Ibérica ISSN: 1139-7241 [email protected] Asociación Europea de Lenguas para Fines Específicos España
Mungra, Philippa; Canziani, Tatiana Lexicographic studies in medicine: Academic Word List for clinical case histories Ibérica, núm. 25, abril, 2013, pp. 39-62 Asociación Europea de Lenguas para Fines Específicos Cádiz, España
Available in: http://www.redalyc.org/articulo.oa?id=287026237003
How to cite Complete issue Scientific Information System More information about this article Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Journal's homepage in redalyc.org Non-profit academic project, developed under the open access initiative Lexicographic studies in medicine: Academic Word List for clinical case histories
Philippa Mungra and Tatiana Canziani University of Rome La Sapienza1 & University of Palermo (Italy) [email protected] & [email protected]
Abstract Medical texts are often thought to pertain to a closed community, but how far the language used by that community overlaps with general academic lexis is unknown. We examined a corpus of clinical case histories using the software RANGE to characterise the lexis of clinical case histories quantitatively and present a wordlist for clinical medicine. Only 58% of the general academic wordlists are found in clinical texts but the 85% overlap with an important academic wordlist, the Coxhead 570, furnishes evidence for the academic nature of the lexis used for clinical cases in Medicine. There was little overlap (38%) between our clinical case wordlist and other wordlists of medical research articles but such overlap might constitute a core of medical lexis. Keywords: lexis, Medical English, Medical Academic Word List (MAWL), clinical case histories, subject-specific wordlists.
Resumen Un estudio lexicográfico del inglés en medicina: El listado de términos académicos para los casos clínicos Se suele pensar que los textos de medicina son principalmente territorio de una comunidad restringida de expertos del sector, pero se conoce poco sobre cómo y en qué medida el lenguaje utilizado por la comunidad médica puede coincidir con el léxico académico general. Con el objetivo de presentar un listado de términos específicos de los casos clínicos, estudiando el léxico desde un punto de vista cuantitativo, se ha examinado un corpus de casos clínicos utilizando el software RANGE. Según el estudio realizado, los resultados han revelado la existencia de una coincidencia del 85% con un importante listado de términos académicos (el denominado Coxhead 570), y una coincidencia del 58% con el
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listado de términos generales. Este hallazgo confirma la naturaleza académica del léxico que se recoge en los casos clínicos. Si bien la coincidencia entre el listado de términos de los casos clínicos y de los listados restantes de artículos científicos en el ámbito médico sea baja (38%), es posible concluir, a nuestro juicio, que esa doble coincidencia conforma, en realidad, un léxico esencial o común en medicina. Palabras clave: léxico, inglés médico, listado académico de términos médicos, casos clínicos, listados de términos específicos.
1. Introduction Medical texts are often thought to pertain to a closed community, but how far the language used by that community overlaps with general academic lexis is unknown. In a fascinating account of the development of the medical journals, Booth (1982) affirms that medical learning up to the turn of the last century was almost entirely based on the reading of patient cases, known variously as cases, case reports or case histories. Few studies have addressed clinical case histories. One of the reasons for this might be that the macro- structure of case histories has not changed radically over many years from its beginnings in the Proceedings of the Royal Society in the 1700s. The evolution of the case report has been studied in terms of structure, content, stylistic features and variations in a diachronic study of medical writing between 1735 and 1985 (Atkinson, 1992) and through vernacularisation of medical treatises between 1850-1900 and 1965-1995 (Taavitsainen & Pahta, 2000). In recent years however, Medical Education has centred heavily on clinical research to find valid justification for clinical questions and decision-making, as part of a school of thought known as Evidence-Based Medicine (EBM). EBM, though important methodologically and didactically, has privileged the study of medical research articles or RAs. Thus in Linguistics, there is a plethora of studies of RAs such as those identifying moves (Nwogu, 1997), moves in introductions ( Hyland, 2000; Lorés, 2004; Samraj, 2005), in the methods section (Hopkins & Dudley-Evans, 1988; Berkenkotter & Huckin, 1999) in the discussion (Skelton & Edwards, 2000; Peacock, 2002), in abstracts like the IMRaD (Introduction, Methods, Results and Discussion) model (Swales, 1990; Paltridge, 1997), in biochemistry RAs (Kanoksilapatham, 2005) and in the evolution of the genre of medical RAs (Swales, 1990; Paltridge, 1997). Other medical genres studied are popularizations (Myers, 2003) dissertations and other academic papers
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(Hyon & Chen, 2004) and Consensus Conference Statements (Mungra, 2007). In RAs and RA abstracts, pragmatic features such as hedges, (Salager- Meyer, 1994), modality (Salager-Meyer, Defives & Hamelinsck, 1998), scholarly gratitude, acknowledgements and scholarly criticisms (Salager- Meyer, Alcaraz Ariza & zambrano, 2003; Salager-Meyer, Alcaraz-Ariza & Pabón-Berbesí, 2009; Salager-Meyer et al., 2011) have been studied. There have been fewer linguistic studies of case reports. The macro- structure of case histories (DeBakey & DeBakey, 1984) and content checklists (McCarthy & Reilly, 2000; Cohen, 2006) have been published by medical journals and editors. Anspach (1988) identified four rhetorical devices of case presentations - depersonalisation, passivation or omission of the agent, use of medical technology as an agent and verbal account markers such as “states”, “report” or “denies” . The depersonalized tone with passive construction is now considered a conventional characteristic of modern case reports (Taavitsainen & Pahta, 2000). Hunter (1996) compared cases to a subjective, personalised narrative. According to Donnelly (1997), when such narratives are generalized, they become a teaching-learning tool because their predictive and diagnostic power gives importance to the genre. Berkenkotter (2008 & 2009) analysed the linguistic and historical evolution of psychiatric case reports emphasizing its role as an invaluable tool in diagnosis of psychiatric disease.
1.1. Problems when teaching the medical literature and NNS Because of a return to a teaching methodology based on a clinical scenario or patient case called Problem-Based Learning or PBL, introduced at McMaster university (Barrows, 1990; Frederiksen, 1999), reading case reports have become increasingly important because it is student-centred and uses the analysis patient data by expert physician-teachers to lead students to the discovery/identification of the underlying pathology and the development of problem-solving skills (Schmidt, 1993). Clinical case histories furnish ample teaching material for physician-training (McCarthy & Reilly, 2000; Taavitsainen & Pahta, 2000; Cohen, 2006), and are widely read by medical students and by both junior and senior professionals since their purpose is instructive and their goal is not explanation but understanding for diagnosis (Taavitsainen & Pahta, 2000; Vandenbroucke, 2001; Berkenkotter, 2008) and to give clinicians “better insight into the unusual riddles which specialists usually encounter in their everyday practice” (Yitschaky, Yitschaky & zadik, 2011: 180).
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For non-native speakers of English such as our case, the lack of language skills may create a barrier in the patient-doctor setting or in problem-based group activity among peer-physicians (Mpofu et al., 1998; Dyke, Jamrozik & Plant, 2001; Koh et al., 2008). For strategies to help professionals prepare publications of clinical cases, there are published guidelines (DeBakey & DeBakey, 1984) and content checklists (McCarthy & Reilly, 2000; Cohen, 2006). For RAs too, a consistent body of literature devoted to identifying strategies exists (Belcher, 1995; Medical Journals Editing, 2002; Okamura, 2006; Divasson-Cilvetti & León- Pérez, 2006; Belcher, 2007). One of the strategies that have received attention in recent years is that of wordlists for vocabulary development based on data from specialized corpora. To the best of our knowledge, no wordlists based on lexis have been used in clinical cases.
1.2. Wordlists: general and specialist wordlists One of the earliest wordlists is that of the General Service List (GSL) by West (1953), corresponding to the most basic level of fluency in general English and consists of roughly the first most frequently used 2,000 words in English, acquired in primary school. Later, Campion and Elley (1971) compiled a list of the 500 most common words and 3,200 most frequently used words. Lexis used in an academic setting was first studied by Praninskas (1972) who compiled the American university Wordlist, based on a corpus of 272,466 words from ten university-level textbooks covering ten academic disciplines. Later, Lynn (1973) and Ghadessy (1979) worked with wordlists most frequently underlined by students who are speakers of other languages, while xue & Nation (1984) published the university Word List (uWL) containing the 800 words most frequently used in the Humanities. Another general wordlist was compiled from written works in English called the British National Corpus or BNC. Subsequently, Coxhead (2000) developed the Academic Word List (AWL), using a corpus of 3.5 million running words from a variety of academic texts. The AWL consists of 570 word families which cover roughly 10% of running words and is now perhaps the most common reference academic wordlist (Coxhead, 2011). Among specialist domains, wordlists for different purposes – either pedagogical or linguistic – have been built in the fields of Computer Science (Lam, 2001) and in Business (Hsu, 2009). In the Engineering field, Mudraya (2006) was the first to build the SEEC (Student Engineering English
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Corpus), a corpus-driven lexical wordlist. Later, Ward (2009) created the BEL (Basic Engineering List) based on a range of topics in various major engineering fields and taken from 3rd and 4th year undergraduate textbooks. The aim was to create a wordlist that could be used in all engineering disciplines by learners with a low level of English. In Agriculture, Martínez, Beck & Panza (2009) created the Agrocorpus, a wordlist based on research articles in the agricultural sciences focusing the importance of creating wordlists based on pragmatic criteria more than on frequency. Two linguistic studies of the lexis of medical RAs have been published (Chen & Ge, 2007; Wang, Liang & Ge, 2008) providing a wordlist of the most frequently used medical academic words in this genre known as the Medical Academic Word List or MAWL but to the best of our knowledge, the lexis of case histories had not been studied despite the fact that they are important in developing and honing clinical decision-making skills (Skinner, 1956; Moran-Campbell, 1976; Barrows, 1990). Given the paucity of lexical studies of case histories, we present here a study of the lexis commonly used by medical and surgical case histories in order to:
1. Determine what differences, if any, there are between the lexis of case histories and other academic publications. 2. Compare our findings of the lexis of case histories with that of other published wordlists in medicine.
2. Procedure 2.1. Collection of the corpus From uRL: http://sciencedirect.com, a public science database, we randomly retrieved 3 journals from each of the 24 medical and surgical topics as seen in Figure 1, and we selected randomly two or three (when available) case histories from each of these 72 journals. All the sample case reports included in our corpus were kept at their original length, and published between the years 1997 and 2011. We used the strict criteria by Wood (2001): published by native speakers (NSs) only according to surname or with affiliations to North American, British, Canadian, or Australian hospitals and universities, and in English-language European journals. The resulting corpus consisted of 200 case histories. The total number of running words was 246,907 with a range of 151 to 2,883 words per case. The
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corpus were kept at their original length, and published betwee n the years 1997 and 2011. We used the strict criteria by Wood (2001): published by native P. MuNGRA & T. CANzIANsI peakers (NSs) only according to surname or with affiliations to North American, British, Canadian , or Australian hospitals and universities, and in English -language European journals. The resulting corpus consisted of 200 case averahgiseto nriuesm. Tbheer t ootafl nruumnbneirn ogf rwunonridngs wino rdths ew acsa 2s4e6 ,h90is7t owritihe sa orafn gteh oef 1c5o1r ptou s was 1,2352.,883 words per case. The average number of ru nning words in the case histories of the corpus was 1,235.
1. Anesthesiology and Pain Medicine 13. Oncology 2. Cardiology and Cardiovascular Medicine 14. Ophthalmology 3. Critical Care and Intensive Care Medicine 15. Orthopedics, Sports Medicine and Rehabilitation 4. Emergency Medicine 16. Otorhinolaryngology and Facial Plastic Surgery 5. Endocrinology, Diabetes and Metabolism 17. Pathology and Medical Technology 6. Forensic Medicine 18. Perinatology, Pediatrics and Child Health 7. Ga stroenterology 19. Psychiatry and Mental Health 8. Health Informatics 20. Pulmonary and Respiratory Medicine 9. Infectious Diseases 21. Radiology and Imaging 10. Medicine and Dentistry (General) 22. Surgery 11. Nephrology 23. Transplantation 12. Obstetrics, Gynecology and Women's Health 24. Urology
Figure 1. Li st of medical and surgical disciplines having clinical case histories.
The publications selected were identified as “cases ” or “case reports” by the The jpourbnlailc iatsteiolfn asn ds ealle ocft ethde mw eharde tihdee fnotlliofiweidn ga esl e“mceanstess/m” oovre s “: c ase reports” by the journal itsel•f anadbs tarallc to/ifn trtohdeumcti ohna/pdr etsheent aftoiolln o; wing elements/moves: • diagn ostic procedure ; • ab•s tramcatn/aignetmroendtu ocf ttihoen p/atpiernets aenndt aotuitoconm; e ; and, • di•a gndoisctuics spiorno/ccoendculurseio; n . The files were saved in electronic form , exported and cleaned for unreadable cha•ractmersa,n aangde mtheenn ts aovfed t hase tpexatt ifeilnets a(enxdte nosuiotnc o.tmxte). ; See Figure 2, which shows a preview of a case containing the elements/moves circled . • discussion/conclusion.
The files were saved in electronic form, exported and cleaned for unreadable chara cters, and then saved as text files (extension .txt). See Figure 2, which show s a preview of a case containing the elements/moves circled.
2.2. T ext normalisation and use of the software
In the automatic creation of a text file from a pdf file, transcription mistakes or misspellings were corrected manually and corrections for names of drugs, abbreviations, symbols or units, were done in order to make the text readable by the Software used called RANGE, retrieved frIboémrica 2H5 (2e0a1t3 )l:e … y-…, Nation & Coxhead (2002). As reference programs, we used three wordlists, namely, two wordlists from the GSL by West (1953), given as the most commonly used 2,000 words in English (also known as GSL-1 & GSL-2) and the third is the Academic Word List (AWL), consisting of 570 families compiled by Coxhead (2000). In addition to these three reference wordlists, we added the Medical Academic WordList (MAWL) of families published by Wang, Liang
44 Ibérica 25 (2013) : 39-62 LExICOGRAPHIC STuDIES IN MEDICINE and Ge, (2008). By using these four reference wordlists against our corpus of 200 clinical cases, we could identify the 2,000 most common words, the most commonly used words in academic domains and the most commonly used words in medical RAs. Any words outside these four lists would be considered peculiar to clinical cases, and thus a candidate for our clinical wordlist, which we called MAWLcc (Medical Academic Word List for Clinical Cases). With an occurrence of over 30 times per 200,000 tokens, this would constitute the MAWLcc wordlist, as indicated by the criteria in section
2.3 bPe. lMoUwNG. RA & T. CANZIANI
Figure 2 . Article outline of a clinical case history in the Table of Contents from Journal of Clinical Anesthesia (2009), 21 (6): 431 -434 . The four parts of the classic clinical case history are encircled.
2.2 . Text normalisation and use of the software Texts were normalised whenever possible, according to standards common In the automatic creation of a text file from a pdf file, transcription mistakes or in spmoisksepnel lincglisn iwcaerl e sccoirerneccted fmora nuuanllyit sa, nds ycmorbreocltsio nasn dfo r nnaammess oof fd rudgrsu, gs or equipambberenvti.a tAio ncso, smympbleotles olirs ut noitfs, cwoerrer edcotnioe nins oarndedr tnoo mrmakea ltihsea tteioxtn rse amdaabyle b bey found in Atphpe eSnodftiwxa re1 .u sCedl ecaanlliendg R AanNdG Es, croetrriinevge do ffro mth He eattelexyt,s Nwatieorn e &d oCnoxeh ebady both (2002) . As reference programs, we used three wordlists, namely, two wordlists reseafrrcohme trhse wGhSLic hby m Wigesht t( 1h9a5v3e), cgriveeant eads ttheex mt odsitf cfoemremnocnelsy busuetd i2n,0te0r0n waol radgs rien ement was mEnognliistho (raeldso aktn tohwen satsa rGt S[Lc-a1s e& 1 G0S],L m-2)id awnda yth [ec athsierd 1 i0s 3th] ea Andca daet mthice W enordd [cases 137, L1i8st4 ( A&W 1L8),8 c]o onsfis tihnge oefn 5t7ir0e f asmciolireisn cgo mpproilecde sbsy. CTohxhee aPde (a2r0s0o0n). Icno aedfdfitcioienn t was to these four reference wordlists, we added the Medical Academic WordList (MAW L) of families published by Wang, Liang and Ge, (2008). By using these four reference wordlists against our corpus of 200 clinical cases, we could identify the 2,000 most common words, the most commonly used words iInb érica 25 (2013) : 39-62 45 academic domains and the most commonly used words in medical RAs. Any words outside these four lists would be considered peculiar to clinical cases, and thus a candidate for our clinical wordlist, which we called MAWLcc (Medical
Ibérica 25 (2013 ): … -… P. MuNGRA & T. CANzIANI
found to show a strong positive correlation at r = 0.99 and the Student t- test was 0.013 (p< 0.95, 14 df). Included with the software was a stoplist which included scientific notation and units ignored by the software which allowed for the possibility to ignore technical words such as the names of drugs placed within square brackets. The program returned data as a percentage of the tokens in each of the reference wordlists. It also returned lists consisting of both tokens/types and word families as well as a final list of tokens not present in any of the reference lists. A family of words (Bauer & Nation, 1993) consisted of the baseword plus its inflected version. Thus a word family would be counted as a single item or baseword such as “surgery” together with all the occurrences of the inflected versions of the baseword, for instance, “surgical”, “surgeon”, “surgeries”, “surgeons” and “surgically” . We extracted only the basewords to create our list of families.
2.3. Criteria for creation of the list The principles used were the same as those by Wang, Liang and Ge (2008) for the creation of a MAWL from research articles (RAs). Our final list consisted of families having the following criteria:
a) Specialized occurrence: we collected all the word families outside the first 2,000 most frequently occurring in the West (1953); b) The baseword families must have a range of at least 50% of all the medical fields, that is, 12 out of the 24 areas shown in Figure 1; c) A frequency of at least 30 occurrences.
We then manually examined our list and eliminated all technical words such as the names of drugs, eponyms and procedures, which would be familiar to physicians. Our final list, MAWLcc was then compared to the MAWL from RAs published by Wang, Liang and Ge (2008) to compare overlap and ranking of the two MAWLs.
46 Ibérica 25 (2013) : 39-62 LExICOGRAPHIC STuDIES IN MEDICINE
3. Results 3.1. Corpus of clinical case histories – characteristics The types of texts included not only single patients but also groups of patients which resulted in a mixed text type having the characteristics of a case with statistical features of research articles in the results and discussion section [case 9] [case 14] [case 79]. In selecting cases for this corpus, we found that surgical disciplines often contain lexis describing procedures or describing reasons for an operation and that such lexis often demonstrated a metaphoric use of nouns and verbs as highlighted in italics in example (1):
(1) An interposition graft of reversed
Although this is a small corpus, we believe it is fully representative of case reports in that it was culled from over 50% of medical fields of the corpus. According to Sinclair (2004), representativeness requires that typically 40- 50% of all word types occur only once in a given corpus. In our corpus, 55.4% of the types occurred at least once.
3.2. Wordlists retrieved after analysis by the software – MAWLcc Following the workings of the software, we retrieved our medical wordlist, MAWLcc using four wordlists as a reference. These are the 2 GSL wordlists, the Coxhead AWL and finally the MAWL from RAs published by Wang, Liang and Ge (2008). The data are plotted in Figure 3 and show the occurrence of each reference list as a percentage; the frequencies of families are given in Table 1, which is the raw software output.
Ibérica 25 (2013) : 39-62 47 LEXICOGRAPHIC STUDIES IN MEDICINE P. MuNGRA & T. CANzIANI
800 722 700
t 577
n 600 e s e r 498 p
s 500 e i l i m a f
f
o 400
s o n 296 300 222 200
100
0 GSL-1 GSL-2 AWL_Coxhead MAWL-Wang Not on any_ CC
% of total running words in the Baseword List Total n o. of families corpus GSL -1 722 18 GSL -2 577 10 .6 AWL 498 13.6 MAWL 222 2.1 Not in the lists therefore peculiar to clinical cases 296
Figure 3. Plot of numbers of families in mBaesdiecwalo crads eL ihsist tories using the GSL -1 and 2, Coxhead -570 and the MAWL published by WangG, LSiLan-1 g and Ge (2008) as reference wordlists. GSL-2 Wordlist T okens / %A W L Types / % Families MAWL GSL -1 60,645 / 38.77 1,893 / 18.01 722 GSL -2 not in the l1is9t,4s5 t3 h e/ 1re2f.o44re peculiar to 1c,1li1n5 ic /a 1l0 c.6a1s es 577 AWL 22,547 / 14.41 1,425 / 13. 55 498 MAWL 9,862 / 6.30 222 / 2.11 222 Not in the lists 43,923 / 28.08 5,858 / 55.72 ????? Total 156,430 10,513 2,019
Table 1. RANGE output (raw data) from 200 case histories.
In the raw data ( see Table 1 ) we retrieved 2 ,019 families recognized by the In ther erfaewre ndcea tlais t(ss. eTeh eT satbrilneg 1“)? ?w?? e? ”r egtivreienv beyd th2e,0 R1A9N fGamE isloieftsw arreec oregfenrisz teod t hbey the reference lists. The string “?????” given by the RANGE software refers to the fact that these words in the corpus were not present in any of the reference wordlists. With the application of the first criterion (elIibmériicna 2a5 t i(2o01n3 ):o … f-… t he GSL- 1 and GSL-2), 720 word families remained. The text coverage of the AWL word families in our clinical corpus was 13.55% (rounded to 13.6% in Figure 3), somewhat higher than the 10.1%, of the AWL words in medical RAs texts reported by Chen & Ge (2007).
48 Ibérica 25 (2013) : 39-62 P. MUNGRA & T. CANZIANI LExICOGRAPHIC STuDIES IN MEDICINE
We fofuacnt dth taht atht e4se9 8w ofardms iilnie tsh eo fco Crpousx hweearde -n5o7t 0p rleiset not fin f anmy iloief st h(ec orerfreeresnpcoe n ding wordlists. With the application of the first criterion (elimination of the GSL -1 to 85%an)d , GwSeL r-e2 )p, r7e2s0e nwto ridn foamuril iceso repmuasi naendd. T mhea yte xbte c ocvoe nrasgide eorfe tdhe s AtrWonLg w eovrdid ence for thfea macilaieds eimn iocu rn actliunricea lo fco orpuurs cwoarsp 1u3s. 5o5f% c(lrionuicndael dc atos e1s3. . 6B% y iwn aFyi goufre c3o)n, trast, somewhat higher than the 10.1%, of the AWL words in medical RAs texts Chen r&ep oGrteed (b2y0 C0h7e)n f &ou Gned ( 2t0h0a7t) .o nly 292 families were present in medical RAs which corresponded to 51.2% of the Coxhead-570. We found that 49 8 families of Coxhead -570 list of families (corresponding to In ou8r5 %co) , rwpeures ,p r2e2se2n t fianm ouilri ecosr pwuse raend fmoauyn bde cionn scidoemredm sotrnon gw eivthid enthce fo6r2 t3he word academic nature of our corpus of clinical cases. By way of contrast, Chen & Ge famili(e2s0 0p7u) bfloiusnhde dt hbaty oWnlya n2g9,2 L fiamnigli easn wd eGre ep r(e2s0en0t8 )in, bmuetd itchala tR aAcsc owuhnicthe d for only 2c%orr eospfo tnhded r tuo n5n1.i2n%g ocfo trhpe uCso.x Thehadis- 5m70i.g ht be interpreted as a result of the clinicaInl roautrh ceorr ptuhsa, n22 r2e fsaemarilciehs nwaetreu rfeo uondf ionu cro mcomropnu ws. ith the 623 word families published by Wang, Liang and Ge (2008), but that accounted for only 2% of the Whenr uwnnei nagp cpolripeuds .t hTeh isla msti gthwt ob ec riniterrpirae tteod tahs ea rreemsulat inofi nthge 2c9li6ni cfalm railthieesr, tohannl y 241 familireess ewarechr en aftouruen odf otuor coocrpcusr. with a frequency of >30 times in the corpus. A comWphelen twe el iasptp loiefd tMheA laWst Ltwcco ccroitenrtia itnoi nthge rtehmeasien in2g4 219 6w foamrdil iefsa,m onilliye s2 4 c1a n be foundf aimni liAesp wperne dfioxu n2d, ttoo ogcectuhr ewr itwh iat hf retqhuee nfcrye qouf e>n3c0i etism eosf i no cthceu crorrepnucs.e Ain our complete list of MAWL CC containing these 24 1 word famili es can be found in corpuAs.p pWened ixi d2e, nttoigfeiethde r wwoitrhd t hfea mfreiqliueesn caiems oofn go cctuhrere ntcoek ienn so urr ectourrpnuse. d W be y the softwiadreen taifniedd wcroerda tfeadm ifliaems ailmieosn ga sth es etoekne nisn reTtuarbnleed 2by, wtheit hso fatw bare aaknd ocrweante do f the families as seen in Table 2, with a breakdown of the individual elements of the indivifdaumai li eesl eamnde tnhetisr forefq uthenec ifeasm. ilies and their frequencies.
Headword = Cell No. of Head word = Clinic No. of occurrences occurrences Cell -mediated 10 Clinical 445 Cells 203 Clinically 70 Cell 208 Clinician 4 Cellular 22 Clinici ans 29 Cellularity 10 Clinico 20 Clinicopathological 17 Clinics 20 Total 453 Total 605
Table 2. Two examples of converting tokens into families and b reakdown of occurrences in the corpus .
In our list of cli nical cases, the most frequent word was “ patien t” which occurred In ou1r, 1l5is5t t iomfes cinli nthiec acol rpcuas,e asn, dt wheas mregoistte rferde iqnu aelln 2t4 wclionricda l waraesa s,“ fpoalltoiwenedt” b yw hich the word “ diagnose ”, both concerning the sick person. The least frequent words occurwreedre 1“ ,a1n5at5o mtiym”,e “ sb oinn e t”h, e“ dcyos prlpasuisa ,” ,a “nindg ewstaiso n r”e agnisdt “eurreedte rin”, auslle d2 430 c tliimniecsa iln areas, followtheed c obryp utsh aen wd porredse “ntd iina gonloy s1e8” c, libnoictahl acroeansc. erning the sick person. The least frequent words were “anatomy”, “bone”, “dysplasia”, “ingestion” and 3.3 . Comparison of our MAWL families with other studies “ureter”, used 30 times in the corpus and present in only 18 clinical areas.
3.3. ComIbpéraicra i2s5 o(2n01 3 o): f… -…o ur MAWL families with other studies It is difficult to compare our data with that of other corpora because our family wordlists were compiled using the GSL with 2-wordlists or the Coxhead-570 AWL, compiled from academic texts written in general English
Ibérica 25 (2013) : 39-62 49 P. MuNGRA & T. CANzIANI
classes. Almost all the word families in GSL-1 and GSL-2 and 498 out of the 570 word-families from Coxhead’s AWL LwEXeICrOeG pRArPeHsIeC nSTtU iDnIE So INu Mr EcDoICrINpE u s. Table 3 shows a comparison with a selection of the most common corpora It is difficult to compare our data with that of other corpora because our family in thew hoardrldis tssc wieenrec ecso. mIpfi l wede urseinmg otvhe GSSLL w-1it ha n2 d-w GordSlLis-ts2 ,o rc othrer eCsopxohneadd i-n5g7 0t o the first 2A,0W0L0, mcoomspti lefdre fqroume nact awdeomridc st,e xotsu rw riettseun litnin gge nleisratl oEfng 3li9sh5 c wlasosreds. s Ashlmaorsetd 153 all the word families in GSL -1 and GSL -2 and 498 out of the 570 word -families familiferso min C ocxohmeadm’so AnW wLi wthe ret hpere swenot rind loiustr cpo urpbulsi. s hed by Wang, Liang and Ge (2008), corresponding to 38.25%. This shared list may be considered a core Table 3 shows a comparison with a selection of the most common corpora in the wordlhisatr df oscri emnceeds. i cIfi nwee, rienm tohvaet GthSLey-1 h aanvd e G bSeL e-2n, fcorurensdp oind ibnog ttho tchlein ficrsat l2 c,0a0s0e s and medicmaol str efrseeqaurecnht waorrtdisc,l eosu.r Treshuelt inrge mlisat inofin 3g9 52 w4o1r dsf asmhairleieds 15o3f faomuilrie sl iisnt (see Appecnodmixm o2n) mwiigthh tt hbee cw oonrdslisdte rpeudb ltisyhpeidc abl yo fW calningi, caLli acnags esa.n d Ge (2008), corresponding to 38.25%. This shared list may be considered a core wordlist for In a mceodmicipnaer, isino nth abt etthweye ehnav eo tbheenr fhoaurnd isnc ibeonthc ecsl,i niscuacl hc asaess aEnnd gmineedeicrailn g or research articles. The remaining 241 families of our l ist ( see Appendix 2) might Agricbuel tcuornes,i daenredd twypiticha lo ouf rc liMnicAaWl caLsecsc . there was very little overlap, as seen in TableI n3 , a wchoimchpa rsisuopnp oberttws eetnh e othhiegr hlhya rds pescciiefnice sn, astucrhe aosf Esnpgeinceiaerlisntg coor rpora (HylanAdgr i&cu lTtusre,, a2n0d 0 7w)i.t h our MAWL CC there was very little overlap, as seen in Table 3, which supports the highly specific nature of specialist corpora ( Hyland & Tse , 2007 ).
Compiled from Wordlist Overlap with families our MAWL CC Academic Wordlists Coxhead (2000) AWL From written academic 570 85% texts Specialist Wordlists 1 Chen & Ge (2007) Medical RAs (u sed 292 No comparison is Coxhead’s 570 AWL as a possible since reference) wordlists were not published 2 Wang, Liang and Ge (2008) Medical RAs (used GSL 623 38.25 % (Medicine) MAWL as reference) 3 Mudraya (2006) Textbooks (BNC as 1,200 1.02% (Engineering) SEEC reference) 4 Mart ínez , Beck & Panza RAs / Coxhead‘s AWL 92 2.9% (2009) (Agriculture) AgroCorpus 5 Ward (2009) (Engineering Textbooks, computing 299 word No comparison is Corpus) BEL work token frequency types (not possib le s ince families) types were used
Table 3 . Comparison with other lexical corpora in the hard sciences to show overlap with MAWLcc.
4. Discussion 4. Discussion 4.1 . Validity of the wordlist 4.1. Validity of the wordlist With respect to the collection of the corpus, we had some difficulty in selecting the publications because of paucity of linguistic publications identifying the rhetorical moves inherent in clinicaIlb écricaas 2e5 (2h01is3 )t: o… r-…ie s, unlike
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RAs, which have the IMRaD structure (Swales, 1990). Because of this, we decided to use the basic structure given to those publications in medical journals characterised as “cases” (McCarthy & Reilly, 2000; Cohen, 2006) having the characteristics indicated in Figure 2, namely, abstract, introduction, description of the case, discussion . Secondly, the presence of mixed subgenres of case series and also of cases from surgical disciplines, may have affected our MAWLcc because of language used in an unorthodox or metaphoric manner as seen in the words in Example 1 in the results. Thirdly, for reasons of comprehension and clarity, we were forced to make a selection of clinical cases prepared by English native-speaking physicians. The reason for this can be explained by examining a text like the following example (2), written by a Brazilian researcher and published in an international journal after peer review. To the casual reader or even a competent medical student, the inter-sentencial reasoning is not clear:
(2) When antibiotics are really needed, their efficacy may be enhanced by the immune system, but in the case of advanced, serious infections in immunocompromised patients, the risk of therapeutic failure is much greater. T he first scenario conceals antibiotic failures , the second ends in severe complications or death but does not call the attention of clinicians because it is the expected outcome.
In the highlighted sentence, it is not clear what the first scenario is. In fact, the author probably means that efficacy may be due not to the antibiotic, but rather to a very active immune system. Therefore, one can prescribe a generic poorly-produced antibiotic, with poor efficacy and it will still work. The second scenario is self-explanatory. A text of this sort is difficult to decodify for two reasons: first, because of the misleading use of the word “scenario” and secondly, because of the compressed contextual implication, that requires a pragmatic referential jump. In linguistic terms, the absence of “well-formedness” (Giora, 1997) and “relevance” (Sperber & Wilson, 1986) make such texts difficult to understand, thus requiring the maximum processing effort. Because of the high frequency of opacity in cryptic texts like this, written by native speakers of other languages, we agreed to select cases according to the conditions of Wood (2001). Despite these difficulties, we believe that our corpus of case histories, though small, is representative of case histories in most of the medical disciplines since the selection criteria follow the canons of Sinclair (2004) regarding representativeness and balance.
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In a comparison with MAWL in Wang, Liang and Ge (2008) based on research articles frequencies and ranking, our MAWLcc is more characteristic of patient care rather than scientific research. This is clearly reflected in the rankings of specific lexical items: we found the verb “to analyze” ranked as #242 as compared to #6 in that of MAWL. Similarly, the word “symptom” , #2 on our list, appeared at #81 in MAWL. Both corpora were culled from medical texts, but belong to different subgenres. In a comparison of these two subgenres, we observed an overlap of 250 lexical families, corresponding to 28.8% of our list of MAWLcc families. Data such as this reflect the highly specific nature of both corpora and furnishes some support for the idea put forward by Hyland and Tse (2007), and supported by Granger and Paquot (2009) that a core of academic lexis is difficult if not impossible to define. Although Hyland and Tse (2007) came to these conclusions by studying mixed corpora including professional and learner texts as well as dissertations and undergraduate theses and Granger & Paquot (2009) assembled their corpus from non-native English student writings, their ideas regarding the specific nature of academic lexis are essentially true; namely, that academic genres in the hard sciences and professional academe are highly specific in nature. Nevertheless, we believe that within a single professional field such as Medicine, an essential or core lexis may exist such as the 153 lexical families we observed in both our wordlist and that of Wang, Liang and Ge (2008). This comparison is an attempt to answer our second query regarding whether the lexis of case histories is very different and how different it is when compared with other published wordlists in medicine. Here we observe that our data validates the academic nature of AWL-570 by Coxhead and that our corpus and the MAWLcc might be considered a complementary wordlist to that of Wang, Liang and Ge (2008). Although other research groups have built corpora of academic English, like MICASE, BAWE or the Louvain corpus, most of these corpora consist of writings by students of varying proficiencies and not professional peer-reviewed publications (Alsop & Nesi, 2009).
4.2. Pedagogical considerations This wordlist presents important lexis used in clinical publications regarding patient care. This list could form a base for specific lexical exercises like word-building since they are field-specific and if implemented within the
52 Ibérica 25 (2013) : 39-62 LExICOGRAPHIC STuDIES IN MEDICINE medical curriculum it would help students to acquire appropriate professional language. This means that students must already have studied basic English and should be familiar with most of the lexis appearing in GSL-1 and GSL-2. The remaining field-specific wordlists – the Coxhead- 570 AWL and the Medical wordlist from RAs (Wang, Liang & Ge 2008) and that of the present study – could be implemented in later years of the medical curriculum. Word-building exercises would help students expand their vocabulary, aid in reading with precision, so important in the hard sciences, and contribute to developing the professional persona . The present wordlist may also be useful in testing for language proficiency, not only for medical students but also for international medical trainees.
5. Conclusions for further research Although we have gathered a small to mid-sized corpus, this study is by no means exhaustive. There are several areas for improvement such as: identifying polysemy, collocational strings or formulaic clusters and other linguistic comparisons such as that done by Méndez-Cendón (2009) in the field of phraseology. Besides this, it would be interesting to compare this wordlist with other concept-oriented glossaries and lexicographic collections such as MeSH words and uMLS (from the National Library of Medicine) and the wordbuilder DEFINDER (Muresan & Klavans, 2002). Although ours is a preliminary work, its main value lies in the didactic application of wordlists for both teaching and testing. We have found that these wordlists can be calibrated to sequential ESP courses in successive years of the medical curriculum as suggested by Baker (1988). This would furnish a good base for students whose first language is not English and who have to develop reading and comprehension skills. This is particularly significant when clarity of meaning and precision in discussing medical principles is important in a field which is rapidly burgeoning.
[Paper received 21 December 2011] [Revised paper accepted 15 August 2012]
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Philippa Mungra has taught English at the 1st Medical School of the university of Rome “La Sapienza” for the past 20 years. Her current research priorities revolve around the structure and evolution of specialist medico-scientific publications from a communicative and textual point of view and Integration of Language and Content (CLIL). She holds a M.Sc in cytogenetics from the university of Western Ontario, Canada where she has carried out her own scientific research on aneuploidy due to aging. She also holds the RSA Certification in TESOL from Cambridge.
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Tatiana Canziani is a graduate from the university of Palermo, where she is currently a researcher. She is responsible for English Language teaching and testing for the entire Health Sciences sector within the Medical School. She is a trained Psychotherapist with experience in the paediatric field. Her current research priorities revolve around the lexicography of medico- scientific publications especially referring to Cognitive Linguistics. She has recently published a review of neuropragmatics regarding metaphor and brain function.
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Appendix 1: List of terms and abbreviations altered to make text readable by Software
1. UNITS
a) Units of volume or size: nml/L = nanomoles per liter were inserted into the stoplist files. 141 x 170 x 208 mm was changed to 141 “by” 170 “by” 208 mm. Abbreviations of measure such as cm or mm for millimetres were inserted into the stoplist file as were other common abbreviations used in clinical medicine to describe laboratory parameters such as ng/ml or Kg/M 2 or m/z. b) Magnitude: such as 10 6 /ml was changed to “million per millilitre” as in the sentence “ ( …) the titre was 0.4x10 6 / ml” c) Slash: / was transcribed as “over” or “per” as in “(…) blood pressure …up to 250 /140 mm Hg”. Similarly, in “(…) upper and lower limb power grades were 4 /5 and 3/5” the slash was transcribed as “over”, common in spoken clinical science.
2. SYMBOLS
a) Mathematical symbols: > was changed to “greater than” or “over” and < “less than” as in the sentence “(…) should be given a therapeutic dose of the drug (5 mg for body weight <50 kg, 7.5 mg for 50 -100 kg and 10 mg for >100 kg) ” b) Hyphens: As required by Nation’s software , hyphens were given spaces before and after the hyphen as in “(…) well - defined, soft - tissue nodules” c) Symbols such as ~ in the phrase “(…) in ~50% of patients” was changed to “approximately” and °C to “degrees centigrade”. d) Acronyms: Commonly used acronyms were spelled out as in “(…) increase in both HR and BP” meaning “heart rate” and “blood pressure ”.
3. OTHER TEXT
a) Listings of pharamaceutical companies, names of authors, procedures, equipment and drugs were enclosed by <> brackets as in the sentence “(…) < Warkentin et al.> (2001) reported the occurrence of
58 Ibérica 25 (2013) : 39-62 LEXICOGRAPHIC STUDIES IN MEDICINE
a. Mathematical symbols: > was changed to “greater than” or “over” and < “less than” as in the sentence “(…) should be given a therapeutic dose of the drug (5 mg for body weight <50 kg, 7.5 mg for 50 -100 kg and 10 mg for >100 kg )” b. Hyphens: As required by Nation’s software , hyphens were given spaces before and after the hyphen as in “(…) well - defined, soft - tissue nodules ” c. Symbols such as ~ in the phrase “(…) in ~50% of patients ” was changed to “approximately” and °C to “degrees centigrade”. d. Acronyms: Commonly used acronyms were spelled out as in “(…) increase in both HR and BP ” meaning “ heart rate” and “ blood pressure ”. 3. OTHER TEXT a. Listings of pharamaceutical companies, names of authors, proced ures, equipment and drugs were enclosed by <> brackets as in the sentence “(…)
Appendix 2: MAWLcc MAWLcc - system by freq FREQ LE1X8 I COGRAPHIC SsTyUstDemIEiSc I N M E D1I7C5 I NE 1 patient 1155 nerve neurologic diagan. ose M a t h e matical symbols: > was changed to “greater than” or “over” and < “less than” as 2 687 19 neurology 160 in the sentence “(…) should be given a therapeutic dose of the drug (5 mg for body symptom radiograph weight <50 kg, 7.5 mg for 50 -100 kg and 10 mg for >100 kg r)a” d iographic 3 b. Hyphens: As req6u2i1re d by Nation’s software , hyphens werrea dgiiovgerna pshpsa c e s b e fore and clinic a f ter the hyphen as in “(…) well - defined, soft2 -0 t issue nodulersa”d iological 158 4 c. Symbols such as5 2~0 in the phrase “(…) in ~50I%nf laomf e p atients ” was changed to infect 21 inflammatory 152 “approximately” and °C to “degrees centigrade”. pelvis d. Acronyms: Commonly used acronyms were s2p2e lled out as in “(…) p ienlcvrice ase in b1o5th1 HR and BP ” meaning “ heart rate” and “ blood pressure ”. 5 431 23 tumors 149 3. OTaHrEteRry T E X T recurrent LExICOGRAPHIC STuDIES IN MEDICINE a. arteLriistits in gs of pharamaceutical companies, name2s4 of authors, prroecceudrruernecse, e q u i p m 1e4n8t and 6 artedrireus g s were enclos4e2d2 by <> brackets as in the sentenccyes t “ ( … ) < W arkentin et al.> (2001) 7 surgery r e p o r ted the occu2rr7e1n ce of
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35 resonance 116 autoimmune 3 5 thrombus 72 resection 73 36 116 73 infant 71 37 posterior 114 nephritis 74 marrow 71 38 107 P. MUNGRA & T. CANZIANI 75 specimen 71 39 hip 106 76 tendon 71 40 distal 105 77 chemotherapy 70 35 35 41 resotonmanocgera p h y 116 1 04 78 transplantation 69 thrombus 72 resection 73 36 42 ultrastohuronmd b o s i s 116 1 03 79 fatal 68 73 infant 71 37 43 posbteorwioer l 114 1 02 80 anomaly 67 44 nephhermitisa t o m a 102 74 81 marbrloawdd e r 71 67 38 45 elevnaetep h r o g e n ic 107 1 00 75 spetchiemraepn y 71 82 therapeutic 67 39 46 hip i n t u b a t e 106 99 76 tendon 71 40 distal 105 77 83 cheamirowtahye r a p y 70 66 47 obstruct 99 bacteria 41 48 tomlyomgrpahpohmy a 104 98 78 transplantatbioan cteremia 69 42 ultramseoduincad t i o n 103 79 84 fatal bacterial 68 66 49 98 43 bowel 102 80 85 anoamnaeluy r y s m 67 65 50 medial 97 44 hematoma 102 81 86 bladbdeenrig n 67 65 45 51 elevmautes c le 100 94 87 thercaeprey bral 65 postoperative 82 67 46 52 intubate 99 90 88 disorder 65 83 airway 66 47 53 obsatrnutcetr i o r 99 89 89 bacltuemriae n 65 48 54 lymfpibhroomsias 98 87 90 resistant 65 medication 84 66 55 anaesthesia 86 91 edema 64 49 medications 98 85 aneeupriyssom de 65 56 congenital 85 50 medial 97 86 92 benign e pisode s 6 5 64 57 discharge 85 51 muscle 94 87 93 ceregbersatal t i o n 65 64 58 posetompeerrgaetinvce y 85 compress 88 disorder 65 52 59 epxocsistioopn e r a t i v e ly 90 84 94 compression 63 89 lumen 65 53 60 antearbiodro m e n 89 83 95 antibiotics 62 54 fibromsyiso c a r d i a l 87 90 96 resiasutatonpt s y 65 62 55 61 anaesthesia 86 82 91 97 edefmorae n s ic 64 62 discontinue episode 56 62 congenital 85 80 92 98 malignaenpt i s o d e 64 62 histologic pathology 57 discharge 85 93 gestation 64 63 80 pathological 62 58 emergency 85 99 compress p athogenesis 30 64 millimeters 79 59 excision 84 94 63 metastasis 100 abscess 61 95 antibiotics 62 60 65 abdom en 83 78 101 differential 61 myocardial 96 autopsy 62 66 carc inoma 77 102 hyperplasia 61 61 myocarditis 82 97 forensic 62 67 disccoonrotinaure y 77 thorax 98 103 malignant t h o racic 6 2 61 62 68 cduifsf c o n t i n u a tion 80 76 histologic 104 pathdolsoe g y 60 P. MuNGRA & T. CANzIANI 69 infusion 76 62 63 histological 80 105 dialysis 59 stab 99 30 LEXICOGRAPHIC STUDIES IN MEDICINE 64 70 millimeters 79 75 106 abuse 58 metastasis 100 abscess 61 71 immune 73 65 metastatic 78 101 107 diffecreernvitxia l 61 58 cervical typical 66 carc inoma 77 102 hyperplasia 61 coagulate 144 45 thorax 67 coronary 77 108 coagulation 58 145 drainage 45 Ibérica 25 (2013 ): … -… 103 61 68 cuff 76 109 drug 58 146 follow -up 45 104 dose 60 69 infusion 76 110 temporal 58 147 hepatic 45 stab 105 dialysis 59 P. MUNGRA & T. CANZIANI 111 administer 57 refer 70 stabbing 75 106 abuse 58 invade 148 45 71 immune 73 107 112 cervix invasive 5 8 57 149 tachycardia 45 autoimmune 3 5 35 resonance 116 113 necrosis 57 clear thrombus 72 resection 73 place 36 116 114 placement 57 150 45 73 Ibérinicfan 2t 5 ( 2 0 1 3 ): … -… 71 37 posterior 114 115 spine 57 151 uterine 45 nephritis 74 marrow 71 116 maternal 55 152 anticoagulation 44 38 107 75 specimen 71 prog ress suggest 39 hip 106 76 tendon 71 117 progression 55 153 44 40 distal 105 77 chemotherapy 70 118 prolong 55 154 suicide 44 41 tomography 104 78 transplantation 69 119 diabetes 54 155 suture 44 42 ultrasound 103 79 fatal 68 120 dissect 54 156 septic 43 43 bowel 102 80 anomaly 67 121 focal 54 157 debridement 42 44 hematoma 102 81 bladder 67 manifest 158 ectopic 42 122 manifestation 54 45 elevate 100 therapy 159 anal 41 82 therapeutic 67 123 shotgun 54 160 cesarean 41 46 intubate 99 function 83 airway 66 161 platelet 41 47 obstruct 99 bacteria 124 dysfunction 53 48 lymphoma 98 bacteremia 125 prognosis 53 162 puncture 41 medication 84 bacterial 66 126 regimen 53 163 ulcer 41 49 98 85 aneurysm 65 127 rupture 53 164 uneventful 41 50 medial 97 86 benign 65 vomit 165 ventilation 41 51 muscle 94 128 vomiting 53 87 cerebral 65 166 vertebral 41 postoperative 129 aortic 52 52 90 88 disorder 65 167 analgesia 40 130 lumbar 52 53 anterior 89 89 lumen 65 168 duct 40 131 headache 51 54 fibrosis 87 90 resistant 65 169 lymph 40 132 hernia 51 55 anaesthesia 86 91 edema 64 170 autonomic 39 episode remark 171 nasal 39 56 congenital 85 92 episode s 64 133 unremarkable 50 172 rotator 39 57 discharge 85 93 gestation 64 134 cav ity 49 58 emergency 85 compress 135 rectal 49 173 worsen 39 coalesce 59 excision 84 94 compression 63 136 transverse 48 174 38 95 antibiotics 62 60 abdom en 83 137 vaginal 48 fix myocardial 96 autopsy 62 concentrate 175 38 61 82 138 concentrations 47 97 forensic 62 176 granuloma 38 discontinue 139 angiography 46 62 80 98 malignant 62 177 ischem ic 38 pathology 140 nausea 46 histologic 178 prescribed 38 63 80 pathological 62 141 nodules 46 99 pathogenesis 30 LEXICOGRAPHIC STUDIES IN MEDICINE 179 radiation 38 64 millimeters 79 142 transfusion 46 metastasis 100 abscess 61 180 susceptibility 38 143 alarm 45 65 78 101 differential 61 typical 66 carc inoma 77 102 hyperplasia 61 coagulate 144 atypical 45 thorax 67 coronary 77 108 58 145 drainage 45 103 thoracic 61 Ibérica 25 (2013 ): … -… 68 cuff 76 109 drug 58 146 follow -up 45 104 dose 60 69 infusion 76 110 temporal 58 147 hepatic 45 stab 105 dialysis 59 111 administer 57 refer 70 75 106 abuse 58 invade 148 reference 45 71 immune 73 107 1 12 cervix 58 57 149 tachycardia 45 113 necrosis 57 clear clearance 60 Ibérica 25 (2013) : 39-62 place 150 unclear 45 Ibérica 25 (2013 ): … -… 114 57 115 spine 57 151 uterine 45 116 maternal 55 152 anticoagulation 44 prog ress suggest 117 55 153 suggestive 44 118 prolong 55 154 suicide 44 119 diabetes 54 155 suture 44 120 dissect 54 156 septic 43 121 focal 54 157 debridement 42 manifest 158 ectopic 42 122 54 159 anal 41 123 shotgun 54 160 cesarean 41 function 124 53 161 platelet 41 125 prognosis 53 162 puncture 41 126 regimen 53 163 ulcer 41 127 rupture 53 164 uneventful 41 vomit 165 ventilation 41 128 53 166 vertebral 41 129 aortic 52 167 analgesia 40 130 lumbar 52 168 duct 40 131 headache 51 169 lymph 40 132 hernia 51 170 autonomic 39 remark 133 50 171 nasal 39 134 cav ity 49 172 rotator 39 135 rectal 49 173 worsen 39 coalesce 136 transverse 48 174 coalition 38 137 vaginal 48 fix concentrate 175 fixation 38 138 47 176 granuloma 38 139 angiography 46 177 ischem ic 38 140 nausea 46 178 prescribed 38 141 nodules 46 179 radiation 38 142 transfusion 46 180 susceptibility 38 143 alarm 45
Ibérica 25 (2013 ): … -… P. MUNGRA & T. CANZIANI
base 213 conservative 33 181 basal 37 214 cranial 33 182 defect 37 series 183 fragment 37 215 33 184 occlude 37 216 viral 33 sense biopsy LEXICOGRAPHIC STUDIES IN MEDICINE 185 sensory 37 217 32 186 vitamin 37 218 breast 32 187 arthritis 36 219 disc 32 typical embolus hospital 144 atypical 45 coagulate 188 embolization 36 220 32 108 58 145 drainage 45 189 intact 36 local 109 drug 58 146 follow -up 45 221 32 190 massive 36 110 temporal 58 147 hepatic 45 LExICOGRAPHIC STuDIES2 I2N2 MEDnICoIdNeE s 32 191 pulse 36 111 administer 57 refer 223 atrial 31 148 reference 45 192 stenosis 36 invade 224 basement 31 112 57 149 tachycardia 45 193 tissue 36 catheter 113 necrosis 57 clear 194 axial 35 225 31 clearance place 195 genetic 35 226 deposition 31 114 57 150 unclear 45 196 infarction 35 227 generic 31 115 spine 57 151 uterine 45 197 osseous 35 228 hysterectomy 31 116 maternal 55 152 anticoagulation 44 prog ress suggest 198 pneumonia 35 229 intrav ascular 31 153 suggestive 44 laparoscopy 117 55 199 ankle 34 230 31 154 suicide 44 118 prolong 55 200 cast 34 231 organism 31 155 suture 44 119 diabetes 54 201 etiology 34 232 pediatric 31 120 dissect 54 156 septic 43 femur 202 femoral 34 233 rash 31 121 focal 54 157 debridement 42 manifest 158 ectopic 42 203 fibrous 34 234 saturation 31 122 54 159 anal 41 204 gastrointestinal 34 235 superficial 31 236 valve 31 123 shotgun 54 160 cesarean 41 205 giant 34 function anatomy 206 neonatal 34 124 53 161 platelet 41 237 30 207 phantom 34 125 prognosis 53 162 puncture 41 bone remiss 238 30 126 regimen 53 163 ulcer 41 208 remission 34 239 dysplasia 30 127 rupture 53 164 uneventful 41 209 technician 34 240 ingestion 30 vomit 165 ventilation 41 210 tubular 34 128 53 P. MUNGRA & T. CANZIANI 241 ureter 30 166 vertebral 41 211 tubules 34 129 aortic 52 242 167 analgesia 40 212 bypass 33 130 lumbar 52 168 duct b a s e 40 131 headache 51 213 conservative 33 169 181 lymph 40 37 132 hernia 51 214 cranial 33 170 182 autodneofmecict 39 37 remark series 133 50 171 183 nasafrl a g m e n t 39 37 215 serial 33 134 cav ity 49 172 184 rotatoocr c l u d e 39 37 216 viral 33 sense biopsy 135 rectal 49 173 185 worsen 39 37 217 biopsies 32 coalesce 136 transverse 48 174 186 vitamin c o a l i t io n 38 37 218 breast 32 137 vaginal 48 187 fix arthritis 36 219 disc 32 concentrate 175 embolus f ixation 38 hospital 138 47 176 188 granuloma 38 36 220 Ibérica 2h5 o (s2p0it1a3li)z:a … tio-…n 32 139 angiography 46 189 intact 36 local 177 ischem ic 38 221 localized 32 140 nausea 46 190 massive 36 178 prescribed 38 222 nodes 32 141 nodules 46 P. MU1N9G1 RA &p uTls. eC A N Z I A N I 36 179 radiation 38 223 atrial 31 142 transfusion 46 192 stenosis 36 180 susceptibility 38 224 basement 31 143 alarm 45 193 tissue 36 base 213 consceartvhaettiever 33 181 194 axial b a s al 37 35 225 catheterization 31 214 cranial 33 182 195 defegcet n e t i c 37 35 226 serieds e position 31 Ibérica 25 (2013 ): … -… 183 196 fragminefanrtc t io n 37 35 215 227 generic 33 31 184 197 occluodsse e o u s 37 35 216 228 viral h y s t e r e c tomy 33 31 sense biopsy 229 intrav ascular 31 185 198 pneumosneina s o r y 37 35 217 32 laparoscopy 199 ankle 34 186 vitamin 37 218 230 breast la p a roscopic 3 2 31 200 cast 34 187 arthritis 36 219 231 disc o r g a n i s m 32 31 201 embeotliuoslo gy 34 hospital 232 pediatric 31 188 femeumr b olization 36 220 32 233 rash 31 189 202 intact 36 34 local 221 234 saturation 32 31 190 203 masfsibivreo u s 36 34 222 235 nodessu p e r f i c i a l 32 31 191 204 pulsge a s t r o i n t e stinal 36 34 223 236 atriavl a l v e 31 31 192 205 stengoisains t 36 34 anatomy 206 neonatal 34 224 basement 31 193 tissue 36 237 catheter anatomic 30 194 207 axiapl h a n t o m 35 34 225 bone 31 remiss 238 bony 30 Ibérica 25 (2013) : 39-62 61 195 208 genetic 35 34 226 deposition 31 239 dysplasia 30 196 209 infartcetciohn n i c i a n 35 34 227 generic 31 240 ingestion 30 197 210 ossetuobuus la r 35 34 228 hysterectomy 31 241 ureter 30 198 211 pneutumbounleias 35 34 229 intrav ascular 31 242 lapa roscopy 199 ankle 34 212 bypass 33 230 31 200 cast 34 231 organism 31 201 etiology 34 232 pediatric 31 femur 20 2 femoral 34 233 rash 31 203 fibrous 34 234 saturation 31 20 4 gastrointestinal 34 235 superficial 31 205 giant 34 236 valve 31 anatomy 206 neonatal 34 237 30 207 phantom 34 bone remiss 238 30 208 Ibérica 25re (m20is1s3io):n … -… 34 239 dysplasia 30 209 technician 34 240 ingestion 30 210 tubular 34 241 ureter 30 211 tubules 34 242 212 bypass 33
Ibérica 25 (2013 ): … -… P. MUNGRA & T. CANZIANI
base 213 conservative 33 181 37 214 cranial 33 182 defect 37 series 183 fragment 37 215 serial 33 184 occlude 37 216 viral 33 sense biopsy 185 37 217 biopsies 32 186 vitamin 37 218 breast 32 187 arthritis 36 219 disc 32 embolus hospital 188 36 220 hospitalization 32 189 intact 36 local 221 localized 32 190 massive 36 222 nodes 32 191 pulse 36 223 atrial 31 192 stenosis 36 224 basement 31 193 tissue 36 catheter 194 axial 35 225 catheterization 31 195 genetic 35 226 deposition 31 196 infarction 35 227 generic 31 197 osseous 35 228 hysterectomy 31 198 pneumonia 35 229 intrav ascular 31 laparoscopy 199 ankle 34 230 laparoscopic 31 200 cast 34 231 organism 31 201 etiology 34 232 pediatric 31 femur 202 34 233 rash 31 203 fibrous 34 P. MuNGRA & T. CANzIA2N3I 4 saturation 31 204 gastrointestinal 34 235 superficial 31 205 giant 34 236 valve 31 anatomy 206 neonatal 34 237 anatomic 30 207 phantom 34 bone remiss 238 bony 30 208 34 239 dysplasia 30 209 technician 34 240 ingestion 30 210 tubular 34 241 ureter 30 211 tubules 34 242 212 bypass 33
Ibérica 25 (2013 ): … -…
62 Ibérica 25 (2013) : 39-62