Predicting return of lung function after a pulmonary exacerbation using the cystic fibrosis respiratory symptom diary-chronic respiratory infection symptom scale

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Gill, Christopher H. Goss, Scott D. Sagel, Michelle L. Wright, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3232522/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Jul, 2024 Read the published version in BMC Pulmonary Medicine → Version 1 posted 12 You are reading this latest preprint version Abstract Background Pulmonary exacerbations (PExs) in people with cystic fibrosis (PwCF) are associated with increased healthcare costs, decreased quality of life and the risk for permanent decline in lung function. Symptom burden, the continuous physiological and emotional symptoms on an individual related to their disease, may be a useful tool for monitoring PwCF during a PEx, and identifying individuals at high risk for permanent decline in lung function. The purpose of this study was to investigate if the degree of symptom burden severity, measured by the Cystic Fibrosis Respiratory Symptom Diary (CFRSD)- Chronic Respiratory Infection Symptom Scale (CRISS), at the onset of a PEx can predict failure to return to baseline lung function by the end of treatment. Methods A secondary analysis of a longitudinal, observational study (N = 56) was conducted. Data was collected at four time points: year-prior-to-enrollment annual appointment, termed “baseline”, day 1 of PEx diagnosis, termed “Visit 1”, day 10–21 of PEx diagnosis, termed “Visit 2” and two-weeks post-hospitalization, termed “Visit 3”. A linear regression model was performed to analyze the research question. Results A regression model predicted that recovery of lung function decreased by 0.2 points for every increase in CRISS points, indicating that participants with a CRISS score greater than 48.3 were at 14% greater risk of not recovering to baseline lung function by Visit 2, than people with lower scores. Conclusion Monitoring CRISS scores in PwCF is an efficient, reliable, non-invasive way to determine a person’s status at the beginning of a PEx. The results presented in this paper support the usefulness of studying symptoms in the context of PEx in PwCF. Figures Figure 1 Introduction Cystic fibrosis (CF) is one of the most common, lethal genetic disorders in the United States, and affects almost 40,000 people (Cystic Fibrosis Foundation, 2022 ). The major health risk for people with CF (PwCF) is acute pulmonary exacerbation (PExs), which are characterized by worsening respiratory symptoms, and associated with decreased quality of life, morbidity and mortality (Goss, 2019 ; Liou et al., 2001 ; Britto et al., 2002 ). PExs are also a major driver of healthcare costs, with the cost of a single episode ranging from $ 60,800- $ 74,830 (Gold et al., 2022). PExs increase the risk for decline in lung function: Sanders et al. ( 2010 ) has shown that 25% of people who are treated for a PEx fail to recover to their baseline lung function by 3 months after antibiotic treatment. Further, PExs are associated with 50% of permanent decline in lung function, and the more frequently PwCF experience PExs the more rapid the decline and risk for respiratory failure (de Boer et al., 2011 ; Waters et al., 2012 ; Sanders et al., 2011 ). Therefore, it is critical to understand what characteristics can predict failure to recover baseline lung function. When PwCF are diagnosed with a PEx they experience an increase in physiological symptoms, or symptom burden (Bell et al., 2020 ; Rosenfeld et al., 2001 ). Symptom burden results from the continuous physiological and emotional symptoms related to the disease and/or treatment for a PEx (Schmid-Mohler et al., 2019 ). Higher symptom burden in chronic illnesses is associated with an increase in healthcare utilization (Deng et al., 2022 ; Zhang et a., 2020). In chronic obstructive pulmonary disease people with high symptom burden had significantly increased healthcare utilization and were more likely to have died by the 5-year follow-up than people with moderate or low symptom burden (Park & Larson, 2014 ). Symptom burden is often measured in PwCF to evaluate efficacy of treatment when PExs occurs. Symptom burden, as measured by the Cystic Fibrosis Respiratory Symptom Diary (CFRSD)-Chronic Respiratory Infection Scale (CRISS) in PwCF has been associated with c-reactive protein (CRP), a marker of systemic inflammation (VanDevanter et al., 2022 ), suggesting that symptom burden increases in response to inflammation or infection, and may be a useful measure for predicting treatment outcomes. The change in symptom burden CRISS score from a person’s baseline during a PEx is a viable efficacy endpoint in clinical trials (VanDevanter et al., 2021 ). However, symptom burden score at onset of PEx therapy has not been analyzed as a predictor to lung function loss in PwCF, and may help us to identify people at increased risk for poor recovery from PExs. We hypothesize that higher symptom burden, as measured by the CFRSD-CRISS, at the beginning of a PEx may predict people who will not recover their lung function by the end of treatment, and identify a group of individuals at risk for permanent decline in lung function. Therefore, the purpose of this study was to investigate if the degree of CRISS score severity at the onset of a PEx can predict failure to return to baseline lung function by the end of treatment. Methods Study Population This study is a secondary analysis of a longitudinal, observational study that explored changes in clinical outcomes and systemic measurements of inflammation in response to antibiotic therapy for PExs in PwCF (Sagel et al. 2015 ). The original study enrolled 123 participants from 6 CF Foundation (CFF) Centers in the United States who were diagnosed with an acute PEx; defined as presenting at least 3 of 11 criteria for PEx and requiring at least 2 IV antibiotics. Data access were acquired from the CFF Therapeutics Development Network Coordinating Center (TDNCC), in Seattle, Washington after review and approval. Data from the original study and matched CFF registry data were provided. Inclusion criteria for the study included PwCF 10 years of age and older. We further restricted our analysis to those with symptom data gathered on Day 1 of PEx diagnosis, and percent-predicted forced expiratory volume in 1 second (ppFEV 1 ) data gathered at the previous year annual visit and as well as Day 10–21 of PEx diagnosis. No data received from the TDNCC contained personally identifiable information or qualifying HIPAA identifiers, and thus The University of Texas at Austin’s Institutional Review Board (IRB) determined that this study met the criteria for exemption from IRB review under 45 CFR 46.104 (4) secondary research data or specimens (no consent required) (IRB ID: STUDY00000967). Timing of Assessments and Measures For the present study we used data from four time points: 1) annual visit data from the year prior to enrollment into the study, termed annual visit; 2) the first day of PEx diagnosis, termed Visit 1; 3) Day 10–21 of the PEx, termed Visit 2; 4) Two-weeks post-hospitalization, termed Visit 3. We measured seven demographic variables: age, sex, race, ethnicity, health insurance, smoking history and exposure to secondhand smoke; and six CF related variables: ppFEV 1 , homozygous delF508 mutation, positive Pseudomonas aeruginosa infection, nutritional status, nights spent in the hospital, and nights spent on home IV antibiotics. Symptoms and burden were collected and measured using the CFRSD-CRISS, which is composed of eight items. The response for each item is scored on a 5-point likert-scale, ranging 0 for no symptoms to 4 for extremely severe symptoms, which address: difficulty breathing, feeling feverish, having chills/sweats, increased cough, increased mucus production, fatigue, chest tightness, and wheezing (Goss et al., 2009 ). Participants missing more than 1 response to the CFRSD were removed from analysis for incomplete data. Each item response has a corresponding score that is totaled for a raw summated score, ranging from 0–24 (Goss et al., 2009 ). The raw summated score is then converted to a continuous Rasch-logit score, ranging from 0-100, termed the CRISS score. The higher the CRISS score the worse the symptom burden. Spirometry measures were gathered at the annual visit, Visit 1 and Visit 2, and the ppFEV 1 was calculated using reference equations (Wang et al., 1993 ; Hankinson et al., 1999 ). Failure to recover baseline lung function by Visit 2 was calculated as the ppFEV 1 at Visit 2 minus the ppFEV 1 at the annual visit. A result of 0 indicated return to baseline lung function, positive result indicated improved recovery of ppFEV 1 and a negative result indicated failure to recover baseline ppFEV 1 by Visit Statistical Analysis Data were assessed for normality and missingness. Descriptive statistics were used to examine the mean and standard deviation of continuous variables, and frequencies for categorical variables. We used linear regression to test the relationship between CRISS score and lung function recovery. We controlled for age, gender, and P. aeruginosa infection due to research showing that PwCF who are female, older and having chronic P. aeruginosa infection are more likely to respond to a lesser extent to PEx treatment (Sanders et al., 2010 ; Szczesniak et al., 2017 ). We visualized the distribution of residuals; measured the covariance ratio levels for levels outside 1 plus three-times the leverage and the residuals for values greater than 3; we tested for independence of variable, outliers, the homogeneity of variance and multicollinearity. R version 4.2.1 was used for all statistical analysis (The R Foundation for Statistical Computing, 2023). Results A total of 56 participants were included in this analysis; attrition was related to missing ppFEV 1 data (n = 67). The demographic and clinical characteristics of the included cohort can be found in Table 1 , and were compared to participants not included. This subset was representative of the overall study cohort. The majority of participants were Non-Hispanic White (n = 52, 92.9%), female (n = 37, 66%) and mean age was 25.1 ( Standard Deviation [SD] = 9.81) years. The majority of participants were positive for P. aeruginosa (n = 44, 78.6%). The median length of hospitalization was 16 nights, and median time spent on home IV antibiotics was 12 nights. The majority of our participants did not use oxygen throughout the year (n = 38, 67.9%) or at the beginning of PEx treatment (n = 49, 91.5%), and no participants smoked (n = 0, 0%). We assessed body mass index (BMI) as a measure of nutritional status for participants 21 years of age and older, and the Center for Disease Control clinical growth charts weight-for-age for participants 12–20. The mean BMI for participants 21 years of age and older was 20.71 kg/m 2 ( SD = 2.63), and the majority of participants less than 21 years of age were normal weight-for-age percentile (n = 13, 61.9%). Table 1 Demographic Characteristics Secondary analysis (N = 56) Parent Study (N = 123) Demographic Variables N (%) N (%) Age 10–20 21 (37.5%) 61 (50.8%) 20+ 35 (62.5%) 59 (49.2%) Gender, Female 37 (66.7%) 72 (60%) Race/Ethnicity White 52 (92.95%) 116 (94.3%) Non-Hispanic 51 (91.1%) 113 (91.8%) Hispanic 1 (1.8%) 3 (2.4%) Black 2 (3.6%) 2 (1.6%) Bi-Racial 2 (3.6%) 2 (1.6%) Insurance Type Medicaid 31 (53.6%) 37 (30.8%) Medicare 5 (8.9%) 9 (7.5%) Private 21 (37.5%) 30 (35%) Private & Medicaid 8 (14.3%) 10 (8.3%) Other 3 3 (2.5%) No Insurance 0 1 (0.8%) Smokes 0 (0%) 0 (0%) Second-hand smoke - - Daily 2 (3.6%) 2 (1.7%) Several Time per Week 2 (3.6%) 3 (2.5%) Several Times per Month 4 (7.14%) 6 (5%) Never 19 (33.9%) 23 ( 19.2%) Oxygen Use - - Throughout the Year 18 (32.1%) 12 (10%) During of PEx 7 (8.5%) 12 (10%) BMI, < 21 years old Underweight (< 5%) 6 (28.6%) 7 (18.4%) Normal weight (5%-85%) 13 (61.9%) 29 (76.3%) Overweight (85%-99%) 2 (9.5%) 2 (5.3%) Homozygous DelF508 35 (62.5) 66 (53.7%) Pseudomonas aeruginosa + culture 44 (78.6%) 55 (44.7%) Mean (SD) Median Min & Max Mean (SD) Median Min & Max Age, all 25.3 (9.81) 23 12, 50 22.38 (9.83) 21 10, 58 10–20 16.1 (2.5) 16 12, 20 15.06 (3.33) 16 10, 20 20+ 30.8 (8.3) 29 21, 50 29.9 (8.51) 27 21, 58 BMI, 21 + years of age 20.1 (2.6) 22 15.5, 23.8 21.2 20.9 16.1, 33.5 ppFEV 1 52.3 (20.2) 55.4 17.5, 93.5 54.7 (21.3) 51.9 17.5, 95.5 Hospital Nights 23.9 (23.1) 15.5 0, 87 25 (29.2) 15 0, 194 Adult 22.3 (23.6) 16 0, 87 26.8 (35.8) 13.5 0, 194 Child 26.8 (22.6) 15 3, 72 23.1 (20.2) 17.5 0, 86 Home Intravenous Antibiotics 18.6 (24.8) 11.5 0, 110 16 (25.9) 6 0, 180 Adult 23.6 (27.3) 19 0, 110 22.4 (30.6) 14 0, 180 Child 10.1 (17.5) 0 0, 71 9.2 (17.4) 0 0, 90 The mean ppFEV 1 at the annual visit was 58.4% ( SD = 21.6), Visit 1 was 52.28% ( SD = 20.24) and Visit 2 was 60.59% ( SD = 23.65). The majority of patients recovered to baseline lung function (n = 34, 60.7%), and the average amount of lung function recovered by Visit 2 from annual visit was 1.52% ( SD = 4.35, range: -6.28-12.8). However, 39.3% of participants still failed to recover to baseline lung function, and 10.4% failed to recover within 10% of their baseline lung function by Visit 2. The most prevalent symptom experienced by participants was increased cough (n = 55, 98.2%), followed by increased mucus (n = 49, 87.5%) and fatigue (n = 45, 80.4%). The most severe symptom experienced was also increased cough, 2.29 ( SD = 0.76), followed by fatigue, 2.09 ( SD = 1.03) then increased mucus, 1.95 ( SD = 1.05) based on a raw score. A summary of frequency and severity of measured symptoms can be found in Table 2 . The mean CRISS score at Visit 1 was 44.75 ( SD = 10.67) and at Visit 2 was 23.69 ( SD = 14.83). Symptom burden significantly improved with IV antibiotic treatment ( p < 0.001), and while CRISS scores were still significantly better ( p < 0.01) at the follow-up appointment 2 weeks post-hospitalization, scores increased again after systemic antibiotic treatment was completed (Fig. 1). Table 2 Symptom Prevalence, Visit 1 N = 56 Frequency (%) Mean Severity (SD) Min, Max Difficulty Breathing 32 (57.1%) 1.23 (1.27) 0, 4 Feverish 11 (19.6%) 0.39 (0.82) 0, 3 Chills/Sweats 10 (17.9%) 0.34 (0.82) 0, 4 Fatigue 45 (80.4%) 2.09 (1.3) 0, 4 Chest Tightness 23 (41.1%) 0.93 (1.26) 0, 4 Cough 55 (98.2%) 2.29 (0.76) 0, 4 Mucus production 49 (87.5%) 1.95 (1.05) 0, 4 Wheezing 24 (42.9%) 0.64 (0.84) 0, 3 CRISS Score – 44.75 (10.67) 0, 61 Figure 1. Longitudinal analysis of CRISS scores over 3 visits. Visits: 1 = Visit 1; 2 = Visit 2; 3 = Visit 3. CRISS score higher numbers indicate more severe symptom burden. CRISS Score and Lung Function We found that CRISS score at Visit 1 significantly predicts failure to recover ppFEV 1 at Visit 2, even when controlling for age, sex, and P. aeruginosa infection. The model was statistically significant, Adjusted R-squared: 0.14 p = 0.02. The coefficients were intercept = 9.66, CRISS score = -0.2, age = 0.12, P. aeruginosa = -1.97, and gender = -1.1. While the model was overall statistically significant, the CRISS score was the only significant predictor within the model ( p 0.05). The model results predict that recovery of lung function decreased by 0.2 points for every increase in CRISS points, indicating that participants with a CRISS score greater than 48.3 were at 14% greater risk of not recovering to baseline lung function by Visit 2, than people with lower scores, when all else is held constant. Discussion In this study of 56 people living with CF, we found that CRISS scores at the onset of PEx significantly predicted failure to recover ppFEV 1 by end of systemic antibiotic treatment, even when controlling for age, sex, and P. aeruginosa infection. Interestingly, these confounding variables chosen a priori were not significant. It is possible that while these variables have a significant relationship to incomplete PEx treatment response (Sanders et al., 2010 ), they do not influence the relationship between symptom burden and failure to recover baseline ppFEV 1 between Day 10–21. Future research should investigate other variables that may influence this relationship such as use of highly effective CFTR modulator therapy and nutrition status. The most common symptoms were increased cough, mucus and fatigue; increased cough and fatigue were the two most severe symptoms experienced, and are similar to previous research (Gold et al., 2019 ). Our results support previous findings that, while CRISS scores are sensitive to IV antibiotics, the majority of CRISS scores increased again after treatment was stopped (VanDevanter et al., 2017 ). As VanDevanter et al. ( 2017 ) implored, PEx research should not only focus on the improvement in clinical end-points seen at the cessation of antibiotic therapy, but they must prioritize the optimization of longitudinal response to PEx treatment, such as symptom burden and ppFEV 1 . The present study supports that symptoms must be monitored even after the cessation of antibiotic therapy, since symptom burden increases again after treatment and higher overall symptom burden may predict a lower likelihood of returning to baseline after treatment. Previously, studies have focused on the change in CRISS score during PEx treatment to be used as a reference for end to clinical treatment, but none have used symptom burden at PEx onset to predict PwCF at high risk for incomplete treatment response. Our results suggest that the higher the symptom burden at the onset of treatment for a PEx, the lower the chances of returning to baseline ppFEV 1 at the completion of antibiotic therapy. Based on this model, a participant with a CRISS score at Visit 1 of 48.3 or greater is less likely to regain baseline lung function by Visit 2. The mean CRISS score of these participants is 44.8 and our model suggests that less than one standard deviation (10.8) above the mean has a 14% higher chance of not recovering their baseline lung function by Day 10–21 of their PEx treatment. Three recent studies (combined N = 1,146) measured the CRISS score at onset of a PEx in PwCF, and their mean or median CRISS scores ranged from 49-56.6 (Roberts et al., 2018 ; VanDevanter et al., 2021 ; VanDevanter et al., 2022 ). This conveys that, on average, PwCF at the beginning of a PEx treated with IV antibiotics consistently have CRISS scores above 48.3. Our results suggest that measuring symptom burden at PEx onset may be a useful tool for identifying PwCF at risk for incomplete treatment response before the end of antibiotic therapy. There is a need for improved monitoring of lung function following PEx treatment. Heltshe et al. (2023) found that 49.6% of participants who received antibiotic treatment returned to baseline lung function when compared to participants not undergoing PEx therapy. The most improvement in lung function following IV antibiotic therapy has been shown to occur within the first 7–10 days of treatment (Goss et al., 2021 ), and any recovered lung function may begin to decline again anywhere between 1–16 weeks after therapy has ended (Cunningham et al., 2003 ; Béghin et al., 2009 ). However, as Heltshe et al. (2023) has identified, previous research on recovery of lung function has been obscured by inherent progression of the CF disease, natural variability in ppFEV 1 and inconsistent observation times (p. 2), which may have mischaracterized that PExs treatment are inadequate. A weakness of the presented secondary analysis is the lack of long term follow-up after treatment has ended and no inclusion of comparators. However, PwCF who do not recover their baseline ppFEV 1 by Day 10–21 of a PEx, a period when they have been receiving IV antibiotics, may be at even higher risk of not recovering to their baseline lung function by 3 months. Utilizing CRISS score we have still identified a group at high risk for failure to recover baseline lung function. Our results support the inclusion of CRISS score in clinical practice to provide an additional measure of individuals response to PEx as well as monitoring CF disease progression, and further research should seek to incorporate consistent measurement times and comparative groups. CRISS score and CRP have been shown to be significantly associated at the beginning of a PEx (VanDevanter et al., 2022 ), and CRP has been shown to significantly predict failure to recover baseline ppFEV 1 when admission levels are greater than 75mg/L, (Sharma et al., 2017 ). The significant relationship between CRP and CRISS score, as well as their abilities to independently predict failure to recover baseline lung function, conveys the clinical relevance of symptom burden as an objective, non-invasive predictor and further research is needed to validate these findings for potential incorporation into clinical practice. Conclusion Measuring symptom burden via the CRISS score is an efficient, reliable, non-invasive way to determine a patient’s status at the beginning of a PEx. Administering the CFRSD-CRISS at the beginning of a PEx may allow clinicians to identify individuals at high-risk for not responding to treatment and permanent decline in lung function. By using a patient's unique symptom experience clinicians may be able to tailor their treatment to the individual to improve lung function recovery between Day 10–21 of a PEx in PwCF. The results presented in this paper support the usefulness of studying symptoms in the context of PEx in PwCF, and future research is needed to validate these findings. Declarations Ethics approval and consent to participate Institutional Review Board (IRB) at The University of Texas at Austin reviewed this study for ethics approval and consent. The IRB determined that this study met the criteria for exemption from IRB review under 45 CFR 46.104 (4) secondary research data or specimens (no consent required) (IRB ID: STUDY00000967). Consent for publication Not applicable. Availability of data and materials Datasets generated and/or analyzed during the current study are available from the Cystic Fibrosis Foundation’s Therapeutics Development Network (https://www.cff.org/researchers/therapeutics-development-network). Data are available at no-cost upon application and peer-review. Competing Interests The authors declare that they have no competing interests. Funding This work was supported by the Cystic Fibrosis Foundation, award numbers: GILL21H0 and SAGEL07B0, and the NIH, award number: 1T32NR019035. NIH/NCATS Colorado CTSA Grant Number UL1 TR002535. Authors contributions ERG wrote the main manuscript and performed the analyses. CHG and JAZ provided major contributions to study creation and assisted with writing of the manuscript. SDS collected primary data used in the study and contributed to the editing and writing of the manuscript. MLW and SHD contributed to study creation and contributed to writing of the study, as well as the figures and tables presented. All authors reviewed the manuscript prior to submission. Acknowledgements We would like to acknowledge and thank the people with cystic fibrosis who participated in this study and provided valuable information. References Bell, S. C., Mall, M. A., Gutierrez, H., Macek, M., Madge, S., Davies, J. C., Burgel, P. R., Tullis, E., Castaños, C., Castellani, C., Byrnes, C. A., Cathcart, F., Chotirmall, S. H., Cosgriff, R., Eichler, I., Fajac, I., Goss, C. H., Drevinek, P., Farrell, P. M., … Ratjen, F. (2020). The future of cystic fibrosis care: a global perspective. In The Lancet Respiratory Medicine 1 (8), 65–124. https://doi.org/10.1016/S2213-2600(19)30337-6 Béghin, L., Michaud, L., Loeuille, G. A., Wizla-Derambure, N., Sayah, H., Sardet, A., Thumerelle, C., Deschildre, A., Turck, D., & Gottrand, F. (2009). Changes in lung function in young cystic fibrosis patients between two courses of intravenous antibiotics against Pseudomonas aeruginosa . Pediatric Pulmonology , 44 (5), 464–471. https://doi.org/10.1002/ppul.21017 Britto, M. T., Kotagal, U. R., Hornung, R. W., Atherton, H. D., Tsevat, J., & Wilmott, R. W. (2002). Impact of recent pulmonary exacerbations on quality of life in patients with cystic fibrosis. Chest , 121 (1), 64–72. https://doi.org/10.1378/chest.121.1.64 Cunningham, S., McColm, J. R., Mallinson, A., Boyd, I., & Marshall, T. G. (2003). Duration of effect of intravenous antibiotics on spirometry and sputum cytokines in children with cystic fibrosis. Pediatric Pulmonology , 36 (1), 43–48. https://doi.org/10.1002/ppul.10311 Cystic Fibrosis Foundation (2022). Patient Registry 2021 Annual Data Report . https://www.cff.org/sites/default/files/2021-11/Patient-Registry-Annual-Data-Report.pdf de Boer, K., Vandemheen, K. L., Tullis, E., Doucette, S., Fergusson, D., Freitag, A., Paterson, N., Jackson, M., Lougheed, M. D., Kumar, V., & Aaron, S. D. (2011). Exacerbation frequency and clinical outcomes in adult patients with cystic fibrosis. Thorax , 66 (8), 680–685. https://doi.org/10.1136/thx.2011.161117 Deng, L. X., Kent, D. S., O'Riordan, D. L., Pantilat, S. Z., Lai, J. C., & Bischoff, K. E. (2022). Symptom burden is associated with increased emergency department utilization among patients with cirrhosis. Journal of Palliative Medicine , 25 (2), 213–218. https://doi.org/10.1089/jpm.2021.0219 Gold, L. S., Patrick, D. L., Hansen, R. N., Goss, C. H., & Kessler, L. (2019). Correspondence between lung function and symptom measures from the Cystic Fibrosis Respiratory Symptom Diary–Chronic Respiratory Infection Symptom Score (CFRSD-CRISS). Journal of Cystic Fibrosis, 18 (6), 886–893. https://doi.org/10.1016/j.jcf.2019.05.009 Gold, L. S., Hansen, R. N., Patrick, D. L., Tabah, A., Heltshe, S. L., Flume, P. A., Goss, C. H., West, N. E., Sanders, D. B., VanDevanter, D. R., & Kessler, L. (2022). Health care costs in a randomized trial of antimicrobial duration among cystic fibrosis patients with pulmonary exacerbations. Journal of Cystic Fibrosis 21 (4), 594–599. https://doi-org.offcampus.lib.washington.edu/10.1016/j.jcf.2022.03.001 Goss, C. H., Edwards, T. C., Ramsey, B. W., Aitken, M. L., & Patrick, D. L. (2009). Patient-reported respiratory symptoms in cystic fibrosis. Journal of Cystic Fibrosis , 8 (4), 245–252. https://doi.org/10.1016/j.jcf.2009.04.003 Goss, C. H. (2019). Acute pulmonary exacerbations in cystic fibrosis. Seminars in Respiratory and Critical Care Medicine, 40 (6), 792–803. https://doi.org/10.1055/s-0039-1697975 Goss, C. H., Heltshe, S. L., West, N. E., Skalland, M., Sanders, D. B., Jain, R., Barto, T. L., Fogarty, B., Marshall, B. C., VanDevanter, D. R., & Flume, P. A. (2021). A randomized clinical trial of antimicrobial duration for cystic fibrosis pulmonary exacerbation treatment. Am J Respir Crit Care Med , 204 (11), 1295–1305. https://doi.org/10.1164/rccm.202102-0461OC Hankinson JL, Odencrantz JR, Fedan KB (1999). Spirometric reference values from a sample of the general U.S. population. Am J Respir Crit Care Med 159 , 179–187. Liou, T. G., Adler, F. R., Fitzsimmons, S. C., Cahill, B. C., Hibbs, J. R., & Marshall, B. C. (2001). Predictive 5-year survivorship model of cystic fibrosis. American Journal of Epidemiology , 153 (4), 345–352. https://doi.org/10.1093/aje/153.4.345 Park, S. K., & Larson, J. L. (2014). Symptom cluster, healthcare use and mortality in patients with severe chronic obstructive pulmonary disease. Journal of Clinical Nursing , 23 (17-18), 2658–2671. https://doi.org/10.1111/jocn.12526 R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Retrieved from: https://www.R-project.org/. Roberts, J. M., Dai, D. L. Y., Hollander, Z., Ng, R. T., Tebbutt, S. J., Wilcox, P. G., Sin, D. D., & Quon, B. S. (2018). Multiple reaction monitoring mass spectrometry to identify novel plasma protein biomarkers of treatment response in cystic fibrosis pulmonary exacerbations. Journal of Cystic Fibrosis , 17 (3), 333–340. https://doi.org/10.1016/j.jcf.2017.10.013 Rosenfeld, M., Emerson, J., Williams-Warren, J., Pepe, M., Smith, A., Montgomery, A. B., & Ramsey, B. (2001). Defining a pulmonary exacerbation in cystic fibrosis. Journal of Pediatrics , 139 (3), 359–365. https://doi.org/10.1067/mpd.2001.117288 Sagel, S. D., Thompson, V., Chmiel, J. F., Montgomery, G. S., Nasr, S. Z., Perkett, E., Saavedra, M. T., Slovis, B., Anthony, M. M., Emmett, P., & Heltshe, S. L. (2015). Effect of treatment of cystic fibrosis pulmonary exacerbations on systemic inflammation. Annals of the American Thoracic Society , 12 (5), 708–717. https://doi.org/10.1513/AnnalsATS.201410-493OC Sanders, D. B., Bittner, R. C. L., Rosenfeld, M., Hoffman, L. R., Redding, G. J., & Goss, C. H. (2010). Failure to recover to baseline pulmonary function after cystic fibrosis pulmonary exacerbation. Am J Respir Crit Care Med , 182 (5), 627–632. https://doi.org/10.1164/rccm.200909-1421OC Sanders, D. B., Bittner, R. C. L., Rosenfeld, M., Redding, G. J., & Goss, C. H. (2011). Pulmonary exacerbations are associated with subsequent FEV1 decline in both adults and children with cystic fibrosis. Pediatric Pulmonology , 46 (4), 393–400. https://doi.org/10.1002/ppul.21374 Schmid-Mohler, G., Yorke, J., Spirig, R., Benden, C., & Caress, A. L. (2019). Adult patients’ experiences of symptom management during pulmonary exacerbations in cystic fibrosis: A thematic synthesis of qualitative research. Chronic Illness , 15 (4), 245–263. https://doi.org/10.1177/1742395318772647 Sharma, A., Kirkpatrick, G., Chen, V., Skolnik, K., Hollander, Z., Wilcox, P., & Quon, B. S. (2017). Clinical utility of C-reactive protein to predict treatment response during cystic fibrosis pulmonary exacerbations. PloS One , 12 (2), e0171229. https://doi.org/10.1371/journal.pone.0171229 Szczesniak, R. D., Li, D., Su, W., Brokamp, C., Pestian, J., Seid, M., & Clancy, J. P. (2017). Phenotypes of rapid cystic fibrosis lung disease progression during adolescence and young adulthood. Am J Respir Crit Care Med, 196 (4), 471–478. https://doi.org/10.1164/rccm.201612-2574OC VanDevanter, D. R., Heltshe, S. L., Spahr, J., Beckett, V. V., Daines, C. L., Dasenbrook, E. C., Gibson, R. L., Raksha, J., Sanders, D. B., Goss, C. H., Flume, P. A., & STOP Study Group (2017). Rationalizing endpoints for prospective studies of pulmonary exacerbation treatment response in cystic fibrosis. Journal of Cystic Fibrosis , 16 (5), 607–615. https://doi.org/10.1016/j.jcf.2017.04.004 VanDevanter, D. R., Heltshe, S. L., Sanders, D. B., West, N. E., Skalland, M., Flume, P. A., Goss, C. H., & STOP-OB Study (2021). Changes in symptom scores as a potential clinical endpoint for studies of cystic fibrosis pulmonary exacerbation treatment. Journal of Cystic Fibrosis 20 (1), 36–38. https://doi.org/10.1016/j.jcf.2020.08.006 VanDevanter, D. R., Heltshe, S. L., Skalland, M., West, N. E., Sanders, D. B., Goss, C. H., & Flume, P. A. (2022). C-reactive protein (CRP) as a biomarker of pulmonary exacerbation presentation and treatment response. Journal of Cystic Fibrosis , 21 (4), 588–593. https://doi.org/10.1016/j.jcf.2021.12.003 Wang, X., Dockery, D.W., Wypij, D., Fay, M.E. & Ferris, B.G. (1993). Pulmonary function between 6 and 18 years of age. Pediatric Pulmonology 15 , 75–88. Waters, V., Stanojevic, S., Atenafu, E. G., Lu, A., Yau, Y., Tullis, E., & Ratjen, F. (2012). Effect of pulmonary exacerbations on long-term lung function decline in cystic fibrosis. European Respiratory Journal , 40 (1), 61–66. https://doi.org/10.1183/09031936.00159111 Zhang, J. C., El-Majzoub, S., Li, M., Ahmed, T., Wu, J., Lipman, M. L., Moussaoui, G., Looper, K. J., Novak, M., Rej, S., & Mucsi, I. (2020). Could symptom burden predict subsequent healthcare use in patients with end stage kidney disease on hemodialysis care? A prospective, preliminary study. Renal Failure , 42 (1), 294–301. https://doi.org/10.1080/0886022X.2020.1744449 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 24 Jul, 2024 Read the published version in BMC Pulmonary Medicine → Version 1 posted Editorial decision: Revision requested 10 Nov, 2023 Reviews received at journal 27 Oct, 2023 Reviews received at journal 17 Oct, 2023 Reviews received at journal 03 Oct, 2023 Reviewers agreed at journal 26 Sep, 2023 Reviewers agreed at journal 24 Sep, 2023 Reviewers agreed at journal 24 Sep, 2023 Reviewers invited by journal 23 Sep, 2023 Editor assigned by journal 23 Sep, 2023 Editor invited by journal 10 Sep, 2023 Submission checks completed at journal 10 Sep, 2023 First submitted to journal 03 Aug, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3232522","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":232014380,"identity":"4b760086-23b9-408f-9ae4-b06f709f2ed5","order_by":0,"name":"Eliana R. Gill","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAn0lEQVRIiWNgGAWjYJCCAw8qwLQBCVoSzpCqhSGxjRQt/NLHLx5InHc4sYG9eZsEUVok+3IKDiRuA2rhOVZGnBaDMzwJIC25DRI5ZsRpsQdrmQPUIv+GSC0GPOwHDiQ2gGzhIVKLxBkeYCAfS69v40krtiBKC38P++MPH2qsjfnZD2+8QZQWBgYeSHSwEakcBNgfkKB4FIyCUTAKRiQAABBGMFR0J8k8AAAAAElFTkSuQmCC","orcid":"","institution":"University of Washington","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Eliana","middleName":"R.","lastName":"Gill","suffix":""},{"id":232014381,"identity":"f51bc222-84b2-4b87-a465-be56d5f4ce4d","order_by":1,"name":"Christopher H. Goss","email":"","orcid":"","institution":"University of Washington","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"H.","lastName":"Goss","suffix":""},{"id":232014382,"identity":"d9204555-1ffe-45ce-aaad-094e78bd2fe0","order_by":2,"name":"Scott D. Sagel","email":"","orcid":"","institution":"University of Colorado Anschutz Medical Campus","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Scott","middleName":"D.","lastName":"Sagel","suffix":""},{"id":232014383,"identity":"ade6686c-0032-4520-ae45-898677c30003","order_by":3,"name":"Michelle L. Wright","email":"","orcid":"","institution":"The University of Texas at Austin","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Michelle","middleName":"L.","lastName":"Wright","suffix":""},{"id":232014384,"identity":"acd9ac8a-969c-4f47-a232-fd949abe1ec5","order_by":4,"name":"Sharon D. Horner","email":"","orcid":"","institution":"The University of Texas at Austin","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sharon","middleName":"D.","lastName":"Horner","suffix":""},{"id":232014385,"identity":"3d90ecb8-48c0-41f0-bc23-239790e212c9","order_by":5,"name":"Julie A. Zuñiga","email":"","orcid":"","institution":"The University of Texas at Austin","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Julie","middleName":"A.","lastName":"Zuñiga","suffix":""}],"badges":[],"createdAt":"2023-08-03 19:59:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3232522/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3232522/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12890-024-03148-w","type":"published","date":"2024-07-24T16:15:18+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":43080240,"identity":"4b84997f-8eea-4860-9573-752532583291","added_by":"auto","created_at":"2023-09-13 15:31:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":326777,"visible":true,"origin":"","legend":"\u003cp\u003eLongitudinal analysis of CRISS scores over 3 visits. Visits: 1= Visit 1; 2= Visit 2; 3= Visit 3. CRISS score higher numbers indicate more severe symptom burden.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3232522/v1/727c8fa15d23cfdb4505ba68.png"},{"id":61596931,"identity":"1fc44fa2-86e7-4c89-8ce2-ae41d2430c4d","added_by":"auto","created_at":"2024-08-01 17:30:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":993991,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3232522/v1/8648b4a2-dc40-40f8-8dda-33896c91e66a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predicting return of lung function after a pulmonary exacerbation using the cystic fibrosis respiratory symptom diary-chronic respiratory infection symptom scale","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCystic fibrosis (CF) is one of the most common, lethal genetic disorders in the United States, and affects almost 40,000 people (Cystic Fibrosis Foundation, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The major health risk for people with CF (PwCF) is acute pulmonary exacerbation (PExs), which are characterized by worsening respiratory symptoms, and associated with decreased quality of life, morbidity and mortality (Goss, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Liou et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Britto et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). PExs are also a major driver of healthcare costs, with the cost of a single episode ranging from \u003cspan\u003e$\u003c/span\u003e60,800-\u003cspan\u003e$\u003c/span\u003e74,830 (Gold et al., 2022). PExs increase the risk for decline in lung function: Sanders et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) has shown that 25% of people who are treated for a PEx fail to recover to their baseline lung function by 3 months after antibiotic treatment. Further, PExs are associated with 50% of permanent decline in lung function, and the more frequently PwCF experience PExs the more rapid the decline and risk for respiratory failure (de Boer et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Waters et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Sanders et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Therefore, it is critical to understand what characteristics can predict failure to recover baseline lung function.\u003c/p\u003e \u003cp\u003eWhen PwCF are diagnosed with a PEx they experience an increase in physiological symptoms, or symptom burden (Bell et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Rosenfeld et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Symptom burden results from the continuous physiological and emotional symptoms related to the disease and/or treatment for a PEx (Schmid-Mohler et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Higher symptom burden in chronic illnesses is associated with an increase in healthcare utilization (Deng et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhang et a., 2020). In chronic obstructive pulmonary disease people with high symptom burden had significantly increased healthcare utilization and were more likely to have died by the 5-year follow-up than people with moderate or low symptom burden (Park \u0026amp; Larson, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSymptom burden is often measured in PwCF to evaluate efficacy of treatment when PExs occurs. Symptom burden, as measured by the Cystic Fibrosis Respiratory Symptom Diary (CFRSD)-Chronic Respiratory Infection Scale (CRISS) in PwCF has been associated with c-reactive protein (CRP), a marker of systemic inflammation (VanDevanter et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), suggesting that symptom burden increases in response to inflammation or infection, and may be a useful measure for predicting treatment outcomes. The change in symptom burden CRISS score from a person\u0026rsquo;s baseline during a PEx is a viable efficacy endpoint in clinical trials (VanDevanter et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, symptom burden score at onset of PEx therapy has not been analyzed as a predictor to lung function loss in PwCF, and may help us to identify people at increased risk for poor recovery from PExs.\u003c/p\u003e \u003cp\u003eWe hypothesize that higher symptom burden, as measured by the CFRSD-CRISS, at the beginning of a PEx may predict people who will not recover their lung function by the end of treatment, and identify a group of individuals at risk for permanent decline in lung function. Therefore, the purpose of this study was to investigate if the degree of CRISS score severity at the onset of a PEx can predict failure to return to baseline lung function by the end of treatment.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy Population\u003c/p\u003e \u003cp\u003eThis study is a secondary analysis of a longitudinal, observational study that explored changes in clinical outcomes and systemic measurements of inflammation in response to antibiotic therapy for PExs in PwCF (Sagel et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The original study enrolled 123 participants from 6 CF Foundation (CFF) Centers in the United States who were diagnosed with an acute PEx; defined as presenting at least 3 of 11 criteria for PEx and requiring at least 2 IV antibiotics. Data access were acquired from the CFF Therapeutics Development Network Coordinating Center (TDNCC), in Seattle, Washington after review and approval. Data from the original study and matched CFF registry data were provided. Inclusion criteria for the study included PwCF 10 years of age and older. We further restricted our analysis to those with symptom data gathered on Day 1 of PEx diagnosis, and percent-predicted forced expiratory volume in 1 second (ppFEV\u003csub\u003e1\u003c/sub\u003e) data gathered at the previous year annual visit and as well as Day 10\u0026ndash;21 of PEx diagnosis. No data received from the TDNCC contained personally identifiable information or qualifying HIPAA identifiers, and thus The University of Texas at Austin\u0026rsquo;s Institutional Review Board (IRB) determined that this study met the criteria for exemption from IRB review under 45 CFR 46.104 (4) secondary research data or specimens (no consent required) (IRB ID: STUDY00000967).\u003c/p\u003e \u003cp\u003eTiming of Assessments and Measures\u003c/p\u003e \u003cp\u003eFor the present study we used data from four time points: 1) annual visit data from the year prior to enrollment into the study, termed annual visit; 2) the first day of PEx diagnosis, termed Visit 1; 3) Day 10\u0026ndash;21 of the PEx, termed Visit 2; 4) Two-weeks post-hospitalization, termed Visit 3. We measured seven demographic variables: age, sex, race, ethnicity, health insurance, smoking history and exposure to secondhand smoke; and six CF related variables: ppFEV\u003csub\u003e1\u003c/sub\u003e, homozygous delF508 mutation, positive \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e infection, nutritional status, nights spent in the hospital, and nights spent on home IV antibiotics.\u003c/p\u003e \u003cp\u003eSymptoms and burden were collected and measured using the CFRSD-CRISS, which is composed of eight items. The response for each item is scored on a 5-point likert-scale, ranging 0 for no symptoms to 4 for extremely severe symptoms, which address: difficulty breathing, feeling feverish, having chills/sweats, increased cough, increased mucus production, fatigue, chest tightness, and wheezing (Goss et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Participants missing more than 1 response to the CFRSD were removed from analysis for incomplete data. Each item response has a corresponding score that is totaled for a raw summated score, ranging from 0\u0026ndash;24 (Goss et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The raw summated score is then converted to a continuous Rasch-logit score, ranging from 0-100, termed the CRISS score. The higher the CRISS score the worse the symptom burden.\u003c/p\u003e \u003cp\u003eSpirometry measures were gathered at the annual visit, Visit 1 and Visit 2, and the ppFEV\u003csub\u003e1\u003c/sub\u003e was calculated using reference equations (Wang et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Hankinson et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Failure to recover baseline lung function by Visit 2 was calculated as the ppFEV\u003csub\u003e1\u003c/sub\u003e at Visit 2 minus the ppFEV\u003csub\u003e1\u003c/sub\u003e at the annual visit. A result of 0 indicated return to baseline lung function, positive result indicated improved recovery of ppFEV\u003csub\u003e1\u003c/sub\u003e and a negative result indicated failure to recover baseline ppFEV\u003csub\u003e1\u003c/sub\u003e by Visit\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData were assessed for normality and missingness. Descriptive statistics were used to examine the mean and standard deviation of continuous variables, and frequencies for categorical variables. We used linear regression to test the relationship between CRISS score and lung function recovery. We controlled for age, gender, and \u003cem\u003eP. aeruginosa\u003c/em\u003e infection due to research showing that PwCF who are female, older and having chronic \u003cem\u003eP. aeruginosa\u003c/em\u003e infection are more likely to respond to a lesser extent to PEx treatment (Sanders et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Szczesniak et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). We visualized the distribution of residuals; measured the covariance ratio levels for levels outside 1 plus three-times the leverage and the residuals for values greater than 3; we tested for independence of variable, outliers, the homogeneity of variance and multicollinearity. R version 4.2.1 was used for all statistical analysis (The R Foundation for Statistical Computing, 2023).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 56 participants were included in this analysis; attrition was related to missing ppFEV\u003csub\u003e1\u003c/sub\u003e data (n\u0026thinsp;=\u0026thinsp;67). The demographic and clinical characteristics of the included cohort can be found in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, and were compared to participants not included. This subset was representative of the overall study cohort. The majority of participants were Non-Hispanic White (n\u0026thinsp;=\u0026thinsp;52, 92.9%), female (n\u0026thinsp;=\u0026thinsp;37, 66%) and mean age was 25.1 (\u003cem\u003eStandard Deviation [SD]\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9.81) years. The majority of participants were positive for \u003cem\u003eP. aeruginosa\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;44, 78.6%). The median length of hospitalization was 16 nights, and median time spent on home IV antibiotics was 12 nights. The majority of our participants did not use oxygen throughout the year (n\u0026thinsp;=\u0026thinsp;38, 67.9%) or at the beginning of PEx treatment (n\u0026thinsp;=\u0026thinsp;49, 91.5%), and no participants smoked (n\u0026thinsp;=\u0026thinsp;0, 0%). We assessed body mass index (BMI) as a measure of nutritional status for participants 21 years of age and older, and the Center for Disease Control clinical growth charts weight-for-age for participants 12\u0026ndash;20. The mean BMI for participants 21 years of age and older was 20.71 kg/m\u003csup\u003e2\u003c/sup\u003e (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.63), and the majority of participants less than 21 years of age were normal weight-for-age percentile (n\u0026thinsp;=\u0026thinsp;13, 61.9%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eDemographic Characteristics\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eSecondary analysis (N\u0026thinsp;=\u0026thinsp;56)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eParent Study (N\u0026thinsp;=\u0026thinsp;123)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic Variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e21 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e61 (50.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e35 (62.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e59 (49.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e37 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e72 (60%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace/Ethnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e52 (92.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e116 (94.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e51 (91.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e113 (91.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e3 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e2 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e2 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBi-Racial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e2 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e2 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsurance Type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicaid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e31 (53.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e37 (30.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e5 (8.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e9 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e21 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e30 (35%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate \u0026amp; Medicaid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e8 (14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e10 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e3 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo Insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e1 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmokes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecond-hand smoke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e2 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e2 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeveral Time per Week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e2 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e3 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeveral Times per Month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e4 (7.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e6 (5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e19 (33.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e23 ( 19.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOxygen Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThroughout the Year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e18 (32.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e12 (10%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuring of PEx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e7 (8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e12 (10%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, \u0026lt; 21 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderweight (\u0026lt;\u0026thinsp;5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e6 (28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e7 (18.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal weight (5%-85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e13 (61.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e29 (76.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight (85%-99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e2 (9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e2 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHomozygous DelF508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e35 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e66 (53.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e\u0026thinsp;+\u0026thinsp;culture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e44 (78.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e55 (44.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eMedian\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eMin \u0026amp; Max\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eMean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eMedian\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eMin \u0026amp; Max\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.3 (9.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12, 50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.38 (9.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10, 58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.1 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12, 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.06 (3.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10, 20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.8 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21, 50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.9 (8.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21, 58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, 21\u0026thinsp;+\u0026thinsp;years of age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.1 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.5, 23.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.1, 33.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eppFEV\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.3 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.5, 93.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.7 (21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.5, 95.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital Nights\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.9 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0, 87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25 (29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0, 194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdult\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.3 (23.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0, 87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.8 (35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0, 194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.8 (22.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3, 72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.1 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0, 86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome Intravenous Antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.6 (24.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0, 110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0, 180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdult\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.6 (27.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0, 110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.4 (30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0, 180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.1 (17.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0, 71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.2 (17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0, 90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe mean ppFEV\u003csub\u003e1\u003c/sub\u003e at the annual visit was 58.4% (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;21.6), Visit 1 was 52.28% (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;20.24) and Visit 2 was 60.59% (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;23.65). The majority of patients recovered to baseline lung function (n\u0026thinsp;=\u0026thinsp;34, 60.7%), and the average amount of lung function recovered by Visit 2 from annual visit was 1.52% (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.35, range: -6.28-12.8). However, 39.3% of participants still failed to recover to baseline lung function, and 10.4% failed to recover within 10% of their baseline lung function by Visit 2. The most prevalent symptom experienced by participants was increased cough (n\u0026thinsp;=\u0026thinsp;55, 98.2%), followed by increased mucus (n\u0026thinsp;=\u0026thinsp;49, 87.5%) and fatigue (n\u0026thinsp;=\u0026thinsp;45, 80.4%). The most severe symptom experienced was also increased cough, 2.29 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.76), followed by fatigue, 2.09 (\u003cem\u003eSD\u0026thinsp;=\u003c/em\u003e\u0026thinsp;1.03) then increased mucus, 1.95 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.05) based on a raw score. A summary of frequency and severity of measured symptoms can be found in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The mean CRISS score at Visit 1 was 44.75 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10.67) and at Visit 2 was 23.69 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;14.83). Symptom burden significantly improved with IV antibiotic treatment (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and while CRISS scores were still significantly better (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) at the follow-up appointment 2 weeks post-hospitalization, scores increased again after systemic antibiotic treatment was completed (Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eSymptom Prevalence, Visit 1\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;56\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean Severity (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMin, Max\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifficulty Breathing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (57.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.23 (1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0, 4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeverish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (19.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.39 (0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0, 3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChills/Sweats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.34 (0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0, 4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (80.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.09 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0, 4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChest Tightness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (41.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.93 (1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0, 4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (98.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.29 (0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0, 4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMucus production\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49 (87.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.95 (1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0, 4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWheezing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (42.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.64 (0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0, 3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRISS Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.75 (10.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0, 61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure 1. Longitudinal analysis of CRISS scores over 3 visits. Visits: 1\u0026thinsp;=\u0026thinsp;Visit 1; 2\u0026thinsp;=\u0026thinsp;Visit 2; 3\u0026thinsp;=\u0026thinsp;Visit 3. CRISS score higher numbers indicate more severe symptom burden.\u003c/p\u003e \u003cp\u003eCRISS Score and Lung Function\u003c/p\u003e \u003cp\u003eWe found that CRISS score at Visit 1 significantly predicts failure to recover ppFEV\u003csub\u003e1\u003c/sub\u003e at Visit 2, even when controlling for age, sex, and \u003cem\u003eP. aeruginosa\u003c/em\u003e infection. The model was statistically significant, Adjusted R-squared: 0.14 \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02. The coefficients were intercept\u0026thinsp;=\u0026thinsp;9.66, CRISS score = -0.2, age\u0026thinsp;=\u0026thinsp;0.12, \u003cem\u003eP. aeruginosa\u003c/em\u003e = -1.97, and gender = -1.1. While the model was overall statistically significant, the CRISS score was the only significant predictor within the model (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) while the three variables we controlled for were not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The model results predict that recovery of lung function decreased by 0.2 points for every increase in CRISS points, indicating that participants with a CRISS score greater than 48.3 were at 14% greater risk of not recovering to baseline lung function by Visit 2, than people with lower scores, when all else is held constant.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study of 56 people living with CF, we found that CRISS scores at the onset of PEx significantly predicted failure to recover ppFEV\u003csub\u003e1\u003c/sub\u003e by end of systemic antibiotic treatment, even when controlling for age, sex, and \u003cem\u003eP. aeruginosa\u003c/em\u003e infection. Interestingly, these confounding variables chosen a priori were not significant. It is possible that while these variables have a significant relationship to incomplete PEx treatment response (Sanders et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), they do not influence the relationship between symptom burden and failure to recover baseline ppFEV\u003csub\u003e1\u003c/sub\u003e between Day 10\u0026ndash;21. Future research should investigate other variables that may influence this relationship such as use of highly effective CFTR modulator therapy and nutrition status.\u003c/p\u003e \u003cp\u003eThe most common symptoms were increased cough, mucus and fatigue; increased cough and fatigue were the two most severe symptoms experienced, and are similar to previous research (Gold et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Our results support previous findings that, while CRISS scores are sensitive to IV antibiotics, the majority of CRISS scores increased again after treatment was stopped (VanDevanter et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). As VanDevanter et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) implored, PEx research should not only focus on the improvement in clinical end-points seen at the cessation of antibiotic therapy, but they must prioritize the optimization of longitudinal response to PEx treatment, such as symptom burden and ppFEV\u003csub\u003e1\u003c/sub\u003e. The present study supports that symptoms must be monitored even after the cessation of antibiotic therapy, since symptom burden increases again after treatment and higher overall symptom burden may predict a lower likelihood of returning to baseline after treatment.\u003c/p\u003e \u003cp\u003ePreviously, studies have focused on the change in CRISS score during PEx treatment to be used as a reference for end to clinical treatment, but none have used symptom burden at PEx onset to predict PwCF at high risk for incomplete treatment response. Our results suggest that the higher the symptom burden at the onset of treatment for a PEx, the lower the chances of returning to baseline ppFEV\u003csub\u003e1\u003c/sub\u003e at the completion of antibiotic therapy. Based on this model, a participant with a CRISS score at Visit 1 of 48.3 or greater is less likely to regain baseline lung function by Visit 2. The mean CRISS score of these participants is 44.8 and our model suggests that less than one standard deviation (10.8) above the mean has a 14% higher chance of not recovering their baseline lung function by Day 10\u0026ndash;21 of their PEx treatment. Three recent studies (combined N\u0026thinsp;=\u0026thinsp;1,146) measured the CRISS score at onset of a PEx in PwCF, and their mean or median CRISS scores ranged from 49-56.6 (Roberts et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; VanDevanter et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; VanDevanter et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This conveys that, on average, PwCF at the beginning of a PEx treated with IV antibiotics consistently have CRISS scores above 48.3. Our results suggest that measuring symptom burden at PEx onset may be a useful tool for identifying PwCF at risk for incomplete treatment response before the end of antibiotic therapy.\u003c/p\u003e \u003cp\u003eThere is a need for improved monitoring of lung function following PEx treatment. Heltshe et al. (2023) found that 49.6% of participants who received antibiotic treatment returned to baseline lung function when compared to participants not undergoing PEx therapy. The most improvement in lung function following IV antibiotic therapy has been shown to occur within the first 7\u0026ndash;10 days of treatment (Goss et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and any recovered lung function may begin to decline again anywhere between 1\u0026ndash;16 weeks after therapy has ended (Cunningham et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; B\u0026eacute;ghin et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). However, as Heltshe et al. (2023) has identified, previous research on recovery of lung function has been obscured by inherent progression of the CF disease, natural variability in ppFEV\u003csub\u003e1\u003c/sub\u003e and inconsistent observation times (p. 2), which may have mischaracterized that PExs treatment are inadequate. A weakness of the presented secondary analysis is the lack of long term follow-up after treatment has ended and no inclusion of comparators. However, PwCF who do not recover their baseline ppFEV\u003csub\u003e1\u003c/sub\u003e by Day 10\u0026ndash;21 of a PEx, a period when they have been receiving IV antibiotics, may be at even higher risk of not recovering to their baseline lung function by 3 months. Utilizing CRISS score we have still identified a group at high risk for failure to recover baseline lung function. Our results support the inclusion of CRISS score in clinical practice to provide an additional measure of individuals response to PEx as well as monitoring CF disease progression, and further research should seek to incorporate consistent measurement times and comparative groups.\u003c/p\u003e \u003cp\u003eCRISS score and CRP have been shown to be significantly associated at the beginning of a PEx (VanDevanter et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and CRP has been shown to significantly predict failure to recover baseline ppFEV\u003csub\u003e1\u003c/sub\u003e when admission levels are greater than 75mg/L, (Sharma et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The significant relationship between CRP and CRISS score, as well as their abilities to independently predict failure to recover baseline lung function, conveys the clinical relevance of symptom burden as an objective, non-invasive predictor and further research is needed to validate these findings for potential incorporation into clinical practice.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eMeasuring symptom burden via the CRISS score is an efficient, reliable, non-invasive way to determine a patient\u0026rsquo;s status at the beginning of a PEx. Administering the CFRSD-CRISS at the beginning of a PEx may allow clinicians to identify individuals at high-risk for not responding to treatment and permanent decline in lung function. By using a patient's unique symptom experience clinicians may be able to tailor their treatment to the individual to improve lung function recovery between Day 10\u0026ndash;21 of a PEx in PwCF. The results presented in this paper support the usefulness of studying symptoms in the context of PEx in PwCF, and future research is needed to validate these findings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eInstitutional Review Board (IRB) at The University of Texas at Austin reviewed this study for ethics approval and consent. The IRB determined that this study met the criteria for exemption from IRB review under 45 CFR 46.104 (4) secondary research data or specimens (no consent required) (IRB ID: STUDY00000967). \u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable. \u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eDatasets generated and/or analyzed during the current study are available from the Cystic Fibrosis Foundation\u0026rsquo;s Therapeutics Development Network (https://www.cff.org/researchers/therapeutics-development-network). Data are available at no-cost upon application and peer-review. \u003c/p\u003e\n\u003cp\u003eCompeting Interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Cystic Fibrosis Foundation, award numbers: GILL21H0 and SAGEL07B0, and the NIH, award number: 1T32NR019035. NIH/NCATS Colorado CTSA Grant Number UL1 TR002535. \u003c/p\u003e\n\u003cp\u003eAuthors contributions\u003c/p\u003e\n\u003cp\u003eERG wrote the main manuscript and performed the analyses. CHG and JAZ provided major contributions to study creation and assisted with writing of the manuscript. SDS collected primary data used in the study and contributed to the editing and writing of the manuscript. MLW and SHD contributed to study creation and contributed to writing of the study, as well as the figures and tables presented. All authors reviewed the manuscript prior to submission.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe would like to acknowledge and thank the people with cystic fibrosis who participated in this study and provided valuable information. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBell, S. C., Mall, M. A., Gutierrez, H., Macek, M., Madge, S., Davies, J. C., Burgel, P. R., Tullis, E., Casta\u0026ntilde;os, C., Castellani, C., Byrnes, C. A., Cathcart, F., Chotirmall, S. H., Cosgriff, R., Eichler, I., Fajac, I., Goss, C. H., Drevinek, P., Farrell, P. M., \u0026hellip; Ratjen, F. (2020). The future of cystic fibrosis care: a global perspective. In \u003cem\u003eThe Lancet Respiratory Medicine 1\u003c/em\u003e(8), 65\u0026ndash;124. https://doi.org/10.1016/S2213-2600(19)30337-6\u003c/li\u003e\n\u003cli\u003eB\u0026eacute;ghin, L., Michaud, L., Loeuille, G. A., Wizla-Derambure, N., Sayah, H., Sardet, A., Thumerelle, C., Deschildre, A., Turck, D., \u0026amp; Gottrand, F. (2009). Changes in lung function in young cystic fibrosis patients between two courses of intravenous antibiotics against \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e. \u003cem\u003ePediatric Pulmonology\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(5), 464\u0026ndash;471. https://doi.org/10.1002/ppul.21017\u003c/li\u003e\n\u003cli\u003eBritto, M. T., Kotagal, U. R., Hornung, R. W., Atherton, H. D., Tsevat, J., \u0026amp; Wilmott, R. W. (2002). Impact of recent pulmonary exacerbations on quality of life in patients with cystic fibrosis. \u003cem\u003eChest\u003c/em\u003e, \u003cem\u003e121\u003c/em\u003e(1), 64\u0026ndash;72. https://doi.org/10.1378/chest.121.1.64\u003c/li\u003e\n\u003cli\u003eCunningham, S., McColm, J. R., Mallinson, A., Boyd, I., \u0026amp; Marshall, T. G. (2003). Duration of effect of intravenous antibiotics on spirometry and sputum cytokines in children with cystic fibrosis. \u003cem\u003ePediatric Pulmonology\u003c/em\u003e, \u003cem\u003e36\u003c/em\u003e(1), 43\u0026ndash;48. https://doi.org/10.1002/ppul.10311\u003c/li\u003e\n\u003cli\u003eCystic Fibrosis Foundation (2022). \u003cem\u003ePatient Registry 2021 Annual Data Report\u003c/em\u003e. https://www.cff.org/sites/default/files/2021-11/Patient-Registry-Annual-Data-Report.pdf\u003c/li\u003e\n\u003cli\u003ede Boer, K., Vandemheen, K. L., Tullis, E., Doucette, S., Fergusson, D., Freitag, A., Paterson, N., Jackson, M., Lougheed, M. D., Kumar, V., \u0026amp; Aaron, S. D. (2011). Exacerbation frequency and clinical outcomes in adult patients with cystic fibrosis. \u003cem\u003eThorax\u003c/em\u003e, \u003cem\u003e66\u003c/em\u003e(8), 680\u0026ndash;685. https://doi.org/10.1136/thx.2011.161117\u003c/li\u003e\n\u003cli\u003eDeng, L. X., Kent, D. S., O\u0026apos;Riordan, D. L., Pantilat, S. Z., Lai, J. C., \u0026amp; Bischoff, K. E. (2022). Symptom burden is associated with increased emergency department utilization among patients with cirrhosis. \u003cem\u003eJournal of Palliative Medicine\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(2), 213\u0026ndash;218. https://doi.org/10.1089/jpm.2021.0219\u003c/li\u003e\n\u003cli\u003eGold, L. S., Patrick, D. L., Hansen, R. N., Goss, C. H., \u0026amp; Kessler, L. (2019). Correspondence between lung function and symptom measures from the Cystic Fibrosis Respiratory Symptom Diary\u0026ndash;Chronic Respiratory Infection Symptom Score (CFRSD-CRISS). \u003cem\u003eJournal of Cystic Fibrosis, 18\u003c/em\u003e(6), 886\u0026ndash;893. https://doi.org/10.1016/j.jcf.2019.05.009\u003c/li\u003e\n\u003cli\u003eGold, L. S., Hansen, R. N., Patrick, D. L., Tabah, A., Heltshe, S. L., Flume, P. A., Goss, C. H.,\u003c/li\u003e\n\u003cli\u003eWest, N. E., Sanders, D. B., VanDevanter, D. R., \u0026amp; Kessler, L. (2022). Health care costs in a randomized trial of antimicrobial duration among cystic fibrosis patients with pulmonary exacerbations. \u003cem\u003eJournal of Cystic Fibrosis 21\u003c/em\u003e(4), 594\u0026ndash;599. https://doi-org.offcampus.lib.washington.edu/10.1016/j.jcf.2022.03.001\u003c/li\u003e\n\u003cli\u003eGoss, C. H., Edwards, T. C., Ramsey, B. W., Aitken, M. L., \u0026amp; Patrick, D. L. (2009). Patient-reported respiratory symptoms in cystic fibrosis. \u003cem\u003eJournal of Cystic Fibrosis\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(4), 245\u0026ndash;252. https://doi.org/10.1016/j.jcf.2009.04.003\u003c/li\u003e\n\u003cli\u003eGoss, C. H. (2019). Acute pulmonary exacerbations in cystic fibrosis. \u003cem\u003eSeminars in Respiratory and Critical Care Medicine, 40\u003c/em\u003e(6), 792\u0026ndash;803. https://doi.org/10.1055/s-0039-1697975\u003c/li\u003e\n\u003cli\u003eGoss, C. H., Heltshe, S. L., West, N. E., Skalland, M., Sanders, D. B., Jain, R., Barto, T. L., Fogarty, B., Marshall, B. C., VanDevanter, D. R., \u0026amp; Flume, P. A. (2021). A randomized clinical trial of antimicrobial duration for cystic fibrosis pulmonary exacerbation treatment. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e, \u003cem\u003e204\u003c/em\u003e(11), 1295\u0026ndash;1305. https://doi.org/10.1164/rccm.202102-0461OC\u003c/li\u003e\n\u003cli\u003eHankinson JL, Odencrantz JR, Fedan KB (1999). Spirometric reference values from a sample of the general U.S. population.\u003cem\u003e Am J Respir Crit Care Med 159\u003c/em\u003e, 179\u0026ndash;187.\u003c/li\u003e\n\u003cli\u003eLiou, T. G., Adler, F. R., Fitzsimmons, S. C., Cahill, B. C., Hibbs, J. R., \u0026amp; Marshall, B. C. (2001). Predictive 5-year survivorship model of cystic fibrosis. \u003cem\u003eAmerican Journal of Epidemiology\u003c/em\u003e, \u003cem\u003e153\u003c/em\u003e(4), 345\u0026ndash;352. https://doi.org/10.1093/aje/153.4.345\u003c/li\u003e\n\u003cli\u003ePark, S. K., \u0026amp; Larson, J. L. (2014). Symptom cluster, healthcare use and mortality in patients with severe chronic obstructive pulmonary disease. \u003cem\u003eJournal of Clinical Nursing\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(17-18), 2658\u0026ndash;2671. https://doi.org/10.1111/jocn.12526\u003c/li\u003e\n\u003cli\u003eR Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Retrieved from: https://www.R-project.org/.\u003c/li\u003e\n\u003cli\u003eRoberts, J. M., Dai, D. L. Y., Hollander, Z., Ng, R. T., Tebbutt, S. J., Wilcox, P. G., Sin, D. D., \u0026amp; Quon, B. S. (2018). Multiple reaction monitoring mass spectrometry to identify novel plasma protein biomarkers of treatment response in cystic fibrosis pulmonary exacerbations. \u003cem\u003eJournal of Cystic Fibrosis\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(3), 333\u0026ndash;340. https://doi.org/10.1016/j.jcf.2017.10.013\u003c/li\u003e\n\u003cli\u003eRosenfeld, M., Emerson, J., Williams-Warren, J., Pepe, M., Smith, A., Montgomery, A. B., \u0026amp; Ramsey, B. (2001). Defining a pulmonary exacerbation in cystic fibrosis. \u003cem\u003eJournal of Pediatrics\u003c/em\u003e, \u003cem\u003e139\u003c/em\u003e(3), 359\u0026ndash;365. https://doi.org/10.1067/mpd.2001.117288\u003c/li\u003e\n\u003cli\u003eSagel, S. D., Thompson, V., Chmiel, J. F., Montgomery, G. S., Nasr, S. Z., Perkett, E., Saavedra, M. T., Slovis, B., Anthony, M. M., Emmett, P., \u0026amp; Heltshe, S. L. (2015). Effect of treatment of cystic fibrosis pulmonary exacerbations on systemic inflammation. \u003cem\u003eAnnals of the American Thoracic Society\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(5), 708\u0026ndash;717. https://doi.org/10.1513/AnnalsATS.201410-493OC\u003c/li\u003e\n\u003cli\u003eSanders, D. B., Bittner, R. C. L., Rosenfeld, M., Hoffman, L. R., Redding, G. J., \u0026amp; Goss, C. H. (2010). Failure to recover to baseline pulmonary function after cystic fibrosis pulmonary exacerbation. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e, \u003cem\u003e182\u003c/em\u003e(5), 627\u0026ndash;632. https://doi.org/10.1164/rccm.200909-1421OC\u003c/li\u003e\n\u003cli\u003eSanders, D. B., Bittner, R. C. L., Rosenfeld, M., Redding, G. J., \u0026amp; Goss, C. H. (2011). Pulmonary exacerbations are associated with subsequent FEV1 decline in both adults and children with cystic fibrosis. \u003cem\u003ePediatric Pulmonology\u003c/em\u003e, \u003cem\u003e46\u003c/em\u003e(4), 393\u0026ndash;400. https://doi.org/10.1002/ppul.21374\u003c/li\u003e\n\u003cli\u003eSchmid-Mohler, G., Yorke, J., Spirig, R., Benden, C., \u0026amp; Caress, A. L. (2019). Adult patients\u0026rsquo; experiences of symptom management during pulmonary exacerbations in cystic fibrosis: A thematic synthesis of qualitative research. \u003cem\u003eChronic Illness\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(4), 245\u0026ndash;263. https://doi.org/10.1177/1742395318772647\u003c/li\u003e\n\u003cli\u003eSharma, A., Kirkpatrick, G., Chen, V., Skolnik, K., Hollander, Z., Wilcox, P., \u0026amp; Quon, B. S. (2017). Clinical utility of C-reactive protein to predict treatment response during cystic fibrosis pulmonary exacerbations. \u003cem\u003ePloS One\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(2), e0171229. https://doi.org/10.1371/journal.pone.0171229\u003c/li\u003e\n\u003cli\u003eSzczesniak, R. D., Li, D., Su, W., Brokamp, C., Pestian, J., Seid, M., \u0026amp; Clancy, J. P. (2017). Phenotypes of rapid cystic fibrosis lung disease progression during adolescence and young adulthood. \u003cem\u003eAm J Respir Crit Care Med, 196\u003c/em\u003e(4), 471\u0026ndash;478. https://doi.org/10.1164/rccm.201612-2574OC\u003c/li\u003e\n\u003cli\u003eVanDevanter, D. R., Heltshe, S. L., Spahr, J., Beckett, V. V., Daines, C. L., Dasenbrook, E. C., Gibson, R. L., Raksha, J., Sanders, D. B., Goss, C. H., Flume, P. A., \u0026amp; STOP Study Group (2017). Rationalizing endpoints for prospective studies of pulmonary exacerbation treatment response in cystic fibrosis. \u003cem\u003eJournal of Cystic Fibrosis\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(5), 607\u0026ndash;615. https://doi.org/10.1016/j.jcf.2017.04.004\u003c/li\u003e\n\u003cli\u003eVanDevanter, D. R., Heltshe, S. L., Sanders, D. B., West, N. E., Skalland, M., Flume, P. A., Goss, C. H., \u0026amp; STOP-OB Study (2021). Changes in symptom scores as a potential clinical endpoint for studies of cystic fibrosis pulmonary exacerbation treatment. \u003cem\u003eJournal of Cystic Fibrosis\u003c/em\u003e \u003cem\u003e20\u003c/em\u003e(1), 36\u0026ndash;38. https://doi.org/10.1016/j.jcf.2020.08.006\u003c/li\u003e\n\u003cli\u003eVanDevanter, D. R., Heltshe, S. L., Skalland, M., West, N. E., Sanders, D. B., Goss, C. H., \u0026amp; Flume, P. A. (2022). C-reactive protein (CRP) as a biomarker of pulmonary exacerbation presentation and treatment response. \u003cem\u003eJournal of Cystic Fibrosis\u003c/em\u003e, \u003cem\u003e21\u003c/em\u003e(4), 588\u0026ndash;593. https://doi.org/10.1016/j.jcf.2021.12.003\u003c/li\u003e\n\u003cli\u003eWang, X., Dockery, D.W., Wypij, D., Fay, M.E. \u0026amp; Ferris, B.G. (1993). Pulmonary function between 6 and 18 years of age. \u003cem\u003ePediatric Pulmonology\u003c/em\u003e \u003cem\u003e15\u003c/em\u003e, 75\u0026ndash;88.\u003c/li\u003e\n\u003cli\u003eWaters, V., Stanojevic, S., Atenafu, E. G., Lu, A., Yau, Y., Tullis, E., \u0026amp; Ratjen, F. (2012). Effect of pulmonary exacerbations on long-term lung function decline in cystic fibrosis. \u003cem\u003eEuropean Respiratory Journal\u003c/em\u003e, \u003cem\u003e40\u003c/em\u003e(1), 61\u0026ndash;66. https://doi.org/10.1183/09031936.00159111\u003c/li\u003e\n\u003cli\u003eZhang, J. C., El-Majzoub, S., Li, M., Ahmed, T., Wu, J., Lipman, M. L., Moussaoui, G., Looper, K. J., Novak, M., Rej, S., \u0026amp; Mucsi, I. (2020). Could symptom burden predict subsequent healthcare use in patients with end stage kidney disease on hemodialysis care? A prospective, preliminary study. \u003cem\u003eRenal Failure\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(1), 294\u0026ndash;301. https://doi.org/10.1080/0886022X.2020.1744449\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3232522/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3232522/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePulmonary exacerbations (PExs) in people with cystic fibrosis (PwCF) are associated with increased healthcare costs, decreased quality of life and the risk for permanent decline in lung function. Symptom burden, the continuous physiological and emotional symptoms on an individual related to their disease, may be a useful tool for monitoring PwCF during a PEx, and identifying individuals at high risk for permanent decline in lung function. The purpose of this study was to investigate if the degree of symptom burden severity, measured by the Cystic Fibrosis Respiratory Symptom Diary (CFRSD)- Chronic Respiratory Infection Symptom Scale (CRISS), at the onset of a PEx can predict failure to return to baseline lung function by the end of treatment.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA secondary analysis of a longitudinal, observational study (N\u0026thinsp;=\u0026thinsp;56) was conducted. Data was collected at four time points: year-prior-to-enrollment annual appointment, termed \u0026ldquo;baseline\u0026rdquo;, day 1 of PEx diagnosis, termed \u0026ldquo;Visit 1\u0026rdquo;, day 10\u0026ndash;21 of PEx diagnosis, termed \u0026ldquo;Visit 2\u0026rdquo; and two-weeks post-hospitalization, termed \u0026ldquo;Visit 3\u0026rdquo;. A linear regression model was performed to analyze the research question.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA regression model predicted that recovery of lung function decreased by 0.2 points for every increase in CRISS points, indicating that participants with a CRISS score greater than 48.3 were at 14% greater risk of not recovering to baseline lung function by Visit 2, than people with lower scores.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eMonitoring CRISS scores in PwCF is an efficient, reliable, non-invasive way to determine a person\u0026rsquo;s status at the beginning of a PEx. The results presented in this paper support the usefulness of studying symptoms in the context of PEx in PwCF.\u003c/p\u003e","manuscriptTitle":"Predicting return of lung function after a pulmonary exacerbation using the cystic fibrosis respiratory symptom diary-chronic respiratory infection symptom scale","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-09-13 15:31:40","doi":"10.21203/rs.3.rs-3232522/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2023-11-10T14:54:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-10-27T10:30:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-10-17T23:43:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-10-03T19:57:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"e2b477df-b77f-4337-b41d-96c8ac732365","date":"2023-09-27T02:56:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6b428145-da09-437e-8d59-1cf1fae99b2f","date":"2023-09-24T14:58:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"c5205d55-7f34-4bf7-9b04-c33c57a1d960","date":"2023-09-24T09:33:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-09-24T02:49:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-09-24T02:11:34+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2023-09-10T06:20:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-09-10T06:18:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pulmonary Medicine","date":"2023-08-03T19:45:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dd55c327-defb-4022-b940-1106b8f661e8","owner":[],"postedDate":"September 13th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-01T17:17:07+00:00","versionOfRecord":{"articleIdentity":"rs-3232522","link":"https://doi.org/10.1186/s12890-024-03148-w","journal":{"identity":"bmc-pulmonary-medicine","isVorOnly":false,"title":"BMC Pulmonary Medicine"},"publishedOn":"2024-07-24 16:15:18","publishedOnDateReadable":"July 24th, 2024"},"versionCreatedAt":"2023-09-13 15:31:40","video":"","vorDoi":"10.1186/s12890-024-03148-w","vorDoiUrl":"https://doi.org/10.1186/s12890-024-03148-w","workflowStages":[]},"version":"v1","identity":"rs-3232522","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3232522","identity":"rs-3232522","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}