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Gastroenteritis ICD-的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列問答集和懶人包總整理
國立中興大學 食品安全研究所 呂瑾立所指導 林育萱的 臺灣非傷寒沙門氏菌與彎曲桿菌感染症之描述性流行病學及預後因子之探討：2002-2017年 （2020），提出Gastroenteritis ICD-關鍵因素是什麼，來自於非傷寒沙門氏菌、彎曲桿菌、食源性疾病、反應性關節炎、30天死亡、全民健康保險資料庫。
而第二篇論文中原大學 環境工程學系 王玉純所指導 王楷瑞的 臺灣極端氣象事件對兒童特定腹瀉病的影響 （2020），提出因為有 極端溫度、極端天氣事件、感染性腹瀉、標準化降水蒸發指數、門診量的重點而找出了 Gastroenteritis ICD-的解答。
臺灣非傷寒沙門氏菌與彎曲桿菌感染症之描述性流行病學及預後因子之探討：2002-2017年
為了解決Gastroenteritis ICD- 的問題，作者林育萱 這樣論述：
非傷寒沙門氏菌（Non-typhoidal Salmonella, NTS）與彎曲桿菌（Campylobacter）是全球重要之食源性病原體，每年共造成7,800萬與9,500萬個腹瀉病例，病癥嚴重會引起腸道外感染、慢性後遺症甚至死亡。因此，本研究目的為描述我國NTS與彎曲桿菌感染症發生率之人、時、地分布，分析不同年代、性別、年齡、縣市、地理區域以及都市化程度對發生率的影響；並進一步探討中老年NTS感染症住院患者之反應性關節炎（reactive arthritis, ReA）發生率、30天死亡率及其危險因子。 本研究兩部分資料來源皆使用我國2002-2017年全民健康保險資料庫
。第一部分為斷代研究（cross-sectional study），以國際疾病分類診斷碼擷取門急診及住院檔NTS與彎曲桿菌感染個案，採納每人每年首筆就醫紀錄，將新發生病例數除以各年度年底人口數計算每十萬人年（105PYs）發生率；並利用2000年世界標準人口進行年代別發生率之標準化；以多變項Poisson迴歸模型分析各變項對發生率之獨立效應。第二部分為前瞻性世代研究（prospective cohort study），挑選2005-2016年首次因NTS感染症住院的中老年病患，排除入院前一年已診斷有ReA的患者，分別追蹤入院後一年內ReA發生情況與入院後30天內存活狀態；以Fine and G
ray競爭風險迴歸模型與Cox比例風險迴歸模型分別估計各項社會人口學因素、臨床特性和過去疾病史與ReA發生風險及30死亡風險之相關性。 第一部分結果顯示，2002-2017年平均NTS感染症發生率為108.7人次/105PYs；2004-2017年平均彎曲桿菌感染症發生率是1.4人次/105PYs。女性NTS感染症發生率比男性高（112.0 vs 105.5/105PYs），且以彰化縣（214.2/105PYs）最為嚴重；男性彎曲桿菌感染症發生率高於女性（1.6 vs 1.2/105PYs），並以新竹市（5.3/105PYs）發生率居各縣市之首。兩種感染症皆以0-4歲為最高風險族
群，且皆與都市化程度呈正相關（p for trend＜0.0001）；但在時間趨勢上，NTS標準化發生率隨年代遞減（235.7至84.4/105PYs，降幅達64.2%），而彎曲桿菌標準化發生率卻在攀升（1.1至2.9/105PYs，升幅達163.6%）。第二部分結果指出，45歲以上NTS感染症住院患者ReA發生率為3.8%，30天死亡率為7.4%。其中，風濕性疾病（adjusted sub-distribution hazard ratio [aSHR]=1.5）、消化性潰瘍（aSHR=1.4）以及慢性肺部疾病（aSHR=1.3）會增加ReA發生風險；入住加護病房（aSHR=0.6）、居住在
北部（aSHR=0.6）、個人投保金額較高（aSHR=0.7）以及具有中度或嚴重肝臟疾病（aSHR=0.3）、失智症（aSHR=0.4）和惡性腫瘤（aSHR=0.5）病史則與較低ReA風險有關。增加死亡風險的危險因子有：入院年代較晚（adjusted hazard ratio [aHR]=1.2）、冬春之際住院（aHR=1.2-1.3）、個人投保金額較低（aHR=1.2）、鄉鎮市區綜合所得稅中位數介於第25至第50百分位（aHR=1.3）、年齡大於65歲（aHR=1.6）、NTS胃腸道外感染（aHR=2.0-4.6）、入住加護病房（aHR=3.2），以及患有充血性心臟衰竭（aHR=1.2）、肝
臟疾病（aHR=1.2及1.8）、腫瘤（aHR=1.9及2.0）之疾病史。 儘管我國在過去近二十年間NTS感染發生率有降低之趨勢，但仍高於許多已開發國家；彎曲桿菌在未列入臨床及食品中毒常規檢驗項目之情況下，就醫發生率仍呈上升趨勢。因此，衛生單位應持續加強這兩種食源性疾病的監測與防治，並提升民眾的風險認知，特別是在都市化程度高的地區以及客家與山地原鄉；亦需注意高風險族群之預後狀況，以降低NTS與彎曲桿菌造成的健康危害。
臺灣極端氣象事件對兒童特定腹瀉病的影響
為了解決Gastroenteritis ICD- 的問題，作者王楷瑞 這樣論述：
Table of content摘要 iAbstract iiAcknowledgement ivTable of content vAbbreviation xv1. Introduction 11.1 Background 11.2 Research objectives 42. Literature review 52.1 Overview of diarrhea 52.1.1 Viral infection 62.1.2 Bacterial infection 72.1.3 Childhood diarrhea 122.2 Global burden of
diarrhea 122.3 Diarrhea infection in Taiwan 152.4 Extreme weather events 152.4.1 Extreme temperature 152.4.2 Drought 172.4.3 Extreme precipitation 212.5 Effects of extreme weather events on diarrhea infection 232.5.1 Effects of extreme temperature on diarrhea infection 232.5.2 Effects of dro
ught on diarrhea infection 242.5.3 Effects of excessive rainfall on diarrhea infection 252.5.4 Summary of literature review and questions need to be answered 343. Materials and methods 353.1 Framework of this study 353.2 Study area 363.3 Data sources 373.3.1 Health data 373.3.2 Weather data
383.4 Definition of extreme weather events 403.4.1 Definition of extreme temperature 403.4.2 Definition of drought and excessive rainfall using the Standardized Precipitation Evapotranspiration Index (SPEI) 403.5 Statistical methods 423.5.1 Determination of reference value 423.5.2 Distributed
Lag Non-linear Models (DLNM) 423.5.3 Meta-analysis 434. Results and discussion 444.1 Climatic characteristics and extreme weather events 444.2 Characteristics of diarrhea infection 654.2.1 Outpatient visits by National Health Research Institute 654.2.2 Numbers of diarrhea visit cases by Taiwan
Centers for Disease Control (CDC) 664.3 Model setting 694.4 Area-age-sex-cause specific relative risk associated with extreme temperatures 704.4.1 All infectious diarrhea 704.4.2 Bacterial diarrhea 784.4.2 Viral diarrhea 794.5 Area-age-sex-cause specific relative risk associated with extreme
weather events indices 824.5.1 All infectious diarrhea 824.5.2 Bacterial diarrhea 864.5.3 Viral diarrhea 894.6 Pooled relative risks of cause-specific diarrhea infection associated with extreme weather events 914.6.1 All infectious diarrhea 914.6.2 Bacterial diarrhea 944.7.3 Viral diarrhea 9
74.6 Study limitations 1005. Conclusion and suggestions 1015.1 Conclusion 1015.2Suggestions 102References 103Response to the committees’ comments and suggestions 142 List of figuresFigure 1.1 Leading cause of deaths among children under five years of age worldwide in 2013 [9] 2Figure 2.1 Diar
rhea infections mortality rate in all ages [7] 13Figure 2.2 Relationship among meteorological, agricultural, hydrological, and socioeconomic drought [95] 18Figure 2.3 Probability distributions of daily precipitation, extremes are denoted by the shaded areas [85] 21Figure 2.4 Drought and its effec
t on public health [94, 123] 25Figure 3.1 Framework of the statistical models’ integration 35Figure 3.2 Region partition and weather station location in Taiwan 39Figure 4.1 Trends of Taiwan monthly average mean temperature (°C) from 1980 to 2016 54Figure 4.2 Trends of Taiwan monthly cumulative r
ainfall (mm) from 1980 to 2016 55Figure 4.3 Trends of Taiwan monthly average maximum temperature (°C) from 1980 to 2016 56Figure 4.4 Trends of Taiwan monthly average minimum temperature (°C) from 1980 to 2016 57Figure 4.5 Trends of Taiwan monthly average relative humidity (%) from 1980 to 2016 5
8Figure 4.6 Trends of Taiwan monthly average sunshine hour (h) from 1980 to 2016 59Figure 4.7 City and county-specific monthly standardized precipitation evapotranspiration index-3 (SPEI-3) from 1980 to 2016 61Figure 4.8 Monthly standardized precipitation evapotranspiration index-3 (SPEI-3) in Nor
th, Chumiao, Central, Yunchianan, Kaoping, and Huatung region from 1980 to 2016 62Figure 4.9 Area specific relative risk (95% confidence interval) of outpatient visits of all population infectious diarrhea associated with the monthly mean average temperatures at 5th and 99th percentiles relative to
the reference temperature from 2000 to 2016 in Taiwan 72Figure 4.10 Area-sex specific relative risk (95% confidence interval) of outpatient visits of all female population infectious diarrhea associated with the monthly mean average temperatures at 5th and 99th percentiles relative to the referenc
e temperature from 2000 to 2016 in Taiwan 73Figure 4.11 Area-sex specific relative risk (95% confidence interval) of outpatient visits of all male population infectious diarrhea associated with the monthly mean average temperatures at 5th and 99th percentiles relative to the reference temperature f
rom 2000 to 2016 in Taiwan 74Figure 4.12 Area-age specific relative risk (95% confidence interval) of outpatient visits of all population aged under five years infectious diarrhea associated with the monthly mean average temperatures at 5th and 99th percentiles relative to the reference temperature
from 2000 to 2016 in Taiwan 75 Figure 4.13 Area-age-sex specific relative risk (95% confidence interval) of outpatient visits of female subpopulation aged under five years all infectious diarrhea associated with the monthly mean average temperatures at 5th and 99th percentiles relative to the refe
rence temperature from 2000 to 2016 in Taiwan 76Figure 4.14 Area-age-sex specific relative risk (95% confidence interval) of outpatient visits of male subpopulation aged under five years all infectious diarrhea associated with the monthly mean average temperatures at 5th and 99th percentiles relati
ve to the reference temperature from 2000 to 2016 in Taiwan 77Figure 4.15 Pooled relative risks of all infectious diarrhea associated with monthly average mean temperature at 5th and 99th percentiles 92Figure 4.16 Pooled relative risks of all infectious diarrhea associated with severely dry and ve
ry wet conditions of monthly SPEI-3 from 2000 to 2016 93Figure 4. 17 Pooled relative risks of bacterial diarrhea associated with monthly average mean temperature at 5th and 99th percentiles 95Figure 4.18 Pooled relative risks of bacterial diarrhea associated with severely dry and very wet conditio
ns of monthly SPEI-3 from 2000 to 2016 96Figure 4.19 Pooled relative risks of viral diarrhea associated with monthly average mean temperature at 5th and 99th percentiles 98Figure 4.20 Pooled relative risks of viral diarrhea associated with severely dry and very wet conditions of monthly SPEI-3 fro
m 2004 to 2016 98 List of tablesTable 2.1 Key diarrhea causing bacterial agents [62, 63] 9Table 2.2 Potential risk factors causing diarrhea in Asia and Africa 14Table 2.3 Definition of extreme temperatures indices by unit[88] 16Table 2.4 List of methods used to define drought event 19Table 2.5
Definitions of extreme precipitation indices by unit [88, 109] 22Table 2.6 Literature review of diarrhea infections associated with climatic factors 27Table 3.1 Taiwan regions and the area coverage 36Table 3.2 Locations of weather stations in Taiwan 38Table 3.3 Standardize precipitation evapotra
nspiration index interpretation 42Table 4.1 Summary statistics of monthly climatic and extreme weather event data from 2000 to 2016 in cities of Taiwan 46Table 4.2 Summary statistics of monthly climatic and extreme weather event data from 2004 to 2016 in 6-regions of Taiwan exclude Yilan region 5
2Table 4.3 Summary of standardized precipitation evapotranspiration index in cities of Taiwan from 1980 to 2016 63Table 4.4 Summary of standardized precipitation evapotranspiration index in North, Chumiao, Central, Yunchianan, Kaoping, and Huatung region from 1980 to 2016 64Table 4.5 Annual case n
umbers of outpatient visits of all infectious diarrhea, bacterial, and viral diarrhea in Taiwan from 2000 to 2016 65Table 4.6 Definition of ICD-10 of diarrhea by this study and Taiwan CDC 66Table 4.7 Cause-specific case numbers of diarrhea stratified by area, age, and sex group from 2000 to 2016 i
n cities of Taiwan 67Table 4.8 Cause-specific case numbers of diarrhea stratified by area, age, and sex group from 2004 to 2016 in regions of Taiwan excluding Yilan region 68Table 4.9 The temperatures of the lowest diarrhea risk by study age and sex in the first-stage of analysis model 69Table 4.
10 Area-age-sex-cause specific relative risk (95% confidence interval) of outpatient visits of viral diarrhea associated with the monthly mean average temperatures at 5th and 99th percentiles relative to the reference temperature from 2000 to 2016 81Table 4.11 Area-age-sex-cause specific relative r
isk (95% confidence interval) of outpatient visits of all infectious diarrhea associated with severely dry and very wet conditions of SPEI-3 from 2000 to 2016 84Table 4.12 Area-age-sex-cause-specific relative risk (95% confidence interval) of outpatient visits of bacterial diarrhea associated with
severely dry and very wet conditions of monthly SPEI-3 from 2000 to 2016 87Table 4.13 Area-age-sex-cause-specific relative risk (95% confidence interval) of outpatient visits of viral diarrhea associated with severely dry and very wet conditions of monthly SPEI-3 from 2000 to 2016 90(page v-xiv)