis of the admission using ICD-10. A list of all included diagnoses is available in the The data for this study were analyzed in a series of case-control designs. The association between prior use of antibiotics and resistance was analyzed with odds ratios (ORs) and 95% confidence intervals (CI95%) from multivariable logistic regression models. The unit of analysis was UTI episodes. Analyses were performed separately for all outcomes and exposure measures. Because of the possible multiple UTI episodes per person, the variance were adjusted, and thereby the confidence interval of the OR, for this excess dependence, by the method of generalized estimating equations . To adjuAn individual with several episodes of UTI could be included more than once if there was a full exposure period of 90 days between the episodes. In a sensitivity analysis, the analyses described above in a dataset were repeated by selecting a single random UTI episode from each individual.E. coli and concurrent antibiotic prescription for UTI. After exclusion of 10,752 urine samples, where a full exposure period was not available , 41,027 UTI episodes were included in the study. The inclusion of urine samples is shown in Within the study period, we identified 51,779 UTI episodes, defined as urine samples with significant growth of The analyses showed that the odds of resistance increased significantly after exposure to antibiotic. There was a dose-response correlation with both the number of antibiotic prescriptions and the number of DDDs. The increase in odds for mecillinam resistance were generally lower than for the other types of resistance, especially for the groups with the highest exposure to antibiotics, i.e., three or more prescriptions and above the 66.6 percentile of DDDs. All results are presented in For all four types of resistance, the odds of resistance increased with decreasing time since the last antibiotic exposure. The odds for mecillinam resistance increased 1.51  times when exposed 61–90 days prior to the UTI episode and 2.13  times when exposed 8–30 days prior to the UTI episode compared to no exposure. For trimethoprim and nitrofurantoin, the corresponding ORs were 2.20  and 2.83 . For multi-resistance, the estimate was even higher. The OR was 5.81  for exposure within 8–30 days. All results are presented in The results of the adjusted analysis of exposure to specific antibiotic agents and odds of resistance are shown in For trimethoprim and nitrofurantoin, exposure to the agent itself increased the odds considerably more than exposure to any other agent. For trimethoprim, the odds increased 6.48  times and for nitrofurantoin the odds increased 8.64  times. For trimethoprim, exposure to all other agents also increased the odds for resistance significantly. Exposure to quinolones significantly increased the odds for resistance both for trimethoprim and nitrofurantoin.For multi-resistance, several agents increased the odds significantly. Exposure to amoxicillin + β-lactamase inhibitor, increased the odds 10.18  times, while exposure to trimethoprim had an OR of 8.67  compared to no exposure. Exposure to phenoxymethylpenicillin or dicloxacillin, sulfamethizole and quinolones did not significantly increase the odds for multi-resistance.The results of the sensitivity analysis (not included in the tables) where individuals could only be included once, and the included sample was chosen randomly showed similar but slightly higher estimates than the main analysis. The results are presented in the The results of the study support current evidence that prior exposure to antibiotics is a risk factor for resistance at the individual patient level. In general, the odds increased with increasing numbers of prescriptions and DDDs and with decreasing time between last antibiotic exposure and the UTI episode.E. coli using individual level data. The results illustrate a clear association between prior outpatient antibiotic use and increased odds for mecillinam resistance in the elderly population. However, the estimates were generally lower than for trimethoprim and nitrofurantoin. Pivmecillinam is mainly used in the Nordic countries but is an interesting option as resistance levels have remained low, despite high use for many years [To our knowledge, this is the first study to examine how prior use of antibiotics affects the risk of UTI caused by mecillinam resistant ny years . In the ny years .In line with our findings, Opatowski et al.  found thE. coli [E. coli only represents a minor segment of resistance in urinary E. coli isolates and these studies therefore only provide a partial picture of the selection of AMR. Mecillinam has been used in the Nordic countries for many years and studies on the relation between mecillinam use and mecillinam resistance are warranted. Our study shows that the use of mecillinam does not drive resistance against itself at the same level as the other antibiotics recommended for UTI in Denmark (trimethoprim and nitrofurantoin). Despite the high use of mecillinam in the past two decades in Denmark, the DANMAP report [E. coli in urinary samples from general practice. A German study likewise showed a low rate of mecillinam resistance [E. coli resistant to mecillinam, indicating no or little clonal spread of mecillinam resistance [E. coli UTI in Denmark in terms of selection.While some studies have examined the risk of prior mecillinam use, these studies have focused on outcomes such as Extended-Spectrum β-Lactamase (ESBL) E. coli ,27 and nP report  has showsistance . Furthersistance . This, tBell et al.  and CostE. coli isolates. To increase the probability of sampling incident UTI episodes and not ASB, we only included urine samples where the patient had redeemed a UTI treatment concurrently. However, some GPs may still treat ASB with antibiotics and we cannot exclude that some cases of ASB have been included. This is a limitation of the study.The main strength of this study is the large number of cases and controls included and the data sources applied. As antibiotics are exclusively available by prescription in Denmark, the DNPR captures outpatient antibiotic accurately. Furthermore, data on microbiological testing were provided by the DCMs, where the culturing and subsequent susceptibility testing rely on international guidelines. Because of the retrospective nature of the study design using routine data from microbiology reports, we did not have information on clonality or other characterization of the resistant E. coli. UTI can be caused by a variety of different pathogens, but E. coli is responsible for the vast majority of all UTIs among the elderly. We did not include all potential uropathogens, as it is difficult to address intrinsic resistance in this study design and there are no internationally recognized breakpoints for all potential uropathogens. Thus, the external validity of the study is limited to including individuals infected with E. coli. Furthermore, our study population was obtained from urine samples analyzed at the DCMs, and our results should therefore only be extended to elderly patients where the GP has performed in-house microbiological testing, very cautiously, if at all. Despite the DNPR having high validity and completeness, we have no knowledge about compliance with redeemed prescriptions or self-medication. Hence, we cannot exclude that some misclassification of exposure has occurred. Another limitation is that we have no information on antibiotic use in the hospital care sector, as antibiotics used in this setting are not captured in the DNPR. However, we adjusted the analysis for hospital admission, and hence sought to limit this potential misclassification bias as much as possible. Finally, we did not have clinical information such as travel history and animal husbandry, which affect resistance prevalence.Further limitations of the study include that we chose to only include UTI episodes caused by E. coli as it does not select for mecillinam resistance at the same level as trimethoprim and nitrofurantoin select for resistance to trimethoprim and nitrofurantoin, respectively.The findings in this study support current evidence of the prior use of antibiotics as a risk factor for selection of resistance. Furthermore, it underlines the importance of studying the elderly population. The elderly population is a high-exposure population and could potentially act as a reservoir for AMR. The study also indicates that mecillinam is a favorable choice for the treatment of UTI caused by


Background: Antibiotics are frequently prescribed in nursing homes, often inappropriately. Data sources are needed to facilitate measurement and reporting of antibiotic use to inform antibiotic stewardship efforts. Previous analyses have shown that the type of nursing-home stay, that is, short stay (<100 days), is a strong predictor of high antibiotic use compared to longer nursing-home stays. The study objective was to compare 2 different data sources, electronic health record (EHR) and long-term care (LTC) pharmacy data, for surveillance of antibiotic use and type of nursing-home stay. Methods: EHR and pharmacy data during 2017 were included from 1,933 and 1,348 US-based nursing homes, respectively. We compared data elements available in each data source for antibiotic use reporting. In each data set, we attempted to describe antibiotic use as the proportion of residents on an antibiotic, days-of-therapy (DOT) per 1,000 resident days (RD), and distribution of antibiotic course duration, overall and at the facility level. Facility proportion of short-stay and long-stay (>100 days) nursing-home residents were calculated using admission dates and census data in the EHR data set and a payor variable in the pharmacy data set (Figure Results: The EHR and pharmacy data sets contained 381,382 and 326,713 residents, respectively (Table Conclusions: Nursing-home antibiotic use data obtained from EHR and pharmacy vendors can be used for calculating antibiotic use measures, which is important for antibiotic use reporting and facility-level tracking to identify opportunities for improving prescribing practices and provide facility-level benchmarks. Further validation of both data sources in the same facilities is needed to compare antibiotic use rates and to determine the most appropriate proxy for type of nursing-home stay for facility-level risk adjustment of antibiotic use rates.rt stay <00 days, rt stay <00 days, rt stay <00 days, Funding: NoDisclosures: None


Radical-directed dissociation (RDD) is a fragmentationtechniquein which a radical created by selective 213/266 nm photodissociationof a carbon–iodine bond is reisolated and collisionally activated.In previous RDD experiments, collisional activation was effected byion-trap collision-induced dissociation (CID). Higher-energy collisionaldissociation (HCD) differs from CID both in terms of how ions areexcited and in the number, type, or abundance of fragments that areobserved. In this paper, we explore the use of HCD for activationin RDD experiments. While RDD-CID favors fragments produced from radical-directedpathways such as a/z-ions and side chain losses regardless of theactivation energy employed, RDD-HCD spectra vary considerably as afunction of activation energy, with lower energies favoring RDD whilehigher energies favor products resulting from cleavage directed bymobile protons (b/y-ions). RDD-HCD therefore affords more tunablefragmentation based on the HCD energy provided. Importantly, the abundanceof radical products decreases as a function of increasing HCD energy,confirming that RDD generally proceeds via lower-energy barriers relativeto mobile-proton-driven dissociation. The dominance of b/y-ions athigher energies for RDD-HCD can therefore be explained by the highersurvivability of fragments not containing the radical after the initialor subsequent dissociation events. Furthermore, these results confirmprevious suspicions that HCD spectra differ from CID spectra due tomultiple dissociation events. Differencesin RDD fragmentation have allowed disambiguation of many classes ofsimilar molecules, including lipid isomers varying only by the positionof double bonds in the fatty acid chains.8 RDD can also distinguish glycan oligomers differingin composition, configuration, and connectivity.10 Inparticular, RDD is noted for sensitivity to stereochemistry, enablingdistinction of glycosphingolipid epimers, which only varied by theorientation of a single OH group in either the axial or equatorialposition.11 In similar applications, RDDhas been used to distinguish isomeric peptides where a single sidechain was inverted from the l to d configuration.1Radical-directed dissociation (RDD) isa tandem mass spectrometrytechnique in which a radical is created site-specifically on a biomoleculeand is subsequently activated by collisions to induce fragmentation.Prior to dissociation, the radical typically migrates to nearby sitesby hydrogen atom abstraction, which lends a high degree of structuralsensitivity to the method.2 It is interesting toconsider why RDD fragmentation is different from traditional CID,given that both methods involve the use of collisional activation.One hint can be derived from a very small minority of peptides thatbehave as antioxidants and are able to sequester radicals and yieldRDD spectra dominated by b/y-ions.12 Thissuggests that in the absence of radical sequestration, RDD is favoredover proton-initiated fragmentation, presumably by facilitating lower-energydissociation thresholds.2 However, ion-trapCID is not well suited for varying energy deposition because ionsare slowly heated by thousands of collisions, and products are cooledimmediately after creation. In contrast, higher-energy collisionaldissociation (HCD) potentially allows for more control over the amountof energy deposited into ions.RDD tends to produce different fragmention types than those observedwith traditional CID experiments on protonated analytes. For peptides,CID spectra are dominated by b/y fragments, while RDD generates primarilya/x and c/z backbone fragments in addition to partial and completeside chain losses.13 In principle, these differences should allowprecursors in HCD to be excited to higher energies than those attainablein ion-trap CID.14 In practice, HCD andCID spectra tend to contain many similar fragment ions, but they arenot identical, and the use of higher HCD energies leads to largerdifferences between the observed spectra.15Although similar methods, HCDand CID differ significantly in themechanism by which energy is delivered to ions. In ion-trap CID, ionsare resonantly excited to cause energetic collisions with helium gas.During the entire excitation period, ions are accelerated from onecollision to another, eventually acquiring enough energy in smallincrements to fragment. In HCD, a beam of precursor ions is acceleratedinto a collision gas cell, allowing for a smaller number of collisionsbut at higher energy per collision relative to CID. Additionally,the time scales of energy transfer are quite different, with CID activationoccurring over milliseconds, while HCD takes only microseconds.16 In addition, higher HCD energies tend to reduce the abundanceof larger fragments, presumably due to increased sequential fragmentationevents that yield smaller fragments.17 Withlarge molecules such as peptides or proteins, more degrees of freedomnecessitate higher energies for dissociation, and fragments oftenhave sufficient internal energy for further degradation.18 Since HCD provides more energy per collisionthan CID, the likelihood for sequential fragmentation is increased.Smaller fragment ions and singly charged fragment ions make up a largerpercentage of peptide HCD spectra and can represent the dominant fragmentsin some cases.19 Large scale comparisonof HCD and CID libraries revealed results consistent with previousobservations.20These fundamental mechanistic differences lead to changesin therelative abundances of fragments made as well as some differencesin types of fragments made, and the differences between HCD and CIDhave been the subject of significant discussion. For example, CIDspectra of peptides tend to contain mostly a, b, or y fragments andneutral losses, while HCD spectra contain these same fragments aswell as more internal fragments and immonium ions.In this paper, weexplore the differences between RDD-CID and RDD-HCDas well as track the changes in fragmentation observed as RDD-HCDenergy is increased. Our results reveal that radical-based fragmentsare more favorably produced during RDD-CID and low-energy RDD-HCD,while b/y fragments and smaller ions dominate higher-energy RDD-HCD.In addition, a stark contrast between the abundance of radical speciesand nonradical species is observed as HCD energy is increased, providinginsight into the relative energy thresholds of RDD versus mobile-proton-baseddissociation.21Organic solvents and reagents were purchasedfrom Fisher Scientific, Sigma-Aldrich, or Acros Organics and usedwithout further purification. FMOC-protected amino acids and Wangresins were purchased from Anaspec, Inc. or Chem-Impex International.β-endorphin (YGGFMTSEKS QTPLVTLFKN AIIKNAYKKG E) was purchasedfrom AnaSpec Inc. (Cat # 24319), and RRLIEDNEYTARG was purchased fromEnzo (Cat # BML-P307-0001). AKAKTDHGAEIVYK was synthesized accordingto a modified solid-phase peptide synthesis protocol.2. After12 h, the reaction precipitate was removed via filtration, and dioxanewas gently evaporated with N2. Following this, covalentattachment of 4IB was achieved by reaction of 50 μg of AKAKTDHGAEIVYKin 25 μL of 100 mM borate buffer (pH 8.5) with 25 μL of6.5 mM 4IB-NHS (10-fold molar excess) in dioxanes for 1 h. Iodo-RRLIEDNEYTARGand 4IB-AKAKTDHGAEIVYK were desalted on a MICHROM Bioresources peptideMicroTrap (P/N TR1/25109/02) directly following iodination to removesalts and reaction byproducts prior to MS analysis. Following iodination,iodo-β-endorphin was desalted on a MICHROM Bioresources proteinMicroTrap (P/N TR1/25109/03).β-endorphinwas iodinated via reaction with NaI, chloramine-T, and sodium metabisulfitein a manner to prevent excess iodination. Briefly, NaI and chloramineT were combined in a 1:2 molar ratio prior to addition to β-endorphin.Following this, 1/3 mol equiv of NaI:chloramine-T was added to 20μL of 1 mM β-endorphin in water and allowed to react for3 min before addition of the next equivalent for a total of 1 molequiv of NaI at 9 min. The reaction was then quenched with 4×molar equivalents of sodium metabisulfite. A 20 μL aliquot of1 mM RRLIEDNEYTARG was iodinated by reaction of peptide, NaI, andchloramine T at a 1:1:2 molar ratio for 10 min. At 10 min, the reactionwas quenched by the addition of 4× molar equivalents of sodiummetabisulfite. AKAKTDHGAEIVYK was covalently modified with 4-iodobenzoicacid (4IB) via reaction with 4IB-N hydroxy succinimide (4IB-NHS).Briefly, 4IB-NHS was synthesized by reaction of 1:1:1 4IB:DCC:NHS(0.5 mmol ea.) in 15 mL of dioxane for 12 h under N2O:ACN:FA (v/v/v), while peptide sprayed with the nano flexsource was diluted to 1 μM in water with 0.1% FA. Peptides wereisolated using the quadrupole prior to either 213 or 266 nm photodissociationin the low-pressure ion trap, after which the radical was reisolatedfor either CID or HCD fragmentation and analysis in the Orbitrap massanalyzer. For RDD-CID, a single normalized collision energy (referredto hereafter as CID energy) was selected, at which the precursor wasno longer observed to be the base peak with the exception of the resultsin All experimentswere performed on a Thermo Orbitrap Fusion Lumos. Peptides were introducedinto the instrument via direct infusion using either a HESI sourceor a modified nano flex source from Thermo Scientific. The nano flexsource was modified with a platinum wire to allow use of tips pulledfrom borosilicate glass (Harvard Apparatus GC100T-10). Peptide sprayedwith the HESI source was diluted to 1 μM in 50:50:0.1 Hn – FRAB0)/FRAB0 ] * 100. Sequence coverageplots were created using MASH (v2.2.0.33927). Side chain losses arecommon in RDD and are labeled by residue and approximate mass lost,i.e., −106Y indicates a 106 Da loss from the side chain oftyrosine.Following acquisition of data, deconvolutionwas performed in FreeStyle (v1.7) with Xtract with the analyzer typeset to “OT”, isotope table set to “protein”,and the relative abundance threshold set to 1%. Fragment ions wereassigned with a 0.01 Da tolerance. Following this, the fractionalabundance of the deconvoluted data was calculated, where fractionalabundance = intensity of fragment ion/sum of all fragment ion intensities.To aid in tracking the changes in fractional abundance as HCD energyis increased, % change was calculated using the first RDD-HCD energyas the initial point. % change was calculated as [. This is likely due to leakage of the excitationwaveform into these nearby m/z’s.Other minor differences include a complementary pair of b12/y19-2 fragments, which are significantly more abundantat higher RDD-CID energies. To further quantify any changes in abundanceas a function of CID energy, ratios of the relative intensities fora representative set of fragment pairs were calculated as shown in Q, changing this parameter also hadlittle effect on the results .To explore the effect of activationparameters on the relative abundances and fragment types observedin RDD-CID, experiments were performed on the 4+ charge state of iodo-β-endorphinat various CID energies 1a–c. Them/z range, while sidechain losses are reduced in fractional abundance, particularly forthe −106Y side chain loss  for several peptides in 3) decrease more quickly. Very similar results are obtainedfor the 5+ charge state of β-endorphin , which may suggest that charge state does not playa significant role. The peptide fragments remaining behind after smallmolecule side chain losses are nearly the same size as the initialpeptide precursors, which should increase the probability for energeticsecondary collisions. Such large species will also have nearly thesame number of low energy dissociation pathways still available asthe original precursor ion; therefore, it is not surprising that furtherdecay is observed at higher HCD energies. Similarly to the previoustwo examples, RDD-HCD experiments on RRLIEDNEYTARG result in decreasesin FRAB for nearly all side chain loss products, with type III sidechain −106Y exhibiting the quickest decrease in FRAB relativeto the other side chain losses .ndorphin S2, which4 experiments.−106Y and −71K exhibited a higher degree of fragmentationthan the nonradical −58K loss . The FRAB of the intact −106Y, −71K, and −58Kprecursors was 0.18, 0.27, and 0.38, respectively. The higher residualprecursor for the nonradical −58K loss is consistent with higher-energydissociation barriers for this fragment.To further explore the stability of radical versusnonradical productions, the peptides produced by side chain losses were reisolated andsubjected to identical CID activation in MS2 The stability of a-ion productsas a function of activation energy is shown in 4+1 fragment behaves in completely the opposite fashion, wherethis shortest fragment decreases in FRAB at higher energies. Importantly,the mechanism that generates this an+1 is known and isspecific to sites N-terminal to Ser/Thr residues.2 Although typical a-ions are nonradical species, the a+1is a radical . Despitebeing the shortest fragment , the radical nature of thea4+1 ion must account for its fragility and reduced FRABas HCD energy is increased. This interpretation is further confirmedupon consideration of the a-ions generated for 4+ β-endorphin,which includes a typical a4 ion . For β-endorphin, fragmentsof length 2–21 are produced in higher FRAB at higher HCD energies,while fragments of length 22–31 are lower in FRAB at higherHCD energies  and will easily undergo secondaryfragmentation with high energy activation in HCD experiments. Thedominant b/y-ions observed at higher HCD energies therefore represent“survivor” ions that have undergone secondary dissociationand have few low-energy dissociation pathways remaining available.Ironically, HCD also appears to enable lower energy activation thanis possible with CID, as is most apparent in the second line of


In order to improve the performance of concrete, it is of great significance to have a better understanding the mechanism and main influencing factors of concrete bubble evolution under the action of polycarboxylate and air-entraining agents. In the present review, with respect to the generation, growth, stability, and rupture of concrete bubbles under the action of polycarboxylate and air-entraining agents, this paper discusses the influence of bubble characteristics on concrete performance and studies bubble regulation by air-entraining agents and polycarboxylate (PCE) superplasticizer. The results show that the acid-to-ether ratio, sulfonic acid group, ester group, and the type of air entraining agent of the polycarboxylate acid structure have a significant impact on the bubbles. The bubble size, specific area, spacing factor, and bubble content have a significant impact on the rheological properties and related mechanical properties of fresh concrete and also affect the appearance quality of concrete. The problems with the experimental methods and theoretical models of concrete bubble research were analyzed, and future research ideas were put forward. For concrete, as a multiphase and porous material, pore structure is an important part of its microstructure which affects multiple of its properties. By adding an appropriate number of bubbles into concrete through admixtures, it is possible to increase the fresh concrete workability and effectively enhance its frost resistance and durability, but too many bubbles will also significantly reduce the concrete strength. Hence, it is particularly important to study the evolution mechanism and influencing factors of concrete bubbles. As a third-generation high-performance water reducer, PCE superplasticizer has various molecular structures. PCE with a special structure can be used as an air-entraining water reducer. Factors such as molecular mass, main chain density, and side-chain length significantly affect its air-entraining properties and the structure characteristics of the generated bubbles . At the The traditional experiment process consumes a lot of time and energy. Nowadays, given the rapidly developing network and computers, developed computer technology can be used to establish appropriate models which provide an intuitive and low-carbon experiment approach to simulate the progress of related experiments and finally reveal the evolution and regulation mechanism of concrete bubbles under the action of PCE. Focusing on the concrete bubble research by domestic and foreign scholars, this paper summarizes the effects of air-entraining agents and the PCE superplasticizer structure on bubbles, as well as the effect of bubbles on concrete properties. Moreover, it anticipated experimental methods and mathematical models for future research of bubble mechanisms. Our research can be reflected in There are generally two or more flow states involving mixtures of different phases in nature; the most common is the gas–liquid two-phase flow state. In this process, bubbles play an important role . Bubbles2+ concentration in the cement slurry increased continuously until reaching the maximum value near the end of the induction period. The air solubility in the pore solution lowered during the induction period, with air released and bubbles formed [According to the volume change of bubbles, the bubble life cycle has four stages: generation, growth, stability, and rupture. The generation of concrete bubbles involves both macroscopic and microscopic factors. Macroscopically, the artificially or mechanically created vortex swirls into the air to form a large number of bubbles with an uneven volume, and a small number of bubbles comes from the air dissolved in the water . Microscs formed . The relThere are two commonly used nucleation mechanisms in bubble evolution: 1. Classical nucleation theory, including two cases of homogeneous nucleation and heterogeneous nucleation; this theory is limited to static fluids in the scope of the application . HoweverEssentially, bubble growth in concrete is when the gas surrounding the bubble diffuses into the bubble interior through the bubble film, generating a pressure difference between the interior and exterior. Scholars generally believe that the pressure gradient between bubbles leads to gas diffusion. Small bubbles have a high gas pressure, while large bubbles have a low gas pressure. Macroscopically, small bubbles converge to large bubbles and gradually become smaller until their disappearance, while large bubbles gradually become larger until they burst. The schematic diagram of gas diffusion is shown in In their process of formation, concrete bubbles will be subjected to upward buoyancy, downward surface tension, bubble inertial forces and drag forces, etc. Bubbles have vertical and horizontal movements. In vertical movements, the rise of bubbles is negatively correlated with the liquid phase viscosity, a process affected by buoyancy, viscous resistance, and self-gravity , as showBubbles have unobvious boundaries between the growth and stabilization stages, and the volume does not change significantly in the stabilization stage. Many factors affect the stability of concrete bubbles including separation pressure and ionic strength, bubble liquid film strength , and the2+ concentration increased during the induction period and the bubble liquid film produced electrostatic repulsion [Separation pressure and ionic strength. Separation pressure refers to the electrostatic repulsion between the two sides of the bubble liquid film, which consists of van der Waals forces and short-range repulsion ,18. Careepulsion  which hiepulsion .Bubble liquid film strength. Film strength is often determined by the surface elasticity and surface viscosity of the adsorption film on the liquid film surface ,24,25. SDiffusion rate of gas through the liquid film. The barrier to gas migration between the gas–liquid interface in fresh concrete, namely, the ability of gas to penetrate the liquid film, determines the bubble diffusion rate . Gas difDeformation is common during the concrete bubble movement, and bubble deformation is the premise of instability and rupture . The watThe stability of concrete bubbles is dynamically balanced. Nonetheless, when the degree of bubble deformation causes the bubble film to rupture and lose its elastic properties, bubble will lose stability and rupture and finally exist in the interior and surface of the hardened concrete in the form of open or closed pores. There are three main reasons for the instability and rupturing of bubbles : coalescCoalescence. According to the classic model of bubble coalescence in aqueous solutions , bubble Using computer CT three-dimensional reconstruction technology, the existence of the bubble coalescence phenomenon in fresh concrete was intuitively proved. Under the action of long side-chain PCE, the small pore-size bubbles in concrete decreased and the large pore-size bubbles increased. Moreover, long side-chain PCE caused earlier bubble coalescence time and earlier bubble rupture time.Liquid film drainage. Drainage means liquid flow relative to the bubble . Bubble Coarsening. Coarsening refers to the process in which bubble size increases through gas diffusion between adjacent tiny bubbles . After cAt present, most research on bubble behavior stays in the stage of clear water solutions. Appropriate mesh size and bubble parameters are important guarantees for reliable and effective simulation results, which are also difficult problems in simulation calculations. Nguyen et al.  studied Some scholars carried out three-dimensional numerical simulations of the interactions between parallel bubbles under the VOF model . A gas–lThe behavior of concrete bubbles is affected by multiple factors such as different types of air-entraining agents and the PCE structure, raw material composition, construction technology, link temperature, ambient air pressure, etc. Air-entraining agents and PCE superplasticizer have the most significant effects. Using the image analysis method, Rath et al.  tested tUnder the same air void in the fresh concrete, the addition of different types of air-entraining agents also created obviously different effects on the average bubble diameter, as shown in Atahan et al.  comparedQiao et al.  and ChenMost PCE graft copolymers contain carboxylic acid adsorption groups on the main chain, while the polyether side chains on the branched chains provide steric groups. Hydrophilic side-chain polyether groups have a strong air-entraining performance. When PCE was added to the concrete, the surface tension of the mixing water decreased, and a large number of unstable bubbles were introduced during the mixing process. Low surface energy facilitated the formation of harmful large bubbles. The bubbles entrained by different molecular PCEs had varying stabilities. For PCEs with carboxyl groups and ester groups, the bubbles easily ruptured, but this was not the case for PCEs with ester groups. It suggests that bubble regulation is closely related to the PCE structure.Acid-to-ether ratio. He Yan  synthesiSulfonic acid group. When a small number of sulfonic acid groups was used to replace the carboxyl groups in the main PCE chain, the fresh mortar with sulfonic acid group-containing PCE had a significantly increased or decreased air void of 5–6%, as shown in Ester group. The ester group is a neutral group that reduces the ionic density and adsorption capacity in the PCE molecule. As the content of ester groups grafted onto the side chain of PCE increased, the concentration of PCE adsorbed on the cement particle surface decreased, while the concentration of PCE left in the pore solution increased, resulting in significantly decreased surface tension at the gas–liquid interface, thereby increasing the air void entrained in the fresh cement mortar. The ester group-containing PCE, as shown in In recent years, some scholars have synthesized low air-entraining PCEs by adjusting the molecular structure or molecular weight of PCE, such as by introducing the antifoaming functional group, PPGA400 (poly (propylene glycol) diacrylate), into the molecular structure  using thBubble parameter is an important condition for establishing bubble structure as an important index affecting the concrete appearance. There are generally three parameters to characterize the bubble structure: gas content, average bubble diameter, and bubble spacing coefficient. Bubble structure is commonly controlled by the control of raw materials, adjustment of the mixing ratio, and composite mixing of chemical admixtures, among which the use of admixtures is the most efficient . Under tBoth durability and construction quality of concrete are affected by its rheological properties . Guo et Khoshroo et al.  found thWhen fresh concrete contains a large number of uniform and tiny bubbles, energy can be better transferred under vibration and compaction. By analyzing the experimental data, Haddad et al.  found thA large number of evenly distributed tiny bubbles can relieve the compressive stress on the solid phase particles due to an increased surface tension, which helps to reduce the drying shrinkage and deformation of concrete . MaghfouDurability has become a major issue for concrete materials and structures in cold regions ,80. A loShon  found thThe structural parameters of concrete bubbles greatly affected rheological and mechanical properties of concrete and the appearance quality after hardening. Chemical admixtures such as PCE and air-entraining agents had highly adjustable chemical structures, but the research on their structural design was not sufficient, so it is necessary to further improve the molecular structure and optimize the structural characteristics of the introduced concrete bubbles, thereby increasing the concrete durability and improving the pore quality after concrete hardening. We can also consider using PFC software to simulate the impact of the number and size of bubbles on the mechanical properties of concrete test blocks.Bubble stability was affected by bubble film strength. The viscosity, elasticity and permeability of bubble film could be used to characterize the bubble film strength. Research on the bubble film interface characteristics, liquid film drainage, bubble coalescence, etc., mostly target clean water; foam and cement mortar lack systematic quantification. In addition, the reported quantitative research on the stability of foam focused on the stability of foam. However, the mechanism of foam stability cannot be fully applied to the stability of foam in fresh concrete. There is no in situ observation or detection of the bubble behavior of fresh concrete, so it is applicable to study the bubble generation and development via the isotope trace method.The “cell model”, as well as the commonly used geometric interface reconstruction VOF-PLIC method, CT three-dimensional reconstruction technology, and the fluid volume VOF model, etc., are mathematical models established for foamed plastics, water, or two-phase systems. Concrete is a three-phase complex system of solid, liquid, and gas. Hence, it is necessary to set reasonable model hypotheses and parameters to qualitatively or semi-quantitatively describe the generation and development of bubbles.To sum up, with the progress of cement hydration in fresh concrete, the physical and chemical properties of concrete experienced constant variations, with its bubble behavior greatly different from that in aqueous solution. The entire evolution process of concrete bubbles was simultaneously affected by multiple factors and then affected the rheological and mechanical properties of concrete. The current scholars’ research on the generation, growth, stability, and rupture of bubbles basically stayed in clean water solutions, and there is no literature on the in situ monitoring of concrete bubbles. Offline experiments need a lot of time and material costs, and it is more economical to use PFC software to simulate and study the impact of bubbles on the performance of concrete. In this work, the formation and rupture process of bubbles in concrete and the main influencing factors were described; the research progress on the effect of air bubbles on the performance of concrete was reviewed:


Recent studies highlighted the importance of the combined effects of prestress loss and corrosion deterioration for concrete girder bridge structures when the effect of damage on the performance level is estimated. The multi-deterioration mechanisms connected with chloride erosion include the cross-sectional area loss of longitudinal bars and stirrups, the reduction in the ductility, the decrease in the strength of steels and the strength loss of concrete in RC columns. For the corroded RC columns and corroded elastomeric bridge bearings, analytical models of the material degradation phenomena were employed for performing the probabilistic seismic performance analysis, which could obtain the system seismic fragility of aging bridges by considering the failure functionality of multiple correlated components . The combined effects of prestress loss and cracking were also considered when developing time-dependent system seismic fragility functions. Here, a typical multi-span reinforced concrete girder bridge was used as a case study for studying the time-variant seismic performance. The results revealed the importance of the joint effects of the multi-deterioration mechanisms when modeling the time-dependent seismic fragility of aging bridge systems, as well as the significance of considering the combined effects of prestress loss and cracking. Reinforced concrete (RC) highway bridges experience prolonged exposure to a chloride environment such that these structures suffer from various forms of lifetime degradation, which result in some changes in the material properties. Corrosion in reinforcing steels initiated by chloride ions penetration into the concrete will cause the loss of cross-sectional area of the steels and the cover cracking of RC columns. Some efforts were made to investigate the potential significance of the deterioration of seismic performance across a large number of aged bridges. Choe et al. ,2 researHowever, it should be noted that the above contributions neglect additional mechanisms, such as stirrup corrosion, cover defects and damaged confined concrete. Specifically, the corrosion of stirrups leads to the strain reduction of confined concrete (or the reduction in confinement levels of core concrete) and the reduction of the shear strength in the concrete components . FurtheAlthough the above works focused on the evaluation of the corrosion effect on the seismic vulnerability of RC bridge components/systems, the joint impacts of the multi-deterioration mechanisms among multiple bridge components, which have a significant impact on the seismic performance, were rarely considered in recent studies. Meanwhile, the corrosion of critical components, including the corrosion of RC columns and the aging of elastomeric bridge bearings, as well as the combined effects of prestress loss and cracking, also have a negative effect on seismic performance. Therefore, bridge columns are assumed to be subjected to salt mist formed from chloride-laden water , and theTo verify the proposed methodology for developing time-dependent fragility curves and offer insights on the effects of the multi-deterioration mechanism of multiple related components on seismic response and vulnerability, a sample MSC concrete girder bridge was considered as a case study in this research. Nearly 67.8% of all bridges in Central and Southeastern United States and approximately 74% in China are of this bridge type . The MSC2. This type of column can be reinforced with 12-#29 longitudinal bars and #13 transverse stirrups spaced at 305 mm. The fixed and expanded bearings for this bridge class are elastomeric pads with two steel dowels, as characterized by Neilson , whSubsequently, the combined effects of the prestress losses and cracking on the seismic fragilities of bridge systems can be quantified by using Equation (48), which also includes the effects of the multi-deterioration of multiple components. Finally, it is stressed that other time-variant approaches, such as the empirical experiment and trial-and-error ,52,53, fThis paper provides a probabilistic method for identifying the time-dependent fragility of an aging bridge system under earthquake events by considering the impacts of multi-deterioration of multiple bridge components, as well as the combined effects of the prestress losses and cracking. A typical MSC concrete girder bridge is used to evaluate the seismic performance by considering the uncertainty models in structural material and corrosion parameters. Chlorine corrosion from deicing salts, which are widely utilized across northern China, can be considered the cause of the degradation and aging of bridge systems. Here, the multi-deterioration mechanisms include the corrosion deterioration of an RC column due to loss of both the steel area  and concrete covers, and the deterioration of elastomeric bearing assemblies due to the reduction in both the shear stiffness of bearing NR pads and steel dowel area. The multi-deterioration mechanisms of RC components of the bridge systems affect the lateral force resistance and seismic responses. In addition, the models for corrosion-induced prestress loss and cracking are introduced to develop time-dependent seismic fragilities of bridge systems. The overall seismic demands found using PSDMs showed a steady increase as the growing service life when joint effects of multi-deterioration of bridge multiple components  were considered. However, there was a decrease in the demand  on other multiple components . Time-variant PSDMs and the components’ capacities were constructed for calculating the seismic fragility of the MSC concrete bridges, which considered the variability in attributes of bridges, ground motion and degraded parameters. The seismic fragility curves at the system level demonstrated a steady increase over time due to corrosion aging. However, individual components, such as expansion bearings in the transverse direction, revealed a decreased vulnerability at the initial time due to the added bearing pad shear stiffness. Subsequently, the dominant effect of the loss of steel dowel areas led to an increase in vulnerability. Moreover, the system seismic fragility considering the combined effects of prestress losses and cracking was more conservative. That meant the effects of both prestress losses and cracking should not be ignored when investigating the seismic fragility of the aging bridge systems. All these system fragility curves presented a more authentic estimation of the seismic vulnerability of aging bridges, and they offered a more accurate basis for life-cycle cost analysis.


P < 0.001). Critical care  and pediatric wards  had the highest proportion of antibiotic users. Amoxicillin/clavulanate was the most frequently used antibiotic at KNH , and ceftriaxone was most used at CPGH  and MTRH . Forty-three percent (326/756) of all antibiotic prescriptions had at least one missed dose recorded. Forty-six percent (204/489) of patients on antibiotics had a specific infectious disease diagnosis, of which 18% (37/204) had soft-tissue infections, 17% (35/204) had clinical sepsis, 15% (31/204) had pneumonia, 13% (27/204) had central nervous system infections and 10% (20/204) had obstetric or gynecological infections. Of these, 27% (56/204) had bacterial culture tests ordered, with culture results available for 68% (38/56) of tests. Missed antibiotic doses, low use of specimen cultures to guide therapy, high rates of antibiotic use, particularly in the pediatric and surgical population, and preference for broad-spectrum antibiotics suggest antibiotic use in these tertiary care hospitals is not optimal. Antimicrobial stewardship programs, policies, and guidelines should be tailored to address these areas.Antimicrobial stewardship encourages appropriate antibiotic use, the specific activities of which will vary by institutional context. We investigated regional variation in antibiotic use by surveying three regional public hospitals in Kenya. Hospital-level data for antimicrobial stewardship activities, infection prevention and control, and laboratory diagnostic capacities were collected from hospital administrators, heads of infection prevention and control units, and laboratory directors, respectively. Patient-level antibiotic use data were abstracted from medical records using a modified World Health Organization point-prevalence survey form. Altogether, 1,071 consenting patients were surveyed at Kenyatta National Hospital , Coast Provincial General Hospital  and Moi Teaching and Referral Hospital . The majority  were ≥18 years and 53% (563/1071) were female. Forty-six percent  were receiving at least one antibiotic. Antibiotic use was higher among children <5 years  than among other age groups (40%, 339/847;  Antimicrobial resistance (AMR) is a major public health concern that is global in scope , 2. It iOveruse and misuse of antimicrobials are considered important drivers of AMR. In the United States, about 30% of antimicrobial therapy is considered inappropriate . In AfriAntibiotic prescribing patterns and antimicrobial stewardship efforts in Kenya are not widely documented. We conducted a point-prevalence survey to describe the antibiotic use prevalence, common antimicrobial drug types, prescribing patterns, and indications for antibiotic use among inpatients, and existing AMS activities in three large public referral hospitals located in three geographically distinct regions of Kenya.This point-prevalence survey was conducted at Kenyatta National Hospital  and at Moi Teaching and Referral Hospital (MTRH) in March–April 2018. According to the WHO protocol for point-prevalence studies —which waModified versions of the World Health Organization (WHO) point-prevalence survey (PPS) forms  were useP < 0.05 considered statistically significant. The survey protocol was approved by the relevant institutional review board (IRB) committees . Written informed consent was obtained from adult respondents and from guardians of children prior to their enrollment. No incentives were provided to study respondents.When not explicitly indicated, antibiotic use for prophylaxis was inferred for patients who had undergone surgeries for which prophylactic antibiotics are recommended, and for HIV-infected patients receiving co-trimoxazole. Diagnoses/indications for which antibiotics were prescribed were recorded following prespecified PPS indication codes, The survey lasted eight days at the Kenyatta National Hospital (KNH) in Nairobi, six days at Coast Provincial General Hospital (CPGH) in Mombasa and ten days at the Moi Teaching and Referral Hospital (MTRH) in Eldoret. KNH reported having 2,075 beds with 83,138 total admissions in 2016, CPGH had 700 beds with 24,205 total admissions (2016) and MTRH had 939 beds with 44,229 total admissions (2016). Of 1,071 patients included in the study, P = 0.26). Antimicrobial use was higher among children <5 years compared to other age groups (70% (150/224) vs 40% (339/847); P < 0.001 Forty-six percent (489/1071) of all patients received at least one antibiotic at the time of the survey, P > 0.05) at CPGH and 33%  at MTRH. There was some variability in the antibiotics used by the surveyed hospitals. Amoxicillin/clavulanate was the most used antibiotic at KNH  while ceftriaxone, a third-generation cephalosporin, was the most used at CPGH  and MTRH , Seven-hundred and fifty-six (756) separate antibiotic prescriptions were recorded . Forty-four percent (167/383) of antibiotics prescribed at KNH had at least one missed dose recorded, compared with 52%  of antibiotic prescriptions were in pediatric wards, where benzylpenicillin , gentamycin  and ceftriaxone  were the most prescribed antibiotics, P < 0.01), 41% , and 42%  of those who did not have a catheter insertion, tube insertion or surgical procedure, respectively, were using an antibiotic. Among surgical patients receiving antibiotics, 71% (130/182) had undergone an invasive surgery during the current admission, while 22% (40/182) and 7% (12/182) had minimally invasive- and non-invasive surgeries, respectively. Of the 484 patients whose HIV status were documented, 61% (50/82) of those with a HIV-positive status were receiving an antibiotic compared with 45%  of HIV-negative patients.More than half of all patients with a documented catheter insertion , tube insertion , or surgical procedure  during the current admission were on an antibiotic. Comparatively 22%  had a single documented diagnosis, 8% (39/489) had two diagnoses and 2% (8/489) had three diagnoses. Twenty-two percent (95/442) of patients with a single diagnosis were given antibiotics for prophylaxis and 32% (143/442) for an unspecified infectious condition . The remaining 46% (204/442)—who constituted 86, 68 and 50 patients at KNH, CPGH and MTRH, respectively—were taking antibiotics for the treatment of a specified/documented infectious diagnosis. The five most common infections were soft-tissue infections , clinical sepsis , pneumonia , central nervous system infections  and obstetric or gynecological infections .P > 0.05). Thirty-four samples were collected for culture from the 29 patients at KNH, 21 from the 18 patients at CPGH and 10 from the 9 patients at MTRH, for a cumulative 65 samples. Cerebrospinal fluid  and pus swabs  were collected most frequently across all hospitals. Other common samples included blood , urine , stool  and sputum .Twenty-seven percent  of patients receiving an antibiotic and with a single specified infectious diagnosis had culture tests ordered. There were more tests ordered at KNH  than at CPGH  or MTRH  but the differences were not statistically significant , pneumonia , soft-tissue infections , and clinical sepsis . For these conditions, culture results were available for 67% (10/15), 73% (11/15), 79% (11/14), and 50% (3/6) of samples submitted for the above diagnoses, respectively. Antibiotic susceptibility testing data were not collected during the survey at KNH and were scant at CPGH and MTRH, and were, therefore, excluded from the analysis.All hospitals had a clinical microbiology laboratory staffed with Kenya Medical Laboratory Technicians and Technologists Board-certified microbiologists. KNH microbiology laboratory conducted 3,930 specimen cultures and 1,509 antibiotic susceptibility tests (ASTs), in the 3-month period preceding the survey compared with 518 cultures and 185 ASTs at CPGH, and 1,200 culture tests and 650 ASTs at MTRH. Only CPGH reported experiencing periodic stockouts of AST reagents.P < 0.023). At the time of the study, no hospital required antimicrobial prescription pre-approval from another physician or pharmacist before administration or required that medical records include a rationale for antibiotic prescriptions. Further, no hospital conducted audits or reviews on the choice and duration of surgical antimicrobials used for prophylaxis. None of the hospitals’ laboratories produced an antimicrobial susceptibility report for the year preceding the survey.KNH and MTRH had Infection Prevention and Control (IPC) committees, and minutes available from meetings held within the six months preceding the survey. Only KNH had an antimicrobial stewardship committee. It was led by an infectious disease physician and provided formal guidelines to assist clinicians in making empirical decisions about antibiotic use. No hospital required clinicians to provide a rationale for prescribing antibiotics or to re-assess antibiotic prescriptions after 48 hours of the initial order. At KNH, 28% (106/383) of antibiotic prescriptions had no “stop” or “review” dates indicated, compared to 37% (70/189) at CPGH and 72% (133/184) at MTRH  was lower than reports from other facilities in Kenya and Africa but higher than what is reported in high income countries/other regions. Recent point-prevalence survey results in two public referral hospitals in Kenya reported 68%  and 55% The beta-lactam antibiotics amoxicillin/clavulanate and ceftriaxone were the most used antibiotics in this survey, as has been reported in other surveys in Kenya , 18 and We found substantive evidence that antibiotic use may not be optimal in the surveyed hospitals. Missed antibiotic doses, low use of specimen cultures to guide therapy, relatively high numbers of antibiotic prescriptions, particularly in the pediatric and surgical populations, and prescription of a broad-spectrum antibiotic like ceftriaxone without providing a rationale or reviewing these prescriptions were prevalent. Addressing all of these areas will be challenging, particularly given the limited resources for stewardship activities. Use of CDC  and WHO We also identified several areas for improvement that may be less resource intensive. The lack of locally generated antibiograms and use of clinical guidelines might be contributing to sub-optimal clinical care and worsening rates of AMR; development of locally appropriate treatment guidelines can help. While it is not possible from this study to determine the impact of oversight committees , clarifying the committees’ roles and responsibilities in optimizing antibiotic use within these hospitals could contribute to improvements in AMS.An aspect that stood out from the survey was the infrequent use of laboratory diagnostics to guide prescribing practices; few patients with suspected infectious syndromes had a culture ordered. Given that patients bear the cost of diagnostic testing and that fewer than 20% have health insurance coverage , cliniciOur survey had several limitations. Firstly, we focused on large government tertiary facilities whose data may not be generalizable to smaller or private facilities within Kenya. Secondly, we did not collect data from some wards and cannot determine the exact percentage of the hospital population included in the study. We, therefore, caution against extrapolating these findings to wards that were excluded. Thirdly, for about half of the surveyed participants, we could not link specific antibiotics with a diagnosis or identify the rationale for their use either due to poor documentation or limited sample sizes for some comparisons.This descriptive study contributes to the growing data on antibiotic use in tertiary care hospitals in Kenya and can be used by health facilities and the Ministry of Health to institute or improve AMS programs, policies, and guidelines. It also highlights important considerations that may be relevant in other low- or middle-income countries. Future research should focus on exploring the rationale underlying antibiotic use by specialties or specific classes of antibiotics, evaluating the appropriateness of antibiotic prescriptions, and identifying the determinants of effective AMS programs, drug and therapeutics committees and infection prevention and control strategies.S1 File(DOCX)Click here for additional data file.S2 File(DOCX)Click here for additional data file.S3 File(XLSX)Click here for additional data file.S4 File(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.