楼主: Imasasor
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如何利用input, infile导入medline文章数据 [推广有奖]

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楼主
Imasasor 发表于 2013-8-1 21:37:51 |AI写论文
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medline.txt (116.96 KB)

附件为我在pubmed下载的medline结果，为37篇英文文章（我们这里称作记录），文件中以"PMID-"隔开的为一个记录
我要生成一个SAS数据集，每个记录(即文章)为一个观测，其中的变量需要包含以下几个：PMID；TI；AB；MH。其它的可有可无。
这四个东西分别代表我文章的id, title, abstract 和 mesh terms，其中变量的值是短杠“-”后面的文字，当然，有些文字可能跨行。

另外，MH可能有多个，我需要将所有的MH合并成一个变量

如何有效地利用infile, input进行导入，望高手指点

非常感谢，些许论坛币，聊表寸心
  1. PMID- 23495623
  2. OWN - NLM
  3. STAT- MEDLINE
  4. DA  - 20130318
  5. DCOM- 20130411
  6. IS  - 1049-510X (Print)
  7. IS  - 1049-510X (Linking)
  8. VI  - 23
  9. IP  - 1
  10. DP  - 2013 Winter
  11. TI  - Depression and type 2 diabetes among Alaska Native primary care patients.
  12. PG  - 56-64
  13. AB  - OBJECTIVES: To assess whether type 2 diabetes mellitus (DM2) and DM2
  14.       complications are associated with presence and severity of depression among
  15.       Alaska Native and American Indian people (AN/Als). DESIGN: Retrospective,
  16.       cross-sectional analysis of medical records. SETTING: Southcentral Foundation
  17.       Primary Care Center (SCF-PCC) in Anchorage, Alaska. PARTICIPANTS: Total of 23,529
  18.       AN/AI adults. PRIMARY OUTCOME MEASURES: Patient Health Questionnaire (PHQ) scores
  19.       (0-9 negative, 10-14 mild, 15-19 moderate, 20+ severe) and DSM-IV depression
  20.       diagnosis. RESULTS: DM2 prevalence was 6% (n=1,526). Of those with DM2, 19% (n =
  21.       292) had one or more DM2 complications and average HbAlc was 7.1%. Prevalence of
  22.       depression diagnosis was similar between AN/Als with and without DM2 (P = .124).
  23.       Among those screened for depression (n = 12,280), there were similar rates of PHQ
  24.       severity between those without and with DM2; respectively 4% (n = 452) vs 4% (n =
  25.       42) mild, 4% (n = 404) vs 3% (n = 29) moderate, and 4% (n = 354) vs 4% (n = 38)
  26.       severe. In multivariable logistic regression, DM2 was not associated with PHQ
  27.       severity (OR 1.02, 95% CI 0.81-1.27) or depression diagnosis (OR 1.27, 95% CI
  28.       1.00-1.62). Increased odds of depression and higher depression severity were
  29.       associated with female sex, younger age, being unmarried, substance
  30.       abuse/dependence, and increased ambulatory visits. Depression was associated with
  31.       number of other chronic conditions among AN/Als with DM2 but not with number of
  32.       complications. CONCLUSIONS: Presence and severity of depression among AN/Al
  33.       primary care patients was not significantly associated with DM2 nor DM2
  34.       complications, despite a slightly higher rate of depression diagnosis among those
  35.       with DM2.
  36. AD  - Research Department, Southcentral Foundation, Anchorage, Alaska 99508, USA.
  37.       ddillard@scf.cc
  38. FAU - Dillard, Denise A
  39. AU  - Dillard DA
  40. FAU - Robinson, Renee F
  41. AU  - Robinson RF
  42. FAU - Smith, Julia J
  43. AU  - Smith JJ
  44. FAU - Khan, Burhan A
  45. AU  - Khan BA
  46. FAU - Dubois, Edward W
  47. AU  - Dubois EW
  48. FAU - Mau, Marjorie K
  49. AU  - Mau MK
  50. LA  - eng
  51. GR  - P20 MD000173/MD/NIMHD NIH HHS/United States
  52. PT  - Journal Article
  53. PT  - Research Support, N.I.H., Extramural
  54. PL  - United States
  55. TA  - Ethn Dis
  56. JT  - Ethnicity & disease
  57. JID - 9109034
  58. SB  - IM
  59. MH  - Adolescent
  60. MH  - Adult
  61. MH  - Alaska
  62. MH  - Depression/epidemiology/*ethnology
  63. MH  - Diabetes Mellitus, Type 2/*complications/epidemiology/*ethnology
  64. MH  - Female
  65. MH  - Humans
  66. MH  - *Indians, North American
  67. MH  - Logistic Models
  68. MH  - Male
  69. MH  - Middle Aged
  70. MH  - Primary Health Care
  71. MH  - Young Adult
  72. EDAT- 2013/03/19 06:00
  73. MHDA- 2013/04/12 06:00
  74. CRDT- 2013/03/19 06:00
  75. PST - ppublish
  76. SO  - Ethn Dis. 2013 Winter;23(1):56-64.

  78. PMID- 22089223
  79. OWN - NLM
  80. STAT- MEDLINE
  81. DA  - 20111117
  82. DCOM- 20120319
  83. IS  - 1760-4788 (Electronic)
  84. IS  - 1279-7707 (Linking)
  85. VI  - 15
  86. IP  - 9
  87. DP  - 2011 Nov
  88. TI  - Older people with diabetes have higher risk of depression, cognitive and
  89.       functional impairments: implications for diabetes services.
  90. PG  - 751-5
  91. AB  - OBJECTIVES: To examine the relationship between diabetes and impairments in
  92.       functional and cognitive status as well as depression in older people. DESIGN:
  93.       Cross-sectional study. SETTING: Elderly Health Centres (EHC) in Hong Kong.
  94.       PARTICIPANTS: 66,813 older people receiving baseline assessment at EHC in 1998 to
  95.       2001. MEASUREMENTS: Diabetes status was defined by self-report and blood glucose
  96.       tests. Functional status was assessed by 5 items of instrumental activities of
  97.       daily living (IADL) and 7 items of activities of daily living (ADL). Cognitive
  98.       status was screened by the Abbreviated Mental Test-Hong Kong version (AMT).
  99.       Depressive symptoms were screened by the Geriatric Depression Scale-Chinese
  100.       version (GDS). RESULTS: Among the subjects, 10.4% reported having regular
  101.       treatment for diabetes, 3.4% had diabetes but were not receiving regular
  102.       treatment, and 86.2% did not have diabetes. After controlling for age, sex and
  103.       education level, those having regular treatment for diabetes were 1.7 times more
  104.       likely (OR=1.65, 95% CI: 1.51-1.80) to have functional impairment, 1.3 times more
  105.       likely (OR=1.28, 95% CI: 1.11-1.48) to have cognitive impairment and 1.3 times
  106.       more likely (OR=1.35, 95% CI: 1.25-1.46) to have depression, than older people
  107.       without diabetes. CONCLUSION: Older people with diabetes may be less capable of
  108.       managing the disease than the younger ones as a result of increased risk of both
  109.       physical and cognitive impairment. This study provided further evidence for the
  110.       need of an international consensus statement regarding care of diabetes in older
  111.       people.
  112. AD  - Faculty of Social Sciences, The University of Hong Kong, Hong Kong.
  113.       phchau@graduate.hku.hk
  114. FAU - Chau, P H
  115. AU  - Chau PH
  116. FAU - Woo, J
  117. AU  - Woo J
  118. FAU - Lee, C H
  119. AU  - Lee CH
  120. FAU - Cheung, W L
  121. AU  - Cheung WL
  122. FAU - Chen, J
  123. AU  - Chen J
  124. FAU - Chan, W M
  125. AU  - Chan WM
  126. FAU - Hui, L
  127. AU  - Hui L
  128. FAU - McGhee, S M
  129. AU  - McGhee SM
  130. LA  - eng
  131. PT  - Journal Article
  132. PT  - Research Support, Non-U.S. Gov't
  133. PL  - France
  134. TA  - J Nutr Health Aging
  135. JT  - The journal of nutrition, health & aging
  136. JID - 100893366
  137. SB  - IM
  138. MH  - Activities of Daily Living/psychology
  139. MH  - Aged
  140. MH  - Aged, 80 and over
  141. MH  - Cognition Disorders/*epidemiology/psychology
  142. MH  - Cross-Sectional Studies
  143. MH  - Depression/*epidemiology/psychology
  144. MH  - Diabetes Mellitus/*epidemiology/psychology
  145. MH  - Educational Status
  146. MH  - Female
  147. MH  - Geriatric Assessment/*statistics & numerical data
  148. MH  - Hong Kong/epidemiology
  149. MH  - Humans
  150. MH  - Logistic Models
  151. MH  - Male
  152. MH  - Prevalence
  153. MH  - Risk Factors
  154. EDAT- 2011/11/18 06:00
  155. MHDA- 2012/03/20 06:00
  156. CRDT- 2011/11/18 06:00
  157. PST - ppublish
  158. SO  - J Nutr Health Aging. 2011 Nov;15(9):751-5.

  160. PMID- 21357362
  161. OWN - NLM
  162. STAT- MEDLINE
  163. DA  - 20110301
  164. DCOM- 20110608
  165. LR  - 20130630
  166. IS  - 1935-5548 (Electronic)
  167. IS  - 0149-5992 (Linking)
  168. VI  - 34
  169. IP  - 3
  170. DP  - 2011 Mar
  171. TI  - Prevalence of depression in individuals with impaired glucose metabolism or
  172.       undiagnosed diabetes: a systematic review and meta-analysis of the European
  173.       Depression in Diabetes (EDID) Research Consortium.
  174. PG  - 752-62
  175. LID - 10.2337/dc10-1414 [doi]
  176. AB  - OBJECTIVE: Meta-analyses have shown that the risk for depression is elevated in
  177.       type 2 diabetes. Whether this risk in individuals with impaired glucose
  178.       metabolism (IGM) or undiagnosed diabetes (UDD) is elevated relative to normal
  179.       glucose metabolism (NGM) or decreased relative to previously diagnosed type 2
  180.       diabetes (PDD) has not been the subject of a systematic review/meta-analysis.
  181.       This study examined the prevalence of depression in IGM and UDD subjects relative
  182.       to each other and to NGM and PDD subjects by reviewing the literature and
  183.       conducting a meta-analysis of studies on this topic. RESEARCH DESIGN AND METHODS:
  184.       EMBASE and MEDLINE databases were searched for articles published up to May 2010.
  185.       All studies that compared the prevalence of depression in subjects with IGM and
  186.       UDD were included. Odds ratios (ORs) were calculated using fixed and
  187.       random-effects models. RESULTS: The meta-analysis showed that the risk for
  188.       depression was not increased in IGM versus NGM subjects (OR 0.96, 95% CI
  189.       0.85-1.08). Risk for depression did not differ between individuals with UDD and
  190.       individuals with either NGM (OR 0.94, 95% CI 0.71-1.25) or IGM (OR 1.16, 95% CI
  191.       0.88-1.54). Finally, individuals with IGM or UDD both had a significantly lower
  192.       risk of depression than individuals with PDD (OR 0.59, 95% CI 0.48-0.73, and OR
  193.       0.57, 95% CI 0.45-0.74, respectively). CONCLUSIONS: Results of this meta-analysis
  194.       show that the risk of depression is similar for NGM, IGM, and UDD subjects. PDD
  195.       subjects have an increased risk of depression relative to IGM and UDD subjects.
  196. AD  - School of Psychology, University of Birmingham, Birmingham, UK. f.pouwer@uvt.nl
  197. FAU - Nouwen, Arie
  198. AU  - Nouwen A
  199. FAU - Nefs, Giesje
  200. AU  - Nefs G
  201. FAU - Caramlau, Isabela
  202. AU  - Caramlau I
  203. FAU - Connock, Martin
  204. AU  - Connock M
  205. FAU - Winkley, Kirsty
  206. AU  - Winkley K
  207. FAU - Lloyd, Cathy E
  208. AU  - Lloyd CE
  209. FAU - Peyrot, Mark
  210. AU  - Peyrot M
  211. FAU - Pouwer, Francois
  212. AU  - Pouwer F
  213. CN  - European Depression in Diabetes Research Consortium
  214. LA  - eng
  215. PT  - Journal Article
  216. PT  - Meta-Analysis
  217. PT  - Review
  218. PL  - United States
  219. TA  - Diabetes Care
  220. JT  - Diabetes care
  221. JID - 7805975
  222. RN  - 50-99-7 (Glucose)
  223. SB  - IM
  224. MH  - Depression/*epidemiology
  225. MH  - Diabetes Mellitus/*diagnosis/*psychology
  226. MH  - Glucose/metabolism
  227. MH  - Glucose Intolerance/*psychology
  228. MH  - Humans
  229. PMC - PMC3041222
  230. OID - NLM: PMC3041222
  231. EDAT- 2011/03/02 06:00
  232. MHDA- 2011/06/09 06:00
  233. CRDT- 2011/03/02 06:00
  234. AID - 34/3/752 [pii]
  235. AID - 10.2337/dc10-1414 [doi]
  236. PST - ppublish
  237. SO  - Diabetes Care. 2011 Mar;34(3):752-62. doi: 10.2337/dc10-1414.
复制代码



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hopewell 查看完整内容

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关键词：Medline infile Input line file 文章 如何

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沙发
hopewell 发表于 2013-8-1 21:37:52
  1. data Ben(drop=key);
  2.     length KEY $5 ID 8 PMID $20 TI $200 AB $3000 MH $500;
  3.     retain key pmid ti ab mh;
  4.     infile "c:\medline.txt" pad end=last;
  5.     input @;
  6.     key=coalescec(substr(_infile_,1,5),key);
  7.     _infile_=substr(_infile_,7);
  8.     select(key);
  9.         when('PMID-') do;
  10.             if id ge 1 then do;
  11.                 output;
  12.                 call missing(pmid,ti,ab,mh);
  13.             end;
  14.             id+1; pmid=_infile_;
  15.         end;
  16.         when('TI  -') ti=_infile_;
  17.         when('AB  -') ab=catx(' ',ab,_infile_);
  18.         when('MH  -') mh=catx('||',mh,_infile_);
  19.         otherwise;
  20.     end;
  21.     if last then output;
  22. run;
复制代码
已有 3 人评分经验 论坛币 学术水平 热心指数 信用等级 收起 理由
Tigflanker + 5 + 3 + 3 + 3 总有看不明白的地方..
stata18 + 1 + 1 + 1 高手，基本功非常扎实。
webgu + 100 + 100 + 5 + 5 + 5 精彩帖子

总评分: 经验 + 100  论坛币 + 105  学术水平 + 9  热心指数 + 9  信用等级 + 9   查看全部评分

观钓颇逾垂钓趣 种花何问看花谁

藤椅
Imasasor 发表于 2013-8-1 22:13:18
楼主明显过虑了，没那么复杂
  1. data a;
  2. infile "E:medline.txt" pad truncover lrecl=400;
  3. input name $1-4 gang $5 content $ 7-400;
  4. run;

  6. data b;
  7. set a;
  8. if name="" and gang="" and content="" then delete;
  9. run;

  11. data c;
  12. set b;
  13. retain name1;
  14. if name^="" then name1=name;
  15. else name=name1;
  16. run;

  18. data d;
  19. set c(drop=name1);
  20. where name in ("PMID","TI","AB","MH");
  21. run;

  23. data e(drop=gang content);
  24. set d;
  25. informat text $3000.;
  26. format text $1000.;
  27. retain text;
  28. if first.name then text=content;
  29. else text=catx("||",text,content);
  30. by name notsorted;
  31. if last.name then output;
  32. run;

  34. data f;
  35. set e;
  36. retain num 0;
  37. if name="PMID" then num+1;
  38. run;

  40. proc transpose data=f out=g;
  41. var text;
  42. id name;
  43. by num;
  44. run;

  46. data h;
  47. set g;
  48. ab=tranwrd(ab,"||"," ");
  49. drop _name_;
  50. run;

  52. proc export data=h outfile="E:\medline.xls" replace;
  53. run;
复制代码
已有 1 人评分经验 论坛币 学术水平 热心指数 信用等级 收起 理由
webgu + 60 + 60 + 3 + 3 + 3 自力更生型的。

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板凳
你的太阳 发表于 2013-8-1 23:05:46
可以考虑下用这个，程序中有些变量的长度可能需要调整，但你说的功能基本能够实现

filename medline "C:\medline.txt";
/*read the file*/
data a;
infile medline truncover;
informat raw $200.;
input raw;
raw = _infile_;
N = _n_;
run;
data b;
set a;
/*processing for PMID*/
informat pmid $30.;
retain PMID ;
if index(upcase(raw),'PMID-') then PMID = scan(raw,2,'-');
/*processing for description, may need to update the length of desc*/
informat desc $5000.;
retain desc " " flag1 0;
if index(upcase(raw),'AB  -') then do;
  desc = substr(raw,7);
  flag1 = 1;
end;
if index(upcase(raw),'AD  -') then flag1=0;
if desc ne " " and substr(raw,1,6)='      ' and flag1=1 then  desc = strip(desc)||' '||strip(raw);
/*processing for TI*/
informat ti $500.;
retain ti " " flag2 0;
if index(upcase(raw),'TI  -') then do;
  TI = substr(raw,7);
  flag2 = 1;
end;
if index(upcase(raw),'AB  -') then flag2 = 0;
if ti ne " " and substr(raw,1,6)='      ' and flag2=1 then  ti = strip(ti)||' '||strip(raw);
/*processing for MH*/
/* the split character is |, you can change the one that you want*/
informat mh $500.;
retain mh " " flag3 0;
if index(upcase(raw),'SB  -') then do;
  mh = "Flag";
  flag3 = 1;
end;
if index(upcase(raw),'EDAT-') then flag3 = 0;
if mh ne " " and flag3=1 and index(raw,'MH  -') then mh = strip(mh)||'|'||strip(substr(raw,7));

run;
proc sort data = b(where=(pmid ne ' '));
by pmid n;
run;
data c;
set b;
by pmid n;
if last.pmid;
mh = substr(mh,6);
keep pmid desc mh ti;
run;

已有 1 人评分经验 论坛币 学术水平 热心指数 信用等级 收起 理由
webgu + 80 + 80 + 3 + 3 + 3 观点有启发

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报纸
webgu 发表于 2013-8-2 21:28:44
呵呵，想起3年前，2010年左右写的一个89行的代码专门处理这个问题，现在一看，真是弱暴了啊。
SAS资源
1. SAS 微信：StatsThinking
2. SAS QQ群：348941365

地板
henryyhl 发表于 2013-8-2 21:37:13
学习了。收藏下。以备不时之需，谢谢各位
It's not going to be easy, but it is going to be worth it.

7楼
Imasasor 发表于 2013-8-3 11:12:41
webgu 发表于 2013-8-2 21:28
呵呵，想起3年前，2010年左右写的一个89行的代码专门处理这个问题，现在一看，真是弱暴了啊。
版主大人也搞过这个东西？
欢迎加入亚太地区第一R&Python数据挖掘群: 251548215；

8楼
jolterheadmmtt 发表于 2013-8-4 14:09:29
真是学到不少
9楼
jolterheadmmtt 发表于 2013-8-4 14:11:04
！！！收藏
10楼
liu5355776 发表于 2014-3-1 09:29:27
good
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