References
[1] Fokkens W, Lund V, Hopkins C, Hellings P, Kern R, Reitsma S,
Toppila-Salmi S, Bernal-Sprekelsen M, Mullol J, Alobid I, et al. 2020
European position paper on rhinosinusitis and nasal polyps 2020.
Rhinology journal 58, 1–464. (doi:10.4193/Rhin20.600).
[2] Liao B, Liu JX, Li ZY, Zhen Z, Cao PP, Yao Y, Long XB, Wang H,
Wang Y, Schleimer R, et al. 2018 Multidimensional endotypes of chronic
rhinosinusitis and their association with treatment outcomes. Allergy
73, 7, 1459–1469. (doi:https://doi.org/10.1111/all.13411).
[3] Wei B, Liu F, Zhang J, Liu Y, Du J, Liu S, Zhang N, Bachert C,
Meng J. 2018 Multivariate analysis of inflammatory endotypes in
recurrent nasal polyposis in a chinese population. Rhinology 56, 3,
216—226. (doi:10.4193/rhin17.240).
[4] Rudmik L, Soler ZM, Mace JC, Schlosser RJ, Smith TL. 2015
Economic evaluation of endoscopic sinus surgery versus continued medical
therapy for refractory chronic rhinosinusitis. The Laryngoscope 125, 1,
25–32. (doi:https://doi.org/10.1002/lary.24916).
[5] Anderson WC, Szefler SJ. 2019 Cost-effectiveness and comparative
effectiveness of biologic therapy for asthma: To biologic or not to
biologic. Annals of allergy, asthma and immunology 122, 4, 367—372.
(doi:10.1016/j.anai.2019.01.018).
[6] Guo C, Liao B, Liu J, Pan L, Z L. 2021 Predicting
difficult-to-treat chronic rhinosinusitis by noninvasive biological
markers. Rhinology 59, 1, 81–90. (doi:10.4193/Rhin20.103).
[7] Koskinen A, Salo R, Huhtala H, Myller J, Rautiainen M,
Kääriäinen J, Penttilä M, Renkonen R, Raitiola H, Mäkelä M, et al. 2016
Factors affecting revision rate of chronic rhinosinusitis. Laryngoscope
Investigative Otolaryngology 1, 4, 96—105. (doi:10.1002/lio2.27).
[8] Rudmik L, Soler ZM, Hopkins C. 2016 Using postoperative snot-22
to help predict the probability of revision sinus surgery. Rhinology 54,
2, 111—116. (doi:10.4193/rhin15.284).
[9] Stein NR, Jafari A, DeConde AS. 2018 Revision rates and time to
revision following endoscopic sinus surgery: A large database analysis.
The Laryngoscope 128, 1, 31–36. (doi:10.1002/lary.26741).
[10] Smith KA, Orlandi RR, Oakley G, Meeks H, Curtin K, Alt JA. 2019
Long-term revision rates for endoscopic sinus surgery. International
Forum of Allergy & Rhinology 9, 4, 402–408. (doi:10.1002/alr.22264).
[11] Younis RT, Ahmed J. 2017 Predicting revision sinus surgery in
allergic fungal and eosinophilic mucin chronic rhinosinusitis. The
Laryngoscope 127, 1, 59–63. (doi:10.1002/lary.26248).
[12] Loftus CA, Soler ZM, Desiato VM, Koochakzadeh S, Yoo F, Storck
KA, Schlosser RJ. 2020 Factors impacting revision surgery in patients
with chronic rhinosinusitis with nasal polyposis. International Forum of
Allergy & Rhinology 10, 3, 289–302. (doi:10.1002/alr.22505).
[13] Loftus CA, Soler ZM, Koochakzadeh S, Desiato VM, Yoo F, Nguyen
SA, Schlosser RJ. 2020 Revision surgery rates in chronic rhinosinusitis
with nasal polyps: meta-analysis of risk factors. International Forum of
Allergy & Rhinology 10, 2, 199–207. (doi:10.1002/alr.22487).
[14] Veloso-Teles R, Cerejeira R. 2017 Endoscopic sinus surgery for
chronic rhinosinusitis with nasal polyps: Clinical outcome and
predictive factors of recurrence. American Journal of Rhinology &
Allergy 31, 1, 56–62. (doi:10.2500/ajra.2017.31.4402).
[15] Mueller S, Wendler O, Nocera A, Grundtner P, Schlegel P, Agaimy
A, Iro H, Bleier B. 2019 Escalation in mucus cystatin 2, pappalysin-a,
and periostin levels over time predict need for recurrent surgery in
chronic rhinosinusitis with nasal polyps. International Forum of Allergy
& Rhinology 9, 1212 – 1219.
[16] Morrissey DK, Bassiouni A, Psaltis AJ, Naidoo Y, Wormald PJ.
2016 Outcomes of modified endoscopiclothrop in aspirin-exacerbated
respiratory disease with nasal polyposis. International Forum of Allergy
& Rhinology 6, 8, 820–825. (doi:10.1002/alr.21739).
[17] Lundberg SM, Erion G, Chen H, DeGrave A, Prutkin JM, Nair B,
Katz R, Himmelfarb J, Bansal N, Lee SI. 2020 From local explanations to
global understanding with explainable ai for trees. Nature Machine
Intelligence 2, 1, 2522–5839.
[18] Friedman JH. 2001 Greedy function approximation: A gradient
boosting machine. The Annals of Statistics 29, 5, 1189–232.
[19] Mendelsohn D, Jeremic G, Wright ED, Rotenberg BW. 2011 Revision
rates after endoscopic sinus surgery: A recurrence analysis. Annals of
Otology, Rhinology & Laryngology 120, 3, 162–166. (doi:
10.1177/000348941112000304). PMID: 21510141.
[20] Chang CC, Tai CJ, Ng TY, Tsou YA, Tsai MH. 2014 Can fess
combined with submucosal resection (smr)/septoplasty reduce revision
rate? Otolaryngology–Head and Neck Surgery 151, 4, 700–705. (doi:
10.1177/0194599814543778). PMID: 25146305.
[21] Hopkins C, Browne J, Slack R, Lund V, Topham J, Reeves B,
Copley L, Brown P, Van Der Meulen J. 2006 The national comparative audit
of surgery for nasal polyposis and chronic rhinosinusitis. Clinical
Otolaryngology 31, 5, 390–398.
(doi:https://doi.org/10.1111/j.1749-4486.2006.01275.x).
[22] Inacio MC, Cafri G, Funahashi TT, Maletis GB, Paxton EW. 2016
Type and frequency of healthcare encounters can predict poor surgical
outcomes in anterior cruciate ligament reconstruction patients.
International Journal of Medical Informatics 90, 32–39. (doi:
https://doi.org/10.1016/j.ijmedinf.2016.03.005).
[23] Lilja MJ, Koskinen A, Virkkula P, Vento SI, Myller J,
Hammaren-Malmi S, Laulajainen-Hongisto A, Hytonen M, Makitie A, Numminen
J, et al. 2021 Factors affecting the control of chronic rhinosinusitis
with nasal polyps: A comparison in patients with or without nerd.
Allergy & Rhinology 12, 21526567211003844.
(doi:10.1177/21526567211003844).
[24] Virkkula P, Penttila E, Vento S, Myller J, Koskinen A,
Hammaren-Malmi S, Laulajainen-Hongisto A, Hytonen M, Lilja M, Numminen
J, et al. 2020 Assessing cut-off points of eosinophils, nasal polyp, and
lund-mackay scores to predict surgery in nasal polyposis: A real-world
study. Allergy and Rhinology 11.
[25] Zhang L, Zhang Y, Gao Y, Wang K, Lou H, Meng Y, C CW. 2020
Long-term outcomes of different endoscopic sinus surgery in recurrent
chronic rhinosinusitis with nasal polyps and asthma. Rhinology 58, 2.
(doi:10.4193/Rhin19.184).
[26] van der Veen J, Seys SF, Timmermans M, Levie P, Jorissen M,
Fokkens WJ, Hellings PW. 2017 Real-life study showing uncontrolled
rhinosinusitis after sinus surgery in a tertiary referral centre.
Allergy 72, 2, 282–290. (doi:https://doi.org/10.1111/all.12983).
[27] Laulajainen-Hongisto A, Turpeinen H, Vento SI, Numminen J,
Sahlman J, Kauppi P, Virkkula P, Hytönen M, Toppila-Salmi S. 2020 High
discontinuation rates of peroral asa treatment for crswnp: A real-world
multicenter study of 171 n-erd patients. The Journal of Allergy and
Clinical Immunology: In Practice 8, 10, 3565–3574.
(doi:https://doi.org/10.1016/j.jaip.2020.06.063).
[28] Steinke JW, Payne SC, Borish L. 2016 Eosinophils and mast cells
in aspirin-exacerbated respiratory disease. Immunology and Allergy
Clinics of North America 36, 4, 719–734. (doi:
https://doi.org/10.1016/j.iac.2016.06.008). Aspirin-Exacerbated
Respiratory Disease.
[29] Brescia G, Barion U, Zanotti C, Giacomelli L, Martini A,
Marioni G. 2017 The prognostic role of serum eosinophil and basophil
levels in sinonasal polyposis. International Forum of Allergy &
Rhinology 7, 3, 261–267. (doi:https://doi.org/10.1002/alr.21885).
[30] Lou H, Meng Y, Piao Y, Wang C, Zhang L, Bachert C. 2015
Predictive significance of tissue eosinophilia for nasal polyp
recurrence in the chinese population. American Journal of Rhinology &
Allergy 29, 5, 350–356. (doi:10.2500/ajra.2015.29.4231).
[31] Brescia G, Pedruzzi B, Barion U, Cinetto F, Giacomelli L,
Martini A, Marioni G. 2016 Are neutrophil-, eosinophil-, and
basophil-to-lymphocyte ratios useful markers for pinpointing patients at
higher risk of recurrent sinonasal polyps? American Journal of
Otolaryngology 37, 4, 339–345. (doi:
https://doi.org/10.1016/j.amjoto.2016.02.002).
[32] Brescia G, Marioni G, Franchella S, Ramacciotti G, Giacomelli
L, Marino F, Martini A. 2016 A prospective investigation of predictive
parameters for post-surgical recurrences in sinonasal polyposis. Archiv
für Klinische und Experimentelle Ohren- Nasen- und Kehlkopfheilkunde
273, 655–660. (doi:10.1007/s00405-015-3598-5).
[33] Tao X, Chen F, Sun Y, Wu S, Hong H, Shi J, Xu R. 2018
Prediction models for postoperative uncontrolled chronic rhinosinusitis
in daily practice. The Laryngoscope 128, 12, 2673–2680. (doi:
https://doi.org/10.1002/lary.27267).
[34] Vlaminck S, Vauterin T, Hellings PW, Jorissen M, Acke F,
Cauwenberge PV, Bachert C, Gevaert P. 2014 The importance of local
eosinophilia in the surgical outcome of chronic rhinosinusitis: A 3-year
prospective observational study. American Journal of Rhinology &
Allergy 28, 3, 260–264. (doi: 10.2500/ajra.2014.28.4024).
[35] Nakayama T, Yoshikawa M, Asaka D, Okushi T, Matsuwaki Y, Otori
N, Hama T, Moriyama H. 2011 Mucosal eosinophilia and recurrence of nasal
polyps - new classification of chronic rhinosinusitis. Rhinology 49, 4,
392—396. (doi:10.4193/rhino10.261).
[36] Ikeda K, Shiozawa A, Ono N, Kusunoki T, Hirotsu M, Homma H,
Saitoh T, Murata J. 2013 Subclassification of chronic rhinosinusitis
with nasal polyp based on eosinophil and neutrophil. The Laryngoscope
123, 11, E1–E9. (doi:https://doi.org/10.1002/lary.24154).
[37] Lyly A, Laulajainen-Hongisto A, Turpeinen H, Vento SI, Myller
J, Numminen J, Sillanpää S, Sahlman J, Kauppi P, Toppila-Salmi S. 2021
Factors affecting upper airway control of nsaid-exacerbated respiratory
disease: A real-world study of 167 patients. Immunity, Inflammation and
Disease 9, 1, 80–89. (doi: https://doi.org/10.1002/iid3.347).
[38] Miglani A, Divekar RD, Azar A, Rank MA, Lal D. 2018 Revision
endoscopic sinus surgery rates by chronic rhinosinusitis subtype.
International Forum of Allergy & Rhinology 8, 9, 1047–1051. (doi:
https://doi.org/10.1002/alr.22146).
[39] Merali ZG, Witiw CD, Badhiwala JH, Wilson JR, Fehlings MG. 2019
Using a machine learning approach to predict outcome after surgery for
degenerative cervical myelopathy. PLOS ONE 14, 4, 1–12. (doi:
10.1371/journal.pone.0215133).
[40] Jalali A Lonsdale H DNPJGMKSGSJJRMAL. 2020 Deep learning for
improved risk prediction in surgical outcomes. Sci Rep. 10, 9289.
(doi:10.1038/s41598-020-62971-3).
[41] Bose S, Kenyon CC, Masino AJ. 2021 Personalized prediction of
early childhood asthma persistence: A machine learning approach. PLOS
ONE 16, 3, 1–17. (doi:10.1371/journal.pone.0247784).
[42] Hastie T, Tibshirani R, Friedman J. 2008 The Elements of
Statistical Learning. Springer Series in Statistics. New York, NY, USA:
Springer New York Inc.
[43] Nuutinen M, Leskelä RL, Suojalehto E, Tirronen A, Komssi V.
2017 Bmc med inform decis mak. Development and validation of classifiers
and variable subsets for predicting nursing home admission 39.
(doi:10.1186/s12911-017-0442-4).
[44] Hamerla G, Meyer HJ, Schob S, Ginat DT, Altman A, Lim T, Gihr
GA, Horvath-Rizea D, Hoffmann KT, Surov A. 2019 Comparison of machine
learning classifiers for differentiation of grade 1 from higher gradings
in meningioma: A multicenter radiomics study. Magnetic Resonance Imaging
63, 244–249. (doi: https://doi.org/10.1016/j.mri.2019.08.011).
[45] Moore W, Meyers D, Wenzel S. 2010 Identification of asthma
phenotypes using cluster analysis in the severe asthma research program.
Am J Respir Crit Care Med 133, 1557–1563.
[46] Minami K, Kabata D, Kakuta T, Fukushima S, Fujita T, Shintani
A, Yoshitani K, Ohnishi Y. 2020 U-shaped association between
intraoperative net fluid balance and risk of postoperative recurrent
atrial tachyarrhythmia among patients undergoing the cryo-maze
procedure: An observational study. Journal of Cardiothoracic and
Vascular Anesthesia (doi:10.1053/j.jvca.2020.10.023).
[47] Tanaka K, Miyake Y, Arakawa M, Sasaki S, Ohya Y. 2011 U-shaped
association between body mass index and the prevalence of wheeze and
asthma, but not eczema or rhinoconjunctivitis: The Ryukyus child health
study. The Journal of asthma : official journal of the Association for
the Care of Asthma 48, 804–10. (doi:10.3109/02770903.2011.611956).
[48] Juhn Y, Liu H. 2019 Natural language processing to advance
ehr-based clinical research in allergy, asthma, and immunology. Journal
of Allergy and Clinical Immunology 145. (doi:
10.1016/j.jaci.2019.12.897).
[49] Sallis BF, Erkert L, Moñino-Romero S, Acar U, Wu R, Konnikova
L, Lexmond WS, Hamilton MJ, Dunn WA, Szepfalusi Z, et al. 2018 An
algorithm for the classification of mrna patterns in eosinophilic
esophagitis: Integration of machine learning. Journal of Allergy and
Clinical Immunology 141, 4, 1354–1364.e9.
(doi:https://doi.org/10.1016/j.jaci.2017.11.027).
[50] Chowdhury NI, Smith TL, Chandra RK, Turner JH. 2019 Automated
classification of osteomeatal complex inflammation on computed
tomography using convolutional neural networks. International Forum of
Allergy & Rhinology 9, 1, 46–52.
(doi:https://doi.org/10.1002/alr.22196).
[51] Katotomichelakis M, Gouveris H, Tripsianis G, Simopoulou M,
Papathanassiou J, Danielides V. 2010 Biometric predictive models for the
evaluation of olfactory recovery after endoscopic sinus surgery in
patients with nasal polyposis. American journal of rhinology and allergy
24, 4, 276—280. (doi: 10.2500/ajra.2010.24.3476).
[52] da Silva DA, ten Caten CS, dos Santos RP, Fogliatto FS, Hsuan
J. 2019 Predicting the occurrence of surgical site infections using text
mining and machine learning. PLOS ONE 14, 12, 1–17. (doi:
10.1371/journal.pone.0226272).
[53] Aram P, Trela-Larsen L, Sayers A, Hills A, Blom A, McCloskey E,
Kadirkamanathan V, Wilkinson J. 2018 Estimating an individual’s
probability of revision surgery after knee replacement: A comparison of
modeling approaches using a national data set. American journal of
epidemiology 187. (doi:10.1093/aje/kwy121).
[54] Karhade AV, Ogink PT, Thio QC, Cha TD, Gormley WB, Hershman SH,
Smith TR, Mao J, Schoenfeld AJ, Bono CM, et al. 2019 Development of
machine learning algorithms for prediction of prolonged opioid
prescription after surgery for lumbar disc herniation. The Spine Journal
19, 11, 1764 – 1771. (doi:
https://doi.org/10.1016/j.spinee.2019.06.002).
[55] Durand WM, DePasse JM, Daniels AH. 2018 Predictive modeling for
blood transfusion after adult spinal deformity surgery. Spine 43, 15,
1058 – 1066. (doi:10.1097/BRS.0000000000002515).
[56] Toppila-Salmi S, Rihkanen H, Arffman M, Manderbacka K,
Keskimaki I, Hytönen M. 2018 Regional differences in endoscopic sinus
surgery in finland: A nationwide register-based study. BMJ Open 8,
e022173. (doi:10.1136/bmjopen-2018-022173).
[57] Lyly A, Laulajainen-Hongisto A, Gevaert P, Kauppi P,
Toppila-Salmi S. 2020 Monoclonal antibodies and airway diseases.
International Journal of Molecular Sciences 21, 24.
(doi:10.3390/ijms21249477).
Table 1. Characteristics of patients without/with status of revision
ESS. P values by Fisher’s exact test.