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1. A review of the application of cellulose hemostatic agent on trauma injuries

Author

Khoshmohabat H, Paydar S, Makarem A, Karami MY, Dastgheib N, Zahraei SAH, Rezaei R, and Mahmoudi Nezhad GS

Subjects
Cellulose hemostatic agent, trauma, injury, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Hadi Khoshmohabat,1 Shahram Paydar,2 Alireza Makarem,1,3 Mohammad Yasin Karami,2 Niloofar Dastgheib,4 Seyed Ali Hossein Zahraei,4 Rohallah Rezaei,2 Golnoush Sadat Mahmoudi Nezhad21Trauma Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran; 2Trauma Research Center, Rajaee (Emtiaz) Trauma Hospital, Shiraz University of Medical Sciences, Shiraz, Iran; 3Department of Urology, Shiraz University of Medical Sciences, Shiraz, Iran; 4Student Research Committee, Shiraz University of Medical Sciences, Shiraz, IranIntroduction: Planning for management of bleeding in trauma injuries is very important. The initial purpose in emergency situations should be immediate establishment of an efficient hemostasis, principally in its topical application. In this study, we aimed to review the major relevant articles in the case of application of cellulose hemostatic agent on trauma injuries.Methods: We searched the online databases such as PubMed, MEDLINE, Wiley, EMBASE, ISI Web of Knowledge, and Scopus. Two reviewers independently searched and assessed the titles and abstracts of all articles.Results: Upon screening the titles and abstracts, 24 studies were identified for full-text review. The oxidized cellulose had the best clotting times, while it demonstrated low absorption ability. Surgical and thermosensitive chitosan hemostatic could be valuable for managing hemorrhage from liver injuries in trauma patients.Conclusion: Recently, the application of cellulose hemostatic agents has been one of the main improvements obtained for controlling bleeding in trauma injuries. However, generally according to the literature review, the decision about using each agent should be made on a case-by-case basis. However, it can be mentioned that the perfect hemostatic agent has not been still identified.Keywords: cellulose hemostatic agent, trauma, injury

Published
2019

2. Outcome Determinants of Patients with Traumatic Pelvic Fractures: A Cohort Study in a Level I Trauma Center in Southern Iran

Author

Paydar S, Chaabi M, Akhavan M, Ghahramani Z, and Dehghankhalili M

Subjects
pelvic fracture, outcome, mortality, surgery, prognosis, Orthopedic surgery, RD701-811
Abstract

Pelvic fracture is a result of devastating injuries and is usually encountered in conjunction with other life- threatening injuries. The aim of the current study was to determine the outcome determinants of patients with pelvic fractures referred to a large trauma center in southern Iran. This retrospective cross-sectional study was conducted in a level I trauma center over a period of three years from 2012 to 2015. We included all patients with pelvic fractures whose medical records had sufficient data. Data were compared between good condition and poor conditions. A total of 327 patients with mean age of 40.1 ± 19.7 years were included. Poor condition was defined as being associated with higher heart rate (p=0.002), lower systolic blood pressure (p

Published
2017
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3. International Nosocomial Infection Control Consortium (INICC) report, data summary of 45 countries for 2012-2017: Device-associated module

Author

Riera, F.O., López, M., Maurizi, D.M., Desse, J.E., Pérez, I., Silva, G.C., Chaparro, G.J., Golschmid, D., Cabrera, R., Montanini, A.M., Bianchi, A.C., Vimercati, J., Rodríguez-del-Valle, M.C., Domínguez, C.V., Saul, P.A., Chediack, V., Piastrelini, M., Cardena, L.P., Ramasco, L., Olivieri, M.S., Gallardo, P.F., Juarez, P.D., Brito, M.P., Botta, P., Alvarez, G., Benchetrit, G., Caridi, M., Stagnaro, J.P., Bourlot, I., García, M., Arregui, N.V., Saeed, N.K., Abdul-Aziz, S., ALSayegh, S., Humood, M.Z., Mohamed-Ali, K., Swar, S., Magray, T.A.S., Aguiar-Portela, T.B., Sugette-de-Aguiar, T., Serpa-Maia, F.I., Fernandes-Alves-de-Lima, L., Teixeira-Josino, L.A., Sampaio-Bezerra, M., Furtado-Maia, R.C., Romário-Mendes, A., Alves-De-Oliveira, A., Vasconcelos-Carneiro, A.P., Anjos-Lima, J. Dos, Pinto-Coelho, K.H., Maciel-Canuto, M.L., Rocha-Batista, M.X., Moreira, T., Rodrigues-Amarilo, N., Lima-de-Barros, T.M., Guimarães, K. Arruda, Batista, C., Santos, C., de-Lima-Silva, F.J., Santos-Mota, E., Karla, L., Ferreira-de-Souza, M.C., Luzia, N., de-Oliveira, S.S, Takeda, C., Azevedo-Ferreira-Lima, D., Faheina, J., Coelho-Oliveira, L.M., do-Nascimento, S.C., Machado-Silva, V.L., Bento-Ferreira, Olszewski, J., Tenorio, M.T., Silva-Lemos, A.C., Ramos-Feijó, C.A., Cardoso, D.M., Correa-Barbosa, M.A., Assunção-Ponte, G., da-Silva-Escudero, D.V., Servolo-Medeiros, E.A., Andrade-Oliveira-Reis, M., Kostadinov, E.D., Dicheva, V.J., Petrov, M.M., Guo, C., Yu, H., Liu, T., Song, G., Wang, C., Cañas-Giraldo, L.M., Marin-Tobar, D.A., Trujillo-Ramirez, E.M., Andrea-Rios, P., Álvarez-Moreno, C., Linares, C., González-Rubio, P.A., Ariza-Ayala, B.E., Gamba-Moreno, L.J., Gualtero-Trujill, S.L., Segura-Sarmiento, S.J., Rodriguez-Pena, J., Ortega, R., Olarte, N., Pardo-Lopez, Y.A., Luis Marino Otela-Baicue, A., Vargas-Garcia, A.R., Roncancio, E.G., Gomez-Nieto, K., Espinosa-Valencia, M., Barahona-Guzman, N., Avila-Acosta, C., Raigoza-Martinez, W., Villamil-Gomez, W., Chapeta-Parada, E.G., Mindiola-Rochel, A.E., Corchuelo-Martinez, A.H., Martinez, A., Lagares-Guzman, A., Rodriguez-Ferrer, M., Yepes-Gomez, D., Muñoz-Gutierrez, G.A., Arguello-Ruiz, A., Zuniga-Chavarria, M.A., Maroto-Vargas, L., Valverde-Hernández, M., Solano-Chinchilla, A., Calvo-Hernandez, I., Chavarria-Ugalde, O., Tolari, G., Rojas-Fermin, R.A., Diaz-Rodriguez, C.V., Huascar, S., Ortiz, M., Bovera, M.M., Alquinga, N., Santacruz, G., Jara, E., Delgado, V., Salgado-Yepez, E., Valencia, F., Pelaez, C., Gonzalez-Flores, H.A., Coello-Gordon, E.E., Picoita, F., Arboleda, M., Garcia, M.F., Velez, J., Valle, M., Unigarro, L., Figueroa, V., Marin, K., Caballero-Narvaez, H., Bayani, V., Ahmed, S.A., Alansary, A.M., Hassan, A.R., Abdel-Halim, M.M., El-Fattah, M.A., Abdelaziz-Yousef, R.H., Hala, A., Abdelhady, K.M., Ahmed-Fouad, H., Mounir-Agha, H., Hamza, H.S., Salah, Z., Abdel-Aziz, D.M., Ibrahim, S.B., Helal, A.M., AbdelMassih, A.F., Mahmoud, A. Reham, Elawady, B., El-sherif, R.H., Fattah-Radwan, Y.A., Abdel-Mawla, T.S., Kamal-Elden, N.M., Kartsonaki, M., Rivera, D.M., Mandal, S., Mukherjee, S., Navaneet, P., Padmini, B., Sorabjee, J.S., Sakle, A.S., Potdar, M.S., Mane, D., Sale, H.K., Abdul-Gaffar, M.M., Kazi, M., Chabukswar, S., Anju, M., Gaikwad, D., Harshe, A., Blessymole, S., Nair, P.K., Khanna, D.K., Chacko, F., Rajalakshmi, A., Mubarak, A., Kharbanda, M., Kumar, S., Mathur, P., Saranya, S., Abubakar, F., Sampat, S., Raut, V., Biswas, S.K., Kelkar, R., Divatia, J.V., Chakravarthy, M., Gokul, B.N., Sukanya, R., Pushparaj, L., Thejasvini, A., Rangaswamy, S., Saini, N., Bhattacharya, C., Das, S., Sanyal, S., Chaudhury, B.N., Rodrigues, C., Khanna, G., Dwivedy, A., Binu, S., Shetty, S., Eappen, J., Valsa, T., Sriram, A., Todi, S.K., Bhattacharyya, M., Bhakta, A., Ramachandran, B., Krupanandan, R., Sahoo, P., Mohanty, N., Sahu, S., Misra, S., Ray, B., Pattnaik, S., Pillai, H., Warrier, A.R., Ranganathan, L., Mani, A.K., Rajagopal, S.K., Abraham, B.K., Venkatraman, R., Ramakrishnan, N., Devaprasad, D., Siva, K., Divekar, D.G., Satish Kavathekar, M.S., Suryawanshi, M.V., Poojary, A., Sheeba, J., Patil, P., Kukreja, S., Varma, K., Narayanan, S., Sohanlal, T., Agarwal, A., Agarwal, M., Nadimpalli, G., Bhamare, S., Thorat, S., Sarda, O., Nadimpalli, P., Nirkhiwale, S., Gehlot, G.S., Bhattacharya, S., Pandya, N., Raphel, A.K.O., Zala, D., Mishra, S.B., Patel, M.H., Aggarwal, D.G.C., Jawadwal, B.Q., Pawar, N.K., Kardekar, S.N., Manked, A.N., Tamboli, A.S., Manked, A., Khety, Z., Singhal, T., Shah, S., Kothari, V., Naik, R., Narain, R., Sengupta, S., Karmakar, A., Mishra, S., Pati, B.K., Kantroo, V., Kansal, S., Modi, N., Chawla, R., Chawla, A., Roy, I., Bej, M., Mukherjee, P., Baidya, S., Durell, A., Vadi, S., Saseedharan, S., Anant, P., Edwin, J.P., Sen, N., Sandhu, K., Sharma, S., Palaniswamy, V., Sharma, P., Selvaraj, M., Saurabh, L., Punia, D.P., Soni, D.K., Misra, R., Harsvardhan, R., Azim, A., Kambam, C., Garg, A., Ekta, S., Lakhe, M., Sharma, C.B., Singh, G., Kaur, A., Singhal, S., Chhabra, K.D., Ramakrishnan, G., Kamboj, H., Pillai, S., Rani, P., Singla, D., Sanaei, A., Maghsudi, B., Sabetian, G., Masjedi, M., Shafiee, E., Nikandish, R., Paydar, S., Khalili, H.A., Moradi, A., Sadeghi, P., Bolandparvaz, S., Mubarak, S., Makhlouf, M., Awwad, M., Ayyad, O., Shaweesh, A.A., Khader, M.M., Alghazawi, A., Hussien, N., Alruzzieh, M., Mohamed, Y.K., ALazhary, M., Abdul Aziz, O.A., Alazmi, M., Mendoza, J., De Vera, P.A., Rillorta, A.S., de Guzman, M., Girvan, M., Torres, M., Alzahrani, N., Alfaraj, S., Gopal, U., Manuel, M.G., Alshehri, R., Lessing, L., Alzoman, H., Abdrahiem, J., Adballah, H., Thankachan, J., Gomaa, H., Asad, T., AL-Alawi, M., Al-Abdullah, N.A., Demaisip, N.L., Laungayan-Cortez, E., Cabato, A.F., Gonzales, J.M., Al Raey, M.A., Al-Darani, S.A., Aziz, M.R., Al-Manea, B., Samy, E., AlDalaton, M., Alaliany, M.J., Alabdely, H.M., Helali, N.J., Sindayen, G., Malificio, A.A., Al-Dossari, H.B., Kelany, A., Algethami, A.G., Mohamed, D., Yanne, L., Tan, A., Babu, S., Abduljabbar, S.M., Al-Zaydani, M.A., Ahmed, H., Al Jarie, A., Al-Qathani, A.S.M., Al-Alkami, H.Y., Alih, S.J.B., Gasmin-Aromin, R., Balon-Ubalde, E., Diab, H.H., Kader, N.A., Hassan-Assiry, I.Y., Albeladi, E., Aboushoushah, S., Qushmaq, N., Fernandez, J., Hussain, W.M., Rajavel, R.D., Bukhari, S.Z., Rushdi, H., Turkistani, A.A., Mushtaq, J.J., Bohlega, E., Simon, S., Damlig, E., Elsherbini, S.G., Abraham, S., Kaid, E., Al-Attas, A., Hawsawi, G., Hussein, B., Esam, B., Caminade, Y., Santos, A.J., Abdulwahab, M.H., Aldossary, A.H., Al-Suliman, S., AlTalib, A.A., Albaghly, N., HaqlreMia, M.E., Altowerqi, R., Ghalilah, K.M., Alradady, M., Al-Qatri, A., Chaouali, M., Shyrine, E.L., Philipose, J., Raees, M., AbdulKhalik, N.S., Madco, M., Acostan, C., Safwat, R., Halwani, M., Abdul-Aal, N.A.H., Thomas, A., Abdulatif, S.M., Ali-Karrar, M.A., Al-Gosn, N., Al-Hindi, A.A., Jaha, R.N., AlQahtani, S.N., Ayugat, E.P., Al-Hussain, M.I., Aldossary, A., Al-Talib, A.A., Haqlre-Mia, M.E., Briones, S., Krishnan, R., Tabassum, K., Alharbi, L., Madani, A., Al-Gethamy, M.A., Alamri, D.M., Spahija, G., Gashi, A., Kurian, A., George, S.M., Mohamed, A.M., Ramapurath, R.J., Varghese, S.T., Abdo, N.M., Foda-Salama, M., Al-Mousa, H.H., Omar, A.A., Salama, M.F., Toleb, M., Khamis, S., Kanj, S.S., Zahreddine, N.K., Kanafani, Z., Kardas, T., Ahmadieh, R., Hammoud, Z., Zeid, I., Al-Souheil, A., Ayash, H., Mahfouz, T., Kondratas, T., Grinkeviciute, D., Kevalas, R., Dagys, A., Mitrev, Z., Bogoevska-Miteva, Z., Jankovska, K., Guroska, S.T., Petrovska, M., Popovska, K., Ng, C., Hoon, Y.M., Hasan, YM.S., Othman-Jailani, M.I., Hadi-Jamaluddin, M.F., Othman, A.A., Zainol, H., Wan-Yusoff, W.N., Gan, C.S., Lum, L.C.S., Ling, C.S., Aziz, F.A., Zhazali, R., Abud-Wahab, M.R., Cheng, T.S., Elghuwael, I.M., Wan-Mat, W.R., Abd-Rahman, R., Perez-Gomez, H.R., Kasten-Monges, M., Esparza-Ahumada, S., Rodriguez-Noriega, E., Gonzalez-Diaz, E., Mayoral-Pardo, D., Cerero-Gudino, A., Altuzar-Figueroa, M.A., Perez-Cruz, J., Escobar-Vazquez, M., Aragon, D.M.L., Coronado-Magana, H., Mijangos-Mendez, J.C., Corona-Jimenez, F., Aguirre-Avalos, G., Lopez-Mateos, A., Martinez-Marroquin, M.Y., Montell-Garcia, M., Martinez-Martinez, A., Leon-Sanchez, E., Gomez-Flores, G., Ramirez, M., Gomez, M.E., Lozano, M., Mercado, V.N., Zamudio-Lugo, I., Gomez-Gonzalez, C.J., Miranda-Novales, M.G., Villegas-Mota, I., Reyes-Garcia, C., Ramirez-Morales, M.K., Sanchez-Rivas, M., Cureno-Diaz, M.A., Matias-Tellez, B., Gonzalez-Martinez, J., Juarez-Vargas, R., Pastor-Salinas, O., Gutierrez-Munoz, V.H., Conde-Mercado, J.M., Bruno-Carrasco, G., Manrique, M.A., Monroy-Colin, V.A., Cruz-Rivera, Z., Rodriguez-Pacheco, J., Cruz, N.L., Hernandez-Chena, B.E., Guido-Ramirez, O., Arteaga-Troncoso, G., Guerra-Infante, F.M., Lopez-Hurtado, M., Caleco, J.A. Denicia, Leyva-Medellin, E.E., Salamanca-Meneses, A., Cosio-Moran, C., Ruiz-Rendon, R., Aguilar-Angel, L.A., Sanchez-Vargas, M., Mares-Morales, R.C., Fernandez-Alvarez, L.C., Castillo-Cruz, B.V., Gonzalez-Ma, M.R., Zavala-Ramír, M.C., Rivera-Reyna, L., del-Moral-Rossete, L.G., Lopez-Rubio, C., Valadez-de-Alba, M., Bat-Erdene, A., Chuluunchimeg, K.H., Baatar, O., Batkhuu, B., Ariyasuren, Z., Bayasgalan, G., Baigalmaa, S., Uyanga, T.S., Suvderdene, P., Enkhtsetseg, D., Suvd-Erdene, D., Chimedtseye, E., Bilguun, G., Tuvshinbayar, M., Dorj, M., Khajidmaa, T., Batjargal, G., Naranpurev, M., Bolormaa, T., Battsetseg, T., Batsuren, Ch, Batsaikhan, N., Tsolmon, B., Saranbaatar, A., Natsagnyam, P., Nyamdawa, O., Madani, N., Abouqal, R., Zeggwagh, A.A., Berechid, K., Dendane, T.P., Koirala, A., Giri, R., Sainju, S., Acharya, S.P., Paul, N., Parveen, A., Raza, A., Nizamuddin, S., Sultan, F., Imran, X., Sajjad, R., Khan, M., Sana, F., Tayyab, N., Ahmed, A., Zaman, G., Khan, I., Khurram, F., Hussain, A., Zahra, F.T., Imtiaz, A., Daud, N., Sarwar, M., Roop, Z., Yusuf, S., Hanif, F., Shumaila, X., Zeb, J., Ali, S.R., Demas, S., Ariff, S., Riaz, A., Hussain, A.S., Kanaan, A., Jeetawi, R., Castaño, E.G., Moreno-Castillo, L.L., García-Mayorca, E., Prudencio-Leon, W.E., Vivas-Pardo, A., Changano-Rodriguez, M.V., Castillo-Bravo, L.I., Aibar-Yaranga, K.F., Marquez-Mondalgo, V.A., Mueras-Quevedo, J., Meza-Borja, C., Flor, J.L., Fernandez-Camacho, Y.M., Banda-Flores, C., Pichilingue-Chagray, J., Castaneda-Sabogal, A., Caoili, J.C., Mariano, M.C., Maglente, R.R., Santos, S., de-Guzman, G., Mendoza, M.T., Javellana, O.P., Tajanlangit, A.N.L., Tapang, A.R.D., Sg-Buenaflor, M.C., Labro, E., Carma, R., Dy, A.M.P., Fortin, J.D., Navoa-Ng, J.A., Cesar, J.L., Bonifacio, B.S., Llames, M.J.P., Gata, H.L.B., Tamayo, A.S., Calupit, H.K.E., Catcho, V.V., Bergosa, L.D., Abuy, M.T.B., Barteczko-Grajek, B., Rojek, S., Szczesny, A., Domanska, M., Lipinska, G., Jaroslaw, J., Wieczoreka, A., Szczykutowicza, A., Gawor, M., Piwoda, M., Rydz-Lutrzykowska, J., Grudzinska, M., Kolat-Brodecka, P., Smiechowicz, K., Tamowicz, B., Mikstacki, A., Grams, A., Sobczynski, P., Nowicka, M., Kretov, V., Shalapuda, V., Molkov, A., Puzanov, S., Utkin, I., Tchekulaev, A., Tulupova, V., Vasiljevic, S., Nikolic, L., Ristic, G., Eremija, J., Kojovic, J., Lekic, D., Simic, A., Hlinkova, S., Lesnakova, A., Kadankunnel, S.K., Abdo-Ali, M.M., Pimathai, R., Wanitanukool, S., Supa, N., Prasan, P., Luxsuwong, M., Khuenkaew, Y., Lamngamsupha, J., Siriyakorn, N., Prasanthai, V., Apisarnthanarak, A., Borgi, A., Bouziri, A., Cabadak, H., Tuncer, G.E., Bulut, C., Hatipoglu, C.A., Sebnem, F.E., Demiroz, A.P., Kaya, A., Ersoz, G., Kuyucu, N., Karacorlu, S., Oncul, O., Gorenek, L., Erdem, H., Yildizdas, D., Horoz, O.O., Guclu, E., Kaya, G., Karabay, O., Altindis, M., Oztoprak, N., Sahip, Y., Uzun, C., Erben, N., Usluer, G., Ozgunes, I., Ozcelik, M., Ceyda, B.M., Oral, M., Unal, N., Cigdem, Y.G., Bayar, M.K., Bermede, O., Saygili, S., Yesiler, I., Memikoglu, O., Tekin, R., Oncul, A., Gunduz, A., Ozdemir, D., Geyik, M.F., Erdogan, S.Y., Aygun, C., Dilek, A., Esen, S., Turgut, H., Sungurtekin, H., Ugurcan, D., Yarar, V., Bilir, Y., Bayram, N., Devrim, I., Agin, H., Ceylan, G., Yasar, N., Oruc, Y., Ramazanoglu, A., Turhan, O., Cengiz, M., Yalcin, A.N., Dursun, O., Gunasan, P., Kaya, S., Senol, G., Kocagoz, A.S., Al-Rahma, H., Annamma, P., El-Houfi, A., Vidal, H., Perez, F., D-Empaire, G., Ruiz, Y., Hernandez, D., Aponte, D., Salinas, E., Vidal, H.R., Navarrete, N., Vargas, R., Sanchez, E., Ngo Quy, C., Thu, T.A., Nguyet, L.T.T., Hang, P.T., Hang, T.T.T., Hanh, T.T.M., Anh, D.P.P., Rosenthal, Víctor Daniel, Bat-Erdene, Ider, Gupta, Debkishore, Belkebir, Souad, Rajhans, Prasad, Zand, Farid, Myatra, Sheila Nainan, Afeef, Majeda, Tanzi, Vito L, Muralidharan, S., Gurskis, Vaidotas, Al-Abdely, Hail M., El-Kholy, Amani, AlKhawaja, Safa A. Aziz, Sen, Suha, Mehta, Yatin, Rai, Vineya, Hung, Nguyen Viet, Sayed, Amani F., Guerrero-Toapanta, Fausto Marcos, Elahi, Naheed, Morfin-Otero, María del Rayo, Somabutr, Suwara, De-Carvalho, Braulio Matias, Magdarao, Mary Shine, Velinova, Velmira Angelova, Quesada-Mora, Ana Marcela, Anguseva, Tanja, Ikram, Aamer, Aguilar-de-Moros, Daisy, Duszynska, Wieslawa, Mejia, Nepomuceno, Horhat, Florin George, Belskiy, Vladislav, Mioljevic, Vesna, Di-Silvestre, Gabriela, Furova, Katarina, Gamar-Elanbya, May Osman, Gupta, Umesh, Abidi, Khalid, Raka, Lul, Guo, Xiuqin, Luque-Torres, Marco Tulio, Jayatilleke, Kushlani, Ben-Jaballah, Najla, Gikas, Achilleas, Sandoval-Castillo, Harrison Ronald, Trotter, Andrew, Valderrama-Beltrán, Sandra L., and Leblebicioglu, Hakan

Published
2020
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9. Shiraz Trauma Transfusion Score: A Scoring System for Blood Transfusion in Trauma Patients

Author

Paydar, S., Sabetian, G., Khalili, H. A., Abbasi, H. R., Bolandparvaz, S., Zahra Ghahramani, Dalfardi, B., Spahn, D. R., University of Zurich, and Ghahramani, Zahra

Subjects
Editorial, 10216 Institute of Anesthesiology, Transfusion, Shiraz Trauma Transfusion Score, lcsh:Medical emergencies. Critical care. Intensive care. First aid, 610 Medicine & health, lcsh:RC86-88.9, Guideline, 2711 Emergency Medicine, Trauma
Published
2016

10. Synthesis and Electrochemical Studies of Novel Cobalt Free (Nd0.9La0.1)1.6Sr0.4 Ni0.75Cu0.25O3.8 (NLSNC4) Cathode Material for IT‐SOFCs.

Author

Shirani‐Faradonbeh, H., Paydar, M. H., Paydar, S., Gholaminezhad, I., and Bazargan‐Lari, R.

Subjects
CATHODES, ELECTRIC conductivity, COMPOSITE materials, COBALT, IMPEDANCE spectroscopy, ELECTROCHEMICAL electrodes
Abstract

A novel cathode material of (Nd0.9La0.1)1.6Sr0.4Ni0.75Cu0.25O3.8 (NLSNC4), is synthesized by solid state reaction and is further investigated in combination with samarium doped ceria (SDC) as composite cathodes including 0, 10, 30, 50, and 70 of SDC electrolyte phase. The X‐ray diffraction analysis showed that NLSNC4 was produced in pure phase and was chemically compatible with SDC electrolyte. Electrical conductivities of single phase and composite cathode materials along with their electrochemical performances on SDC electrolytes in symmetric cells were measured by DC four‐probe method and electrochemical impedance spectroscopy (EIS), respectively. Results indicated that the maximum electrical conductivity is 135.56 S cm−1 at 350 °C, measured for single phase NLSNC4, sintered at 1,300 °C. Polarization resistance of pure NLSNC4 cathode was 2.71 Ω cm2 at 800 °C, and NLSNC4‐x wt.% SDC composite cathodes displayed Rp value of 0.35, 0.14, 0.12, and 0.32 Ω cm2 at 800 °C, for x = 10, 30, 50, and 70, respectively. [ABSTRACT FROM AUTHOR]

Published
2019
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12. Helicopter emergency medical service in fars province: the referral trauma center of South of iran

Author

Moradian, M. J., Rastegarfar, B., Salahi, R., Hamidreza Abbasi, Paydar, S., Rastegar, M. R., Dehghani, M., Mousavi, S., Shirzad, E., Khorrami, M., Esnaashar, M., and Bolandparvaz, S.

Subjects
Helicopter, Short Communication, Iran, Trauma, Ambulance, Air transfer
Abstract

Background Considering the limited available resources, high cost of the helicopter emergency medical service (HEMS), and high load of trauma patients especially in our centers, a careful assessment of HEMS in our center seemed to be necessary for trauma patients. Methods From April 2001 to September 2007, the data of all patients transferred by HEMS were extracted including: Annual number of services, clinical category, number of proper or improper services, and rescue time for HEMS and ground ambulance. The criteria for the properly transferred group included: Death or being operated in the first 24 hours of admission, admission in ICU care units, and transfer of more than three patients in one mission. Others were considered as improper group. Results In this period through 185 flights, 225 victims were transferred. The most common reason of HEMS dispatching was trauma. The most difference of rescue time between ground ambulance and HEMS was recorded in Lamerd that was transferring patients with HEMS needed 3 hours less than ground ambulance. However, in Sarvestan, Dashte-Arjan, and Marvdasht, transferred patients with ground ambulance needed less time than air transfer. Most of transferred patients were from Kazeroon, Nourabad and Lamerd respectively while 46.3% of patients were in the proper group, and the rest were considered as improper group. Conclusion Our study revealed that helicopter dispatch to the cities like Lamerd, Lar, Khonj, Abadeh can be more effective, whereas, for the towns like Marvdasht, Dashte-Arjan, Sarvestan, Sepidan, Saadatshar, Tang Abolhayat use of HEMS should be limited to specific conditions. Our study showed inclusion of physicians in the decision making team increased the number of transferred cases.

Published
2011

16. Influence of A-Site Modifications on the Properties of La0.21Sr0.74−xCaxTi0.95Fe0.05O3−δBased Fuel Electrode for Solid Oxide Cell

Author

Paydar, S., Kooser, K., Möller, P., Volobujeva, O., Granroth, S., Lust, E., and Nurk, G.

Abstract

To make solid oxide fuel cell (SOFC) systems commercially attractive it’s essential to reduce manufacturing cost and improve the stability of membrane electrode assembly (MEA). In this research, the influence of A-site modification on electrical and electrochemical performance of 5% A-site deficient La0.21Sr0.74−xCaxTi0.95Fe0.05O3−δ(x = 0.26 − 0.69) (LSCTF5-x) hydrogen electrode has been studied. Results indicate that the magnitude of A-site deficiency and Ca concentration in A-site influence the conductivity, catalytic activity and stability of the electrodes considerably. The highest stability was observed in the case of La0.21Sr0.26Ca0.48Ti0.95Fe0.05O3−δanode composition. The maximal total electrical conductivity of porous electrode layer made of LSCFT5-x was 3.5 S cm−1at 850 °C characteristic of the La0.211Sr0.26Ca0.48Ti0.95Fe0.05O3−δmaterial in 97% H2+ 3% H2O atmosphere. The best electrochemical performance was observed in the case of La0.21Sr0.37Ca0.37Ti0.95Fe0.05O3−δ, which showed polarization resistance value equal to 0.44 Ω cm2after 100 h of stabilization at 800 °C in humidified (1.7% H2O) H2atmosphere. During the stability test the fuel cell with optimal anode composition 50 wt% La0.21Sr0.26Ca0.48Ti0.95Fe0.05O3−δ+ 50 wt% Ce0.9Gd0.1O2-δshowed power density of 437 mW cm−2at 850 °C in 98.3% H2+ 1.7% H2O atmosphere.

Published
2023
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18. Ventral neural patterning by Nkx homeobox genes: Nkx6.1 controls somatic motor neuron and ventral interneuron fates.

Author

Sander, M, Paydar, S, Ericson, J, Briscoe, J, Berber, E, German, M, Jessell, T M, and Rubenstein, J L

Abstract

There is growing evidence that sonic hedgehog (Shh) signaling regulates ventral neuronal fate in the vertebrate central nervous system through Nkx-class homeodomain proteins. We have examined the patterns of neurogenesis in mice carrying a targeted mutation in Nkx6.1. These mutants show a dorsal-to-ventral switch in the identity of progenitors and in the fate of postmitotic neurons. At many axial levels there is a complete block in the generation of V2 interneurons and motor neurons and a compensatory ventral expansion in the domain of generation of V1 neurons, demonstrating the essential functions of Nkx6.1 in regional patterning and neuronal fate determination.

Published
2000

20. The evolution of a malignancy risk prediction model for thyroid nodules using the artificial neural network

Author

Paydar, S., Pourahmad, S., Azad, M., Bolandparvaz, S., Taheri, R., Zahra Ghahramani, Zamani, A., Jeddi, M., Karimi, F., Dabbaghmanesh, M. H., Shams, M., and Abbasi, H. R.

Subjects
Artificial neural network, Thyroid nodules, Malignancy, Artificial neural network Received: April 25, lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens, lcsh:RC254-282, Risk prediction model, Accepted: August 12
Abstract

Background: Clinically frank thyroid nodules are common and believed to be present in 4% to 10% of the adult population in the United States. In the current literature, fine needle aspiration biopsies are considered to be the milestone of a model which helps the physician decide whether a certain thyroid nodule needs a surgical approach or not. A considerable fact is that sensitivity and specificity of the fine needle aspiration varies significantly as it remains highly dependent on the operator as well as the cytologist’s skills. Practically, in the above group of patients, thyroid lobectomy/isthmusectomy becomes mandatory for attaining a definitive diagnosis where the majority (70%-80%) have a benign surgical pathology. The scattered nature of clinically gathered data and analysis of their relevant variables need a compliant statistical method. The artificial neural network is a branch of artificial intelligence. We have hypothesized that conduction of an artificial neural network applied to certain clinical attributes could develop a malignancy risk assessment tool to help physicians interpret the fine needle aspiration biopsy results of thyroid nodules in a context composed of patient’s clinical variables, known as malignancy related risk factors. Methods: We designed and trained an artificial neural network on a prospectively formed cohort gathered over a four year period (2007-2011). The study population comprised 345 subjects who underwent thyroid resection at Nemazee and Rajaee hospitals, tertiary care centers of Shiraz University of Medical Sciences, and Rajaee Hospital as a level I trauma center in Shiraz, Iran after having undergone thyroid fine needle aspiration. Histopathological results of the fine needle aspirations and surgical specimens were analyzed and compared by experienced, board-certified pathologists who lacked knowledge of the fine needle aspiration results for thyroid malignancy. Results: We compared the preoperative fine needle aspiration and surgical histopathology results. The results matched in 63.5% of subjects. On the other hand, fine needle aspiration biopsy results falsely predicted malignant thyroid nodules in 16% of cases (false-negative). In 20.5% of subjects, fine needle aspiration was falsely positive for thyroid malignancy. The Resilient back Propagation (RP) training algorithm lead to acceptable accuracy in prediction for the designed artificial neural network (64.66%) by the cross- validation method. Under the cross-validation method, a back propagation algorithm that used the resilient back propagation protocol - the accuracy in prediction for the trained artificial neural network was 64.66%. Conclusion: An extensive bio-statistically validated artificial neural network of certain clinical, paraclinical and individual given inputs (predictors) has the capability to stratify the malignancy risk of a thyroid nodule in order to individualize patient care. This risk assessment model (tool) can virtually minimize unnecessary diagnostic thyroid surgeries as well as FNA misleading.

26. Objective structured clinical examination (OSCE)-based assessment of the Advanced trauma life support (ATLS) course in Iran

Author

Abbasi, H. R., Mitra Amini, Bolandparvaz, S., Paydar, S., Ali, J., and Sefidbakht, S.

Subjects
Surgeons, Advanced Trauma Life Support (ATLS®), Objective Structured Clinical Examination (OSCE), lcsh:Medical emergencies. Critical care. Intensive care. First aid, Original Article, lcsh:RC86-88.9, Course, Iran, Trauma
Abstract

Objective: To evaluate the effect of advance trauma life support (ATLS®) training on general surgery residents clinical reasoning skills using the national boards-style objective structured clinical examination (OSCE). Methods: This cross-sectional single-center study was conducted in Shiraz University of Medical Sciences including 51 surgery residents that participated in a mandatory national board style OSCE between May 2014 and May 2015. OSCE scores of two groups of general surgery residents including 23 ATLS® trained and 28 non-ATLS® trained were compared using Mann-Whitney U test. The exam was graded out of 20 points and the passing score was ≥14 including 40% trauma cases. Results: There were 8(15.7%) women and 43(84.3%) men among the participants with mean age of 31.12 ± 2.69 and 33.67 ± 4.39 years in women and men respectively. Overall 7 (87.5%) women and 34 (79.07%) men passed the OSCE. The trauma section OSCE score was significantly higher in the ATLS® trained participants when compared to non-ATLS®(7.79 ± 0.81vs.6.90 ± 1.00; p=0.001). In addition, the total score was also significantly higher in ATLS® trained residents (16.07 ± 1.41 vs. 14.60 ± 1.40; p=0.001). There was no association between gender and ATLS® score (p=0.245) or passing the OSCE (p=0.503). Conclusion: ATLS® training is associated with improved overall OSCE scores of general surgery residents completing the board examinations suggesting a positive transfer of ATLS learned skills to management of simulated surgical patients including trauma cases.

30. A case of gastric zygomycosis in a diabetic patient successfully treated with total gastrectomy

Author

Paydar S, Baezzat S, Fazelzadeh A, and Bita Geramizadeh

Subjects
Zygomycosis, Gastrectomy, Diabetes, Case Report
Abstract

Zygomycosis is regarded as a rare fetal infection in diabetics and other immunocompromised patients. The usual manifestations of this infection are: rhinosinusitis, pansinusitis, rhino-orbital and rhinocerebral. Primary gastrointestinal (GI) zygomycosis is a rare disease with a high mortality rate. The stomach is the most common site involved in GI mucormycosis. There are few reported cases of GI zygomycosis in the literature. Here we report a case of a diabetic woman with abdominal pain secondary to gastric zygomycosis that successfully responded to surgical treatment.

35. Left-sided Amyand hernia

Author

Johari Hamed, Paydar Shahram, Davani Sam, Eskandari Shima, and Johari Masumeh

Subjects
Medicine
Published
2009

37. Conjunctival mass as an initial presentation of mantle cell lymphoma: a case report

Author

Khanlari Mahsa, Bagheri Babak, Vojdani Reza, Mohammadianpanah Mohammad, Paydar Shahram, and Daneshbod Yahya

Subjects
Lymphoma, Orbit, Conjunctiva, Mantle cell lymphoma, t(11, 14), SOX 11, Medicine, Biology (General), QH301-705.5, Science (General), Q1-390
Abstract

Abstract Background To describe a rare manifestation of mantle cell lymphoma (MCL) in conjunctiva, with clinical, hisologic, immunohistologic and genetic findings together with review of the Literature. Case presentation Most ocular adnexal lymphomas are extranodal marginal zone B-cell lymphomas of mucosa-associated lymphoid tissue (MALT). A few cases of ocular adnexal mantle cell lymphomas have been reported in the literature. We present a case of mantle cell lymphoma presenting as right conjunctival mass of at least three months duration in a 64-year-old man. Histopathologic examination showed a proliferation of monomorphous small-to-medium-sized lymphoid cells with cleaved nuclei in the subconjunctiva. By immunohistochemistry, the infiltrate was positive for CD20, CD5, BCL-2, cyclin D1, and the transcription factor SOX11. Fluorescent in situ hybridization demonstrated the presence of IGH-CCND1 fusion indicating t(11;14). Conclusion A rigorous approach to initial diagnosis and staging of small cell lymphomas of the ocular adnexa is needed. The recognition of ocular MCL requires appropriate immunohistochemical staining and/or genetic confirmation to differentiate this rare form of presentation of MCL from other more frequent small cell lymphomas.

Published
2012
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45. Development and validation of the Iranian Minimum Data Set for Epidermolysis Bullosa: A mixed method approach.

Author

Paydar S, Pahlevanynejad S, Asadi F, Ehtesham H, and Sabahi A

Subjects
Humans, Cross-Sectional Studies, Databases, Factual, Datasets as Topic, Focus Groups, Iran epidemiology, Delphi Technique, Epidermolysis Bullosa epidemiology
Abstract

Minimum Data Set (MDS) enables integration in data collection, uniform data reporting, and data exchange across clinical and research information systems. The current study was conducted to determine a comprehensive national MDS for the Epidermolysis Bullosa (EB) information management system in Iran. This cross-sectional descriptive study consists of three steps: systematic review, focus group discussion, and the Delphi technique. A systematic review was conducted using relevant databases. Then, a focus group discussion was held to determine the extracted data elements with the help of contributing multidisciplinary experts. Finally, MDSs were selected through the Delphi technique in two rounds. The collected data were analyzed using Microsoft Excel 2019. In total, 103 data elements were included in the Delphi survey. The data elements, based on the experts' opinions, were classified into two main categories: administrative data and clinical data. The final categories of data elements consisted of 11 administrative items and 92 clinical items. The national MDS, as the core of the EB surveillance program, is essential for enabling appropriate and informed decisions by healthcare policymakers, physicians, and healthcare providers. In this study, a MDS was developed and internally validated for EB. This research generated new knowledge to enable healthcare professionals to collect relevant and meaningful data for use. The use of this standardized approach can help benchmark clinical practice and target improvements worldwide., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Paydar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Published
2025
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46. Bridging silicon and carbon worlds with digital twins and on-chip systems in drug discovery.

Author

Akbarialiabad H, Seyyedi MS, Paydar S, Habibzadeh A, Haghighi A, and Kvedar JC

Subjects
Humans, Carbon chemistry, Silicon chemistry, Drug Discovery instrumentation, Drug Discovery methods, Lab-On-A-Chip Devices, Precision Medicine instrumentation, Precision Medicine methods
Abstract

This perspective discusses the convergence of digital twin (DT) technology and on-the-chip systems as pivotal innovations in precision medicine, substantially advancing drug discovery. DT leverages extensive health data to create dynamic virtual patient models, enabling predictive insights and optimized treatment strategies. Concurrently, on-the-chip systems from the Carbon world replicate human biological processes on microfluidic platforms, providing detailed insights into disease mechanisms and pharmacological interactions. The convergence of these technologies promises to revolutionize drug development by enhancing therapeutic precision, accelerating discovery timelines, and reducing costs. Specifically, it assesses their role in drug development, from refining therapeutic precision to expediting discovery timelines and reducing the final price. Nevertheless, integrating these technologies faces challenges, including data collection and privacy concerns, technical intricacies, and clinical adoption barriers. This manuscript argues for interdisciplinary cooperation to navigate these challenges, positing DTs and on-the-chip technologies as foundational elements in personalized healthcare and drug discovery., Competing Interests: Competing interests: The authors declare no competing interests. Ethics Approval: As the nature of this study did not involve any human or animal subjects, interventions, or data collection, ethics committee approval was not required., (© 2024. The Author(s).)

Published
2024
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48. Comparison of gauze packing, sponge-based, and hemostatic surgicel wound stasis dressings to treat hemorrhages from grade IV liver injuries: An experimental study.

Author

Lashkarizadeh MM, Ghaedi A, Abolghasemi H, Rabiee M, Mehrabani D, Ahadian S, Bazrgar A, Moqbel Esfahani S, and Paydar S

Abstract

Background: Uncontrolled bleeding is still the major factor leading to preventable deaths following trauma. This study sought to assess the effectiveness of mini sponge-based wound stasis, cellulose-based local hemostatic, and traditional gauze dressings for the control of hemorrhages resulting from grade 4 liver injuries in rats., Methods: Thirty Sprague-Dawley rats were divided into three equal groups. In the first group, a liver laceration was treated with gauze packing. The second group received XStat minisponge dressing (MDS), and the third group was administered a combination of MDS dressing and Surgicel hemostatic agent. After gaining access to the intra-abdominal cavity, a liver laceration measuring 10 mm in length, 5 mm in depth, and extending to the middle lobe was created. The dressings were removed after 2 and 10 min to assess the amount of bleeding, and any bleeding was documented again after 48 h. Intraperitoneal adhesions were evaluated during euthanasia., Results: At 2 min post-injury, the gauze packing group had an average bleeding volume of 0.97 ± 0.15 mL, compared to 1.08 ± 0.25 mL in the MDS group (P = 0.26) and 1.02 ± 0.18 mL in the MDS + Surgicel group (P = 0.69). At 10 min, the bleeding volumes were 0.13 ± 0.05 mL, 0.22 ± 0.01 mL (P = 0.09), and 0.14 ± 0.05 mL (P = 0.19), respectively. At 48 h, significant differences were observed in bleeding volumes (gauze: 0.55 ± 0.18 mL, MDS: 1.15 ± 0.21 mL, MDS + Surgicel: 0.82 ± 0.06 mL, P < 0.001). Mortality rates after 14 days were 0 % in the gauze packing group, 60 % in the MDS group (P = 0.001), and 60 % in the MDS + Surgicel group (P = 0.001). The gauze packing group displayed no adhesions, while the other groups exhibited adhesions in the liver, bowel, omentum, and abdominal wall., Conclusion: Our results indicate that, when it comes to managing bleeding in severe liver injuries, traditional gauze packing remains the tried-and-true method, showing superior effectiveness in terms of blood loss and mortality when compared to XStat minisponge dressings and the fibrillar Surgicel hemostatic agents., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Shahram Paydar reports financial support was provided by 10.13039/501100004320Shiraz University of Medical Sciences. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Published
2024
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50. Comparing NEWS2, TRISS, and RTS in predicting mortality rate in trauma patients based on prehospital data set: a diagnostic study.

Author

Yousefi MR, Karajizadeh M, Ghasemian M, and Paydar S

Subjects
Humans, Male, Female, Cross-Sectional Studies, Retrospective Studies, Middle Aged, Adult, Iran epidemiology, Early Warning Score, Aged, Injury Severity Score, Trauma Severity Indices, Emergency Medical Services, Prognosis, Hospital Mortality, Wounds and Injuries mortality, Wounds and Injuries diagnosis
Abstract

Background: In the recent years, National Early Warning Score2 (NEWS2) is utilized to predict early on, the worsening of clinical status in patients. To this date the predictive accuracy of National Early Warning Score (NEWS2), Revised Trauma Score (RTS), and Trauma and injury severity score (TRISS) regarding the trauma patients' mortality rate have not been compared. Therefore, the objective of this study is comparing NEWS2, TRISS, and RTS in predicting mortality rate in trauma patients based on prehospital data set., Methods: This cross-sectional retrospective diagnostic study performed on 6905 trauma patients, of which 4191 were found eligible, referred to the largest trauma center in southern Iran, Shiraz, during 2022-2023 based on their prehospital data set in order to compare the prognostic power of NEWS2, RTS, and TRISS in predicting in-hospital mortality rate. Patients are divided into deceased and survived groups. Demographic data, vital signs, and GCS were obtained from the patients and scoring systems were calculated and compared between the two groups. TRISS and ISS are calculated with in-hospital data set; others are based on prehospital data set., Results: A total of 129 patients have deceased. Age, cause of injury, length of hospital stay, SBP, RR, HR, temperature, SpO2, and GCS were associated with mortality (p-value < 0.001). TRISS and RTS had the highest sensitivity and specificity respectively (77.52, CI 95% [69.3-84.4] and 93.99, CI 95% [93.2-94.7]). TRISS had the highest area under the ROC curve (0.934) followed by NEWS2 (0.879), GCS (0.815), RTS (0.812), and ISS (0.774). TRISS and NEWS were superior to RTS, GCS, and ISS (p-value < 0.0001)., Conclusion: This novel study compares the accuracy of NEWS2, TRISS, and RTS scoring systems in predicting mortality rate based on prehospital data. The findings suggest that all the scoring systems can predict mortality, with TRISS being the most accurate of them, followed by NEWS2. Considering the time consumption and ease of use, NEWS2 seems to be accurate and quick in predicting mortality based on prehospital data set., (© 2024. The Author(s).)

Published
2024
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