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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 杜裕康(YU-KANG TU) | |
dc.contributor.advisor | 杜裕康(YU-KANG TU | yukangtu@ntu.edu.tw | ), | |
dc.contributor.author | Chien-Hua Tseng | en |
dc.contributor.author | 曾健華 | zh_TW |
dc.date.accessioned | 2023-03-19T22:08:38Z | - |
dc.date.copyright | 2022-06-09 | |
dc.date.issued | 2022 | |
dc.date.submitted | 2022-06-02 | |
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J Chronic Dis, 1987. 40(5): p. 373-83. 39.Wyss, R., et al., The role of prediction modeling in propensity score estimation: an evaluation of logistic regression, bCART, and the covariate-balancing propensity score. Am J Epidemiol, 2014. 180(6): p. 645-55. 40.Rosenbaum, P.R. and D.B. Rubin, Reducing Bias in Observational Studies Using Subclassification on the Propensity Score. Journal of the American Statistical Association, 1984. 79(387): p. 516-524. 41.Schoenfeld, D., Survival methods, including those using competing risk analysis, are not appropriate for intensive care unit outcome studies. Critical care (London, England), 2006. 10(1): p. 103-103. 42.Resche-Rigon, M., E. Azoulay, and S. Chevret, Evaluating mortality in intensive care units: contribution of competing risks analyses. Critical care (London, England), 2006. 10(1): p. R5-R5. 43.Fine, J.P. and R.J. Gray, A Proportional Hazards Model for the Subdistribution of a Competing Risk. Journal of the American Statistical Association, 1999. 94(446): p. 496-509. 44.Service, F.J., et al., Mean amplitude of glycemic excursions, a measure of diabetic instability. Diabetes, 1970. 19(9): p. 644-55. 45.Lanspa, M.J., et al., Coefficient of glucose variation is independently associated with mortality in critically ill patients receiving intravenous insulin. Crit Care, 2014. 18(2): p. R86. 46.Kovatchev, B.P., et al., Symmetrization of the blood glucose measurement scale and its applications. Diabetes Care, 1997. 20(11): p. 1655-8. 47.Kovatchev, B.P., et al., Algorithmic evaluation of metabolic control and risk of severe hypoglycemia in type 1 and type 2 diabetes using self-monitoring blood glucose data. Diabetes Technol Ther, 2003. 5(5): p. 817-28. 48.Hill, N.R., et al., Normal reference range for mean tissue glucose and glycemic variability derived from continuous glucose monitoring for subjects without diabetes in different ethnic groups. Diabetes Technol Ther, 2011. 13(9): p. 921-8. 49.Semler, M.W., et al., Balanced Crystalloids versus Saline in Critically Ill Adults. N Engl J Med, 2018. 378(9): p. 829-839. 50.Lobo, D.N. and S. Awad, Should chloride-rich crystalloids remain the mainstay of fluid resuscitation to prevent 'pre-renal' acute kidney injury?: con. Kidney Int, 2014. 86(6): p. 1096-105. 51.Jones, A.E., et al., Lactate clearance vs central venous oxygen saturation as goals of early sepsis therapy: a randomized clinical trial. Jama, 2010. 303(8): p. 739-46. 52.Toporek, A.H., et al., Balanced Crystalloids versus Saline in Critically Ill Adults with Hyperkalemia or Acute Kidney Injury: Secondary Analysis of a Clinical Trial. Am J Respir Crit Care Med, 2021. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84327 | - |
dc.description.abstract | 背景: 各類輸液在體液復甦時可能帶來不同的副作用。不同病人族群的臨床試驗結果發現各類輸液的優缺點有不一致的結論。在敗血症病人族群中,乳酸林格試液較生理食鹽水能降低死亡率,但此差異可否推論到術後病人、外傷病人則沒有定論,且不同輸液對於各器官的影響缺乏整體的綜合比較。敗血症病人中有很大部分有慢性腎病變、肝病變、肺病變等,不同輸液是否會造成有共病症、慢性器官病變病患的副作用,是值得且需要詳細探討,才能給予臨床實際治療時最好的建議。 方法: 此論文第一部分利用系統性文獻搜尋與網絡統合分析去比較各類輸液於敗血症、手術、外傷病人的差異(PROSPERO website, registration number: CRD42018115641)。搜尋資料庫包含PubMed、EMBASE及Cochrane CENTRAL,並利用相關發表文章的參考文獻進行收集。收錄分析的隨機分派研究需主要針對急重症需要體液復甦的病患,給予的治療需是乳酸林格式液(lactated Ringer’s)、生理食鹽水(Saline)、白蛋白(albumin)、乙烴澱粉輸液(hydroxyethyl starch)及明膠輸液(gelatin)其中兩種的比較。系統性文獻評讀利用Risk of Bias工具2.0版本,並藉由CINeMA (Confidence in Network Meta-Analysis)工具統整證據等級;網絡統合分析利用隨機效應模型。 論文第二部分則是前瞻性世代研究,利用一間台灣醫學中心加護病房資料進行分析,該醫學中心針對敗血症病患進行標準評估與照護,進而可取得各類慢性病病患對於不同輸液的詳細反應生理及血液生化數據。再利用Cox回歸模型(Cox regression model)控制干擾因子比較死亡率、利用competing risk model排除死亡個案後比較住院天數,線性混合模型(Linear mixed model)比較各類重複測量數據。 結果: 第一部分的統合分析共有53個隨機分派研究(26351位病患),共評估7類輸液。敗血症與手術病人中,相較於接受生理食鹽水(Saline)與乙烴澱粉輸液(hydroxyethyl starch),接受乳酸林格式液(lactated Ringer’s)與白蛋白(albumin)的病患存活率較佳、急性腎病變較少、輸血量較少。特別是敗血症的病患中,乳酸林格式液(lactated Ringer’s)較生理食鹽水(Saline)能顯著下降死亡率( 0.84; 95% CI 0.74 to 0.95)。然而外傷病人中,各類輸液差異較不明顯,但於外傷性腦損傷病人中,生理食鹽水(Saline)與乙烴澱粉輸液(hydroxyethyl starch)卻反而較乳酸林格式液(lactated Ringer’s)與白蛋白(albumin)明顯下降死亡率,特別是生理食鹽水(Saline)相較於白蛋白(albumin)能顯著增加存活率(Odd ratios, 0.55; 95% CI 0.35 to 0.87)。 第二部分的世代研究納938位病人,乳酸林格式液(lactated Ringer’s)較生理食鹽水(saline)降低死亡率(adjusted hazard ratio, 0.59; 95% CI 0.43-0.81)且住院天數較短(subdistribution hazard ratio, 1.39; 95% C.I. 1.15-1.67),而此差異於慢性肺病變的病人較明顯,於慢性腎病變、慢性肝病變中較不顯著。 結論: 第一部分的統合分析發現在敗血症病人中,乳酸林格式液(lactated Ringer’s)、白蛋白(albmin)較生理食鹽水(saline)、乙烴澱粉輸液(hydroxyethyl starch)降低死亡率,但在外傷性腦損傷的病人,反而生理食鹽水(Saline)與乙烴澱粉輸液(hydroxyethyl starch)較乳酸林格式液(lactated Ringer’s)與白蛋白(albumin)明顯下降死亡率。第二部分的世代研究發現乳酸林格式液(lactated Ringer’s)較生理食鹽水(Saline)的死亡率下降,只在慢性肺病變顯著,在於慢性腎病變、慢性肝病變中較不顯著。因此,病患類別、病患是否有哪些共病症,在輸液選擇上是非常重要的。 | zh_TW |
dc.description.abstract | Background: Crystalloids and colloids, used for volume resuscitation, are associated with adverse effects. Clinical trial findings on the adverse effects of various fluid types are conflicting in patients with different conditions. Most sepsis patients had chronic kidney disease, chronic liver disease, chronic pulmonary disease and diabetes mellitus, and whether those solutions lead to adverse effects in those patients with organ failure is still unclear. Methods: The first part of this thesis is to use systemic review and network meta-analysis to compare the effects of different fluid types in the treatment of sepsis, surgical and trauma patients. Electronic databases (PubMed, EMBASE, and Cochrane CENTRAL) and reference lists of relevant articles were searched from their inception until January 2020. Clinical trials on critically ill adults requiring the following types of fluid resuscitation were included: balanced crystalloid, saline, iso-oncotic albumin, hyperoncotic albumin, low molecular weight hydroxyethyl starch (L-HES), high molecular weight HES, and gelatin. Network meta-analyses were conducted using random-effects model to calculate odds ratio (OR) and mean difference. Risk of Bias tool 2.0 was used to assess bias. CINeMA (Confidence in Network Meta-Analysis) web application was used to rate the confidence in synthetic evidence. Second part of this thesis is a prospective cohort study, conducted in a medical intensive care unit (ICU) in central Taiwan. We applied the standard sepsis evaluation protocol and identified heart, lung, liver, kidney, and endocrine comorbidities. We also evaluated resuscitation responses including central venous pressure, central venous oxygen saturation, and serum lactate level simultaneously. Propensity-score matching and Cox regression were used to compare patients’ mortality. The competing risk model compared the lengths of hospital stays with the subdistribution hazard ratio (SHR). Results: In the first part, fifty-eight trials (n=26,351 patients) comparing seven fluid types were included in our network meta-analysis. Among patients with sepsis and surgery, lactated Ringer’s and albumin achieved better survival, fewer acute kidney injury, and smaller blood transfusion volumes than saline and L-HES. In those with sepsis, lactated Ringer’s significantly reduced mortality than saline (OR, 0.84; 95% CI 0.74 to 0.95) and L-HES (OR, 0.81; 95% CI 0.69 to 0.95) and reduced acute kidney injury than L-HES (OR, 0.80; 95% CI 0.65 to 0.99). However, it required the greatest resuscitation volume among all fluid types, especially in trauma patients. In patients with traumatic brain injury, saline and L-HES achieved lower mortality than albumin and lactated Ringer’s; especially saline was significantly superior to iso-oncotic albumin (OR, 0.55; 95% CI 0.35 to 0.87). In the second part, the cohort study included 938 patients in the analysis. The lactated Ringers group had a lower mortality rate (adjusted hazard ratio, 0.59; 95% CI 0.43-0.81) and shorter lengths of hospital stay (SHR, 1.39; 95% C.I. 1.15-1.67) than the saline group; the differences were greater in patients with chronic pulmonary disease and small and nonsignificant in those with chronic kidney disease, moderate to severe liver disease and cerebral vascular disease. The resuscitation efficacy was the same between fluid types, but serum lactate levels were significantly higher in the lactated Ringers group than in the saline group (0.12 mg/dL/hour; 95% C.I.: 0.03, 0.21), especially in chronic liver disease patients. Compared to the saline group, the lactated Ringers group achieved target glucose level earlier in both diabetes and non-diabetes patients. Conclusions: Our network meta-analysis found that lactated Ringer’s and albumin decreased mortality more than L-HES and saline in sepsis patients; however, saline or L-HES, was better than iso-oncotic albumin or lactated Ringer’s in traumatic brain injury patients. In the cohort study, Lactate Ringer’s solution provides greater benefits to patients with chronic pulmonary disease than to those with chronic kidney disease, or with moderate to severe liver disease. Comorbidities are important in choosing resuscitation fluid types. | en |
dc.description.provenance | Made available in DSpace on 2023-03-19T22:08:38Z (GMT). No. of bitstreams: 1 U0001-3005202215213200.pdf: 8285760 bytes, checksum: 16e39adc5be5bf56c0b20533909c5996 (MD5) Previous issue date: 2022 | en |
dc.description.tableofcontents | 謝辭···i 中文摘要···ii 英文摘要···iv 圖目錄···xi 表目錄···xii Chapter 1 Introduction···1 Chapter 2 Literature review···3 2.1 Weakness in current evidences···3 2.2 Solutions for weakness in the previous meta-analysis···10 Chapter 3 Materials and Methods···12 3.1 Systematic review [Study 1]···12 3.2 Network meta-analysis (NMA) [Study 1]···14 3.3 Sequential network meta-analysis [Study 1]···15 3.4 Database for retrospective analysis [Study 2]···17 3.5 Statistical methods for mortality and lengths of stay in the ICU and hospital [Study 2]···19 3.6 Statistical method for repeated measured data [Study 2]···20 Chapter 4 Results for network meta-analysis [Study 1]···21 4.1 Systematic review···21 4.2 NMA Results for sepsis patients···23 4.3 NMA Results for surgical patients···27 4.4 NMA Results for trauma and traumatic brain injury patients···30 Chapter 5 Results for retrospective cohort study [Study 2]···32 5.1 Patient characteristics···32 5.2 Mortality and lengths of ICU and hospital stays···34 5.3 Other important outcomes···39 Chapter 6 Discussion for network meta-analysis [Study 1]···45 Chapter 7 Discussion for cohort study [Study 2]···49 Chapter 8 Conclusion···51 Reference list···52 Appendix 1:Systematic reviews and meta-analysis published on fluid resuscitation in critically-ill patients···1 Appendix 2:PRISMA checklist···3 Appendix 3:Protocol and Search strategies···9 3.1. Review eligibility criteria···9 3.2. Search vocabulary···10 Appendix 4:Excluded studies and reasons···12 Appendix 5:List of included studies···15 5.1. Sepsis patients···15 5.1.1. Study group and primary outcome···15 5.1.2. Study population and enrollment criteria···16 5.1.3. Baseline characteristics···20 5.1.4. Resuscitation goal and fluid volume···22 5.2. Surgical patients···25 5.2.1 Population, intervention, outcome···25 5.2.2 Baseline characteristics, resuscitation goal and fluid volume···27 5.3. Traumatic patients···29 5.3.1 Population, intervention, outcome···29 5.3.2 Baseline characteristics and fluid volume···31 5.4. References···32 Appendix 6:Assessment of transitivity···38 6.1. Age···39 6.2. Male percentage···40 6.3. Sample size···41 6.4. APACHE···42 6.5. SAPS···43 6.6. SOFA···43 6.7. Mean arterial pressure···45 6.8. Lactate level···46 6.9. Vasopressor···47 6.10. Source of sepsis from lung (pneumonia)···48 6.11. Year···48 Appendix 7:Risk of bias···50 7.1. Sepsis patients···50 7.1.1. Risk of bias assessment for the individual domains in sepsis trials···50 7.1.2. Risk of bias assessment for the individual studies in sepsis trials···51 7.1.3. Risk of bias notes for the individual studies in sepsis trials···52 7.2 Surgical patients···53 7.2.1. Risk of bias assessment for studies in surgical trials···53 7.2.2. Risk of bias assessment for the individual studies in surgical trials···54 7.2.3. Risk of bias notes for the individual studies in surgical trials···55 7.3 Trauma patients···56 7.3.1. Risk of bias assessment for studies in trauma trials···56 7.3.2. Risk of bias assessment for the individual studies in trauma trials···57 7.3.3. Risk of bias notes for the individual studies in trauma trials···58 Appendix 8:Results···59 8.1. Extracted outcome data in sepsis patients···59 8.1.1. Mortality in sepsis patients···59 8.1.2. Resuscitation fluid volume in sepsis patients···60 8.1.3. No. of acute kidney injury in sepsis patients···61 8.1.4. No. of renal replacement events in sepsis patients···62 8.1.5. Blood transfusion volume in sepsis patients···63 8.1.6. No. of bleeding events requiring transfusion in sepsis patients···64 8.1.7. Allergic events in sepsis patients···65 8.2. Extracted outcome data in surgical patients···66 8.2.1. Mortality data in surgical patients···66 8.2.2. Resuscitation fluid volume in surgical patients···67 8.2.3. No. of acute kidney injury in surgical patients···68 8.2.4. Blood transfusion volume in surgical patients···69 8.3. Extracted outcome data in trauma patients···70 8.3.1. Mortality in trauma patients···70 8.3.2. Resuscitation fluid volume···in trauma patients···71 8.3.3. No. of acute kidney injury in trauma patients···72 8.3.4. Blood transfusion volume in trauma patients···73 8.4. Extracted outcome data in traumatic brain injury patients···74 8.4.1. Mortality in traumatic brain injury patients···74 Appendix 9:League table and Relative ranking···75 9.1. Sepsis patients···75 9.1.1. Mortality in sepsis patients···75 9.1.2. Resuscitation fluid volume in sepsis patients···77 9.1.3. Acute kidney injury in sepsis patients···79 9.1.4. Blood transfusion volume in sepsis patients···81 9.2. Relative ranking probability in surgical patients···83 9.2.1. Mortality in surgical patients···83 9.2.2. Resuscitation fluid volume in surgical patients···85 9.2.3. Acute kidney injury in surgical patients···87 9.2.4. Blood transfusion volume in surgical patients···89 9.3. Relative ranking probability in trauma patients···91 9.3.1. Mortality in trauma patients···91 9.3.2. Fluid resuscitation volume in trauma patients···93 9.3.3. Adverse renal events in trauma patients···95 9.3.4. Blood transfusion volume in trauma patients···97 9.3.5. Mortality in traumatic brain injury patients···99 9.4. Interval plot for surgical and trauma patients···101 Appendix 10:Publication bias···104 10.1. Publication bias in sepsis patients···104 10.1.1 Mortality in sepsis patients···104 10.1.2. Resuscitation fluid volume in sepsis patients···105 10.1.3. Acute kidney injury in sepsis patients···106 10.1.4. Blood transfusion volume in sepsis patients···107 10.2. Publication bias in surgical patients···108 10.2.1. Mortality in surgical patients···108 10.2.2. Resuscitation fluid volume in surgical patients···109 10.2.3. Acute kidney injury in surgical patients···110 10.2.4. Blood transfusion among in surgical patients···111 10.3. Publication bias in trauma patients···112 10.3.1.Mortality in trauma patients···112 10.3.2. Mortality in traumatic brain injury patients···113 Appendix 11:Inconsistency···114 11.1. Inconsistency in sepsis patients···115 11.1.1. Mortality in sepsis patients···115 11.1.2. Resuscitation fluid volume in sepsis patients···117 11.1.3. Acute kidney injury in sepsis patients···118 11.1.4. Blood transfusion among in sepsis patients···119 11.2. Inconsistency in surgical patients···120 11.2.1. Mortality in surgical patients···120 11.2.2. Resuscitation fluid volume in surgical patients···122 11.2.3. Acute kidney injury in surgical patients···123 11.2.4. Blood transfusion among in surgical patients···125 11.3. Inconsistency in traumatic patients···127 11.3.1. Mortality in traumatic patients···127 Appendix 12:Meta-regression···128 12.1. SUCRA and mean ranks changes before and after model adjust in sepsis trials···128 12.2. Significance for meta-regression model in sepsis trials···128 Appendix 13:Grading the evidence using CINeMA web application···129 13.1. Sepsis patients···129 13.1.1 Confidence rating in sepsis trails for mortality···129 13.1.2 Confidence rating in sepsis trails for fluid resuscitation volume···130 13.1.3 Confidence rating in sepsis trails for acute kidney injury···131 13.1.4 Confidence rating in sepsis trails for blood transfusion volume···132 13.2. Surgical patients···133 13.2.1 Confidence rating in surgical trails for mortality···133 13.2.2 Confidence rating in surgical trails for fluid resuscitation volume···134 13.2.3 Confidence rating in surgical trails for adverse renal events···135 13.2.4 Confidence rating in surgical trails for blood transfusion volume···136 13.3. Trauma patients···137 13.3.1 Confidence rating in trauma trails for mortality···137 13.3.2 Confidence rating in trauma trails for acute kidney injury···138 13.4. Traumatic brain injury patients···139 Appendix 14:Sensitivity analysis···140 14.1. Exclusion with largest trial (The SMART randomized trial)···140 14.1.1. Mortality···140 14.1.2. Fluid resuscitation volume···141 14.1.3. Acute kidney injury···142 14.1.4. Blood cell transfusion volume···143 14.2. Inclusion with pilot study (The SALT Randomized Trial)···144 14.2.1. Mortality···144 14.2.2. Acute kidney injury···145 | |
dc.language.iso | en | |
dc.title | 重症休克病患的體液復甦序貫式網絡統合分析以及臨床資料分析 | zh_TW |
dc.title | Fluid resuscitation for critically ill patients–Sequential Network meta-analysis and Clinical data analysis | en |
dc.type | Thesis | |
dc.date.schoolyear | 110-2 | |
dc.description.degree | 博士 | |
dc.contributor.oralexamcommittee | 陳杰峰(CHIEH-FENG CHEN),簡國龍(KUO-LIONG CHIEN),李文宗(WEN-CHUNG LEE),張淑惠(SHU-HUI CHANG) | |
dc.subject.keyword | 體液復甦,生理食鹽水,乳酸林格式液,膠體溶液, | zh_TW |
dc.subject.keyword | Fluid resuscitation,Normal saline,Ringer's lactate,Colloid, | en |
dc.relation.page | 199 | |
dc.identifier.doi | 10.6342/NTU202200833 | |
dc.rights.note | 同意授權(限校園內公開) | |
dc.date.accepted | 2022-06-02 | |
dc.contributor.author-college | 公共衛生學院 | zh_TW |
dc.contributor.author-dept | 流行病學與預防醫學研究所 | zh_TW |
dc.date.embargo-lift | 2022-06-09 | - |
顯示於系所單位: | 流行病學與預防醫學研究所 |
文件中的檔案:
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U0001-3005202215213200.pdf 授權僅限NTU校內IP使用(校園外請利用VPN校外連線服務) | 8.09 MB | Adobe PDF | 檢視/開啟 |
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