Thank you. Thank you very much, everyone, for coming, and thank you so much for the organizers and the moderator today. My name is Diego Maselli. I'm from the University of Texas in San Antonio, and it's a pleasure to present this project. This is a lung function with an eosinophilic phenotype, and this is analysis of the bronchiectasis U.S. registry, and I'm presenting on behalf of the investigators and my co-authors as well. My name is Diego Maselli again. For disclosures, I have no relevant specific disclosures for this talk. So as you know, there's a lot of buzz about bronchiectasis in general over the past couple of years, but now there's also a buzz about these subtypes of different types of bronchiectasis, particularly the eosinophilic phenotype has been under discussions over the past year or so. As we remember, when we read about bronchiectasis, we always hear about that neutrophilic predominant type of disease, but we know that there's a subtype of patients that may have different types of inflammatory patterns. Last year, as part of EMBARQ, the large registry bronchiectasis in Europe, they published in the Blue Journal an analysis that showed that around one-fifth of the patients in the registry had that eosinophilic phenotype, although there was no association specifically to exacerbations when they did a subgroup kind of analysis of another cohort, the PROMIS cohort, which is, they looked at patients that were infected with Pseudomonas at a different trial. They noticed that patients that had an eosinophilic phenotype, particularly those that had more than 300 cells per microliter, had an increased risk of exacerbations. Most recently, this is data from the Spanish registry from Miguel Angel Martinez, and he looked at around 1,000 patients and looked at this phenotype, and very interestingly, he noticed this U-type of pattern, which I was surprised about. He looked at patients that had low eosinophil counts and also high eosinophil counts in relationship to inhaled corticosteroids, and what he noticed was that definitely the eosinophils have a role in some of these outcomes, particularly in this case with severity of the disease and also with exacerbations, and inhaled corticosteroids tended to blunt a little bit that part. And obviously, we have now therapies that can potentially affect these eosinophilic pathways. We have at least three approved medications. As you know, there's more out there, and there's evidence that patients with bronchiectasis can be treated potentially successfully when they have coexistent asthma in this case. This is data from the Dutch registry, again, presented very recently last month, that looked at patients that had eosinophilic bronchiectasis, bronchiectasis and asthma, and treated with IMT-L5 therapy were successful. So for that reason, our objective was to really evaluate if we can find specific characteristics using the U.S. Bronchiectasis and NTM Research Registry. The study design is a retrospective study that was conducted from the baseline characteristics of the registry. We utilized patients that had at least one eosinophil count, this is in the blood, and defined, at least in our registry, the eosinophilic phenotype was defined as those that had more than 150 cells per microliter as that definition. This is the characteristics of the cohort. The cohort as of last year, end of last year, had around 5,000 patients. The patients that had actually a eosinophil count, CVC with a differential, were around 870 patients or so, and we classified them between those that had high eosinophils, again, threshold of 150, and as we can see, around 50% of them met that criteria. And these are some of the baseline characteristics when we compare both groups. I'm going to make some highlights, which I know these are questions that people have always. The proportion of patients that had asthma or COPD were quite comparable between both groups, high eosinophils versus low eosinophils. But what was interesting is that we started to see a bit of a pattern that patients that had high eosinophils had more symptoms, respiratory symptoms, in this case fatigue and shortness of breath. And what was also interesting is that these patients also had a little bit of more incidence of use of inhaled corticosteroids, potentially because they were reactive to it and responsive to it, and they found some benefit in it. And what I thought was the most captivating part of it was that lung function in these patients was significantly lower. Those patients that have high eosinophils that we defined had lower lung function. And when we looked at the multivariate model, those patients that had high versus low FEV1, we found that patients that had that eosinophilic phenotype increased the risk of around 21% of having low lung function when you control for other factors, in this case in this model. And importantly, there was no difference of exacerbations between either group. Mainly the difference that we found using this cutoff was more symptoms and worse lung function. So obviously there's limitations in the studies. This is a retrospective design. The registry was designed not to look at eosinophilic phenotypes. It was designed to look at other things, NTM infections and other things. Some of the patients had only one measurement. That's always a criticism because as you know, sometimes there might be fluctuations in the eosinophil counts and they were not measuring during exacerbation. And with all these registries, as you know, there's some missing data that might confound. So in conclusion, we found that our patients with that eosinophilic phenotype that we defined as more than 150 cells per microliter had different characteristics, particularly with symptoms and lung function. No differences were detected with exacerbations. But we continue to see that these patients, although perhaps not as frequent as that neutrophilic phenotype, may have specific characteristics, distinct characteristics from others. Thank you so much for your attention and for the invitation. Thank you so much. Time okay? Perfect. So perfect timing. Thank you. We still have one more minute. And now Andrew has come also. I would like to thank. So any questions from the audience? So start things up because Diego has to go to another session. But I encourage you all to stay until the end of this session. No. So maybe I'll start. So Diego, tell me, in terms of the covariates of interest, why not just one-year history of exacerbations? Why put two-year history? Very good question. The registry, the database looked at two years before, so that was the model of the variable that we had available. That's the reason, yes. Okay. And can I have one question? Of course. Please. One minute. And what about the biologic therapy that we all see in asthma? How do you perspective the management of this subgroup of patients with bone criectasis? Do you think they were still the same or more are coming? Yes, yes. Definitely there's a lot of interest in this subgroup of patients. I think in clinical practice, we see it all the time that we see a patient with asthma that has a little bit of bronchiectasis here and there, particularly when it's not the primary diagnosis. We elect to sometimes treat, depending on the patient. Obviously, we do the rest of the measures that we have to do for airway clearance and all the things that we know, trying to find the underlying cause, et cetera, et cetera. But it's been shown in some subpopulations. ABPA, for example, has been effective. And my patients that have asthma slash bronchiectasis overlap, I've seen some benefits with it. And as I showed you from the Dutch registry, there's others that show that it can be effective in these patients. Okay. Thank you. Any more questions? Thank you so much. Okay. Thank you. Thank you, Diego. So now to back on the line with Ashwagosha. Pardon. So he will bring us... Nice example about temperature, climate change, and COPD hospitalizations. Hi. Good morning, everyone. Today I'd like to talk to you all about how temperature would affect COPD hospitalization. I am basically looking at the Medicare database as my population in the older adults. I'm Ashwagosha Parthasarathy. People call me Ashwa for obvious reasons. And I'm from Rutgers University in New Jersey. Yeah. So a little bit of background. I'm sure all of you know this by now. But COPD is the fourth largest cause of death in the U.S. And by 2050, we are projected to have almost 30 million people diagnosed with this disease. What makes this hard for the older adults is a compounding effect of comorbidities that they already have, age-related changes in the lung, and impaired immunity causing excess exacerbations. So yeah. Before... So I just want to set the premise for my study. The thing is that there's been a lot of studies which have been going on around exposure to temperature and various illnesses. Hypertension, diabetes, and cardiovascular diseases. There's been a lot of buzz around this area. When it comes to COPD, there has been a study done in the same population, but they just looked at heat. They did not look at the winter side of things. The reason we are currently very interested in this topic is because, as all of us know, climate change has been a big factor. And what happens with climate change is there will be polar vortex destabilization, and that would cause extreme cold snaps in the continental years. What that means is we are now experiencing, even if it is for shorter durations, harsher winters compared to the previous years. So yeah. The aim would be to assess the association between ambient temperature and COPD hospitalization during the winter months in the older Medicare population. That is the aim of the study. So the way we went about doing this is we first took the Medicare population and then we linked it with PRISM. PRISM is a database in the U.S. where they have four kilometer by four kilometer resolution data on mean, max, and minimum temperature. And they have adjusted it for elevation, coastal proximity, more than the things I've mentioned here. It's a very complex model. So what we did is we took the four into four resolution and we converted it into zip code level linkage so we can do it easier with the Medicare population. And then we took a 3% random sample. From that sample, we chose people with ICD-9 and 10 diagnosis of COPD. Yeah. The next thing I want to talk to you about is the design of the study. We used a case crossover study design. The reason we used this design is principally because this, one, this is very famous for temporal exposure and acute events. Two, here, we don't really have to control for a lot of time invariant variables. It is built in. So say, for example, a patient was diagnosed, hospitalized on a particular day, the one in the red. We would choose a case date on the same day as the week as the case, five weeks in either direction. And this would be within season, meaning from December to January. The reason we chose just December and January is it boils down to the temperature differences in the continental U.S. Because we have a really large span of land, we wanted to make sure we chose months which were the coldest across the board. We first did a descriptive analysis of our data set, and then we moved on to time trend analysis of the daily temperature over time. Then finally, we did a conditional logistic regression model to look at association. Okay. So this is an example of one of the years that we looked at. I randomly picked 2016. And each and every month, so this is basically daily temperature data which has been smoothened out. As we can see, January and December, we saw that it was the coldest out of the entire year. We did this for all the years from 2007 to 2019, and we also repeated this analysis for all the regions across the U.S. to make sure we were choosing the coldest months. Yeah. So all in all, the study population, most of them were between 65 to 85. A large population was white, and we got a higher, like, percentage of population from the south. Okay. So to the core of our analysis, right, this is the conditional logistic regression model we did. And what we saw was after 65 Fahrenheit, we saw a steady increase in the risk of hospitalization as we moved towards the colder temperatures, right? And when we binned it, we found that, like, when we collapsed it into more particular bins, we found two temperature ranges. Yeah. First, it starts at 65, and another peak is at 20. so 65 and 20 are two temperature ranges where we found to be a drastic shift and then yeah, obviously 15 and above would be the highest. Yeah, so now let's talk about evidence, like evidence regarding this topic. This is the first national level study that has been done in the US with respect to how winter months, the cold affect COPD hospitalization. A few studies have been done in the UK, which has been close to this, but not this study design, they chose a cross-sectional analysis, which has its own limitations obviously, yeah. And yeah, so why? This is multifactorial, we haven't really nailed down why exactly there is increased hospitalization with cold. It is believed to be a complex mechanism of reasons and mostly, there has been a study published in Just actually, which in young adults showed that when they were exposed to cold air at zero Fahrenheit, there was direct and reflex bronchoconstriction. Yeah, the limitations of our study, yes. One of the main limitation, which actually affects all of this design is zip code level exposure might not really be individual exposure, right? And also, the patient's zip code might be linked in the Medicare registry, but he might actually be somewhere else. That is a limitation that is in all these large database studies. We have not really incorporated air pollution, green space, humidity, and a lag model. We are on the way of doing it. This is still primary analysis. We are also making sure that we take the, basically do more than just 3% of the population. We are looking at doing it across the Medicare population. Yeah, so to conclude, exposure to temperature, oh yeah, temperature under 65, and especially below 20 would risk the exacerbation to hospitalization. Yeah, thank you. Thank you. I'm sorry, I had to tell you about one minute to go. So, any questions about? Ashbery. Yeah, stay. You can stay. Yes, we have a question. Can I ask a couple questions? So, is it, you did average temperature. Is it more temperature, acute temperature drops preceding an exacerbation, or absolute temperature? And did you look at that? We looked at absolute daily temperatures. It was not average. Okay. Yeah. And then another question. So, can you tease out circulating respiratory illnesses during the winter, if there are an increased number of respiratory illnesses, which could increase incidence of exacerbation? Oh, yeah. For now, we are only looking at COPD, right? But future, yeah, we would wanna look at other respiratory illnesses and how that affects us as well. But we haven't really gotten to that point. This is like preliminary analysis. Yeah, thank you. Hi, Elizabeth Short from MedPage Today. I noticed that the extreme weather seemed to correlate with what those regions were already experiencing. But in the last few years, with things like recent cold snaps in the south and parts of the west, do you expect these COPD results to seem a little bit more widespread regionally, since it's becoming more extreme throughout the country? Yeah, so we did do a regional analysis, and we sort of found almost the same trend. The reason I did not put this up was mainly due to time restraints. But yeah, we did see, even in the south, where it is supposed to be hotter than the rest, we saw the same trend, yeah. Thank you. Thank you. So when you pointed out the limitations of using zip code data, but it could also be a strength. And it lends itself to these GIS studies where you do mapping. And you could imagine what you can do here is some overlays of, perhaps, as the first question asked about, say, viral instance of viral infections when the data is definitely available, and that could be overlaid to that. You could also put proximity to hospitals and a variety of other things to make the data. It's very provocative, and my hat is off to you, because it's extremely timely. And becoming more and more timely that we understand this. But it also lends itself to many opportunities of layering the data to better understand it. Thank you. Thank you. Yeah, surely. Yeah. OK. Thank you. Thank you. Thank you. So we have to move on to the next presentation of Anna Gutmann about sialic acid in person solids as biomarkers of airway mucous irritation. So, hello, everyone, and thank you for having me. My name is Anna Gutmann, and I'm a Genentech employee and stakeholder. Today I will present you two methods for evaluation of airway mucosideration that might be very beneficial for patients and for drug development purposes. Mucosideration is associated with mucoobstructive lung diseases, but it is very rarely measured. So why is it so important for us to be able to evaluate this measurement? It was shown that in patients with airway mucoobstructive diseases, they have much more dehydrated and concentrated airway mucus. This means that they have higher mucin concentration, which eventually leads to formation of very thick and sticky mucus. This mucus is a main driver for the variety of the symptoms these patients have, such as, for example, decreased mucosalary clearance, increased rates of infections and inflammations. It also leads to airway remodeling and eventually to airway obstruction. Sialic acid is a surrogate for mucin concentration, and the reason for that is because mucins are highly sialiated, meaning that there is a direct correlation between mucin concentration and sialic acid concentration. It was also shown in COPD patients that sialic acid is associated with exacerbations and diagnosis of chronic bronchitis. And this is why it is so important for us to be able to evaluate this measurement. Nowadays there are methods for such evaluation, for example, mass spectrometry, which is a very good method, but it is still not available in most of the labs today. Our goal was to explore, optimize, and correlate simple methods for quantification of airway mucocidration to support more common use in clinical practices and pharmacotherapeutic trials. Today I will present you two methods. The first one would be measuring percent of solids. The way this method works is by collecting airway mucus or sputum sample. We then weigh the sample, and once we know the weight, we dehydrate it overnight. On the next day, when the sample is dry, we weigh it again. And by using both of these weights, we can calculate the percent of solids in the initial sample. As part of the optimization, the first step that was very important for us was to identify the ideal starting volume. For that, we evaluated four different volumes, 25, 50, 100, and 200 microliters. Each dot here represents one replicate that we're taking from these volumes. As you can see, the lowest variability was observed when we used 100 microliters. Using higher volumes will be challenging because, as you might know, many times when we collect airway mucus samples, the volume of the samples is very limited. Next, we evaluated both 50 microliters and 100 microliters using a secondary sample set. And as you can see, the lowest variability was observed when we used 100 microliters. And this was the volume that we decided to proceed with. Next, we wanted to identify the ideal processing method. Usually, when you collect airway mucus sample, the sample is characterized by many small individual mucus plugs. Our goal was to identify the variability between testing few of those plugs from the same sample versus pooling the plugs together, creating this one homogenous matrix and taking replicates from that matrix. Each dot here represents the average of triplicates that we're taking from each sample. As you can see, in the blue box, which is the non-pooled fraction or the individual plugs tested, the variability between the replicates was very high. It was at the average of 25.2 percent. However, when we pooled our plugs together and created this one homogenous matrix, the variability decreased dramatically to 7.8 percent. And this was the method that we decided to continue with. So now, we had our method optimized. And the next step would be to evaluate patient samples. As you can see, we evaluated both COPD and CF patients. Each dot here represents the average of triplicates that we're taking from each sample. First, I would like to point out the very low variability that we were able to get using this method. The variability is represented as the percent CV on top of the boxes. As you can see, for the COPD patient population, the variability was 5.8, and for the CF group, it was 4.9, which is very low, and it means that this method is very reproducible. Next, I would like to point out the percent of solids of those groups. It is represented in the middle in white, in the middle of the box in white color. For the COPD group, it was 3.4 percent, and for the CF group, it was 6.6 percent, which is also replicating data that was previously published in the literature. An interesting observation that we saw in the CF group was that there was one patient with relatively low percent of solids. This is the patient that is circled here in orange. When we went back and reevaluated the medical history of this patient, we saw that he was on ETI treatment. So this makes sense. So as you can see, this method is very simple to use and very reproducible. This is a two-day method, so for our goals, we wanted to also find a method that will be a bit higher throughput, and this is why we decided to evaluate sialic acid concentration. As I mentioned before, there is a direct correlation between sialic acid concentration and mucin concentration, and the way this method works was by collecting airway mucus sample. For this method, we can collect as little as 30 microliters. We then weigh the sample, and once we know the weight, we add proportional volumes of hydrolyzing reagent. Then we perform hydrolysis, neutralization, and spin down the sample to collect the supernatant. Then using the supernatant, a commercial colorimetric kit, and a plate reader, we can quantify the sialic acid concentration in the sample. Supernatant that is deriving from raw mucus will contain the total sialic acid fraction, and our goal was to evaluate the correlation between the total sialic acid fraction to the percent of solids. As you can see, there was a very good correlation of 0.9. However, it is very important to mention that many times, labs do not get the raw mucus. What they do get is a PBS wash of this mucus. PBS wash will contain the free sialic acid fraction, and we also evaluated the correlation between the free sialic acid fraction to the percent of solids, and as you can see, there was still correlation of 0.6. So to conclude, today I presented to you two methods for evaluation of airway mucus hydration. The first one was percent of solids, which is a very simple and reproducible method. It requires low volumes, and this is a two-day protocol which can be usable and suitable for small sample set and small clinical trials. Then I presented to you evaluation of sialic acid concentration, which is a plate-based method that can be performed in most, if not all, the labs, but you have to have a plate reader for that. This method requires as little as 30 microliters, and it correlated very nicely with percent of solids. This is a one-day protocol, and this can be used for larger sample sets and larger clinical trials. So to conclude, mucus hydration biomarkers can be used to identify patients who are at risk for poor outcomes, like, for example, exacerbations, and they also can be used to identify treatment response in clinical trials or drug development. I would like to thank my colleagues, Michelle and Daniel, that helped me with this project, and thank you for listening. Any questions? Hello. Good morning. I'm Vamsi Gunter from Denver. I have a question regarding, I love how you presented this. My question is if we already have stored samples, is that something from which you can work to using this technique or does this need to be a fresh sample processed fairly quickly to dehydrate? No, so you can use frozen samples as well. Okay, maybe I can get your contact info afterwards. Yes, of course. Is this equipment suitable for clinical ambulatory practice? It can be. It can be, right? Any idea about the costs? Sorry. Well, it's not supposed to be. It's pretty easy to use. It's not supposed to be that expensive. And the goal of this entire project was to allow very simple and easy to use methods, as opposed to mass spectrometry, which is a bit complicated and definitely not available in most of the clinics. Clinical practice. Yes, so this is supposed to replace it and it's much faster and much easier. I have a question about the interpatient variability. So did you do any studies where you repeated the test in short periods of time, same patient, to see if the values were similar? Or even for different phenotypes. Thank you for kind introduction, Professor Chairman. My name is Hyewon Choi from, and I'm a radiologist from Korea. This is my disclosure slide. And COPD is one of the leading causes of death and with increasing economic and social burden. So, Government recommends the active surveillance to identify the undiagnosed patient with respiratory symptoms and risk factors. But indeed, significant patient remains undiagnosed, and CT would be useful to identify the patient who need additional spirometry for early diagnosis. On chest CT, emphysema can be evaluated either visually or constatively. In visual assessments, it is classified into central lobe line and parasympathetic emphysema. And recently, Prague further divided CT finding into 10 specific CT subtypes to reflect the heterogeneous course of the disease. And in Korea, on cancer screening program, radiologists report above more than degree emphysema as significant incidental findings. But more than half of the underdiagnosed patient exhibit less than mild degree emphysema on chest CT. So we hypothesize that the subdivided CT finding is more effective for COPD screening. Emphysema quantification also proven as independent predictors, radiology factors for airflow obstruction. And recently, one study used emphysema quantification from low-dose chest CT scan in lung cancer screening participants, and they revealed a reasonable performance. Even though there are several limitations of quantification, recently, deep learning enabled the reliable quantification in various CT protocol. So it is expected the increasing use of the emphysema quantification in clinical practice. But to our knowledge, no study have compared the emphysema quantification in visual assessments for predicting airflow obstruction. So we aim to investigate the performance of the emphysema quantification in predicting airflow obstruction by comparing the visual CT assessment and also investigate the association with these clinical outcomes. This is a single-center retrospective study, and we included patients older than 60 years of age and underwent non-thoracic surgery under the general anesthesia. In our hospital, these patients required to complete the spirometry and ABGA before the surgery. Of these, we included patients who had the chest CT scan take less than three-month interval with the spirometry and had more than 30-pack-year smoking history. So 565 patients were included. We collected the following clinical data after reviewing the preoperative anesthesia evaluation form. The pulmonary function test was based on the result of the prebronchodilator spirometry. And we analyzed chest CT taken with the standard tools, and it is reconstructed with three-millimeter slice thickness using the standard soft kernel. To evaluate emphysema first, visual CT assessments was conducted by two thoracic radiologists, and they classified into seven specific subtypes, and these were no abnormality, bronchial wall thickening, mild central lobe emphysema, substantial paraceptor emphysema, and moderate to severe central lobe emphysema considering its distribution. The seven specific CT subtypes is reassigned into normal, non-moderate, and moderate to higher degree according to the emphysema grade. This is a representative case of the visual CT assessment. For emphysema quantification, we adopted the LAEA, means the percentage of the lower attenuated area under the negative 950-housefield unit. The primary outcome was air flow obstruction, and secondary outcomes were baseline hypoxia defined as the less than 80-millimeter mercury of PaO2 on ABGA and the development of the postoperative respiratory complication. The complication was re-evaluated by a pulmonologist after leaving the medical chart, and we consider positive when there is no treatment. As statistical analysis, first, we compared the baseline characteristics according to the visual CT assessment, and then conducted ROC curve analysis for predicting air flow obstruction in terms of never-evaluated radiologic parameters. And for outcomes, we did logistic regression analysis. Here are the results. Among the 565 patients, about 41.5 patients showed air flow obstruction on their prebronchodilator spirometry, but only 64 patients had the history of the COPD. Regarding CT findings, the most common findings was no abnormality, followed by bronchial wall thickening and mild central lobe emphysema. The mean LAE was 1.5%, and baseline hypoxia was found in 27% of the patients, and the postoperative complication was developed in 44 patients, accounting for about 8% of the participants. The table shows the result of spirometry and the clinical outcome according to the visual CT assessment time. And all CT abnormality shows the significant higher percentage of the air flow obstruction than no abnormality. But the instance of the hypoxia and the postoperative complication rate were not different among the visual CT subtypes. In ROC curve analysis, LAE showed the highest AUC value as the 0.75 for predicting air flow obstruction. And subdivided CT type is more higher than visual emphysema grade. And the result was consistent for predicting moderate air flow obstruction. With a cutoff of 0.5, emphysema quantification released a sensitivity of 60% and specificity of 81%. In multivariate logistic regression analysis, age, positive presence of respiratory symptom, TB history, CT abnormal types were associated with independent predictive factors for air flow obstruction. For secondary outcome, we conducted only univariate regression analysis. And the LAE shows the association with the baseline hypoxia and the development of postoperative respiratory complication. There are several limitations. First, it is retrospective single-center study. And all CT was scanned from the single vendor. And emphysema quantification was assessed using the 3mm slice thickness rather than 1mm slice thickness. And the result of the spirometry was based on the pre-bronchodilator study. One of the secondary outcomes, the baseline hypoxia should be assessed in accordance with the clinical situation. In conclusion, emphysema quantification shows the better performance than visual CD assessment in predicting air flow obstruction. And it may enhance the performance of chest CD as screening tool. And our study emphasized the potential benefit of incorporating the emphysema quantification in high-risk patients who underwent chest CD. And further studies are necessary to determine the optimal cutoff value of the LAE and its validation. Thank you for your listening. Thank you. So thank you, Chai. Any questions from the audience? So, obviously doing a CAT scan preoperatively is for most operations as a post-op tool for airway obstruction would be expensive and spirometry may be easier, less complicated, but these patients were undergoing thoracic surgery. And there's also an increasing number of patients, thankfully, who are having low-dose CT scans. So, the population of patients with CT scans prior to an operation does lend itself to using CT as a tool, so I think that's important. The question I have is, you mentioned that they're having thoracic surgery, and thoracic surgery is a big sort of bag of different types of procedures. Was there any subgroup analysis that looked at the different types of thoracic surgeries that were performed and the outcome measurements? Actually, we included a non-thoracic patient who received non-thoracic surgery to evaluate the post-op respiratory complication because the thoracic surgery, the prevalence of the respiratory complication is high, so we excluded the patient. And so, we included non-thoracic surgery, especially for patients who received abdomen surgery. Yeah, I guess I was looking at the degree of surgery or surgical resection. Was it a segmentectomy? Was it a lobectomy or more? The volume of whatever the procedure was, again, correlated with outcomes. Perhaps that's something for the future. The last presentation of this morning, this session, is from Ishita Shah. The title is Personal Volumetric Air Sampler Game Changer for Allergic Congenital Viruses. Good morning, everyone. I shall be discussing about the personal volumetric air sampler, a game changer for the allergic rhinoconjunctivitis. I'm Dr. Ishita Shah from India. I do not have any financial relationship to disclose. Going towards introduction, allergic rhinitis is a type 1 hypersensitivity reaction of the nose and the eye and is one of the most prevalent allergic diseases affecting around one-fifth of the general population. So 40% of the population of Europe and USA and 20 to 30% of the population in India suffer from the allergic rhinoconjunctivitis with predominance in the younger population. So though it's not a life-threatening condition or cause permanent damage or vision loss, it does have a negative effect on the quality of life. Exposure to the pollens and indoor allergens act as unavoidable triggers and managing patients with anti-allergic tablets, tropical corticosteroids, for a longer duration carries its own side effect. IACI guidelines now approves the modified skin prick testing, guided immunotherapy to provide relief to these patients on a longer duration. So what we did was we have developed a user-friendly portable personal volumetric air sampler that is produced locally and this device is designed to collect allergen from the patient's surrounding environment, assisting in creating a tailor-made immunotherapy for the refractory cases. So I would not go into much details of the differential diagnosis of the red eye, but typically when a patient comes to us with the pink eye or conjunctivitis, it is further divided into the allergic, infectious, autoimmune, nonspecific. We are all aware about the classifications. What is allergic rhinoconjunctivitis? So rhinoconjunctivitis is further divided into the allergic, infectious, and non-allergic rhinitis. There are different forms of rhinitis that may coexist with the allergic form and that may alter the clinical presentation, but the immunotherapy and modified skin prick testing is only advisable in the allergic form of the rhinitis. What we did was we took informed consent and we enrolled 24 patients of the allergic rhinoconjunctivitis in our study. Detailed history, thorough examination, and preliminary investigations were done before taking them for the modified skin prick testing. The skin prick testing was performed as per the reports. The customized treatment plans were made that included immunotherapy for the patient. And they were put on the immunotherapy and those patients were monitored very closely for the response. Patient who did not significantly respond to immunotherapy, they were reviewed again for the missing history of the allergen. For further evaluation, the specially designed and locally made personal volumetric air sampler was given to the patient to use at home and the work atmosphere to those patients who did not elicit the response to our treatment. The saffron-stained glycerin-coated slide are placed in this device to trap the allergens. And this was placed in patient's home, office, and surrounding three times a day for three days. In total, nine slides were collected for each patient. Slides were then studied by the microbiologist and botanist to identify the causative agents and new allergens were prepared accordingly. So again, we repeated the modified skin prick testing on the non-responsive patients with this new allergen and a modified immunotherapy was administered as per the result. So this is the device we produced. We included the patient who had a refractive allergic rhinitis diagnosed by the ophthalmologist after ruling out all other causes. Those who were given a trial of short-term treatment by an ophthalmologist were included. Diagnosed case of allergic rhinitis was included and we excluded the patient who were newly diagnosed case of the rhinitis or conjunctivitis. So we defined the response like complete response, partial, and no response. Those who were totally symptom-free with the immunotherapy were labeled as a complete responsor. The frequency and intensity of symptoms decreased by 50% or more. Such patients were labeled as partial responders and those who did not show any response or symptoms were unchanged less than 25%, then they were labeled as non-responsor. The results. So the chart one shows the age distribution and we can see that the most commonly the age group was between the 15 to 35 years old and the patient has a symptom duration of 2 to 6 years of duration. So this is the modified skin prick testing results where the most common allergens found were dust, dust mites, pollens, and food. So this chart shows the response to the immunotherapy and food restriction after 6 months. So we can see that out of 24, 18 patients showed the complete response and 6 patients showed partial or no response. So as I say, 18 patients were symptom-free within 5 to 6 months and 2 patients showed reduced intensity of their symptoms. The remaining 6% responded partially or did not respond at all. So those patients were re-evaluated. This is the follow-up chart of the patient who responded. So within 6 months of period, these 18 patients were tapered off of their eye drops and other supportive therapy. Monthly checkups were taken up, up to 2 years, and after completing 6 months of their immunotherapy, they were put on the maintenance therapy. So the new allergens, those were found with the personal volumetric air sampler, which was not tested, was Salmonia Salmon, Sevia Pentadra, Pytoselium Ducey, and Penicillium Species. The immunotherapy was made. Patients were put on this immunotherapy according to the result. Out of these 6, the 5 patients showed complete response within 6 months of revised immunotherapy, but 1 patient did not show the response. So this is the one example of the result that we achieved after 6 months of immunotherapy. Going towards discussion, so we can make hundreds of memes and laugh on the allergic rhinoconductivitis, but it can really be a nightmare for the patient who is actually suffering from it. Additional studies indicate that the incidence and prevalence of allergic condition has increased dramatically during last, past 40 years, and it continues on the rise. It has received the, allergic rhinitis has received the extensive research, whereas allergic conjunctivitis, despite being common, has not been subjected in depth study. So allergies affect more than 15% of the world population. According to the CDC, 1 in 4 U.S. adults and 1 in 5 U.S. children have allergies. 10% of this patient never seek medical advice, but instead they resort for the self-medication. While inadequate treatment of the rhinoconductivitis may not lead to permanent eye damage, it does affect the day-to-day life. So rhinoconductivitis can also potentially lead to the development of bronchial asthma if not treated at the right time and by right manner. And because it is impractical to completely change one's environment to avoid the allergen, we can rely on the skin prick testing, immunotherapy, and pharmacotherapy to offer a cure to this patient. Missing causative agents during allergy testing leads to an incomplete response to immunotherapy from a patient, the patient, and a continuation of the symptoms, and this is why it is crucial to identify all the causative allergen that has caused the symptoms. And that's where the personal volumetric air sampler can be a game changer. Just one more slide. Last one. Yeah. So as our result shows, that 75% of the patients from this study showed an immediate and lasting improvement, but when we incorporated the data after personal volumetric air sampler and started the patient on the immunotherapy, the cure rate improved from 75% to 95%. And sublingual or subcutaneous allergic administration of the culprit allergen not only desensitize a patient, but also delivers a long-term clinical benefit, and that effects last beyond few years. And it can definitely, the high cost of healthcare can be significant burden on the individual and the society as a whole, but if we develop a device locally, that can reduce the financial burden for the community, and it can really be helpful for the guided treatment. Thank you.

personal volumetric air sampler

allergens

patients

allergic rhinitis

skin prick testing

home environment

work environment

microbiologists

botanists