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1. Cost and appropriateness of treating asthma with fixed-combination drugs in local health care units in Italy

Author

Ruggeri I, Bragato D, Colombo GL, Valla E, and Di Matteo S

Subjects
Medicine (General), R5-920, Therapeutics. Pharmacology, RM1-950
Abstract

Isabella Ruggeri,1 Donatello Bragato,2 Giorgio L Colombo,3,4 Emanuela Valla,3 Sergio Di Matteo41Servizio Governo Area Farmaceutica, Azienda Sanitaria Locale, Milano, Binasco, 2Data Solution Provider, Milan, 3University of Pavia, Department of Drug Sciences, School of Pharmacy, 4Studi Analisi Valutazioni Economiche, MilanBackground: Bronchial asthma is a chronic airways disease and is considered to be one of the major health problems in the Western world. During the last decade, a significant increase in the use of β2-agonists in combination with inhaled corticosteroids has been observed. The aim of this study was to assess the appropriateness of expenditure on these agents in an asthmatic population treated in a real practice setting.Methods: This study used data for a resident population of 635,906 citizens in the integrated patient database (Banca Dati Assistito) of a local health care unit (Milano 2 Azienda Sanitaria Locale) in the Lombardy region over 3 years (2007–2009). The sample included 3787–4808 patients selected from all citizens aged ≥ 18 years entitled to social security benefits, having a prescription for a corticosteroid + β2-agonist combination, and an ATC code corresponding to R03AK, divided into three groups, ie, pressurized (spray) drugs, inhaled powders, and extrafine formulations. Patients with chronic obstructive lung disease were excluded. Indicators of appropriateness were 1–3 packs per year (underdosed, inappropriate), 4–12 packs per year (presumably appropriate), and ≥13 packs per year (overtreatment, inappropriate).Results: The corticosteroid + β2-agonist combination per treated asthmatic patient increased from 37% in 2007 to 45% in 2009 for the total of prescribed antiasthma drugs, and 28%–32% of patients used the drugs in an appropriate manner (4–12 packs per years). The cost of inappropriately used packs increased combination drug expenditure by about 40%, leading to inefficient use of health care resources. This trend improved during the 3-year observation period. The mean annual cost per patient was higher for powders (€223.95) and sprays (€224.83) than for extrafine formulation (€142.71).Conclusion: Based on this analysis, we suggest implementation of better health care planning and more appropriate prescription practices aimed at optimizing use of health care resources for the treatment of bronchial asthma. The results of our study should be extended to other regional/national reference local health care units, in order to define and compare average standard costs per pathology, and consolidated through the wide sample considered.Keywords: asthma, antiasthma drugs, general medicine, appropriateness, pharmacoeconomics, health economics

Published
2012

2. First Study of Rapidity Gaps in e + e Annihilation

Author

Abe, K, Abt, I, Akagi, T, Allen, N, Ash, W, Aston, D, Baird, K, Baltay, C, Band, H, Barakat, M, Baranko, G, Bardon, O, Barklow, T, Bashindzhagyan, G, Bazarko, A, Bendavid, R, Benvenuti, A, Bilei, G, Bisello, D, Blaylock, G, Bogart, J, Bolton, T, Bower, G, Brau, J, Breidenbach, M, Bugg, W, Burke, D, Burnett, T, Burrows, P, Busza, W, Calcaterra, A, Caldwell, D, Calloway, D, Camanzi, B, Carpinelli, M, Cassell, R, Castaldi, R, Castro, A, Cavallisforza, M, Chou, A, Church, E, Cohn, H, Coller, J, Cook, V, Cotton, R, Cowan, R, Coyne, D, Crawford, G, Doliveira, A, Damerell, C, Daoudi, M, Desangro, R, Desimone, P, Dellorso, R, Dervan, P, Dima, M, Dong, D, Du, P, Dubois, R, Eisenstein, B, Elia, R, Etzion, E, Falciai, D, Fan, C, Fero, M, Frey, R, Furuno, K, Gillman, T, Gladding, G, Gonzalez, S, Hallewell, G, Hart, E, Hasan, A, Hasegawa, Y, Hasuko, K, Hedges, S, Hertzbach, S, Hildreth, M, Huber, J, Huffer, M, Hughes, E, Hwang, H, Iwasaki, Y, Jackson, D, Jacques, P, Jaros, J, Johnson, A, Johnson, J, Johnson, R, Junk, T, Kajikawa, R, Kalelkar, M, Kang, H, Karliner, I, Kawahara, H, Kendall, H, Kim, Y, King, M, King, R, Kofler, R, Krishna, N, Kroeger, R, Labs, J, Langston, M, Lath, A, Lauber, J, Leith, D, Lia, V, Liu, M, Liu, X, Loreti, M, Lu, A, Lynch, H, Ma, J, Mancinelli, G, Manly, S, Mantovani, G, Markiewicz, T, Maruyama, T, Massetti, R, Masuda, H, Mazzucato, E, Mckemey, A, Meadows, B, Messner, R, Mockett, P, Moffeit, K, Mours, B, Muller, D, Nagamine, T, Narita, S, Nauenberg, U, Neal, H, Nussbaum, M, Ohnishi, Y, Osborne, L, Panvini, R, Park, H, Pavel, T, Peruzzi, I, Piccolo, M, Piemontese, L, Pieroni, E, Pitts, K, Plano, R, Prepost, R, Prescott, C, Punkar, G, Quigley, J, Ratcliff, B, Reeves, T, Reidy, J, Rensing, P, Rochester, L, Rowson, P, Russell, J, Saxton, O, Schalk, T, Schindler, R, Schumm, B, Sen, S, Serbo, V, Shaevitz, M, Shank, J, Shapiro, G, Sherden, D, Shmakov, K, Simopoulos, C, Sinev, N, Smith, S, Snyder, J, Stamer, P, Steiner, H, Steiner, R, Strauss, M, Su, D, Suekane, F, Sugiyama, A, Suzuki, S, Swartz, M, Szumilo, A, Takahashi, T, Taylor, F, Torrence, E, Trandafir, A, Turk, J, Usher, T, Vavra, J, Vannini, C, Valla, E, Venuti, J, Verdier, R, Verdini, P, Wagner, S, Waite, A, Watts, S, Weidemann, A, Weiss, E, Whitaker, J, White, S, Wickens, F, Williams, D, Williams, S, Willocq, S, Wilson, R, Wisniewski, W, Woods, M, Word, G, Wyss, J, Yamamoto, R, Yamartino, J, Yang, X, Yellin, S, Young, C, Yuta, H, Zapalac, G, Zdarko, R, Zeitlin, C, Zhou, J, Abe K, Abt I, Akagi T, Allen NJ, Ash WW, Aston D, Baird KG, Baltay C, Band HR, Barakat MB, Baranko G, Bardon O, Barklow T, Bashindzhagyan GL, Bazarko AO, BenDavid R, Benvenuti AC, Bilei GM, Bisello D, Blaylock G, Bogart JR, Bolton T, Bower GR, Brau JE, Breidenbach M, Bugg WM, Burke D, Burnett TH, Burrows PN, Busza W, Calcaterra A, Caldwell DO, Calloway D, Camanzi B, CARPINELLI, Massimo, Cassell R, Castaldi R, Castro A, CavalliSforza M, Chou A, Church E, Cohn HO, Coller JA, Cook V, Cotton R, Cowan RF, Coyne DG, Crawford G, DOliveira A, Damerell CJS, Daoudi M, DeSangro R, DeSimone P, DellOrso R, Dervan PJ, Dima M, Dong DN, Du PYC, Dubois R, Eisenstein BI, Elia R, Etzion E, Falciai D, Fan C, Fero MJ, Frey R, Furuno K, Gillman T, Gladding G, Gonzalez S, Hallewell GD, Hart EL, Hasan A, Hasegawa Y, Hasuko K, Hedges S, Hertzbach SS, Hildreth MD, Huber J, Huffer ME, Hughes EW, Hwang H, Iwasaki Y, Jackson DJ, Jacques P, Jaros J, Johnson AS, Johnson JR, Johnson RA, Junk T, Kajikawa R, Kalelkar M, Kang HJ, Karliner I, Kawahara H, Kendall HW, Kim Y, King ME, King R, Kofler RR, Krishna NM, Kroeger RS, Labs JF, Langston M, Lath A, Lauber JA, Leith DWGS, Lia V, Liu MX, Liu X, Loreti M, Lu A, Lynch HL, Ma J, Mancinelli G, Manly S, Mantovani G, Markiewicz TW, Maruyama T, Massetti R, Masuda H, Mazzucato E, McKemey AK, Meadows BT, Messner R, Mockett PM, Moffeit KC, Mours B, Muller D, Nagamine T, Narita S, Nauenberg U, Neal H, Nussbaum M, Ohnishi Y, Osborne LS, Panvini RS, Park H, Pavel TJ, Peruzzi I, Piccolo M, Piemontese L, Pieroni E, Pitts KT, Plano RJ, Prepost R, Prescott CY, Punkar GD, Quigley J, Ratcliff BN, Reeves TW, Reidy J, Rensing PE, Rochester LS, Rowson PC, Russell JJ, Saxton OH, Schalk T, Schindler RH, Schumm BA, Sen S, Serbo VV, Shaevitz MH, Shank JT, Shapiro G, Sherden DJ, Shmakov KD, Simopoulos C, Sinev NB, Smith SR, Snyder JA, Stamer P, Steiner H, Steiner R, Strauss MG, Su D, Suekane F, Sugiyama A, Suzuki S, Swartz M, Szumilo A, Takahashi T, Taylor FE, Torrence E, Trandafir AI, Turk JD, Usher T, Vavra J, Vannini C, Valla E, Venuti JP, Verdier R, Verdini PG, Wagner SR, Waite AP, Watts SJ, Weidemann AW, Weiss ER, Whitaker JS, White SL, Wickens FJ, Williams DA, Williams DC, Williams SH, Willocq S, Wilson RJ, Wisniewski WJ, Woods M, Word GB, Wyss J, Yamamoto RK, Yamartino JM, Yang X, Yellin SJ, Young CC, Yuta H, Zapalac G, Zdarko RW, Zeitlin C, Zhou J., Abe, K, Abt, I, Akagi, T, Allen, N, Ash, W, Aston, D, Baird, K, Baltay, C, Band, H, Barakat, M, Baranko, G, Bardon, O, Barklow, T, Bashindzhagyan, G, Bazarko, A, Bendavid, R, Benvenuti, A, Bilei, G, Bisello, D, Blaylock, G, Bogart, J, Bolton, T, Bower, G, Brau, J, Breidenbach, M, Bugg, W, Burke, D, Burnett, T, Burrows, P, Busza, W, Calcaterra, A, Caldwell, D, Calloway, D, Camanzi, B, Carpinelli, M, Cassell, R, Castaldi, R, Castro, A, Cavallisforza, M, Chou, A, Church, E, Cohn, H, Coller, J, Cook, V, Cotton, R, Cowan, R, Coyne, D, Crawford, G, Doliveira, A, Damerell, C, Daoudi, M, Desangro, R, Desimone, P, Dellorso, R, Dervan, P, Dima, M, Dong, D, Du, P, Dubois, R, Eisenstein, B, Elia, R, Etzion, E, Falciai, D, Fan, C, Fero, M, Frey, R, Furuno, K, Gillman, T, Gladding, G, Gonzalez, S, Hallewell, G, Hart, E, Hasan, A, Hasegawa, Y, Hasuko, K, Hedges, S, Hertzbach, S, Hildreth, M, Huber, J, Huffer, M, Hughes, E, Hwang, H, Iwasaki, Y, Jackson, D, Jacques, P, Jaros, J, Johnson, A, Johnson, J, Johnson, R, Junk, T, Kajikawa, R, Kalelkar, M, Kang, H, Karliner, I, Kawahara, H, Kendall, H, Kim, Y, King, M, King, R, Kofler, R, Krishna, N, Kroeger, R, Labs, J, Langston, M, Lath, A, Lauber, J, Leith, D, Lia, V, Liu, M, Liu, X, Loreti, M, Lu, A, Lynch, H, Ma, J, Mancinelli, G, Manly, S, Mantovani, G, Markiewicz, T, Maruyama, T, Massetti, R, Masuda, H, Mazzucato, E, Mckemey, A, Meadows, B, Messner, R, Mockett, P, Moffeit, K, Mours, B, Muller, D, Nagamine, T, Narita, S, Nauenberg, U, Neal, H, Nussbaum, M, Ohnishi, Y, Osborne, L, Panvini, R, Park, H, Pavel, T, Peruzzi, I, Piccolo, M, Piemontese, L, Pieroni, E, Pitts, K, Plano, R, Prepost, R, Prescott, C, Punkar, G, Quigley, J, Ratcliff, B, Reeves, T, Reidy, J, Rensing, P, Rochester, L, Rowson, P, Russell, J, Saxton, O, Schalk, T, Schindler, R, Schumm, B, Sen, S, Serbo, V, Shaevitz, M, Shank, J, Shapiro, G, Sherden, D, Shmakov, K, Simopoulos, C, Sinev, N, Smith, S, Snyder, J, Stamer, P, Steiner, H, Steiner, R, Strauss, M, Su, D, Suekane, F, Sugiyama, A, Suzuki, S, Swartz, M, Szumilo, A, Takahashi, T, Taylor, F, Torrence, E, Trandafir, A, Turk, J, Usher, T, Vavra, J, Vannini, C, Valla, E, Venuti, J, Verdier, R, Verdini, P, Wagner, S, Waite, A, Watts, S, Weidemann, A, Weiss, E, Whitaker, J, White, S, Wickens, F, Williams, D, Williams, S, Willocq, S, Wilson, R, Wisniewski, W, Woods, M, Word, G, Wyss, J, Yamamoto, R, Yamartino, J, Yang, X, Yellin, S, Young, C, Yuta, H, Zapalac, G, Zdarko, R, Zeitlin, C, Zhou, J, Abe K, Abt I, Akagi T, Allen NJ, Ash WW, Aston D, Baird KG, Baltay C, Band HR, Barakat MB, Baranko G, Bardon O, Barklow T, Bashindzhagyan GL, Bazarko AO, BenDavid R, Benvenuti AC, Bilei GM, Bisello D, Blaylock G, Bogart JR, Bolton T, Bower GR, Brau JE, Breidenbach M, Bugg WM, Burke D, Burnett TH, Burrows PN, Busza W, Calcaterra A, Caldwell DO, Calloway D, Camanzi B, CARPINELLI, Massimo, Cassell R, Castaldi R, Castro A, CavalliSforza M, Chou A, Church E, Cohn HO, Coller JA, Cook V, Cotton R, Cowan RF, Coyne DG, Crawford G, DOliveira A, Damerell CJS, Daoudi M, DeSangro R, DeSimone P, DellOrso R, Dervan PJ, Dima M, Dong DN, Du PYC, Dubois R, Eisenstein BI, Elia R, Etzion E, Falciai D, Fan C, Fero MJ, Frey R, Furuno K, Gillman T, Gladding G, Gonzalez S, Hallewell GD, Hart EL, Hasan A, Hasegawa Y, Hasuko K, Hedges S, Hertzbach SS, Hildreth MD, Huber J, Huffer ME, Hughes EW, Hwang H, Iwasaki Y, Jackson DJ, Jacques P, Jaros J, Johnson AS, Johnson JR, Johnson RA, Junk T, Kajikawa R, Kalelkar M, Kang HJ, Karliner I, Kawahara H, Kendall HW, Kim Y, King ME, King R, Kofler RR, Krishna NM, Kroeger RS, Labs JF, Langston M, Lath A, Lauber JA, Leith DWGS, Lia V, Liu MX, Liu X, Loreti M, Lu A, Lynch HL, Ma J, Mancinelli G, Manly S, Mantovani G, Markiewicz TW, Maruyama T, Massetti R, Masuda H, Mazzucato E, McKemey AK, Meadows BT, Messner R, Mockett PM, Moffeit KC, Mours B, Muller D, Nagamine T, Narita S, Nauenberg U, Neal H, Nussbaum M, Ohnishi Y, Osborne LS, Panvini RS, Park H, Pavel TJ, Peruzzi I, Piccolo M, Piemontese L, Pieroni E, Pitts KT, Plano RJ, Prepost R, Prescott CY, Punkar GD, Quigley J, Ratcliff BN, Reeves TW, Reidy J, Rensing PE, Rochester LS, Rowson PC, Russell JJ, Saxton OH, Schalk T, Schindler RH, Schumm BA, Sen S, Serbo VV, Shaevitz MH, Shank JT, Shapiro G, Sherden DJ, Shmakov KD, Simopoulos C, Sinev NB, Smith SR, Snyder JA, Stamer P, Steiner H, Steiner R, Strauss MG, Su D, Suekane F, Sugiyama A, Suzuki S, Swartz M, Szumilo A, Takahashi T, Taylor FE, Torrence E, Trandafir AI, Turk JD, Usher T, Vavra J, Vannini C, Valla E, Venuti JP, Verdier R, Verdini PG, Wagner SR, Waite AP, Watts SJ, Weidemann AW, Weiss ER, Whitaker JS, White SL, Wickens FJ, Williams DA, Williams DC, Williams SH, Willocq S, Wilson RJ, Wisniewski WJ, Woods M, Word GB, Wyss J, Yamamoto RK, Yamartino JM, Yang X, Yellin SJ, Young CC, Yuta H, Zapalac G, Zdarko RW, Zeitlin C, and Zhou J.

Abstract

We present the first study of rapidity gaps in e+e- annihilations using Z0 decays collected by the SLD experiment at SLAC. Our measured rapidity gap spectra fall exponentially with increasing gap size over five decades, and we observe no anomalous class of events containing large gaps. This supports the interpretation of the large-gap events measured in pp and ep collisions in terms of exchange of color-singlet objects. The presence of heavy flavors or additional jets does not affect these conclusions.

Published
1996

7. Transforming fatigue assessment: Smartphone-based system with digitized motor skill tests.

Author

Valla E, Toose AJ, Nõmm S, and Toomela A

Subjects
Humans, Tremor diagnosis, Quality of Life, Machine Learning, Smartphone, Motor Skills
Abstract

Background: The condition of fatigue is a complex and multifaceted disorder that encompasses physical, mental, and psychological dimensions, all of which contribute to a decreased quality of life. Smartphone-based systems are gaining significant research interest due to their potential to provide noninvasive monitoring and diagnosis of diseases., Objective: This paper studies the feasibility of using smartphones to collect motor skill related data for machine learning based fatigue detection. The authors' main goal is to provide valuable insights into the nature of fatigue and support the development of more effective interventions to manage it., Methods: An application for smartphones running on Android OS is developed. Two aim-based reaction tests, an Archimedean spiral test, and a tremor test, were assembled. 41 subjects participated in the study. The resulting dataset consists of 131 trials of fatigue assessment alongside digital signals extracted from the motor skill tests. Six machine learning classifiers were trained on computed features extracted from the collected digital signals., Results: The collected dataset SmartPhoneFatigue is presented for further research. The real-world utility of this database was shown by creating a methodology to construct a fatigue predictive model. Our approach incorporated 60 distinct features, such as kinematic, angular, aim-based, and tremor-related measures. The machine learning models exhibited a high degree of prediction rate for fatigue state, with an accuracy exceeding 70%, sensitivity surpassing 90%, and an f1-score greater than 80%., Conclusion: The results demonstrate that the proposed smartphone-based system is suitable for motion data acquisition in non-controlled environments and shows promise as a more objective and convenient method for measuring fatigue., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Published
2023
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