Oral bacteria play important roles in human health and disease. Oral samples collected using ethanol-containing mouthwash are widely used for oral microbiome studies. However, ethanol is flammable and not ideal for transportation/storage in large quantities, and some individuals may avoid ethanol due to the burning sensation or due to various personal, medical, religious, and/or cultural factors. Here, we compared ethanol-free and ethanol-containing mouthwashes using multiple microbiome metrics and assessed the stability of the mouthwash samples stored up to 10 days before processing. Forty volunteers provided oral wash samples collected using ethanol-free and ethanol-containing mouthwashes. From each sample, one aliquot was immediately frozen, one was stored at 4°C for 5 days and frozen, while the third aliquot was stored for 5 days at 4°C and 5 days at ambient temperature to mimic shipping delays and then frozen. DNA was extracted, the 16S rRNA gene V4 region was amplified and sequenced, and bioinformatic processing was performed using QIIME 2. Microbiome metrics measured in the two mouthwash types were very similar, with intraclass correlation coefficients (ICCs) for alpha and beta diversity metrics greater than 0.85. Relative abundances of some taxa were significantly different, but ICCs of the top four most abundant phyla and genera were high (> 0.75) for the comparability of the mouthwashes. Stability during delayed processing was also high for both mouthwashes based on alpha and beta diversity measures and relative abundances of the top four phyla and genera (ICCs ≥ 0.90). These results demonstrate ethanol-free mouthwash performs similarly to ethanol-containing mouthwash for microbial analyses, and both mouthwashes are stable for at least 10 days without freezing prior to laboratory processing. Ethanol-free mouthwash is suitable for collecting and shipping oral wash samples, and these results have important implications for planning future epidemiologic studies of the oral microbiome. The human oral cavity is estimated to harbor 700 or more bacterial species, in addition to fungi, viruses, archaea, and protozoa, making the oral microbiome one of the most complex microbial communities found in the human body , 2. The Different types of samples have been used to study the oral microbiome, including saliva, supra- and sub-gingival plaque, and oral swabs from the cheeks, gums, and tongue ,10. AmonAlthough standard Scope® mouthwash is widely used to collect oral washes in epidemiologic studies, there are some practical considerations for such ethanol-containing mouthwashes in future collections. The ethanol in these mouthwashes serves as a solvent and preservative . HoweverAlcohol-free  mouthwashes do not contain ethanol and provide an alternative method for oral wash collections. Aside from ethanol, alcohol-free formulations of mouthwashes contain many of the same ingredients as ethanol-containing mouthwashes, generally consisting of water, humectant , surfactant (foaming agent), flavor, sweeteners, color, preservatives, and active ingredients with antimicrobial properties for plaque and gingivitis control  –26. HoweHere, we tested the use of an ethanol-free mouthwash to collect oral washes for studying the oral microbiome. We evaluated the comparability of ethanol-free and ethanol-containing mouthwashes based on multiple microbiome metrics. We also assessed the sensitivity of mouthwash samples to processing delays by storing samples for up to 10 days to mimic shipping delays that may occur during collections shipped via mail or other carriers. The results of this study will be informative for planning oral wash collections for future microbiome studies.Forty healthy volunteers were recruited from the Research Donor Program at the Frederick National Laboratory for Cancer Research  under an approved protocol . Eligible individuals were employees of the Frederick National Laboratory or Fort Detrick community, between 40–65 years old, weighed 110 pounds or more, did not have dentures or dental implants, and were in excellent health without known heart, lung, kidney, bleeding disorders, infectious disease or other chronic illnesses. Written informed consent was obtained from all participants. Study participants completed questionnaires providing information about demographics, oral hygiene practices, overall oral health, and recent antibiotic use. An equal number of men (n = 20) and women (n = 20) were recruited. The mean age of the participants was 52.4 years (standard deviation [SD] 7.21), and most participants were white (87.5%). The majority of participants self-reported good to excellent oral health (90.0%) with no gum disease (80.0%). Approximately half of the participants had no lost teeth (55%), and most subjects had had dental caries (92.5%). All participants reported practicing daily toothbrushing. Approximately half (52.5%) of the participants reported using a mouthwash product  at least once a week within the month prior to sample collection. One subject reported using antibiotics within 1–4 weeks prior to sample collection, and five subjects received professional dental cleaning within the month prior to sample collection (12.5%). There were no missing numbers in the questionnaire data mentioned above.This study is reported according to the Strengthening The Organization and Reporting of Microbiome Studies (STORMS) guidelines for human microbiome research  and another with ethanol-containing mouthwash . The ingredients of the ethanol-free mouthwash contained cetylpyridinium chloride (0.07%), water, glycerin, flavor, poloxamer 407, sodium saccharin, methylparaben, sucralose, propylparaben, and Blue 1. For the ethanol-containing mouthwash, the ingredients were water, ethanol (15 wt%), glycerin, flavor, polysorbate 80, sodium saccharin, sodium benzoate, cetylpyridinium chloride, benzoic acid, Blue 1, and Yellow 5. Participants were provided two home-collection kits containing the mouthwashes along with instructions for collecting the samples. The two mouthwash samples were collected on two consecutive days, where half of the participants were randomly assigned to provide ethanol-free mouthwash samples on the first day and ethanol-containing mouthwash samples on the second day, and vice versa for the other half of the participants. Participants were instructed to pour 10 mL of the mouthwash into a sterile screw-cap container (with a fill line), which they then poured into their mouth and swished for 30 seconds. After this, participants spit the mouthwash back into the screw-cap container. Mouthwash samples were collected in the morning and kept cold (~4°C) with an ice pack before being transferred to the laboratory on the same day for aliquoting and storage. Participants were instructed not to drink, eat, chew gum, use tobacco products, or brush their teeth at least one hour prior to oral wash collection.Upon receiving the mouthwash samples at the laboratory, three equal-volume aliquots (3 mL) were created from each sample. One aliquot was immediately processed and frozen, and two aliquots were stored for 5 and 10 days prior to processing and freezing. Stored samples were kept at 4°C through 5 days, after which the “10 day” samples were moved to ambient temperature (22°C) for the remaining 5 days. For processing, all samples were centrifuged  to obtain the cell pellet, which was resuspended in 2.5 mL of 1X Tris-EDTA (pH 8.0) and stored as two 1 mL aliquots at -80°C until analysis.μL) was added to sample aliquots (400 μL of resuspended cell pellet), mixed for 1 min, and Proteinase K (40 μL) was added and mixed for 20 min at 70°C to digest proteins and other contaminants. Then, a lysis/binding buffer (400 μL) and magnetic binding beads (40 μL) were added and mixed for 5 min to simultaneously lyse cells and capture DNA on the bead surfaces. Bound DNA was collected and washed in a wash buffer  for 2 min, 80% ethanol  for 80 sec, again with 80% ethanol (500 μL) for 30 sec, and SPM buffer (500 μL) for 1 min. The beads were dried for 2 min before eluting purified DNA in the elution buffer (150 μL) for 6 min at 75°C. The V4 region of the 16S rRNA gene was PCR amplified using barcoded 515F/806R primers, followed by amplicon sequencing using the Illumina MiSeq v2  to obtain 250-bp paired end reads, as described in detail previously [Samples were processed in three batches of 96 samples, with samples from the same individual (3 freezing time-points x 2 mouthwashes = 6 samples per subject) kept in the same batch. Each extraction batch contained the following quality control samples: one chemostat community sample , and sixeviously . MicrobiBioinformatic data processing was performed using the QIIME 2 pipeline . Raw paiFor the chemostat community quality control samples, the coefficients of variation (CVs) were less than 8% for all alpha diversity metrics across the chemostat samples. The CVs for the relative abundances of the top four most abundant phyla were between 9–28% . Principal coordinates analysis (PCoA) plots generated from beta diversity matrices showed a clear separation between the quality control samples and the study samples  were obtained using PERMANOVA to estimate the proportion of variability in the microbial composition explained by between-subject differences, sample collection date, mouthwash type, and sample processing delay time. The Wilcoxon signed-rank test with Bonferroni correction for multiple comparisons was used to test for differences in the untransformed relative abundances of taxa between paired samples of ethanol-free and ethanol-containing mouthwash from the phylum to genus level. To quantify the comparability of ethanol-free and ethanol-containing mouthwashes and the stability of each mouthwash during delayed processing, intraclass correlation coefficients (ICCs) were calculated for multiple microbiome metrics: alpha  and beta diversity , and relative abundances of the top four phyla  and genera . Specifically, ICCs were estimated for each microbiome metric using linear mixed-effects models (lmer function in the lme4 R package): Differences in the extracted DNA yields between ethanol-free and ethanol-containing mouthwashes and the different delayed processing times were assessed using the Wilcoxon signed-rank test and the Kruskal-Wallis test, respectively. The comparability of ethanol-free and ethanol-containing mouthwashes and the stability of the two mouthwash types after delayed processing were assessed based on alpha and beta diversity metrics and relative abundances of taxa. Alpha diversity metrics were compared between paired samples of ethanol-free mouthwash and ethanol-containing mouthwash using the Wilcoxon signed-rank test. Differences in alpha diversity metrics between delayed processing time points were assessed using linear mixed-effects models (lmer function in the lmerTest package); sample collection date (day 1 vs day 2) and processing delay time (0 vs 5 vs 10 days) were included as fixed effects and subjects were included as random effects, with each mouthwash modeled separately. PCoA was performed using beta diversity matrices to visually assess the separation of samples by mouthwash type and processing delay time. Differences in the microbial composition by the mouthwash type and processing delay time were tested using permutational multivariate analysis of variance  on the beta diversity matrices. Distance-based coefficients of determination  ng for ethanol-free mouthwash and 1,803  ng for ethanol-containing mouthwash  and the Shannon index , but not for Faith’s PD  and the Shannon index  were significantly different between the two mouthwashes, but there was no difference for Faith’s PD  calculated using permutational analysis of variance (PERMANOVA) showed that more than half of the variability in microbial composition was explained by between-subject differences  and only a small proportion was explained by mouthwash type  was not explained by any of the variables included in the model , relative abundances of Bacteroidetes  and Epsilonbacteraeota  were higher and Fusobacteria  and Actinobacteria  were lower in ethanol-free mouthwash compared with ethanol-containing mouthwash. At the genus level, there were no differences in the relative abundances of the top five most abundant genera, which included Streptococcus (adj P = 1.00), Prevotella 7 (adj P = 1.00), Haemophilus (adj P = 0.788), Gemella (adj P = 1.00), and Veillonella (adj P = 0.0833). Relative abundances of some of the less abundant genera were significantly different between the two mouthwashes, such as Prevotella , Fusobacterium , Rothia , Leptotrichia , and Actinomyces . For a full list of differences in relative abundances of taxa between the two mouthwashes at each taxonomic level, along with mean/median relative abundances in each mouthwash type, see Relative abundances of many taxa were significantly different between ethanol-free and ethanol-containing mouthwashes at each taxonomic level  were greater than 0.85 and 0.75, respectively.ICCs were calculated for various microbiome metrics to quantify the comparability of ethanol-free and ethanol-containing mouthwashes . The comP > 0.60) and Faith’s PD . However, there was a significant increase in the Shannon index when comparing ethanol-free mouthwash samples processed immediately  and those processed 10 days after collection . For ethanol-containing mouthwash, all alpha diversity metrics showed an increase over delayed processing time. There was a marginal increase in observed ASVs between ethanol-containing mouthwash samples processed immediately upon collection  and those processed 5 days after collection , and observed ASVs further increased in samples processed 10 days after collection . For Faith’s PD, there was no difference between ethanol-containing mouthwash samples processed immediately and those processed 5 days after collection (P = 0.365). However, there was a significant difference in Faith’s PD between immediately processed ethanol-containing mouthwash samples  and those after 10 days of delayed processing . For the Shannon index, there was a significant and noticeable gradual increase at both 5  and 10 days  of delayed processing compared with immediately processed  ethanol-containing mouthwash samples.For ethanol-free mouthwash, no differences were observed over delayed processing time for alpha diversity measured by observed ASVs  compare oral washes collected with ethanol-free and ethanol-containing mouthwashes for microbiome analysis, and (2) evaluate the stability of the oral microbiome after storage for up to 10 days to assess the sensitivity of ethanol-free and ethanol-containing mouthwashes to delayed processing. For the first aim, the results showed that ethanol-free mouthwash generally performed very similarly to ethanol-containing mouthwash, with some differences in the relative abundances of certain taxa. However, no differences were observed in the overall microbial compositions of the two mouthwashes. For the second aim, both mouthwashes showed high stability during delayed processing based on alpha and beta diversity metrics, and relative abundances of the top four abundant phyla and genera. These results demonstrate that ethanol-free mouthwash can be used as an alternative to ethanol-containing mouthwash for collecting and mailing oral wash samples for oral microbiome studies.While the microbiome profiles measured in ethanol-free and ethanol-containing mouthwashes were similar, there were some differences, particularly in the relative abundances of specific taxa, which may have been due to differences in the chemical ingredients of the mouthwashes. The specific brands of ethanol-free and ethanol-containing mouthwashes used in this study both contained the ingredient, cetylpyridinium chloride, a quaternary ammonium compound frequently used as an antimicrobial agent in over-the-counter oral care products to reduce plaque accumulation and gingival inflammation , 38. TheFor both ethanol-free and ethanol-containing mouthwashes, more than half of the variability in microbial composition was due to inter-individual differences, but a large proportion (> 40%) of the remaining was not explained by any of the other experimental factors considered in this study, which included mouthwash type, processing time, and collection date . The comThe type of mouthwash used for oral wash collections should be consistent for all subjects and time points within a given epidemiologic study whenever possible as using a mix of different mouthwashes may introduce systematic errors. For example, in our study, there was a significant difference in observed ASVs between ethanol-free and ethanol-containing mouthwashes when sample processing was delayed by 5 days, with a difference of 5 ASVs (ethanol-free: 125 vs ethanol-containing: 130); and this difference in mean observed ASVs increased to 10 after 10 days of delayed processing (ethanol-free: 125 vs ethanol-containing: 135). In a recent case-cohort study nested within three, prospective cohort studies in the United States that evaluated associations between the oral microbiome and the risk of developing lung cancer, mean observed ASVs differed by approximately 10 between lung cancer cases and the referent subcohort within each of the three cohorts at baseline, and this was found to be a statistically significant difference in that analysis . Since tIn many epidemiologic studies, particularly large-scale studies where participants are recruited from a large geographical area, self-administered collection procedures provide a logistically and economically feasible means to obtain samples from study participants. The mouthwash collection method is simple, inexpensive, noninvasive, and can be performed at home by the participants themselves without supervision by trained personnel. In an ideal setting, samples are chilled, transported to the laboratory for processing, and frozen until analysis immediately after collection. However, this is not possible when sample collection is performed at home or in other settings that are not within close proximity to laboratories. Realistically, sample processing is often delayed for multiple days from the time of collection to when the samples are received in the laboratory. Our results demonstrate that ethanol-free mouthwash can accommodate delayed processing, as seen by the stability of the oral microbiome in ethanol-free mouthwash samples for up to 10 days in conditions mimicking cold shipment warming up to ambient temperatures over time. Compared with ethanol-containing mouthwash, it is possible that ethanol-free mouthwash may provide more stability during delayed processing for some microbiome metrics, such as for alpha diversity, as seen in the present study. Furthermore, ethanol-free mouthwash samples can be shipped safely by mail and stored without concerns about flammability since they do not contain ethanol. Therefore, for future epidemiologic studies, investigators should consider oral wash collections using ethanol-free mouthwash, which has the same advantages of being low cost and easy to collect but without some of the challenges of ethanol-containing mouthwash.Our study has several strengths and limitations. We directly compared Crest® Scope® mouthwash, the most widely used mouthwash for epidemiologic investigations, with an ethanol-free alternative from the same brand  using multiple microbial metrics commonly measured in microbiome studies. The two mouthwashes were compared within the same individual, and the order of collection was randomized across participants to prevent any bias due to one mouthwash type consistently being collected before the other. We also assessed the stability of both mouthwashes during delayed processing to account for potential shipping delays that may occur during mail-in collections. Our results are likely to be generalizable to other populations–an exception may be unhealthy individuals since our study population only included healthy individuals. One limitation is that we did not compare multiple types of ethanol-containing and ethanol-free mouthwashes that included different active ingredients. Another potential limitation of our study is that we did not assess the stability of the oral microbiome in the mouthwashes at temperatures higher than ambient temperature. Therefore, it is unclear how processing delays will impact mouthwash samples shipped in hot climates. Furthermore, we only evaluated bacterial communities using 16S rRNA sequencing, so it is unclear how the mouthwashes compare using other sequencing methods  or amplicon sequencing of other kingdoms . We also did not assess the long-term stability after freezing  for measuring the oral microbiome in mouthwashes, which may have important implications for establishing biorepositories of oral wash samples.In this study, we compared the use of ethanol-free mouthwash and ethanol-containing mouthwash for oral microbiome studies. We found that the two mouthwashes performed similarly overall, but there were differences in the relative abundances of some phyla and genera. We also found that both mouthwashes demonstrated high stability during delayed processing of up to 10 days without freezing, before the samples were processed in the laboratory. These results indicate that ethanol-free mouthwash is suitable as an alternative to ethanol-containing mouthwash for collecting oral wash samples and shipping by mail in epidemiologic studies.S1 TableDifferential abundance was tested using the Wilcoxon signed-rank test with Bonferroni correction for multiple testing.(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S1 File(DOCX)Click here for additional data file.S2 File(XLSX)Click here for additional data file.S3 File(XLSX)Click here for additional data file.


J Manag Care Spec Pharm, 2020;26(10):1256This article has been corrected. Please see Targeted immunomodulators (TIMs) are used for the treatment of moderate to severe rheumatoid arthritis (RA) and include biologic and nonbiologic medications with different mechanisms of action. Data describing disease activity levels in RA are not directly available in claims databases but can be determined using a claims-based effectiveness algorithm. Rheumatology has benefited from the recent introduction of new drugs, many with new mechanisms of action. We provide an analysis of this broader range of medications.To (a) describe and summarize the effectiveness of available TIMs for the treatment of moderate to severe RA and (b) determine the RA-related health care costs per effectively treated patient, using recent data.This was a retrospective analysis using data from the IBM MarketScan Commercial Claims and Encounters Database from July 1, 2012, through December 31, 2016. Index date was the new prescription claim for a TIM . A 6-month pre-index baseline period was used to determine demographic and clinical characteristics. Patients without a TIM claim during the baseline period were considered naive; patients with a TIM claim in the baseline period that was different than the index TIM were assessed as receiving second-line therapy. A claims-based algorithm was used to assess 12-month treatment effectiveness and total RA-related costs. Costs included RA-related pharmacy costs and medical costs.Data from 14,775 patients were analyzed, including patients prescribed abatacept , adalimumab , certolizumab pegol (n = 387), etanercept , golimumab (n = 577), infliximab (n = 969), tocilizumab (n = 451), and tofacitinib (n = 889). Of these, 705 were receiving second-line therapy. TIM effectiveness by first-line and second-line therapy, respectively, were abatacept 27.1%, 18.1%; adalimumab 30.9%, 22.1%; certolizumab pegol 20.9%, 14.3%; etanercept 31.4%, 31.5%; golimumab 32.7%, 22.2%; infliximab 21.9%, 21.3%; tocilizumab 30.9%, 30.6%; and tofacitinib 26.0%, 21.6%. The main reason for failing effectiveness was not achieving an 80% medication possession ratio or being nonadherent. The 1-year total RA-related cost per effectively treated patient for first-line and second-line therapies, respectively, were abatacept $121,835, $174,090; adalimumab $112,708, $154,540; certolizumab pegol $149,946, $236,743; etanercept $102,058, $94,821; golimumab $108,802, $140,651; infliximab $155,123, $185,369; tocilizumab $93,333, $109,351; and tofacitinib $100,306, $130,501.The effectiveness of TIMs from this real-world experience showed that the range of patients who were effectively treated with first-line therapy was higher for certain tumor necrosis factor inhibitors and tocilizumab. The percentages of effectively treated patients were generally lower in second-line treatment compared with first-line except for etanercept, which had the same percentage between lines of therapy. Etanercept had the lowest RA-related cost per effectively treated patient among tumor necrosis factor inhibitors in first-line use and the lowest RA-related cost per effectively treated patient compared with all second-line treatments. What is already known about this subjectTargeted immunomodulators (TIMs) are effective at reducing the signs and symptoms, improving health-related quality of life, and halting radiographic progression of joint disease in patients with moderate to severe rheumatoid arthritis (RA); however, patients have variable responses to these medications.A validated, claims-based algorithm has been used to identify these effectively treated patients in a claims database.What this study addsDespite more options and opportunities for switching therapy, first-line treatment effectiveness rates for existing TIMs were similar to those observed in prevous studies, while newer TIMs were slightly less effective in first-line and second-line use.The percentages of effectively treated patients varied, except for etanercept and infliximab, and were generally lower for second-line therapy than for first-line therapy.The mean costs of 1-year RA-related costs per effectively treated patient varied, and, except for etanercept, were higher for second-line therapy than for first-line therapy.1 The high prevalence and long-term disability associated with RA have a significant effect on health care systems.2 Direct costs, which are managed by payers, include medications, diagnostic procedures and tests, hospitalizations, professional fees, therapeutic interventions, mechanical aids, physiotherapy, and nursing expenses.3 In 2003, the direct cost of RA and other rheumatic conditions was $80.8 billion in the United States, and indirect costs were $47 billion.4 Effective treatment for RA is necessary to prevent or reduce direct and indirect costs.Rheumatoid arthritis (RA) affects approximately 41 in 100,000 people in the United States, representing about 1.5 million adults.5 Multiple studies have used this algorithm to evaluate and compare the effectiveness of RA medications7 and to estimate the cost of treatment per effectively treated patients.11 The previous studies were conducted using claims data up to 2011, since that time, several newer targeted immunomodulators (TIMs) to treat RA have become available. The availability of these drugs has provided more mechanisms of action that may encourage greater switching between drug classes, leading to underestimation of rates of effectiveness based on the algorithm.Health care claims are a common source of real-world data to evaluate health care resource utilization and costs; however, claims data do not include any measures of disease activity level or treatment effectiveness. An effectiveness algorithm was developed and validated against disease activity scores using registry data to estimate effectiveness of therapy in patients with RA.The objectives of this study were to (a) describe and summarize the effectiveness of TIMs for the treatment of RA and (b) determine the current RA-related health care costs among RA patients treated with TIMs. These updated data should provide useful information regarding the cost per effective treatment for RA for payers to use in decision making.We used administrative claims data from the IBM MarketScan Commercial Claims and Encounters Database. This database contains deidentified information on geographically diverse, commercially insured patients in the United States. Analyses of health care claims data do not meet the definition of human subject research, and institutional review board approval was therefore not required. No identifiable private information or protected health information was provided.The study period for this retrospective, observational study was July 1, 2012-December 31, 2016. The index date was the first use of a TIM. A 6-month pre-index period (baseline period) was used to determine demographic and clinical characteristics, as well as first-line and second-line treatments. Patients were followed for 12 months starting the day after the index date (follow-up period).TIMs included in this analysis were the following: T-cell costimulation modulator abatacept; the tumor necrosis factor inhibitor (TNFi) medications adalimumab, certolizumab pegol, etanercept, golimumab, and infliximab; the interleukin-6 receptor blocker tocilizumab; and the Janus kinase (JAK) inhibitor tofacitinib.International Classification of Diseases, Ninth/Tenth Revision, Clinical Modification (ICD-9-CM or ICD-10-CM) diagnosis code  for 1 year following index date for effectively treated patients. Health care costs were attributable to RA if there was an RA diagnosis code in any position of a nondiagnostic outpatient medical claim. For hospitalizations, the entire cost was attributable to RA if RA was the primary discharge diagnosis. RA-related medications included conventional disease-modifying antirheumatic drugs (DMARDs) and TIMs.Study outcomes included the percentage of patients considered effectively treated for each TIM and RA-related costs per effectively treated patients. Treatment effectiveness was assessed using the validated claims-based effectiveness algorithm.The algorithm is composed of 6 criteria. Treatment effectiveness was defined as the absence of all of the events listed below during the period from index date through the end of the 12-month follow-up period.Nonadherence. For self-administered drugs  and tofacitinib, nonadherence was defined as medication possession ratio (MPR) of ≤ 80%. MPR was calculated as the total days supply for the index therapy divided by the total follow-up days (365 days fixed follow-up period). If a patient refilled a medication before the previous days supply running out, the days supply was extended for a maximum of 14 days . For infused drugs , a proportion of days covered (PDC) of ≤ 80% was calculated using the expected duration of clinical benefit. For the infused drug infliximab, nonadherence was defined as too few infusions corresponding to the lower end of the permissible dosing schedule during the follow-up period.Increased index medication dose. The threshold for index medication dose increase was defined separately for each medication. For self-administered drugs  and tofacitinib, an increase in index biologic dose was measured by calculating a daily dose for every claim for the index drug during the 12-month follow-up period and comparing that value with the daily dose of the index claim. The patient was categorized as having an increased dose if a subsequent claim had a daily dose greater than the index claim (daily dose = [strength × quantity]/days supply). For infused drugs , an increase in index biologic dose was measured by calculating the cost per unit of the last claim for the index drug during the 12-month follow-up period and comparing that value with the cost per unit on the index claim. If the last claim had a cost per unit that was greater than the index claim, the patient was categorized as having a dose increase .Addition of a conventional DMARD. Adding a conventional DMARD  was defined as the new use of a conventional DMARD .Switch of biologic medications. If a patient had a claim for a biologic that was different than the index drug, they were categorized as having switched treatments. The biologics that were used to determine a switch in therapy included abatacept, adalimumab, anakinra, certolizumab pegol, golimumab, infliximab, rituximab, tocilizumab, and tofacitinib .Addition of glucocorticoid or increased glucocorticoid dose ≥ 20% . If patients had no prescription for an oral glucocorticoid in the baseline period, they were categorized as adding or initiating an oral glucocorticoid if they had > 30 days of cumulative oral glucocorticoid use between day 91 after index and the end of the 12-month follow-up period. The dose increase of oral glucocorticoid was measured in patients who had claims for oral glucocorticoids in the baseline period. Dose increase was defined by capturing the cumulative dose of all glucocorticoid claims during the baseline period and comparing it with the 6 months before the end of the 12-month follow-up period. If the cumulative dose in the second 6 months was ≥ 120% of the cumulative dose in the baseline period, the patient was categorized as having a dose increase.Receipt of ≥ 2 intra-articular injections in 1 year. If a patient had ≥ 2 procedure codes for a joint injection on different days between day 91 after index and the end of the 12-month follow-up period, they were categorized as having excessive parenteral or intra-articular joint injections.Each criterion was captured independently, so a patient could fail as few as 0 or as many as 6 criteria. Patients were considered effectively treated if they did not meet any of the 6 criteria in the algorithm during the 12-month follow-up period and were considered noneffectively treated if they failed ≥ 1 of the 6 criteria.A total of 14,775 patients were eligible to be included in the analysis . The meaFor patients receiving first-line therapy, the golimumab and etanercept cohorts had the highest percentages of effectively treated patients , followed by adalimumab and tocilizumab (30.9% each). The certolizumab pegol and infliximab cohorts had the lowest percentages of effectively treated patients , followed by etanercept  and golimumab  and new RA medications (tocilizumab and tofacitinib). We found that the golimumab, etanercept, adalimumab, and tocilizumab cohorts seemed to have the highest percentages of effectively treated patients for first-line therapy, and etanercept and tocilizumab cohorts were highest for second-line therapies based on the algorithm. One-year total mean RA-related costs per effectively treated patient were variable, and except for etanercept, costs per effectively treated patients for second-line therapy were higher than costs per effectively treated patients for first-line therapy for each medication.11 This update to previous studies showed that effectiveness of these RA medications has not changed, suggesting that the older medications retain their effectiveness and that the availability of medications with new mechanisms of action has not hastened the need to switch therapy. For those patients who fail effectiveness criteria, older medications and newer medications offer effective alternative options. Effectiveness of second-line therapies for RA has not been extensively studied; however, it is important to understand if medications maintain effectiveness as second-line therapies in real-world settings. Similar to results from another study,12 etanercept showed greater effectiveness than other biologic medications as second-line therapy. In our study, except for etanercept, the percentage of effectively treated patients was lower when TIMs were used as second-line therapy compared with their use as first-line therapy. A study by Popp et al. (2018) pointed out that for those medications that have dose adjustment in their labeling, such as infliximab, the removal of the “no dose-escalation” criterion drastically reduced the cost per effectively treated patient.13 However, it is important to consider that the original validation of the algorithm was only done with these 6 criteria. Therefore, it is unclear how the elimination of 1 criterion may affect the measured clinical effectiveness of these medications.Rates of effective treatment in our study were similar to those reported in previous studies.15 Consistent with those studies, our study showed that, except for etanercept, second-line therapy was associated with higher 1-year total RA-related costs. Recent studies have shown that patients who switch to a TIM with a different mechanism of action than the first-line TIM are more likely to be effectively treated and have generally lower costs with second-line therapy than switching to a TIM with a similar mechanism of action.18 Future studies are warranted to examine the effectiveness and cost per effectively treated patient for cohorts that switch from one TIM to another with the same mechanism of action compared with those that switch to a TIM with a different mechanism of action.Switching RA therapy is common in clinical practice. Only 1 in 3 patients in our analysis received effective treatment with their first-line therapy in the first year based on the algorithm, which means many patients received treatment that was not effective over the first year. Studies have shown that failure to respond to an RA therapy is associated with higher costs, including all-cause and RA-related costs.This study was subject to the usual limitations of a claims-based analysis, including the potential for miscoding. The patient population consisted of individuals with commercial health coverage or private Medicare supplemental coverage; therefore, the results might not be generalizable to RA patients with other types of insurance or without health insurance coverage. Since claims data do not contain disease severity indicators, our analysis could not entirely discard selection bias from the results. Costs did not include rebates or other cost offsets. Our study looked at effectiveness using a claims-based algorithm that was validated for first-line medication use only; therefore, the validity of our effectiveness and cost per effectively treated results for second-line patients may be limited. The population of patients receiving second-line therapy was small, and results should be interpreted with caution.This updated analysis of administrative claims data showed that the range of effectiveness of first-line TIMs in real-world practice was higher for certain TNFis and tocilizumab. In contrast to the other TIMs, etanercept, infliximab, and tocilizumab had a similar percentage of effectively treated patients for first-line and second-line therapies, whereas other TIMs had lower rates for second-line therapy. Similarly, only etanercept demonstrated lower 1-year mean total RA-related costs per effectively treated patient, with second-line therapy compared with first-line therapy. The results from this study should assist payers with evaluating effectiveness and costs of currently used TIMs for RA.


History of maltreatment was assessed at baseline (Childhood Trauma Questionnaire), and depressive symptoms (Beck Depression Inventory-II) and eating behavior (Dutch Eating Behavior Questionnaire) were assessed at all time points. Participants’ mean age and median BMI were 45.1 ± 11.7 years and 46.7 (IQR 42.4–51.9) kg/m2, respectively. Histories of emotional (EA), physical (PA) and sexual abuse (SA) and emotional (EN) and physical (PN) neglect were reported by 47.7%, 25.2%, 39.6%, 51.4% and 40.5%, respectively, with 78.4% reporting at least one form of maltreatment. Changes in weight and depressive symptoms were not different between patients with vs. without a history of maltreatment. However, those with vs. without SA demonstrated limited changes in emotional eating (EE) at 12 M, while those without showed improvements. Conversely, patients with vs. without EN showed greater improvements in external eating (ExE) at 6 M, but differences were no longer observed by 12 M. Results indicate that histories of SA and EN are associated with changes in eating behaviors post-BS and have implications for assessment, monitoring and potential intervention development.We aimed to explore the relationships between childhood maltreatment and changes in weight, depressive symptoms and eating behavior post-bariatric surgery (BS). Participants ( Bariatric surgery (BS) is currently the most effective long-term treatment for severe obesity and its related co-morbidities . HoweverThe REsearch on Bariatric care for Obesity tReatmeNt (REBORN) study is a longitudinal study that assesses adult patients undergoing BS through an ongoing prospective longitudinal study. Patients who were scheduled for a primary BS at a single university bariatric center were approached to participate in REBORN and completed all assessments on site on the day of their clinic visits. For the purpose of the current study, a retrospective analysis of the prospective data from the REBORN database was performed.The research institution’s ethics board ) approved the study protocol (REB# 2015-1176), and informed consent was obtained from all study participants prior to participation. Recruitment and data collection procedures of the study were in place to maintain patient confidentiality, which was detailed in the consent form.Participants’ inclusion criteria for the REBORN study were being admitted for BS (any type) within the university bariatric center, and the exclusion criteria were having had a previous BS. For the purpose of the current report, participants from the REBORN study who were 18 years old and older and completed all items of the Childhood Trauma Questionnaire (CTQ) at baseline were included.n = 111) were included in the current report. Baseline sociodemographic characteristics of those who completed the CTQ (n = 111) and those who did not (n = 486) indicated no significant differences between these groups  and 6 months (6 M) and 12 months post-surgery (12 M). Measures were completed at all time points, except for the CTQ which was administrated only at baseline. Baseline and 6 M assessments were conducted in person on site on the day of their clinic visits, and 12 M assessments were conducted online or by phone.2.Weight was measured on a digital medical scale and height was measured by a stadiometer, as well as being self-reported (prior to measurement). These measures were taken at baseline and at 6 M post-surgery; however, only self-reported measures were obtained at 12 M. A sensitivity analysis conducted to validate the accuracy of these self-reported measures in our cohort showed sufficient agreement between the self-reported and the measured anthropometric measures see , as repoThe CTQ is a self-rating instrument that retrospectively assesses maltreatment during childhood and adolescence. It consists of 28 items, 25 of which are attributed to 5 sub-scales of childhood maltreatment: sexual abuse (SA); physical abuse (PA); emotional abuse (EA); emotional neglect (EN); and physical neglect (PN). An additional three items measure the minimization/denial of the trauma ,26,27. TThe Beck Depression Inventory-II (BDI-II) is a 21-item self-report questionnaire that measures depressive symptomatology, in which patients rate the severity of depressive symptoms during the previous 2 weeks on a 4-point scale ranging from 0 to 3 ,31. TotaThe Dutch Eating Behavior Questionnaire (DEBQ) evaluates emotional eating (EE), external eating (ExE) and restrained eating (RE) behaviors and is composed of 33 items that are evaluated by a 5-point Likert-like scale (ranging from never to very often) ,35. The p < 0.05 for all analyses. If normality was rejected by the Kolmogorov–Smirnov test, non-parametric tests were used. Continuous variables are presented as means ± standard deviation (SD) or median and interquartile range (IQR), as appropriate, and dichotomous/categorical variables as proportions. In a first step, descriptive statistics at baseline were calculated to characterize the sample in terms of sociodemographic characteristics as well as anthropometrics, eating behaviors, depressive symptoms and prevalence rates of different forms of childhood maltreatment. Comparisons between groups of their continuous variables were carried out using either the independent-samples t-test or the Mann–Whitney test, while comparisons between dichotomous or categorical variables were assessed using the Pearson chi-square (x2) test. The impact of childhood maltreatment on the course of weight loss outcomes, eating behaviors and depressive symptom scores at 6 M and 12 M after BS was analyzed with linear mixed models with repeated measures. Post-operative BMI, %EWL, eating behaviors and depressive symptom scores were included as dependent variables and time (baseline (pre-surgery), 6 M follow-up, 12 M follow-up) and childhood maltreatment  as fixed factors. These models were adjusted for sociodemographic variables , surgery type and baseline BMI.Statistical analyses were conducted using both SPSS and R statistical (ggplot package) programs. The significance threshold was n = 111) underwent either sleeve gastrectomy (SG) (n = 98), Roux-en-Y gastric bypass (RYGB) (n = 10) or single anastomosis duodeno-ileal bypass with sleeve gastrectomy (SADI) (n = 3). The mean age and median BMI of participants were 45.1 ± 11.7 years and 46.7 (IQR of 42.4–51.9) kg/m2, respectively, and this sample included 84.7% (n = 94) females. Baseline characteristics of the total sample and according to sex are reported in Table S2, respectively. Prior to BS, females had lower rates of type 2 diabetes, hypercholesterolemia and reduced BMI compared to males and higher scores on the emotional eating and CTQ sexual abuse sub-scales  decreased significantly over time from pre- to post-surgery for all patients . There wThis study is among the few that have simultaneously evaluated the prospective impact of childhood maltreatment on three important BS outcomes, i.e., changes in weight, depressive symptoms and eating behaviors from pre- to post-surgery. The high number of patients who experienced at least one form of abuse or neglect in our sample (nearly 80% of patients) is quite striking. Nonetheless, previous reports in bariatric candidates living with severe obesity ranged from 66–70% ,17,37, wDespite being related to changes in eating behaviors, a history of childhood maltreatment was not associated with post-surgery weight outcomes. While it is difficult to compare across available studies due to the variability in methods and study populations, our results add to the previous literature, showing that childhood maltreatment may not impact weight loss after BS , at leasAlthough weight loss is the most commonly reported BS outcome, it is important to consider other post-operative outcomes that may directly or indirectly influence weight changes post-BS. Several studies to date have found significant relationships between a history of abuse and neglect and non-weight-related outcomes, including eating psychopathology, depressive symptoms and even inpatient hospitalizations . Our resUnfortunately, we were limited by the sample size and the relatively short length of follow-up to be able to test some more advanced associations  that could have shed light on the nature of the relationships between varied factors, i.e., eating behaviors, depression course and weight measures, in relation to a history of childhood maltreatment. Nevertheless, taken together with our findings, the available literature suggests that there may be differences between the type of maltreatment and the dynamics of problematic eating behaviors and their associations with pre- and post-operative weight and mental health status. This highlights a need for future studies with larger sample sizes and longer follow-ups to disentangle the mechanisms linking childhood maltreatment to obesity ,35 and hIn the current study, depressive symptom scores were demonstrated to be higher at all time points among participants exposed to all types of maltreatment except for PN. The results of other studies that examined the association of childhood maltreatment with post-operative depressive symptoms are mixed , but a nThis study had some limitations, including evaluation by self-report measures without a psychiatric interview and the lack of data on psychiatric co-morbidities and other potentially important eating disorder diagnoses . Moreover, this study was not able to assess moderation and/or mediation models or undertake potential sub-group analyses to examine the interactions between different factors that could explain the relationships and process between childhood maltreatment, psychological factors and BS outcomes. Nevertheless, the current study had a number of notable strengths. First, it included validated measures of childhood maltreatment, depressive symptoms and eating behaviors. With the exception of the PN scale, the internal consistency of all other instruments used and their sub-scales within our sample was robust. A second strength is the prospective nature of this study design and a follow-up that extended to 12 M post-surgery. Third, the majority of published research on childhood maltreatment and BS has focused on the pre-surgical period, and on SA specifically, and as such, this study adds to the extant literature by focusing on several types of maltreatment. Fourth, in contrast to previous studies in this field, we were able to adjust for some important confounding factors  in our multivariate models. Finally, though we had a relatively small sample who completed the CTQ, there did not seem to be a selection bias with our cohort (see In conclusion, our results indicate that childhood maltreatment does not have a significant effect on 12-month weight changes after BS. However, given the extremely high prevalence of childhood maltreatment experienced by bariatric patients and their associations with both pre- and post-BS eating behaviors and depressive symptoms, a history of maltreatment may have important clinical implications, including playing a role in the etiology of dysfunctional eating behavior, which may reflect a maladaptive coping mechanism for abuse .The inclusion of a broader set of psychological assessments, continued monitoring and the development of psychological interventions seem essential to support patients’ adaptive recovery from abuse and the adoption of healthier eating patterns after surgery.Future prospective studies with larger sample sizes and longer follow-ups are needed to disentangle the mechanisms linking childhood maltreatment to obesity and how these are impacted by BS.


COVID-19 mass vaccination is the only hopeful savior to curb the pandemic. Vaccine distribution to achieve herd immunity is hindered by hesitance and negative attitude of the public against COVID-19 vaccination. This study aims to evaluate the vaccine hesitancy and attitudes in major cities in Pakistan as well as their determinants.A cross-sectional telephonic survey was conducted in June 2021 in major cities of Pakistan including Karachi, Lahore, Islamabad, Peshawar, and Gilgit, from unvaccinated urban population aged 18 years or older. Random Digit Dialing through multi-stage stratified random sampling was used to ensure representation of each target city and socio-economic classes. Questionnaire collected information on socio-demographics, COVID-19-related experiences, risk perception of infection, and receptivity of COVID-19 vaccination. Multivariate logistic regression analyses were performed to identify key determinants of vaccine hesitancy and acceptance.n = 284, 36%) and concerns with ‘vaccine safety and side effects’ , while most reported vaccine motivation reasons were ‘health safety’  and ‘to end the pandemic’ .The prevalence of vaccinated population in this survey was 15%. Of the 2270 respondents, 65% respondents were willing to vaccinate, while only 19% were registered for vaccination. Factors significantly associated with vaccine willingness were older age , tertiary education , being employed , perceived risk of COVID-19 , and higher compliance with standard operating procedures . The most common vaccine hesitancy reasons were ‘no need’ (Although our study found 35% hesitancy rate of COVID-19 vaccine, there were noticeable demographic differences that suggest tailored communication strategy to address concerns held by most hesitant subpopulation. Use of mobile vaccination facilities particularly for less mobile and disadvantaged, and implementation and evaluation of social mobilization strategy should be considered to increase overall COVID-19 vaccination acceptance and coverage.The online version contains supplementary material available at 10.1186/s12889-023-15905-3. COVID-19 emerged as one of the biggest health and humanitarian crises in recent times and persists with resurgent waves . Until rThe availability of COVID-19 vaccines from late 2020 onwards opened up the possibility of curbing the epidemic by rapidly inducing immunity in societies through mass vaccinations. Researchers have estimated that, depending on the efficacy of the vaccine being used, 60–80% of a population needs to be vaccinated to control transmission , 5. ConvHowever, the expedited development and approval process for new vaccines has fueled doubts about their safety and efficacy . The facPopulations residing in low- and middle-income countries have expressed considerable vaccine hesitancy of 38% due to mistrust and fears of potential side effects . Such ferd month. Since COVID-19 is an epidemic of proximity that has mainly affected populous cities [This study was conducted in June 2021, when Pakistan’s vaccination effort was in its 3s cities , our stus cities –18.This study explored the intent of individuals in Pakistani cities to receive COVID-19 vaccination and assess factors associated with acceptance or refusal of the COVID-19 vaccine, in order to better inform the ongoing vaccination campaign. Given constraints of collecting data during an upsurge in viral transmission at the time of study design (but not necessarily during data collection), data were collected randomly through telephonic interviews.A cross-sectional survey was conducted via telephone during June 2021 in five densest urban centers of Pakistan: Karachi, Lahore, Islamabad, Peshawar, and Gilgit. All unvaccinated urban individuals that were aware of COVID-19 and its vaccination drive in Pakistan, residing in these five cities, and aged 18 years or older were eligible to participate. Those who refused to participate in the study or did not consent were automatically excluded from the study. Those who were already vaccinated, unaware of COVID-19 or unaware of Pakistan’s vaccination program, were also excluded from the study.Our final sample comprised of 2270 individuals from Karachi (750), Lahore (650), Islamabad (385), Peshawar (385), and Gilgit 100)  compliance, sources of COVID-19 information , knowledge/awareness of the available vaccines, and willingness to accept COVID-19 vaccination. The complete questionnaire is provided in Supplementary Material (Table S1). Prior to implementation, the survey questionnaire was pilot-tested among 25 respondents  with assumed similar characteristics to our sample. The questionnaire was improved for internal validity where issues arose.P (defined as the probability of success) took a value of 1 if an individual responded ‘Yes’ to the question ‘Would you be willing to take COVID-19 vaccine offered by the government?’ and 0 otherwise for model 1. Furthermore, in model 2, P took a value of 1 if the answer to ‘Have you registered for COVID-19 vaccination?’ was a ‘Yes’ and 0 otherwise. The independent variables were same for both models which included socio-demographic characteristics , risk perception of COVID-19, prior self- or family infection of COVID-19, and SOPs compliance score.Sociodemographic characteristics of respondents were expressed as frequencies and percentages. Reasons for vaccine willingness and hesitancy were also reported descriptively. Odds ratios adjusted for sex, age group, education level, and occupation were calculated for socioeconomic status, sources of information, risk perception of COVID-19, prior self- or family experience with COVID-19 and SOP compliance score. Determinants of vaccine acceptance and registration to receive vaccinations by respondents were modelled using multivariate logistic regression analysis since the dependent variables were binary in nature. We estimated two multivariate logistic regression models with heteroskedasticity-adjusted robust standard errors:Post-stratification weights were computed in all regression analyses to match the distribution of population among cities with the target proportions from most recent census data. Stata 17 software was used for statistical analysis.n = 2,337) declined to participate in the study and 19%  did not complete the survey. Of the remaining 6,648 respondents, 4,378 did not meet the inclusion criteria  were either uneducated or educated less than the primary (Grade 5) level. Majority of the respondents were working (67%), and 45% were from lower or lower-middle socioeconomic strata  or higher (17%); only 16% (Television (55%) and social media (37%) were the leading sources of information about COVID-19, related preventive measures, and vaccines. Information from workplace or educational institutions, radios, and religious leaders was mentioned by < 1% respondents. This pattern was similar across all cities.Lived experience of COVID-19 infection was uncommon. Only 3.5% of respondents reported having experienced the infection themselves and 5% reported it in a family member. Only 1% reported hospitalization for themselves or a family member. Experience of COVID-19 infection was more frequent in Islamabad (6% for self and 11% for a family member) and Peshawar (7% and 9% respectively).n = 109) believed COVID-19 poses no risk. Most respondents reported they were either moderately (31%) or highly compliant with government recommended SOPs for public gatherings (55%)  respondents believed COVID-19 is an extreme risk to the community, while only 5% (%) Table .Table 2SAmong 6,648 respondents who participated in the survey  and 75% of those that were willing to receive the vaccine had not yet registered to receive it. Those registered to receive vaccination were more likely 51–60 years old, had tertiary education, had previously experienced COVID-19, and described themselves as highly compliant with SOPs. They also reported having seen information about vaccination on the internet/social media or had received a call or SMS text about it  or were unsure , 36% felt that they did not need vaccination and 31% were concerned about vaccine safety or side effects. Among those who intended to receive the vaccine, 70% did so to protect their own health, while 24% wanted to help curb the pandemic . Despite the high refusal and ineligibility, our sample corresponded to the socio-demographic distribution of the population, and we ensured weightage during analysis to account for the city-wise population and socioeconomic distribution.We suggest several concrete policy implications in Pakistan. Firstly, communication strategy focusing on youth and women, is important to address overall COVID-19 vaccination hesitancy. Messages should be tailored to address concerns regarding vaccine safety, side-effects, myth busting and importance of vaccination in youth. Secondly, to combat possible difficulty in registration and access to centers for older adults, mobile vaccination vans should be exploited, and national volunteer networks should be engaged to assist older adults in vaccination registration. Thirdly, involvement of government institutes is highly necessary in influencing the public. This urges the frequency in releasing updated statistic on the current burden of COVID-19 and the current vaccinated individuals in the country to further motivate others to increase willingness and registration for the COVID-19 vaccine. Lastly, respondents’ reliance on health workers, social media, friends, and families as information sources imply leveraging general pro-vaccination stance to increase COVID-19 vaccination uptake. Engaging local health workers, insisting them to share credible vaccination experiences, asserting celebrities’ endorsement could be effective social signals in driving positive shift of social norms towards greater vaccination acceptance.Our findings suggest several policy implications in Pakistan. Since there are no particular myths or misconception-based reservations to vaccination, communication must focus on promoting the value of vaccination rather than to overcome fears. More importantly, given the relatively (with respect to many other countries) low lived experience with the virus in many communities, perhaps a community-based approach, for example, mobile outreach may be applied to low-caseload communities. This may also help vaccinate women who tend to have lower mobility and access to healthcare. The approach would also suggest the need to include community organizations and grass-root workers in mobilizing the vaccination effort. Future research may include a formal evaluation of how effective each of these approaches is in overcoming hesitancy and mobilizing for vaccinations.Additional file 1: Table S1. Survey tool used in the study.


The COVID-19 pandemic overwhelmed the capacity of health facilities globally, emphasizing the need for readiness to respond to rapid increases in cases. The first wave of COVID-19 in Uganda peaked in late 2020 and demonstrated challenges with facility readiness to manage cases. The second wave began in May 2021. In June 2021, we assessed the readiness of health facilities in Uganda to manage the second wave of COVID-19.Referral hospitals managed severe COVID-19 patients, while lower-level health facilities screened, isolated, and managed mild cases. We assessed 17 of 20 referral hospitals in Uganda and 71 of 3,107 lower-level health facilities, selected using multistage sampling. We interviewed health facility heads in person about case management, coordination and communication and reporting, and preparation for the surge of COVID-19 during first and the start of the second waves of COVID-19, inspected COVID-19 treatment units (CTUs) and other service delivery points. We used an observational checklist to evaluate capacity in infection prevention, medicines, personal protective equipment (PPE), and CTU surge capacity. We used the “ReadyScore” criteria to classify readiness levels as > 80% (‘ready’), 40–80% (‘work to do’), and < 40% (‘not ready’) and tailored the assessments to the health facility level. Scores for the lower-level health facilities were weighted to approximate representativeness for their health facility type in Uganda.The median (interquartile range (IQR)) readiness scores were: 39%  for all health facilities, 63%  for referral hospitals, and 32%  for lower-level facilities. Of 17 referral facilities, two (12%) were ‘ready’ and 15 (88%) were in the “work to do” category. Fourteen (82%) had an inadequate supply of medicines, 12 (71%) lacked adequate supply of oxygen, and 11 (65%) lacked space to expand their CTU. Fifty-five (77%) lower-level health facilities were “not ready,” and 16 (23%) were in the “work to do” category. Seventy (99%) lower-level health facilities lacked medicines, 65 (92%) lacked PPE, and 53 (73%) lacked an emergency plan for COVID-19.Few health facilities were ready to manage the second wave of COVID-19 in Uganda during June 2021. Significant gaps existed for essential medicines, PPE, oxygen, and space to expand CTUs. The Uganda Ministry of Health utilized our findings to set up additional COVID-19 wards in hospitals and deliver medicines and PPE to referral hospitals. Adequate readiness for future waves of COVID-19 requires additional support and action in Uganda. Ensuring the readiness of health facilities  to respond during public health emergencies is essential to effective epidemic management . Health In February 2020, the World Health Organisation (WHO) released a COVID-19 strategic response preparedness plan to guide health facilities in preparing for COVID-19 outbreaks . The plaFrom March 21, 2020, when the first case was reported, through approximately August 2020, Uganda registered few COVID-19 cases, mostly among travellers and their contacts . HoweverThe second wave of COVID-19 in Uganda was driven primarily by the SARS-CoV-2 Delta variant, which was concurrently causing massive outbreaks in many other countries, including neighbouring Kenya . We asseAs of November 2018, Uganda had a total of 6,937 health facilities, including public, private not-for-profit, and private for-profit facilities . Of thesWe selected all 17 referral health facilities, including three national referral hospitals (NRH) and 14 regional referral hospitals (RRH) that were managing COVID-19. We selected 71 lower-level health facilities using multistage sampling. First, we randomly divided the country into seven subregions and selected two districts from each: one with and the other without a referral health facility. From each district, we listed all the health facilities and randomly selected one general hospital (GH), one health centre IV (HC IV), two health centres III (HC III), and two health centres II (HC II).We conducted in-person interviews with each health facility head or CTU visited about COVID-19 response challenges in their health facilities.We interviewed heads of health facilities using a structured questionnaire. We obtained information on the first and the start of the second waves of COVID-19 in relation to case management, coordination and communication and reporting, and preparation for the surge of COVID-19. We conducted on-site inspection of the CTUs and other service delivery points in the health facility using a readiness assessment tool developed by the US Centers for Disease Control and Prevention (CDC) for non-US health care settings and revised to suit Uganda’s situation . We asseWe imported clean data into EpiInfo version 7 for analysis. We assigned a value of one to a “Yes” response and a zero to a “No” response and computed readiness scores for each health facility as the proportion of the responses that were “Yes”. We determined a facility’s level of readiness using the “ReadyScore” criteria . The criWe used weighted analysis for lower-level health facilities, basing the weights on the strata  and the representation of the selected facilities, by facility level, within each stratum. For example, weights for HC II in districts with referral hospitals were calculated based on the total number of HC II and the number of HC II selected within those districts. We used complex sample frequencies in Epi-Info to obtain percentages of each variable. We used QGIS software to map the geographical distribution of the health facilities visited.The 88 health facilities assessed were widely distributed across the country Fig. . At the The overall median  readiness score for all health facilities was 39% IQR: 27, 51%). The median readiness score in referral facilities was 63% , while the weighted median score for lower-level facilities was 32% . Of the 17 referral facilities, only two (12%), both regional referral hospitals, were “ready”, while 15 (88%) were in the “work to do” category. Fifty-five (77%) lower-level health facilities were in the “not ready” category  knew their maximum capacity in the event of a surge of COVID-19 cases. However, 11 (65%) reported that they could not identify additional space to accommodate expanding numbers of COVID-19 patients if needed, and 12 (71%) did not include in their plans the option to stop non-essential services in case of an overwhelming surge of COVID-19 cases  lower-level health facilities lacked emergency response plans for COVID-19. Communication and reporting were poor in lower-level health facilities; 29 (48%) lacked personnel designated to report suspected or confirmed cases of COVID-19  lower-level health facilities reported that their health workers did not receive COVID-19 training. Triage for respiratory patients was lacking in lower-level health facilities and some referral health facilities; in addition, 59 (82%) of the lower-level health facilities and 8 (47%) referral facilities lacked a physical barrier to separate health workers and patients during the patient review. Fifty-four (76%) lower-level health facilities and two (29%) referral hospitals lacked areas to isolate patients with acute respiratory symptoms  than heads at lower-level health facilities  knew how to estimate the critical PPE supply consumption rate. In relation to the number of COVID-19 patients admitted at the time of assessment, 14 (82%) referral health facilities lacked essential medicines, nine (53%) lacked adequate PPE appropriate for COVID-19, and 12 (71%) did not have adequate oxygen supply and cylinders. Among lower-level facilities, all but one  lacked medicines, and most  had inadequate PPE supplies  was below the recommended target score of at least 80% . Scores We observed that most health facilities lacked triaging systems and triage staffing. At the beginning of the pandemic, WHO recommended that all health facilities have COVID-19 triaging stations, irrespective of the health facility level, to improve the identification of possible cases before they entered facilities and potentially spread infection . A triagTwo-thirds of health facilities admitting COVID-19 patients in our study lacked extra space for admitting more COVID-19 patients in case of a surge. In other countries, such challenges led to some health facilities utilising other wards, such as emergency departments, to manage COVID-19 patients, while others turned away COVID-19 patients . SimilarAccording to WHO, at least 80% of COVID-19 cases are mild and can be managed as outpatients . HoweverThere were some limitations in the assessment. Responders may have been biased to seem more prepared than they were, or even less prepared in order to advocate for additional support such as training staff. In addition, due to variabilities in training and supply of essential medicines and PPE across the health facilities, it was challenging to attribute the gaps in specific facilities to specific causes. We were un able to reach the anticipated number of lower level health facilities due to some districts missing particular levels of health facilities. Nevertheless, we subjected our calculations to weighting to cater for the differences in the health facilities.Few health facilities were ready to manage COVID-19, necessitating additional support from the Government of Uganda and other supporting partners. Major gaps were in essential drugs, PPEs, and oxygen, and the capacity to admit more COVID-19 patients. We presented our findings to the MoH, and the incident management team utilized them to support the health facilities in the response. In addition, the findings from the survey were utilised by the MoH to plan for the possible future COVID-19 case surges: for example, more oxygen cylinders were procured for the health facilities to prevent oxygen shortages during other surges. The National Medical Stores made an emergency supply of medicines and personal protective equipment to the under-equipped referral hospitals. Also, an isolation ward was created at Kiruddu National Referral Hospital to separate COVID-19 patients from those with other medical conditions. Infection prevention and control were strengthened and respiratory areas were created in health facilities across the country.


Nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) is a rare lymphoma entity accounting for ≈5% of all Hodgkin lymphoma (HL) cases. Since pathological characteristics and clinical presentation of NLPHL differ from classical HL and often resemble indolent B-cell non-Hodgkin lymphoma (B-NHL), nodular lymphocyte-predominant B-cell lymphoma has been proposed as an alternative name. In recent years, NLPHL has increasingly been treated with B-NHL-directed approaches, although more data are available on HL-directed treatment strategies. Overall, the outcomes of NLPHL patients are excellent, and the excess mortality in comparison with the general population is low. Future research in NLPHL will thus aim to determine strategies to reduce treatment intensity whenever possible. The definition of the optimal use of HL-directed and B-NHL-directed approaches in this disease is also pending.Nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) is a rare B cell-derived lymphoma entity accounting for ≈5% of all Hodgkin lymphoma (HL) cases. In recent decades, patients with newly diagnosed NLPHL have usually been treated very similarly to classical HL (cHL). The 10-year overall survival rates with HL-directed approaches are in excess of 90%. However, pathological and clinical characteristics of NLPHL resemble indolent B-cell non-Hodgkin lymphoma (B-NHL) in some aspects. Thus, nodular lymphocyte-predominant B-cell lymphoma has been proposed as an alternative name, and the use of B-NHL-directed treatment strategies has become more common in NLPHL despite limited data. Given the often indolent clinical course of NLPHL, even in the case of relapse, the majority of patients with disease recurrence do not require high-dose chemotherapy and autologous stem cell transplantation but are treated sufficiently with low-intensity approaches such as single-agent anti-CD20 antibody treatment. The establishment of novel prognostic scores for NLPHL patients may optimize risk group and treatment allocation in newly diagnosed and relapsed disease. Nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) is a rare B-cell lymphoma with an incidence of approximately 0.1–0.2/100.000/year. Roughly 75% of patients are male, and the median age at initial diagnosis is around 40 years . . 26]. Standard approaches in the treatment of advanced cHL have also been applied in individuals with advanced NLPHL. However, the most common chemotherapy protocols in advanced cHL, i.e., ABVD and escalated BEACOPP, may not be optimal for the treatment of advanced NLPHL for different reasons. NLPHL patients treated with ABVD have a higher lymphoma recurrence rate than their counterparts with cHL. According to a matched-pair analysis including 42 patients with advanced NLPHL and 84 patients with advanced cHL mostly treated with ABVD or ABVD-like protocols, the time to progression, defined as the time from the date of diagnosis to the date of relapse or death from any lymphoma, was significantly impaired for patients with NLPHL due to an increased rate of lymphoma recurrence with either NLPHL histology or histological transformation into aggressive B-NHL . In contData on outcomes of NLPHL patients treated with rituximab either alone or in combination with conventional chemotherapy have become available in recent years.A phase II study conducted by the GHSG aimed at minimizing the risk for the development of toxicities in patients with stage IA NLPHL without clinical risk factors. Thus, treatment was limited to four weekly standard doses of rituximab. All 28 patients included in the study responded to treatment. No grade III/IV toxicities were reported . Howevern = 81) or chemotherapy plus rituximab (n = 112). Systemic treatment in the chemotherapy alone group consisted of ABVD in all but one patient, whereas patients in the chemotherapy plus rituximab group had either ABVD (n = 66) or CHOP  (n = 46). The 5-year PFS rate for the patients receiving rituximab-containing treatment was 89.6% and thus significantly better than for the patient group treated without rituximab (5-year PFS rate: 72.7%). Among the patients who had chemotherapy plus rituximab, no PFS difference was detected between those who had ABVD and those who had CHOP. The 5-year OS rates for patients receiving rituximab-containing and rituximab-free approaches were 98.8% and 95.0%, respectively, and did thus not differ between the groups  Outcomes of NLPHL patients receiving BR (bendamustine and rituximab) have been reported initially in a small case series comprising nine patients. Of these, seven patients had newly diagnosed disease. All patients responded to treatment. After a median observation time of 34 months, no case of relapse occurred . A folloAn analysis using the Swedish Lymphoma Registry included 158 patients who had been diagnosed with NLPHL between 2000 and 2014. It investigated trends in the use of rituximab over time. The proportion of patients receiving rituximab either alone or in combination with systemic treatment increased from 3% between 2000 and 2004 to 54% between 2010 and 2014. The increase was more pronounced in patients with stage IIB-IV disease (increase from 7% between 2000 and 2004 to 100% between 2010 and 2014) than in patients with stage I-IIA disease (increase from 2% between 2000 and 2004 to 30% between 2010 and 2014). The more frequent use of rituximab correlated with a significant improvement in terms of OS in the most recent period . HoweverPatients with NLPHL experience disease recurrence slightly more often than patients with cHL. In particular, late relapses are more common. While the prognosis of patients with late relapse is still excellent, patients with disease recurrence within 24 months from the initial NLPHL diagnosis have an impaired OS. According to an analysis from the GHSG, including 471 NLPHL patients who had stage-adapted first-line treatment within the randomized HD7-HD15 studies, patients who never developed disease recurrence or relapsed more than 24 months after the initial NLPHL diagnosis had 10-year OS rates of 93.6% and 95.9%, respectively. In contrast, the 10-year OS rate for patients with disease recurrence less than 24 months after the initial NLPHL diagnosis was only 47.1% . The timPatients with late NLPHL recurrence, low lymphoma burden, and no or little symptoms at relapse are often treated sufficiently with low-intensity approaches such as single-agent anti-CD20 antibody treatment. A small phase II study conducted by the GHSG included 15 patients with relapsed NLPHL. Treatment consisted of four weekly standard doses of rituximab. The overall response rate was 94%. After a median observation time of 63 months, the median time for disease progression was 33 months. One patient died during follow-up . A phaseIn patients with NLPHL recurrence after RT alone and in those who only had limited amounts of chemotherapy during first-line treatment, stage-adapted conventional chemotherapy optionally combined with an anti-CD20 antibody and RT can be considered as salvage treatment. Among 99 patients with relapsed NLPHL included in a retrospective analysis conducted by the GHSG, 27 had second-line treatment comprising conventional chemotherapy. The 5-year PFS and OS estimates for these patients were 68.0% and 77.8%, respectively  43]. . 43]. High-dose chemotherapy and autologous stem cell transplantation (ASCT) can be restricted to a minority of patients with relapsed NLPHL, i.e., those presenting with risk factors such as a short time interval between first-line treatment and disease recurrence. According to retrospective analyses on relapsed NLPHL from the GHSG and two large cancer centers in North America, respectively, only 31% and 20% of patients received high-dose chemotherapy followed by ASCT as second-line treatment. The 5-year PFS rates with this approach were 84.6% in the GHSG analysis and 83.0% in the analysis from North America ,44. The Approximately 10% of NLPHL patients develop histological transformation into aggressive B-NHL within 10 years from the initial lymphoma diagnosis ,13. SpleAt present, patients with early-stage NLPHL are treated with limited-field RT alone in case of stage IA disease without clinical risk factors and CMT consisting of a brief chemotherapy (two cycles of ABVD in early-stage favorable disease and four cycles in early-stage unfavorable disease) followed by limited-field consolidation RT in case of early-stage favorable and early-stage unfavorable disease, respectively. Data on the optimal use of B-NHL-directed approaches in early-stage NLPHL have not been available until now. In advanced NLPHL, first-line treatment with B-NHL-directed protocols such as R-CHOP appears more appropriate than the use of HL-directed protocols such as ABVD and escalated BEACOPP in many cases. This is due to the reduced disease control with ABVD (at least if administered without rituximab) and the often unfavorable risk–benefit ratio with escalated BEACOPP (a relevant proportion of patients may be overtreated with this intensive protocol as the extent of disease is commonly limited even in cases with advanced NLPHL). In relapsed NLPHL, treatment is chosen individually based on factors such as the time interval between the initial diagnosis and disease recurrence, prior treatment, and lymphoma and symptom burden at relapse. Future strategies in the first-line treatment of NLPHL should aim at reducing treatment intensity whenever possible while maintaining the efficacy achieved with current approaches. To this end, novel tools allowing a more precise definition of risk groups are required. Based on a refined risk group allocation that may implement clinical presentation, pathological characteristics, and imaging results, low-risk patients will ideally be treated sufficiently with few cycles of non-intensive chemotherapy or chemoimmunotherapy optionally followed by RT, whereas a small group of high-risk patients will likely receive more intensive chemotherapy supplemented by rituximab. In relapsed NLPHL, a more concise identification of the few patients who benefit from intensive salvage treatment with high-dose chemotherapy and ASCT is needed to prevent overtreatment in patients who do not necessitate intensive salvage therapy. International collaborations between study groups and other institutions are required to achieve these goals.


Rapid and accurate diagnosis of microbial keratitis (MK) could greatly improve patient outcomes. Here, we present the development of a rapid, accessible multicolour fluorescence imaging device (FluoroPi) and evaluate its performance in combination with fluorescent optical reporters (SmartProbes) to distinguish bacterial Gram status. Furthermore, we show feasibility by imaging samples obtained by corneal scrape and minimally invasive corneal impression membrane (CIM) from ex vivo porcine corneal MK models.max 488 nm); Gram positive, Merocy-Van (exmax 590 nm). We evaluated FluoroPi with bacteria (Pseudomonas aeruginosa and Staphylococcus aureus) isolated from ex vivo porcine corneal models of MK by scrape (needle) and CIM with the SmartProbes.FluoroPi was built using a Raspberry Pi single-board computer and camera, light-emitting-diodes (LEDs), and filters for white-light and fluorescent imaging, with excitation and detection of bacterial optical SmartProbes: Gram-negative, NBD-PMX , and imaging and postprocessing with FluoroPi were straightforward, confirming ease of use.FluoroPi provides <1 µm resolution and was able to readily distinguish bacteria isolated from ex vivo models of MK from tissue debris when combined with SmartProbes, retrieved by both scrape and CIM. Single bacteria could be resolved within the field of view, with limits of detection demonstrated as 10FluoroPi coupled with SmartProbes provides effective, low-cost bacterial imaging, delineating Gram-negative and Gram-positive bacteria directly sampled from a preclinical model of MK.This study provides a crucial stepping stone toward clinical translation of a rapid, minimally invasive diagnostic approach for MK. We found that sensitivity, specificity, negative predictive value, positive predictive value, and accuracy were equivalent to or better at matching gold-standard culture results compared to conventional Gram stain.––Pseudomonas aeruginosa and Staphylococcus aureus, respectively) isolated from corneal scrapes of ex vivo porcine models of MK utilizing fluorescent optical reporters 7-nitrobenz-2-oxa-1,3-diazole (NBD)-polymyxin (PMX) (exmax 488 nm)max 590 nm),We have sought to address these limitations through the development of a proof-of-concept, low-cost (comparable price point to a cell phone), dual-channel fluorescence imaging device (FluoroPi) which further combines white-light morphological imaging. The two main approaches to producing low-cost fluorescent imaging devices have been the use of a smartphone as the basis of detection,We have further explored the incorporation of a CIM with our ex vivo porcine MK models. The CIM has recently been introduced into routine clinical practice at the St. Paul's Eye Unit  and demonstrated significantly improved culture positivity rates compared to traditional scraping methodologies, attributed to enhanced sampling.An overview of the developed FluoroPi device is given in the Results section. Details of the image capture and processing methods are provided below, and the full FluoroPi device details, image postprocessing, and technical characterization, including resolution and field of view (FoV) determination, are outlined in the The samples were imaged with a commercial widefield imaging system (Leica DMI8 Basic), with bright-field, fluorescein isothiocyanate (FITC)-cube, and Texas Red–cube imaging parameters selected  and a 40× air objective. Three FoVs per sample were collected. Imaging parameters were kept consistent within experimental repeats. Images captured with the commercial system were processed with Leica LAS X software and cropped to match the imaging FoV of FluoroPi. Brightness and contrast adjustments were consistent across datasets.https://picamera.readthedocs.io/en/release-1.13/)The FluoroPi system can be operated in several imaging modes. Operating the camera via open-source Python scripts . This was done using the preview imaging mode of the system. Captured images were stored on the Raspberry Pi camera and subsequently transferred to a personal computer (PC) for postprocessing. At least three images were captured per slide. All imaging sessions were repeated independently at least three times.For each slide, the regions of interest were chosen by scanning over the sample using the Commercially available fluorescent beads were utilized to test the performance of the device. The beads included (1) Inspek green fluorescent beads , and (2) fluorescent purple particles . The bead stock solutions were vortexed prior to dilution 1:10 in sterile saline . Then, 20 µL of the diluted samples was added to glass slides, mounted with a coverslip, and sealed with clear nail polish. The beads were added to slides independently and in combination for individual and dual samples, respectively.Pseudomonas aeruginosa PA01 and Gram-positive bacteria Staphylococcus aureus ATCC25923 (planktonic bacteria experiments) and S. aureus IHMA2190153 (ex vivo porcine model experiments) were utilized for this study as representative Gram-negative and Gram-positive bacteria. Single colonies were picked from fresh Luria-Bertani (LB) agar plates and were used to inoculate 10 mL LB broth; they were grown for 16 hours with shaking (250 rpm) at 37°C. The cultures were diluted to optical density at 600 nm (OD600) = 0.1 and grown to mid-log phase (∼OD600 = 0.7). An OD600 of 1 /mL) for each strain was harvested and washed in sterile saline (Baxter) with microcentrifugation at 13,000 rpm for 1 minute. The resultant pellet was resuspended in 1 mL sterile saline. As required, bacterial samples were serially diluted 1:10 in saline within a 96-well plate to prepare bacterial samples for limit of detection testing and plating of CFU.The Gram-negative bacteria ,The NBD-PMX and Merocy-Van SmartProbes were manufactured in-house following reported protocolsn = 18) were excised and prepared based on methods previously described.,P. aeruginosa or S. aureus suspension or vehicle control was seeded onto the surface of the central cornea by pipetting and allowed to dry onto the cornea surface (n = 6 per group). Then, 3 mL of Dulbecco's modified Eagle's medium ) was added to the well with care taken not to wet the cornea. The corneas were incubated at 37°C for 18 hours, at which point corneal defects (clouding) indicating ulceration and established infections were visible  or CIM , n = 3 per group; MilliporeSigma, Burlington, MA). The visibly infected area of the cornea was scraped using a needle  to mimic clinical specimen retrieval, applied directly to a glass slide, and left to air dry. Alternatively, the infected area was sampled using a CIM by gently placing the CIM onto the cornea for 5 seconds. Then, 100 µL sterile saline was added to the CIM, mixed with the sample, and then transferred to an Eppendorf tube. Of this, 20 µL was added to a glass slide and left to air dry; 20 µL of 2.5 µM NBD-PMXAfter overnight incubation, the cornea were sampled by two methods: corneal scrape . Homogenized tissue samples and CIM samples were plated onto LB agar and incubated at 37°C overnight. The FluoroPi device A, 1B conThe resolution was found to be ∼630 nm by performing a Gaussian fit to a line profile of the smallest features of a United States Air Force (USAF) 1951 test target (2.19 µm/line) B. FurtheIn the first instance, a combination of commercial green and red microsphere beads were imaged with FluoroPi and a commercial fluorescence microscope. The commercial beads were selected for the initial validations based on their comparable size to bacteria (<2.5 µm) and similar spectral profiles to NBD-PMX (green beads) and Merocy-Van (red beads), in addition to their exhibiting high photostability and fluorescence intensity. FluoroPi was able to resolve individual beads in bright-field (white-light LED) and distinguish the two types based on their fluorescence intensity and spectral profiles . There wP. aeruginosa and S. aureus as representative Gram-negative and Gram-positive bacteria labeled with SmartProbes NBD-PMX and Merocy-Van, respectively, and compared to the commercial microscope. The SmartProbes were imaged singularly (P. aeruginosa (green) and Merocy-Van labeled only Gram-positive S. aureus (red),,3 CFU/mL for P. aeruginosa labeled with NBD-PMX and 104 CFU/mL for Merocy-Van-labeled S. aureus with FluoroPi  and S. aureus (n = 6) to represent two common bacterial pathogens isolated from clinical cases of MK.n = 6) were subject to the same epithelium damage as the MK cases (Ex vivo porcine models of MK were established with MK cases a. SampliMK cases  and a coMK cases  without n = 3) demonstrated a large amount of debris deposited onto the slides. Although the size and morphology were similar to that observed for bacteria, no fluorescence signal was detected from either SmartProbe by FluoroPi or the commercial microscope (P. aeruginosa (n = 3) and S. aureus (n = 3) MK cornea scrapes, which showed bright green (P. aeruginosa) and red (S. aureus) fluorescence across the FoVs, indicating that the Gram specificity of NBD-PMX and Merocy-Van were retained .White LED imaging of the uninfected control cornea scrapes .,,–Fluorescence microscopy is an increasingly attractive approach for the rapid detection of pathogensTypically, the development of such microscopes has been hampered by the costs associated with components such as the objectives required for submicron imaging resolution for single bacterial cell detection, as well as the availability of sensors with the required sensitivity. Here, we were able to overcome these limitations with a single mass-produced lens combined with efficient optical filtering, and we exploited recent advances in sensor technology,–3 CFU/mL for P. aeruginosa labeled with NBD-PMX and 104 CFU/mL for Merocy-Van-labeled S. aureus. Demonstrating this level of sensitivity is an important metric for characterizing FluoroPi performance because often 104 to 105 CFU/mL is a clinically relevant threshold for diagnosing an infection (vs. colonization) in a range of indications.,,The combination of dual imaging modalities, white light transmission imaging, and multicolor fluorescence imaging provides a powerful platform for validation of acquired imagery, with the co-registration of morphological and fluorescence signatures helping to reduce false-positive results due to any off-target labeling or non-fluorescent cellular debris. We have demonstrated that FluoroPi performs as well as a commercially available fluorescence microscope (which is at least an order of magnitude more expensive) and is able to resolve single bacteria along with those in aggregates from ex vivo porcine models of MK We utilized our ex vivo porcine MK models to compare scrape and CIM sampling methodologies and assess the performance of the SmartProbes with the added challenge of tissue and cellular debris, a common feature of MK smear microscopy. The two SmartProbes were added in combination to freshly prepared slide samples; the coverslips were added, and the samples were imaged within the same day. No washing or additional preparation steps were required, offering ease of workflow. Overall, much more tissue debris was transferred to the slides from scrapes compared to the CIM sampling technique. This tissue debris was only visible by white-light imaging and was not stained erroneously by the SmartProbes, confirming their specificity to Gram-positive and Gram-negative bacteria.Interestingly, the samples collected by scrape were in much larger aggregates compared to those collected by CIM. This could be attributed to the CIM being a less invasive collection technique compared to the scrape with a needle or could be attributed to the addition of saline to retrieve the sample from the CIM. Importantly, the samples collected from the ex vivo porcine corneas and labeled with NBD-PMX looked similar  to those collected from patients in a previous clinical study assessing the feasibility of the SmartProbe to label Gram-negative bacteria,To translate the FluoroPi technology, we are adapting the current prototype to a more robust, user-friendly version. This will include an on-device graphical user interface for better ease of operation, integration of the current postprocessing to enable real-time image processing, and full enclosure of the system to make it more robust. Three-dimensional printing of the enclosure, mountings, and stages, along with the use of a single power supply and LED driver (which are becoming available for the Raspberry Pi), will further greatly reduce the cost of the current version. The next iteration of the FluoroPi device will then undergo evaluation with clinical samples as part of future validation studies.P. aeruginosa and S. aureus) were successfully identified across all corneas evaluated by both sample collection techniques. The sample preparation methodology, image capture, and postprocessing are straightforward and could be performed across multiple levels of the healthcare system. Our prototype FluoroPi and optical SmartProbes demonstrate that our approach is sensitive (able to detect single bacteria) and specific for bacterial Gram status detection.We have developed and evaluated a low-cost accessible imaging platform capable of multicolor fluorescence, combined with white-light morphological imaging. The device has been shown to have the resolution to resolve single bacteria and, in conjunction with appropriate fluorescent reporters, successfully distinguish between the exemplar Gram-negative and Gram-positive bacteria at the cost point of a cell phone. We have demonstrated the feasibility of bacterial keratitis smear microscopy in an ex vivo porcine MK infection model with FluoroPi, with slides prepared by both conventional corneal scrape, and a less invasive approach with CIM for sample retrieval. The Gram statuses of the model bacteria (