ORIGINAL_ARTICLE
Ultrasound Guided Infraclavicular Block for Pain Control After Upper Extremity Surgery
Background: Opioids added to local anesthetics for peripheral nerve blocks may intensify analgesia and prolong analgesic and sensorial block duration. These agents may also cause potentiation and prolongation of motor block. Objective: This study compared the postoperative effects of 30 mL of 0.25% bupivacaine +50 mcg fentanyl and 30 mL of 0.25% bupivacaine + 100 mcg fentanyl solutions for the ultrasound-guided infraclavicular block in patients undergoing elbow and forearm surgery. Methods: In this randomized double-blind study, thirty-six patients with risk of ASA class I-III were randomly allocated into 2 randomized groups. Ultrasound-guided infraclavicular blocks with 30 mL of 0.25% bupivacaine + 50 mcg fentanyl for group 1 and 30 mL of 0.25% bupivacaine + 100 mcg fentanyl for group 2 were performed before patients emerged from general anesthesia. After surgery, pain levels at rest and during movement were evaluated using the 10-cm visual analog scale (VAS) at recovery room admission, at the 15th and 30th minutes in the recovery room, and at the 2nd, 6th, 12th and 24th hours postoperatively. Both morphine and rescue analgesic requirements were recorded. Sensorial and motor block durations, patient satisfaction, and complications related to the infraclavicular block were recorded. Results: In both groups, no significant difference in VAS pain scores, total morphine and total rescue analgesic requirements, duration of sensorial and motor block, or patient satisfaction were observed. None of the patients experienced any complications. Conclusion: The mixtures of 0.25% bupivacaine + 50 mcg fentanyl and 0.25% bupivacaine + 100 mcg fentanyl showed similar postoperative effects.
https://www.jhpr.ir/article_67492_5fae38554ec74fabdada3b9dcc2e8604.pdf
2018-10-01
108
112
10.15171/hpr.2018.24
analgesia
Brachial Plexus Block
Bupivacaine
Fentanyl
Ultrasonography
Derya
Yalçın
dr.deryayalcin@outlook.com
1
Department of Anesthesiology and Reanimation, Ersin Arslan Educational and Research Hospital, Gaziantep, Turkey
AUTHOR
Dilek
Erdoğan Arı
dilekerdoganari@gmail.com
2
Department of Anesthesiology and Reanimation, Fatih Sultan Mehmet Educational and Research Hospital, Istanbul, Turkey
LEAD_AUTHOR
Ceren
Köksal
cerenhazer@gmail.com
3
Department of Anesthesiology and Reanimation, Fatih Sultan Mehmet Educational and Research Hospital, Istanbul, Turkey
AUTHOR
Cansu
Akın
cansuakin.iu@gmail.com
4
Department of Anesthesiology and Reanimation, Fatih Sultan Mehmet Educational and Research Hospital, Istanbul, Turkey
AUTHOR
Sinan
Karaca
mdsnn@hotmail.com
5
Department of Orthopedics and Traumatology, Fatih Sultan Mehmet Educational and Research Hospital, Istanbul, Turkey
AUTHOR
Özgür
Karakuş
ozgunkarakus@hotmail.com
6
Department of Orthopedics and Traumatology, Fatih Sultan Mehmet Educational and Research Hospital, Istanbul, Turkey
AUTHOR
Nadeau MJ, Levesque S, Dion N. Ultrasound-guided regional anesthesia for upper limb surgery. Can J Anaesth. 2013;60(3):304- 320. doi:10.1007/s12630-012-9874-6.
1
Senapathi TGA, Widnyana IMG, Aribawa I, et al. Ultrasoundguided bilateral superficial cervical plexus block is more effective than landmark technique for reducing pain from thyroidectomy. J Pain Res. 2017;10:1619-1622. doi:10.2147/JPR.S138222.
2
Karakaya D, Buyukgoz F, Baris S, Guldogus F, Tur A. Addition of fentanyl to bupivacaine prolongs anesthesia and analgesia in axillary brachial plexus block. Reg Anesth Pain Med. 2001;26(5):434-438. doi:10.1053/rapm.2001.24675.
3
Farooq N, Singh RB, Sarkar A, Rasheed MA, Choubey S. To Evaluate the Efficacy of Fentanyl and Dexmedetomidine as Adjuvant to Ropivacaine in Brachial Plexus Block: A Doubleblind, Prospective, Randomized Study. Anesth Essays Res. 2017;11(3):730-739. doi:10.4103/aer.AER_30_17.
4
Nishikawa K, Kanaya N, Nakayama M, Igarashi M, Tsunoda K, Namiki A. Fentanyl improves analgesia but prolongs the onset of axillary brachial plexus block by peripheral mechanism. Anesth Analg. 2000;91(2):384-387. doi:10.1213/00000539- 200008000-00028.
5
Paluvadi VR, Manne VS. Effect of Addition of Fentanyl to Xylocaine Hydrochloride in Brachial Plexus Block by Supraclavicular Approach. Anesth Essays Res. 2017;11(1):121- 124. doi:10.4103/0259-1162.186609.
6
Vazin M, Jensen K, Kristensen DL, et al. Low-Volume Brachial Plexus Block Providing Surgical Anesthesia for Distal Arm Surgery Comparing Supraclavicular, Infraclavicular, and Axillary Approach: A Randomized Observer Blind Trial. Biomed Res Int. 2016;2016:7094121. doi:10.1155/2016/7094121.
7
Bhardwaj S, Devgan S, Sood D, Katyal S. Comparison of Local Wound Infiltration with Ropivacaine Alone or Ropivacaine Plus Dexmedetomidine for Postoperative Pain Relief after Lower Segment Cesarean Section. Anesth Essays Res. 2017;11(4):940- 945. doi:10.4103/aer.AER_14_17.
8
Hadzic A, Arliss J, Kerimoglu B, et al. A comparison of infraclavicular nerve block versus general anesthesia for hand and wrist day-case surgeries. Anesthesiology. 2004;101(1):127- 132. doi:10.1097/00000542-200407000-00020.
9
Luyet C, Schupfer G, Wipfli M, Greif R, Luginbuhl M, Eichenberger U. Different Learning Curves for Axillary Brachial Plexus Block: Ultrasound Guidance versus Nerve Stimulation. Anesthesiol Res Pract. 2010;2010:309462. doi:10.1155/2010/309462.
10
Dingemans E, Williams SR, Arcand G, et al. Neurostimulation in ultrasound-guided infraclavicular block: a prospective randomized trial. Anesth Analg. 2007;104(5):1275-1280, tables of contents. doi:10.1213/01.ane.0000226101.63736.20.
11
Brull R, Lupu M, Perlas A, Chan VW, McCartney CJ. Compared with dual nerve stimulation, ultrasound guidance shortens the time for infraclavicular block performance. Can J Anaesth.2009;56(11):812-818. doi:10.1007/s12630-009-9170-2.
12
Feierman DE, Klinkowitz E, Keilin C, et al. Chart Review of PACU Outcomes for Patients Who Had Ambulatory Shoulder Surgery with Peripheral Nerve Block (PNB) and General Anesthesia Compared to General Anesthesia (GA). Open J Anesthesiol. 2015;5(7):173-176. doi:10.4236/ojanes.2015.57031.
13
Swain A, Nag DS, Sahu S, Samaddar DP. Adjuvants to local anesthetics: Current understanding and future trends. World J Clin Cases. 2017;5(8):307-323. doi:10.12998/wjcc.v5.i8.307.
14
Chin KJ, Alakkad H, Adhikary SD, Singh M. Infraclavicular brachial plexus block for regional anaesthesia of the lower arm. Cochrane Database Syst Rev. 2013(8):Cd005487. doi:10.1002/14651858.CD005487.pub3.
15
Kilka HG, Geiger P, Mehrkens HH. [Infraclavicular vertical brachial plexus blockade. A new method for anesthesia of the upper extremity. An anatomical and clinical study]. Anaesthesist. 1995;44(5):339-344. doi:10.1007/s001010050162.
16
Lanz E, Theiss D, Jankovic D. The extent of blockade following various techniques of brachial plexus block. Anesth Analg. 1983;62(1):55-58. doi:10.1213/00000539-198301000-00009.
17
Murphy DB, McCartney CJ, Chan VW. Novel analgesic adjuncts for brachial plexus block: a systematic review. Anesth Analg. 2000;90(5):1122-1128. doi:10.1097/00000539-200005000-00023.
18
Vester-Andersen T, Husum B, Lindeburg T, Borrits L, Gothgen I. Perivascular axillary block IV: blockade following 40, 50 or 60 ml of mepivacaine 1% with adrenaline. Acta Anaesthesiol Scand. 1984;28(1):99-105. doi:10.1111/j.1399-6576.1984.tb02020.x.
19
Vester-Andersen T, Christiansen C, Sorensen M, KaalundJorgensen HO, Saugbjerg P, Schultz-Moller K. Perivascular axillary block II: influence of injected volume of local anaesthetic on neural blockade. Acta Anaesthesiol Scand. 1983;27(2):95-98. doi:10.1111/j.1399-6576.1983.tb01913.x.
20
Martin R, Dumais R, Cinq-Mars S, Tetrault JP. [Axillary plexus block by simultaneous blockade of several nerves. I. Influence of the volume of the anesthetic solution]. Ann Fr Anesth Reanim. 1993;12(3):229-232. doi:10.1016/S0750-7658(05)80645-8.
21
Sert H, Muslu B, Usta B, Colak N, Irem Demircioglu R, Gozdemir M. A comparison of articaine and fentanyl-supplemented articaine for hemodialysis fistula creation under ultrasoundguided axillary block. Ren Fail. 2011;33(3):280-284. doi:10.3109/0886022x.2011.560502.
22
Zainab F, Faruq MO, Talukder M, Yeasmeen S, Alam AS, Haque AF. Anaesthetic and analgesic efects of adding fentanyl to bupivacaine-lignocaine mixtures in supraclavicular brachial plexus block a comparative study with or without fentanyl. Bangladesh Med J. 2015;44(1):26-31. doi:10.3329/bmj.v44i1.26348.
23
ORIGINAL_ARTICLE
CONUT: A Useful Alarm of Malnutrition in the Centralized Laboratory of a Spanish Hospital
Background: Hospital malnutrition, usually secondary to various diseases and their treatments, is an important problem in our clinical practice. For its proper assessment, it is crucial to use a nutritional alert system, such as the CONUT (COntrol NUTrition) program; this tool uses 3 analytical parameters: serum albumin, total cholesterol, and total lymphocyte count. Objective: The current study assessed the results of the implementation of this program in the University Hospital Ramón y Cajal. Methods: The CONUT program has been used in the University Hospital Ramón y Cajal since 2013. This retrospective study, throughout 2016, was conducted in the Central Laboratory of Chemical Biochemistry at the University Hospital Ramón y Cajal. All blood tests with serum albumin, total cholesterol, and total lymphocyte count were studied. The degree of malnutrition was assessed using the scale of normal (=0), mild (=4), moderate (=8), and severe (=12). Results: In 2016, there were 405406 analytics performed in the laboratory of University Hospital Ramón y Cajal. The CONUT tool was applied to 3.64% of them (14741 analytics). In the outpatient setting, the highest malnutrition index comprised patients from the liver transplant consultation department, followed by the cardiology, rheumatology, and oncology departments. With inpatients, the hematology, cardiology, and endocrinology departments showed the most severe malnutrition index. Conclusion: The CONUT system seemed to provide useful information about the cohort of the studied hospital. The results showed that 94% of the patients were not classified with malnutrition, there was no gender predilection, and they were younger than the rest. Patients with more severe malnutrition were usually older and male.
https://www.jhpr.ir/article_68174_ca441563bda457f645dd8b409db34e47.pdf
2018-10-01
113
117
10.15171/hpr.2018.25
Malnutrition
Early Diagnosis
Laboratories
Nutritional Status
Miriam
Menacho-Román
m.menachoroman@gmail.com
1
Clinical Biochemistry Department. University Hospital “Ramón y Cajal”, Madrid, Spain
AUTHOR
Gilberto
Pérez-López
beto_med@hotmail.com
2
Endocrinology Department. University Hospital “Ramón y Cajal”, Madrid, Spain
AUTHOR
José Manuel
del Rey-Sánchez
josemanuel.delrey@salud.madrid.org
3
Clinical Biochemistry Department. University Hospital “Ramón y Cajal”, Madrid, Spain
AUTHOR
Domingo
Ly-Pen
domingoly@gmail.com
4
Abbey House Medical Centre, Navan, Ireland
LEAD_AUTHOR
Antonio
Becerra-Fernández
a.becerrafernandez@gmail.com
5
Endocrinology Department. University Hospital “Ramón y Cajal”, Madrid, Spain
AUTHOR
García de Lorenzo A, Álvarez Hernández J, Planas M, et al. Multidisciplinary consensus work-team on the approach to hospital malnutrition in Spain. Nutr Hosp. 2011;26(4):701- 710. doi:10.1590/S0212-16112011000400006.
1
Moriana M, Civera M, Artero A, et al. Validez de la valoración subjetiva global como método de despistaje de desnutrición hospitalaria. Prevalencia de desnutrición en un hospital terciario (Validity of subjective global assessment as a screening method for hospital malnutrition. Prevalence of malnutrition in a tertiary hospital). Endocrinol Nutr. 2014;61:184-189. doi:10.1016/j.endonu.2013.10.006.
2
Ulíbarri Pérez JI, Fernández G, Rodríguez Salvanés F, et al. Proyecto para la Prevención, Detección precoz y Control de la Desnutrición Clínica. (Proyecto CONUT). Actualizado en Octubre 2013. Project for the Prevention, Early detection and Control of Clinical Malnutrition (The CONUT project). https://controlnutricional.files.wordpress.com/2010/12/proyectoconut-octubre-2013.pdf. Accessed May 11, 2018. Updated October 2013.
3
Cereda E, Pedrolli C, ZagamiA, et al. Nutritional risk, functional status and mortality in newly institutionalised elderly. Br J Nutr. 2013;110:1903-1909. doi:10.1017/S0007114513001062.
4
Alcorta MD, Alvarez PC, Cabetas RN, et al. The importance of serum albumin determination method to classify patients based on nutritional status. Clin Nutr ESPEN. 2018;25:110- 113. doi:10.1016/j.clnesp.2018.03.124.
5
Xie Y, Zhang H, Ye T, et al. The geriatric nutritional risk index independently predicts mortality in diabetic foot ulcers patients undergoing amputations. J Diabetes Res. 2017;2017: 5797194. doi:10.1155/2017/5797194.
6
Takahashi S, Suzuki K, Kojima F, et al. Geriatric nutritional risk index as a simple predictor of mortality in maintenance hemodialysis patients: a single center study. Int J Clin Med. 2015;6:354-362. doi:10.4236/ijcm.2015.65046.
7
Sun X, Luo L, Zhao X, et al. Controlling Nutritional Status (CONUT) score as a predictor of all-cause mortality in elderly hypertensive patients: a prospective follow-up study. BMJ Open. 2017;7:e015649. doi:10.1136/bmjopen-2016-015649.
8
Ulíbarri Pérez JI, Fernández G, Rodríguez Salvanés F, et al. Nutritional screening; control of clinical undernutrition with analytical parameters. Nutr Hosp. 2014;29(4):797-811. doi:10.3305/nh.2014.29.4.7275.
9
Molina Soria JB, Lobo Támer G, Pérez de la Cruz AJ, et al. Prevalencia de desnutrición al ingreso en un hospital general básico (Prevalence of malnutrition to income in a basic general hospital). Nutr Hosp 2017;34(6):1390-1398. doi:10.20960/nh.1133.
10
Rentero Redondo L, Iniesta Navalón C, Gascón Cánovas JJ, et al. Desnutrición en el paciente anciano al ingreso hospitalario, un viejo problema sin solucionar (Malnutrition in the elderly patient to hospital admission, an old problem unsolved). Nutr Hosp. 2015;1;32:2169-2177. doi:10.3305/ nh.2015.32.5.9712.
11
Secretaría General del Servicio Madrileño de Salud. Comunidad de Madrid. Hospital Universitario “Ramón y Cajal”. Memoria 2016. Edición electrónica 9/2017. http://www.madrid.org/cs/Satellite?blobcol=urldata&blobheader=application%2Fpdf&blobheadername1=Contentdisposition&blobheadername2=cadena&blobheadervalue1=filename%3DMemoria+2016.pdf&blobheadervalue2=language%3Des%26site%3DHospitalRamonCajal&blobkey=id&blobtable=MungoBlobs&blobwhere=1352944025120&ssbinary=true.
12
Abd Aziz NAS, Teng NIMF, Abdul Hamid MR, et al. Assessing the nutritional status of hospitalized elderly. Clin Interv Aging. 2017:12:1615-1625. doi:10.2147/CIA.S140859.
13
ORIGINAL_ARTICLE
Evaluation of Flow Cytometry and Kleihauer Techniques for Quantification of Fetomaternal Hemorrhage: A Prospective Cohort Study in Southwestern Iran
Background: Quantification of fetal red blood cells (RBCs) in maternal blood is of great importance to calculate appropriate dose of post-deliver anti D immunoglobulin in a rhesus D (RhD)-negative woman. Objective: The aim of this study is to evaluate a direct immunofluorescence flow cytometry technique in artificial and clinical samples and compared it to the Kleihauer-Betke test (KBT). Methods: This study was a prospective cohort design. Blood samples from 26 pregnant women who gave birth to RhD positive babies were tested using direct immunofluorescence flow cytometry and KBT techniques to determine the amount of FMH in the maternal circulation. The zone of D-positive cells was identified employing artificial samples including 0.3%, 0.6%, 1%, 1.5%, 2%, 5%, 10%, and 50% of D-positive fetal cells in D-negative maternal cells. Results: Analysis of 26 clinical samples for FMH showed consistent quantification with the flow cytometry and Kleihauer techniques. Although a good correlation was found between the KBT and flow cytometry results, in artificial samples containing more than 2% of fetal RhD positive cells, the flow cytometry results were closer to theoretical percentages. In a patient with FMH >4 mL, the FMH and consequently the required vial of Ig were overestimated using KBT. Conclusion: Most of the FMH calculated could have been neutralized by doses less than 625 IU, whereas the routine dose in Iran is more than double that amount (1500 IU). This achievement demonstrates that adjusting between the RhD immune globulin (RhDIg) dose and FMH size is inevitable.
https://www.jhpr.ir/article_74129_c865fa028422e59c971312f47dd83228.pdf
2018-10-01
118
122
10.15171/hpr.2018.26
Fetomaternal Transfusion
Rho (D) Immune Globulin
Flow Cytometry
Pregnancy
Fetus
Rh Blood-Group System
Zeinab
Keshavarz
setareh.bidar@yahoo.com
1
Diagnostic Laboratory Sciences and Technology Research Center, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
Leili
Moezzi
2
Diagnostic Laboratory Sciences and Technology Research Center, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
Reza
Ranjbaran
3
Diagnostic Laboratory Sciences and Technology Research Center, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
Abbas
Behzad-Behbahani
4
Diagnostic Laboratory Sciences and Technology Research Center, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
Masooma
Abdullahi
5
Diagnostic Laboratory Sciences and Technology Research Center, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
Mahdokht
Mahmoodi
6
Diagnostic Laboratory Sciences and Technology Research Center, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
Sedigheh
Sharifzadeh
sharifsd@sums.ac.ir
7
Diagnostic Laboratory Sciences and Technology Research Center, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
LEAD_AUTHOR
Dajak S, Stefanovic V, Capkun V. Severe hemolytic disease of fetus and newborn caused by red blood cell antibodies undetected at first-trimester screening (CME). Transfusion. 2011;51(7):1380- 1388. doi:10.1111/j.1537-2995.2010.03006.x.
1
Daniels G. The molecular genetics of blood group polymorphism. Hum Genet. 2009;126(6):729-742. doi:10.1007/s00439-009-0738-2.
2
Avent ND, Reid ME. The Rh blood group system: a review. Blood. 2000;95(2):375-387.
3
Heitman J, Agre P. A new face of the Rhesus antigen. Nat Genet. 2000;26(3):258-259. doi:10.1038/81532.
4
Conroy MJ, Bullough PA, Merrick M, Avent ND. Modelling the human rhesus proteins: implications for structure and function. Br J Haematol. 2005;131(4):543-551. doi:10.1111/j.1365-2141.2005.05786.x.
5
Van Kim CL, Colin Y, Cartron JP. Rh proteins: key structural and functional components of the red cell membrane. Blood Rev. 2006;20(2):93-110. doi:10.1016/j.blre.2005.04.002.
6
Pourfathollah AA, Oody A, Honarkaran N. Geographical distribution of ABO and Rh (D) blood groups among Iranian blood donors in the year 1361(1982) as compared with that of the year 1380 (2001). Sci J Iran Blood Transfus Organ. 2004;1(1):11-17.
7
Pelikan DM, Scherjon SA, Mesker WE, et al. Quantification of fetomaternal hemorrhage: a comparative study of the manual and automated microscopic Kleihauer-Betke tests and flow cytometry in clinical samples. Am J Obstet Gynecol. 2004;191(2):551-557. doi:10.1016/j.ajog.2004.01.007.
8
Ali MS, El Amin AY, Gamal M, Abdulla N, Mohamed A. Foetal maternal haemorrhage detection with the Kleihauer technique for postnatal immunoglobulin dose evaluation in Sudan. NZ J Med Lab Science. 2005;59(1):6-9.
9
Ramsey G. Inaccurate doses of R immune globulin after rh-incompatible fetomaternal hemorrhage: survey of laboratory practice. Arch Pathol Lab Med. 2009;133(3):465-469. doi:10.1043/1543-2165-133.3.465.
10
Regan F, Kumar S, Contreras M. Haemolytic disease of the newborn and its prevention. In: Contreras M, ed. ABC of Transfusion. 4th ed. Chichester, UK: Wiley-Blackwell Pub; 2009:27-32.
11
Crowther C, Middleton P. Anti-D administration after childbirth for preventing Rhesus alloimmunisation. Cochrane Database Syst Rev. 2000(2):Cd000021. doi:10.1002/14651858.CD000021.
12
Payam Khaja Pasha R, Shokri F. Immunologic basis and immunoprophylaxis of RhD induced hemolytic disease of the newborn (HDN). Iran J Immunol. 2008;5(4):189-200.
13
Stedman CM, Baudin JC, White CA, Cooper ES. Use of the erythrocyte rosette test to screen for excessive fetomaternal hemorrhage in Rh-negative women. Am J Obstet Gynecol. 1986;154(6):1363-1369. doi:10.1016/0002-9378(86)90725-8.
14
Sebring ES, Polesky HF. Detection of fetal hemorrhage in Rh immune globulin candidates. A rosetting technique using enzyme-treated Rh2Rh2 indicator erythrocytes. Transfusion. 1982;22(6):468-471. doi:10.1046/j.1537-2995.1982.22683068604.x.
15
Bayliss KM, Kueck BD, Johnson ST, et al. Detecting fetomaternal hemorrhage: a comparison of five methods. Transfusion. 1991;31(4):303-307. doi:10.1046/j.1537-2995.1991.31491213292.x.
16
Hoyer JD, Penz CS, Fairbanks VF, Hanson CA, Katzmann JA. Flow cytometric measurement of hemoglobin F in RBCs: diagnostic usefulness in the distinction of hereditary persistence of fetal hemoglobin (HPFH) and hemoglobin S-hPFH from other conditions with elevated levels of hemoglobin F. Am J Clin Pathol. 2002;117(6):857-863. doi:10.1309/A63X-HG9T-VYG2-X6TX.
17
The estimation of fetomaternal haemorrhage. BCSH Blood Transfusion and Haematology Task Forces. Transfus Med. 1999;9(1):87-92.
18
Wylie BJ, D’Alton ME. Fetomaternal hemorrhage. Obstet Gynecol. 2010;115(5):1039-1051. doi:10.1097/AOG.0b013e3181da7929.
19
Kim YA, Makar RS. Detection of fetomaternal hemorrhage. Am J Hematol. 2012;87(4):417-423. doi:10.1002/ajh.22255.
20
Nath S, Vidyasagar D. Detection of fetomaternal hemorrhage. Indian J Pediatr. 1990;57(5):611-613. doi:10.1007/BF02728698.
21
Kumpel BM. Analysis of factors affecting quantification of fetomaternal hemorrhage by flow cytometry. Transfusion. 2000;40(11):1376-1383. doi:10.1046/j.1537-2995.2000.40111376.x.
22
Porra V, Bernaud J, Gueret P, et al. Identification and quantification of fetal red blood cells in maternal blood by a dual-color flow cytometric method: evaluation of the Fetal Cell Count kit. Transfusion. 2007;47(7):1281-1289. doi:10.1111/j.1537-2995.2007.01271.x.
23
Woodfield G, Davis K, Francis A, et al. Guidelines for laboratory assessment of fetomaternal haemorrhage. Sydney: Australian and New Zealand Society of Blood Transfusion Inc; 2002.
24
Kleihauer E, Braun H, Betke K. [Demonstration of fetal hemoglobin in erythrocytes of a blood smear]. Klin Wochenschr. 1957;35(12):637-638. doi:10.1007/BF01481043.
25
Mollison PL. Quantitation of transplacental haemorrhage. Br Med J. 1972;3(5817):31-34. doi:10.1136/bmj.3.5817.31.
26
Austin E, Bates S, de Silva M, et al. Working Party of the British Committee for Standards in Haematology, Transfusion Taskforce. Guidelines for the Estimation of Fetomaternal Haemorrhage; 2009.
27
Lloyd-Evans P, Kumpel BM, Bromelow I, Austin E, Taylor E. Use of a directly conjugated monoclonal anti-D (BRAD-3) for quantification of fetomaternal hemorrhage by flow cytometry. Transfusion. 1996;36(5):432-437. doi:10.1046/j.1537-2995.1996.36596282587.x.
28
Nelson M, Zarkos K, Popp H, Gibson J. A flow-cytometric equivalent of the Kleihauer test. Vox Sang. 1998;75(3):234- 241. doi:10.1046/j.1423-0410.1998.7530234.x.
29
Davis BH, Olsen S, Bigelow NC, Chen JC. Detection of fetal red cells in fetomaternal hemorrhage using a fetal hemoglobin monoclonal antibody by flow cytometry. Transfusion. 1998;38(8):749-756. doi:10.1046/j.1537-2995.1998.38898375514.x.
30
Davis B, Olsen S, Bigelow N, Chen J. Detection of fetal red cells in fetomaternal hemorrhage using a fetal hemoglobin monoclonal antibody by flow cytometry. Obstet Gynecol Surv. 1999;54(3):153-154. doi:10.1097/00006254-199903000-00004.
31
Kennedy GA, Shaw R, Just S, et al. Quantification of feto-maternal haemorrhage (FMH) by flow cytometry: anti-fetal haemoglobin labelling potentially underestimates massive FMH in comparison to labelling with anti-D. Transfus Med. 2003;13(1):25-33. doi:10.1046/j.1365-3148.2003.00416.x.
32
ORIGINAL_ARTICLE
Voluntary/Involuntary Admissions/Readmissions of Psychiatric Patients in a University Hospital in Turkey From 2008 to 2016
Background: The treatment and hospitalization of psychiatric patients has been a dilemma for many years. Many countries have different specific legislations regarding the hospitalization and treatment of mental patients. Objective: In the current study, 4100 voluntary/involuntary psychiatric admissions and readmissions to a university hospital in Turkey were investigated, and patient groups were compared in terms of demographic variables and psychiatric diagnoses based on DSM IV-TR. Methods: The records of patients who had been hospitalized approximately 4–6 weeks were reviewed by two psychiatrists, and the patients were then divided into groups on the basis of single/multiple admissions and voluntary/involuntary admissions. The groups were compared based on psychiatric diagnoses. Results: Schizophrenia was the most common diagnosis in 71.5% (n = 865) of patients with multiple admissions. The second most common diagnosis was bipolar affective disorder with 13.1% (n = 159). The rate of schizophrenia in both voluntary and involuntary hospitalizations was significant (34.5% and 54.6%, respectively). However, depression, the second most common diagnosis requiring hospitalization with a rate of 23.2% of voluntary hospitalizations, accounted for only 3.7% of involuntary hospitalizations. Conclusion: Males constituted almost 75% of the single admission group. This difference may result from the socioeconomic and cultural profile of Turkey, as mental disorders make marriage impossible and are hidden in females suffering from them. Different findings from different cultures on single/multiple admissions and voluntary/involuntary admissions of patients lead to the conclusion that specific legislation covering treatment or hospitalization for mental disorders is needed in every country.
https://www.jhpr.ir/article_69412_c1ec80be89b31ccf8c8fb7166c5c2bcc.pdf
2018-10-01
123
129
10.15171/hpr.2018.27
Hospitalization
Voluntary
Involuntary
Readmission
Admission
Bahadır
Geniş
bahadirgenis06@gmail.com
1
Department of Psychiatry, Faculty of Medicine, Gazi University, Ankara, Turkey
LEAD_AUTHOR
Behçet
Coşar
behcetcosar@gmail.com
2
Department of Psychiatry, Faculty of Medicine, Gazi University, Ankara, Turkey
AUTHOR
Selçuk
Candansayar
scsayar@gmail.com
3
Department of Psychiatry, Faculty of Medicine, Gazi University, Ankara, Turkey
AUTHOR
Nermin
Gürhan
nermingurhan@gmail.com
4
Department of Nursing, Faculty of Health Sciences, Gazi University, Ankara, Turkey
AUTHOR
Curran WJ, Harding TW. The law and mental health: harmonizing objectives, a comparative survey of existing legislation together with guidelines for its assessment and alternative approaches to its improvement. Geneva: World Health Organization; 1978:161.
1
Turkish Psychiatric Association Mental Health Law Draft. Turkish Psychiatric Association Websites. http://www.psikiyatri.org.tr/299/ruh-sagligi-yasasi-taslaginin-yedi-yillik-ve-ruh-sagligi-platformunun-dort-aylik. Updated 06.01.2007. Accessed 01.12.2017.
2
Cooper AJ. A clinical study of violence in patients referred on a Form I to a general hospital psychiatric unit. Can J Psychiatry. 1988;33(8):711-715. doi:10.1177/070674378803300808.
3
Okin RL. The relationship between legal status and patient characteristics in state hospitals. Am J Psychiatry. 1986;143(10):1233-1237. doi:10.1176/ajp.143.10.1233.
4
Riley R, Richman A. Involuntary hospitalization in Canadian psychiatric inpatient facilities, 1970-1978. Can J Psychiatry. 1983;28(7):536-541. doi:10.1177/070674378302800706.
5
Gove WR, Fain T. A comparison of voluntary and committed psychiatric patients. Arch Gen Psychiatry. 1977;34(6):669-676. doi:10.1001/archpsyc.1977.01770180055004.
6
Tremblay PF, King PR, Baines GR. Clinical and demographic characteristics of voluntary and involuntary psychiatric inpatients. Can J Psychiatry. 1994;39(5):297-299. doi:10.1177/ 070674379403900511.
7
Priebe S, Katsakou C, Amos T, et al. Patients’ views and readmissions 1 year after involuntary hospitalisation. Br J Psychiatry. 2009;194(1):49-54. doi:10.1192/bjp.bp.108.052266.
8
Sanguineti VR, Samuel SE, Schwartz SL, Robeson MR. Retrospective study of 2,200 involuntary psychiatric admissions and readmissions. Am J Psychiatry. 1996;153(3):392-396. doi:10.1176/ajp.153.3.392.
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Addington D, Holley HL. A comparison of voluntary with remanded schizophrenics. Can J Psychiatry. 1989;34(2):89-93. doi:10.1177/070674378903400203.
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Sanguineti VR, Brooks MO. Factors related to emergency commitment of chronic mentally ill patients who are substance abusers. Hosp Community Psychiatry. 1992;43(3):237-241. doi:10.1176/ps.43.3.237.
11
Kallert TW, Glockner M, Schutzwohl M. Involuntary vs. voluntary hospital admission. A systematic literature review on outcome diversity. Eur Arch Psychiatry Clin Neurosci. 2008;258(4):195-209. doi:10.1007/s00406-007-0777-4.
12
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington DC: American Psychiatric Association; 2000.
13
Bernardo AC, Forchuk C. Factors associated with readmission to a psychiatric facility. Psychiatr Serv. 2001;52(8):1100-1102. doi:10.1176/appi.ps.52.8.1100.
14
Cuffel BJ, Held M, Goldman W. Predictive models and the effectiveness of strategies for improving outpatient follow-up under managed care. Psychiatr Serv. 2002;53(11):1438-1443. doi:10.1176/appi.ps.53.11.1438.
15
Houston KG, Mariotto M. Outcomes for psychiatric patients following first admission: relationships with voluntary and involuntary treatment and ethnicity. Psychol Rep. 2001;88(3 Pt 2):1012-1014. doi:10.2466/pr0.2001.88.3c.1012.
16
Riecher A, Rossler W, Loffler W, Fatkenheuer B. Factors influencing compulsory admission of psychiatric patients. Psychol Med. 1991;21(1):197-208. doi:10.1017/ S0033291700014781.
17
Feigon S, Hays JR. Prediction of readmission of psychiatric inpatients. Psychol Rep. 2003;93(3 Pt 1):816-818. doi:10.2466/pr0.2003.93.3.816.
18
Munk-Jorgensen P, Mortensen PB, Machon RA. Hospitalization patterns in schizophrenia. A 13-year follow-up. Schizophr Res. 1991;4(1):1-9. doi:10.1016/0920-9964(91)90004-B.
19
Singh H, Bhalchandra DA, Sarmukaddam S, Chaturvedi SK. Readmission of psychiatric patients in India: sociodemographic factors. Int J Cult Ment Health. 2014;7(4):398-409. doi:10.108 0/17542863.2013.835330.
20
Fennig S, Rabinowitz J, Fennig S. Involuntary first admission of patients with schizophrenia as a predictor of future admissions. Psychiatr Serv. 1999;50(8):1049-1052. doi:10.1176/ps.50.8.1049.
21
Chang CM, Lee Y, Lee Y, Yang MJ, Wen JK. Predictors of readmission to a medical-psychiatric unit among patients with minor mental disorders. Chang Gung Med J. 2001;24(1):34-43.
22
Gultekin BK, Celik S, Tihan A, Beskardes AF, Sezer U. Sociodemographic and Clinical Characteristics of Psychiatric Inpatients Hospitalized Involuntarily and Voluntarily in a Mental Health Hospital. Noro Psikiyatr Ars. 2013;50(3):216- 221. doi:10.4274/npa.y6245.
23
Zhou JS, Xiang YT, Zhu XM, et al. Voluntary and Involuntary Psychiatric Admissions in China. Psychiatr Serv. 2015;66(12):1341-1346. doi:10.1176/appi.ps.201400566.
24
Salize HJ, Dressing H. Epidemiology of involuntary placement of mentally ill people across the European Union. Br J Psychiatry. 2004;184:163-168. doi:10.1192/bjp.184.2.163.
25
Zeppegno P, Airoldi P, Manzetti E, Panella M, Renna M, Torre E. Involuntary psychiatric admissions: A retrospective study of 460 cases. Eur J Psychiat. 2005;19(3):133-143. doi:10.4321/S0213-61632005000300001.
26
Schuepbach D, Novick D, Haro JM, et al. Determinants of voluntary vs. involuntary admission in bipolar disorder and the impact of adherence. Pharmacopsychiatry. 2008;41(1):29-36. doi:10.1055/s-2007-993213.
27
ORIGINAL_ARTICLE
Design and Evaluation of a Mobile-Based Application for Patients With Type 2 Diabetes: Case Study of Shariati Hospital in Tehran, Iran
Background: With regard to the particularly high prevalence, cost, and number of disabilities associated with diabetes, increasing patients’ knowledge and skills for managing the disease can help minimize the risks of complications. Objective: The present study aimed to design and evaluate a mobile-based application with which patients with type 2 diabetes can increase their knowledge of and skills for managing their disease. Methods: The current developmental-applied study was conducted in 2016 in a library and used a 2-step sectional format. The research population comprised 15 physicians and endocrinologists working in medical centers associated with Tehran University of Medical Sciences and 20 physicians and patients. Based on the library study, a checklist was designed and then distributed among participants. Their responses were analyzed using SPSS software version 20. Results: The data was divided into 4 main sections: identity information (patient demographics), clinical information, education curriculum related to diabetes management, and program requirements for diabetes management, which consisted of 52 subsets. The evaluation of the system by doctors and patients showed that the system has high capabilities. Conclusion: Mobile-based programs can help diabetics control blood glucose levels, reduce diabetes complications, and promote overall health.
https://www.jhpr.ir/article_68430_cf017d5af70e9d8d526633a376e12bc3.pdf
2018-10-01
130
136
10.15171/hpr.2018.28
Diabetes
Self Care
Mobile Health
Reza
Safdari
rsafdari@tums.ac.ir
1
Department of Health Information Management, Faculty Member of Paramedical School, Tehran University of Medical Sciences, Tehran, Iran
AUTHOR
Leila
Shahmoradi
leilashahmoradi1@gmail.com
2
Department of Health Information Management, Faculty Member of Paramedical School, Tehran University of Medical Sciences, Tehran, Iran
AUTHOR
Ali
Garavand
virya67@yahoo.com
3
Department of Health Information Management and Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
AUTHOR
Nasim
Aslani
aslaninasim@yahoo.com
4
Department of Health Information Management, Iran University of Medical Sciences, Tehran, Iran
AUTHOR
Aliasghar
Valipour
virya67@gmail.com
5
Department of Epidemiology, Faculty Member of Abadan School of Medical Sciences, Abadan, Iran
AUTHOR
Hassan
Bostan
h.bostan68@gmail.com
6
Department of Health Information Technology, Abadan School of Medical Sciences, Abadan, Iran
LEAD_AUTHOR
World Health Organization. Definition, diagnosis and classification of diabetes mellitus and its complications. Geneva, Switzerland: World Health Organization; 1999.
1
Ahmadi M, Aslani N. Capabilities and advantages of cloud computing in the implementation of electronic health record. Acta Inform Med. 2018;26(1):24-28. doi:10.5455/aim.2018.26.24-28.
2
Mulcahy K, Maryniuk M, Peeples M, et al. Diabetes self-management education core outcomes measures. Diabetes Educ. 2003;29(5):768-770, 773-784, 787-768 passim. doi:10.1177/014572170302900509.
3
Wantland DJ, Portillo CJ, Holzemer WL, Slaughter R, McGhee EM. The effectiveness of Web-based vs. non-Web-based interventions: a meta-analysis of behavioral change outcomes. J Med Internet Res. 2004;6(4):e40. doi:10.2196/jmir.6.4.e40.
4
Pinciroli F, Corso M, Fuggetta A, Masseroli M, Bonacina S, Marceglia S. Telemedicine and e-health. IEEE Pulse. 2011;2(3):62-70. doi:10.1109/MPUL.2011.941524.
5
Piette JD. Interactive behavior change technology to support diabetes self-management: where do we stand? Diabetes Care. 2007;30(10):2425-2432. doi:10.2337/dc07-1046.
6
Norris SL, Lau J, Smith SJ, Schmid CH, Engelgau MM. Self-management education for adults with type 2 diabetes: a meta-analysis of the effect on glycemic control. Diabetes Care. 2002;25(7):1159-1171. doi:10.2337/diacare.25.7.1159.
7
Funnell MM, Kruger DF, Spencer M. Self-management support for insulin therapy in type 2 diabetes. Diabetes Educ. 2004;30(2):274-280. doi:10.1177/014572170403000220.
8
Marrero DG, Vandagriff JL, Kronz K, et al. Using telecommunication technology to manage children with diabetes: the Computer-Linked Outpatient Clinic (CLOC) Study. Diabetes Educ. 1995;21(4):313-319. doi:10.1177/014572179502100409.
9
Ibbini M. A PI-fuzzy logic controller for the regulation of blood glucose level in diabetic patients. J Med Eng Technol. 2006;30(2):83-92. doi:10.1080/03091900500049528.
10
Wu Y, Yao X, Vespasiani G, et al. Mobile App-Based Interventions to Support Diabetes Self-Management: A Systematic Review of Randomized Controlled Trials to Identify Functions Associated with Glycemic Efficacy. JMIR Mhealth Uhealth. 2017;5(3):e35. doi:10.2196/mhealth.6522.
11
Boyle L, Grainger R, Hall RM, Krebs JD. Use of and Beliefs About Mobile Phone Apps for Diabetes Self-Management: Surveys of People in a Hospital Diabetes Clinic and Diabetes Health Professionals in New Zealand. JMIR Mhealth Uhealth. 2017;5(6):e85. doi:10.2196/mhealth.7263.
12
Clements MA, Staggs VS. A Mobile App for Synchronizing Glucometer Data: Impact on Adherence and Glycemic Control Among Youths With Type 1 Diabetes in Routine Care. J Diabetes Sci Technol. 2017;11(3):461-467. doi:10.1177/1932296817691302.
13
Iranian Diabetes Society. Books Set. http://www.ids.org.ir/. Accessed 15 Feb 2015.
14
Farjami A, Haghpanah S, Arasteh P, et al. Epidemiology of hereditary coagulation bleeding disorders: A 15-year experience from southern Iran. Hosp Pract Res. 2017;2(4):113-117. doi:10.15171/hpr.2017.27.
15
Ko GT, So WY, Tong PC, et al. From design to implementation--the Joint Asia Diabetes Evaluation (JADE) program: a descriptive report of an electronic web-based diabetes management program. BMC Med Inform Decis Mak. 2010;10:26. doi:10.1186/1472-6947-10-26.
16
Jennings A, Powell J, Armstrong N, Sturt J, Dale J. A virtual clinic for diabetes self-management: pilot study. J Med Internet Res. 2009;11(1):e10. doi:10.2196/jmir.1111.
17
Atkinson E. Web analytics and think aloud studies in web evaluation: understanding user experience. London University; 2007
18
Holmen H, Wahl AK, Cvancarova Smastuen M, Ribu L. Tailored Communication Within Mobile Apps for Diabetes Self-Management: A Systematic Review. J Med Internet Res. 2017;19(6):e227. doi:10.2196/jmir.7045.
19
Perez-Gandia C, Facchinetti A, Sparacino G, et al. Artificial neural network algorithm for online glucose prediction from continuous glucose monitoring. Diabetes Technol Ther. 2010;12(1):81-88. doi:10.1089/dia.2009.0076.
20
Holopainen A, Galbiati F, Voutilainen K, EHIT L. Use of modern mobile technologies to enhance remote self-care services. Helsinki, Finland: 2006;139.
21
Quinn CC, Clough SS, Minor JM, Lender D, Okafor MC, Gruber-Baldini A. WellDoc mobile diabetes management randomized controlled trial: change in clinical and behavioral outcomes and patient and physician satisfaction. Diabetes Technol Ther. 2008;10(3):160-168. doi:10.1089/dia.2008.0283.
22
Roek MG, Welschen LM, Kostense PJ, Dekker JM, Snoek FJ, Nijpels G. Web-based guided insulin self-titration in patients with type 2 diabetes: the Di@log study. Design of a cluster randomised controlled trial [TC1316]. BMC Fam Pract. 2009;10:40. doi:10.1186/1471-2296-10-40.
23
Cho JH, Lee HC, Lim DJ, Kwon HS, Yoon KH. Mobile communication using a mobile phone with a glucometer for glucose control in Type 2 patients with diabetes: as effective as an Internet-based glucose monitoring system. J Telemed Telecare. 2009;15(2):77-82. doi:10.1258/jtt.2008.080412.
24
Dobson R, Whittaker R, Murphy R, et al. The use of mobile health to deliver self-management support to young people with type 1 diabetes: a cross-sectional survey. JMIR Diabetes. 2017;2(1):e4. doi:10.2196/diabetes.7221.
25
Goyal S, Nunn CA, Rotondi M, et al. A Mobile App for the Self-Management of Type 1 Diabetes Among Adolescents: A Randomized Controlled Trial. JMIR Mhealth Uhealth. 2017;5(6):e82. doi:10.2196/mhealth.7336.
26
Gao C, Zhou L, Liu Z, Wang H, Bowers B. Mobile application for diabetes self-management in China: Do they fit for older adults? Int J Med Inform. 2017;101:68-74. doi:10.1016/j.ijmedinf.2017.02.005.
27
Zhang X, Han X, Dang Y, Meng F, Guo X, Lin J. User acceptance of mobile health services from users’ perspectives: The role of self-efficacy and response-efficacy in technology acceptance. Inform Health Soc Care. 2017;42(2):194-206. doi:10.1080/17538157.2016.1200053.
28
Garavand A, Samadbeik M, Kafashi M, Abhari S. Acceptance of Health Information Technologies, Acceptance of Mobile Health: A Review Article. J Biomed Phys Eng. 2017;7(4):403- 408.
29
Zaires S, Perrakis G, Bekri E, Katrakazas P, Lambrou G, Koutsouris D. Chronic Disease Management via Mobile Apps: The Diabetes Case. In: Eskola H, Väisänen O, Viik J, Hyttinen J, eds. EMBEC & NBC 2017. EMBEC 2017, NBC 2017. IFMBE Proceedings, vol 65. Singapore: Springer; 2017:177-180. doi:10.1007/978-981-10-5122-7_45.
30
ORIGINAL_ARTICLE
Hypereosinophilic Cardiac Involvement Presenting With Left Ventricular Massive Thrombus and Cardioembolic Stroke: A Case Report
Introduction: It is well known that the tendency toward thrombosis is increased in cancer patients. The increase in cancer procoagulant and tissue factor levels, endothelial damage, and stasis due to compression are among the most accused causes of thrombosis in cancer patients. Hypereosinophilia is a rare condition that causes endothelial damage leading to thrombosis. Case Presentation: We present a 64-year-old male patient with cardiac involvement of hypereosinophilia which developed in the T-cell lymphoma ground resulting in a fatal cardioembolic stroke. Despite normal left ventricular (LV) contractions, almost half of the ventricular volume was full of thrombus in this case. Conclusion: Hypereosinophilia is a rare cause of thrombus formation in the left ventricle in patients with preserved ejection fraction. However, hypereosinophilic cardiac involvement can lead to rapid, progressive, life-threatening complications.
https://www.jhpr.ir/article_68188_33c14f40ab6dde4a6c1fa1ad89cf8f0b.pdf
2018-10-01
137
139
10.15171/hpr.2018.29
Eosinophilia
Cardiac
Left Ventricular
Thrombosis
Stroke
Muhammet
Gurdogan
drmgurdogan@gmail.com
1
Department of Cardiology, Faculty of Medicine, Trakya University, Edirne, Turkey
LEAD_AUTHOR
Ugur
Ozkan
drugurozkan@hotmail.com
2
Department of Cardiology, Faculty of Medicine, Trakya University, Edirne, Turkey
AUTHOR
Servet
Altay
svtaltay@gmail.com
3
Department of Cardiology, Faculty of Medicine, Trakya University, Edirne, Turkey
AUTHOR
Fulya
Puyan
fulyapuyan@gmail.com
4
Department of Pathology, Faculty of Medicine, Trakya University, Edirne, Turkey
AUTHOR
Alzand BS, Ilhan M. Thrombus in a normal left ventricle. Neth Heart J. 2008;16(1):24-25. doi:10.1007/BF03086113.
1
Gotlib J. World Health Organization-defined eosinophilic disorders: 2014 update on diagnosis, risk stratification, and management. Am J Hematol 2014;89(3):325-337. doi:10.1002/ajh.23664.
2
Ogbogu PU, Rosing DR, Horne MK 3rd. Cardiovascular manifestations of hypereosinophilic syndromes. Immunol Allergy Clin North Am. 2007;27(3):457-475. doi:10.1016/j.iac.2007.07.001.
3
Schooley RT, Flaum MA, Gralnick HRA, et. al. A clinicopathologic correlation of the idiopathic hypereosinophilic syndrome. II. Clinical manifestations. Blood. 1981;58(5):1021–1026.
4
Weller PF, Bubley GJ. The idiopathic hypereosinophilic syndrome. Blood. 1994;83(10):2759-2779.
5
Roufosse FE, Goldman M, Cogan E. Hypereosinophilic syndromes. Orphanet J Rare Dis. 2007;2:37. doi:10.1186/1750-1172-2-37.
6
Shah R, Ananthasubramaniam K. Evaluation of cardiac involvement in hypereosinophilic syndrome: complementary roles of transthoracic, transesophageal, and contrast echocardiography. Echocardiography. 2006;23(8):689-691. doi:10.1111/j.1540-8175.2006.00288.x.
7
Ebrahimifar P, Shahabi J. Right ventricular thrombosis as a manifestation of Behçet’s syndrome. ARYA Atheroscler. 2017;13(2):91-94.
8
Eren NK, Emren SV, Duygu H, et.al. Left ventricular thrombus formation in a patient with normal ejection fraction. Arch Turk Soc Cardiol. 2013;41:625-628. doi:10.5543/tkda.2013.71598.
9
Lee CH, Chen CC, Chern MS. Thrombolytic therapy for acute left atrial thrombus formation in one patient with heart failure and atrial fibrillation. Circ J. 2007;71(4):604-607. doi:10.1253/circj.71.604.
10