请作为心血管病方向的专家,阅读文章后给文章重新定一个更加贴合的标题,并给出建设性的修改意见

생성일: 2025년 11월 2일

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manuscript.docx

请作为心血管病方向的专家,阅读文章后给文章重新定一个更加贴合的标题,并给出建设性的修改意见

사고

Proposing improvements

I’m crafting an enhanced title in Chinese for academic tone. Evaluating all sections: methods, validation, bias, and effect size. Progressing through each carefully.

Ensuring consistency

I'm examining definitions, shock severity, vasopressor doses, and shock index consistency. Adjusting units, standardizing language, and avoiding references to future dates.

Structuring and emphasizing

I’m organizing the response, recognizing the study, suggesting titles, and listing constructive revision ideas. Highlighting significant contributions and notifying users about crucial caution points.

Ensuring precise coding

I’m auditing ICD codes, highlighting potential misclassifications, and verifying mappings. This meticulous approach should prevent errors in the cardiogenic shock-related data analysis.

Refining recommendations

I'm working through suggestions to refine cardiogenic shock definition, address coding issues, and present detailed risk analyses. Emphasizing clarity and precision to enhance the study's robustness.

Calculating E-value

I'm gathering info on the E-value formula: E-value = HR + sqrt(HR*(HR-1)). For HR=1.803, things get interesting.

Providing calibration and vignettes

They're adding calibration methods and clinical vignettes, considering MIMIC dataset disclaimers, exploring hazard modeling nonlinearity, using natural log transformation of BAR, and examining the impact of serum albumin levels.

Enhancing clarity

I’m piecing together a comprehensive response that includes a draft title, alternative titles, a overall evaluation, and specific suggestions for abstract, introduction, methods, results, discussion, tables/figures, and supplementary materials, all in Chinese.

Reasoned for 3m 7s

답변

下面给出我作为心血管病学方向审稿人的建议:先给出一个更贴切、便于被读者与检索系统理解的标题,然后按“重要性优先”提供建设性修改清单,最后给出可直接套用的摘要与图表/附录改进模板。以下意见均基于您稿件的研究设计、结果与表格内容(MIMIC‑IV v3.1、入组1,011例CS、主要终点30天全因死亡、BAR在多时点Cox与RCS、并有机器学习验证)而提出。(manuscript.docx)


一、推荐新标题(主推 + 备选)

主推标题:
“ICU首日血尿素氮/白蛋白比值(BAR)与心源性休克短期及远期死亡风险:基于MIMIC‑IV的回顾性队列研究(n=1,011)”
——突出人群(CS)暴露(ICU首日BAR)结局(30/60/120/365天死亡)数据来源(MIMIC‑IV),并明确样本量与研究设计,便于检索与读者定位。(manuscript.docx)

备选标题:

  1. “BAR对心源性休克分层预后的价值:来自MIMIC‑IV的多时点生存分析与机器学习证据” (manuscript.docx)
  2. “早期BAR作为心源性休克死亡风险标志物:回顾性多时点Cox与RCS分析” (manuscript.docx)
  3. “血尿素氮/白蛋白比值与心源性休克30天至1年死亡:MIMIC‑IV 1,011例研究” (manuscript.docx)

二、总体评价(一句话结论)

本文以易得、廉价的ICU首日BAR作为暴露,显示其与30天至365天死亡近似线性正相关,且在充分调整后仍独立关联;并用机器学习作一致性与可解释性验证,具有可临床转化的潜力。但需要在病例定义、阈值临床可解释性、增量价值、校准与外部验证等方面补强。(manuscript.docx)


三、主要修改建议(按影响程度排序)

A. 研究对象与病例定义

  1. 严格核对与优化CS判定的ICD编码:稿中采用 ICD‑9 785.51 与 ICD‑10 R57.0 是CS常用编码,但同时出现 T81.11XA(术后休克)等可能引入非心源性或医源性休克的编码;建议限定/敏感性分析仅使用明确心源性休克编码(如R57.0、785.51),并报告编码组合的阳性预测值或以血流动力学/血乳酸+血管活性药物使用等临床标准进行二次验证。这将显著降低误分层风险。(manuscript.docx)
  2. 阐明“索引时间”与随访:已写“以ICU入科为零时点”,建议明确死亡信息来源(院内/出院后链接来源)、失访处理右删截细节,并在补充材料给出数据抽取SQL伪代码。(manuscript.docx)

B. 暴露(BAR)与潜在干预的处理

  1. 明确BAR的计算单位与换算:建议在方法中以公式展示:BAR = BUN(mg/dL) / Albumin(g/dL), 单位 mg·g⁻¹;并说明时间窗(首24小时最早一次)与异常值处理(如winsorize 1%/99%)。(manuscript.docx)
  2. 考虑“治疗影响”敏感性分析:ICU首日CRRT可急速影响BUN,白蛋白输入可改变白蛋白水平;建议增加排除或调整首24小时接受CRRT/白蛋白输入人群的敏感性分析,或以“是否白蛋白制剂输入/CRRT”为交互项探讨效应修饰。(manuscript.docx)

C. 统计分析与结果表达

  1. 提升临床可解释性:目前主要呈现“每 +1 mg·g⁻¹”的HR(30天HR≈1.026)。建议同时报告“每 +5 / +10 mg·g⁻¹”的HR,便于床旁直观理解(示例:每 +5 mg·g⁻¹ ≈ HR 1.14;每 +10 mg·g⁻¹ ≈ HR 1.29,基于对数线性假设的换算)。表2可新增一列“标准化增量HR”。(manuscript.docx)
  2. 给出分位点阈值与绝对风险:请在正文或表脚中明确T1/T2/T3的cut‑off数值,并报告各分组30/60/120/365天KM累计死亡率(绝对风险),增强临床沟通价值。(manuscript.docx)
  3. 增量价值与校准(强烈建议):在“完全调整模型”基础上,评估加入BAR后的C‑index(或时依AUC)变化、IDI/NRI、Brier分数与校准曲线/斜率;机器学习部分也应给出AUROC、AUPRC(点估计与95%CI)校准,而非仅展示PR与DCA图,以数据支撑“增益”。如受版面限制,可置于补充材料。(manuscript.docx)
  4. 比例风险检验与非线性呈现:已说明用Schoenfeld与RCS,建议在补充材料提供PH检验p值表RCS结点设置;如存在轻微违背,可考虑限时段Cox加时变项敏感性分析。(manuscript.docx)
  5. 比值陷阱与组分分析:为排除“比值”驱动的数学假象,建议补充以下敏感性分析:
    • BUN、白蛋白分别进入模型,并比较其对结局的独立贡献;
    • 以**BAR +(BUN与白蛋白其一)**并存的模型,观察BAR是否仍保留信息;
    • log(BAR)或以样条替代分组,验证稳健性。(manuscript.docx)
  6. 协变量与事件数配比:主要终点30天死亡377/1011(37.3%),建议在正文说明事件/参数比值、VIF诊断与(若可能)惩罚化Cox降维(已提Boruta,可同步说明用于Cox或仅用于ML)。(manuscript.docx)
  7. 异质性与亚组:稿中提示无显著交互(P‑interaction>0.05)。建议重点呈现AMI‑CS vs 非AMI‑CSCKD分期是否CRRT的森林图,并在图注写明协变量与事件数,提高可判读性。(manuscript.docx)
  8. E‑value:正文仅给出T3 vs T1 E‑value≈3.0作为举例,建议系统报告主要比较与关键亚组的E‑value(点估计+下界E‑value),并将计算方法置于补充材料,增强“未测混杂强度”解释力度。(manuscript.docx)

D. 结果呈现与图表

  1. 表1一致性与单位:目前存在“中文/英文混排、单位不统一(如℉/℃、K/μL与×10⁹/L)、个别中文备注占位符(如‘?’、‘中位数’)”等问题;建议全表SI单位化(或在美式单位后并列SI)、删除占位符补全变量定义。(manuscript.docx)
  2. 图2–3:在KM与RCS图上标注BAR tertile阈值风险表HR基准线;RCS建议在图注写明结点数参考值。(manuscript.docx)
  3. 机器学习图(PR/DCA/SHAP):请在图注标明模型名称、特征集、重采样方案、平均与95%CI;SHAP建议同时给出summary beeswarm典型个体force plot(当前文本已提及),并把超参数与搜索空间置于补充材料。(manuscript.docx)

E. 讨论与结论表述

  1. 语气收敛:将“预测/临床应用”改为**“预后关联/辅助分层”;强调外部验证前不宜设定固定阈值**。可加入“以绝对风险为导向的临床阈值设定需要多中心验证+决策分析”的表述。(manuscript.docx)
  2. 机制阐释与临床落地:建议添加床旁应用示例(如“BAR>某一切点时,建议加强血流动力学再评估/肾脏支持/并行复苏目标监测”),并讨论与SOFA、乳酸、肌酐的互补关系。(manuscript.docx)

四、次要与文字/版式层面的建议

  • 摘要重构为四段式(背景‑目的‑方法‑结果‑结论),给出关键数字:样本量、事件数、主要HR(如每+1 mg·g⁻¹ HR 1.026, 95%CI 1.011–1.041;T3 vs T1 HR≈1.80)、各时点趋势P值。可在“结果”最后补一行临床意义。(manuscript.docx)
  • 补充材料:完善变量字典/单位换算/生理合理范围缺失率表PH检验表完整模型系数外推限制说明代码可用性与STROBE清单。(manuscript.docx)
  • 参考文献:统一引用格式(期刊缩写、DOI),移除不必要的URL追踪参数,尽量使用主要研究/指南作为引证主干。(manuscript.docx)

五、可直接套用的小改模板(供参考)

1) 结构式中文摘要(≤250字,可据实替换具体数字)

背景: 心源性休克(CS)死亡率高,缺乏简便的床旁生物标志物。
目的: 评估ICU首日血尿素氮/白蛋白比值(BAR)对CS短期与远期死亡的预后价值。
方法: 基于MIMIC‑IV v3.1回顾性队列,纳入首次ICU入住且满足CS诊断的成人患者(n=1,011)。暴露为首24小时最早一次BAR;主要结局为30天全因死亡,次要结局为60/120/365天死亡。采用多层次Cox、限制性立方样条与预设亚组分析,并进行多重插补与多模型敏感性分析。
结果: 30天内死亡377例(37.3%)。完全调整后,每+1 mg·g⁻¹ BAR对应死亡风险增加2.6%(HR 1.026, 95%CI 1.011–1.041);最高分位(T3)相较最低分位(T1)死亡风险增高约80%(P趋势≤0.001)。关联在60/120/365天保持稳定,RCS提示近线性关系。
结论: ICU首日BAR为CS患者从30天至1年的稳健、可获得的预后指标,可作为现有评分的补充;需外部验证与基于绝对风险的临床阈值研究。(manuscript.docx)

2) 图表补充示例

  • 表2新增列: “每+5 / +10 mg·g⁻¹增量HR(近似)”,并给出各时点T1/T2/T3累计死亡率
  • 图3(RCS): 在x轴标注T1/T2/T3阈值常见临床BAR范围(如10、15、20 mg·g⁻¹),y轴添加HR=1参考线与95%CI半透明带。(manuscript.docx)

六、两点快速“加分项”(易于实现)

  1. 报告“绝对风险”与“增量判别/校准”指标(如ΔC‑index、AUPRC、校准斜率/截距),哪怕放在补充材料,也能显著增强方法学说服力。(manuscript.docx)
  2. 给出BAR与常用指标的并列模型(SOFA±乳酸±肌酐 ±BAR),并用决策曲线展示加入BAR的净临床获益区间(正文可简述,细节置补充)。(manuscript.docx)

结语

总体而言,稿件的核心发现清晰且具有实践意义:ICU首日BAR与CS多时点死亡呈稳健、近线性关联,并在多维度分析(传统统计与ML)中一致。若能按以上要点在病例定义临床可解释性与增量价值图表/补充材料完整度方面进一步打磨,文章的方法学严谨性与发表竞争力将显著提升。(manuscript.docx)

如果需要,我可以根据您目标期刊的字数与结构要求,把上述建议具体落实到稿件段落/图表的逐条改写清单

질문

image.pngimage.png

这段是不是没有写的必要?帮我重新整理一下method部分,参照回顾性研究的格式,删去不必要的内容

사고

Revising methods

I'm thinking through the Methods section, trimming repetitions, refining data definitions, and enhancing clarity. Did you spot any excessive phrasing or redundant details?

Enhancing the structure

Refining the Methods section: trimming redundancy, clarifying data points, and avoiding extraneous details. Also, integrating citation markers for precision.

Adjusting for clarity

I'm reworking the Methods section with succinct English and Mandarin subsections. Adding citations and combining redundant points, ensuring the narrative is precise and cohesive.

Reasoned for 4m 37s

답변

好的。我先直接回答你图里那段是否有必要写,然后给出按回顾性队列研究常见结构精简后的《Methods/方法》可直接替换版(中文),并附上删减清单,把不必要或重复的信息移到补充材料(Supplement)。以下整理均依据你当前稿件的数据来源、纳排标准、暴露/结局定义、缺失值处理与统计方案而改写。(manuscript.docx)


先答:图中那段要不要写?

如果你指的是**“所有连续变量均行Shapiro–Wilk正态性检验(几乎均P<0.0001),因此以中位数(IQR)描述并用Kruskal–Wallis/卡方检验比较;缺失值以MICE(m=20)插补……”这整段(稿件里出现了重复表述**),正文可以精简为一两句即可;检验细节、每个变量的缺失比例与插补模型参数放Supplement更合适。当前写法冗长且重复,不影响读者理解核心方法,建议删除/移补。(manuscript.docx)


方法(精简与规范版|可直接替换正文)

注:保留了审稿/读者判断所必需的信息;将过程性细节与长名单移至Supplement。(manuscript.docx)

研究设计与数据来源

我们开展单中心回顾性队列研究,数据来自 MIMIC‑IV v3.1(Beth Israel Deaconess Medical Center,2008–2019),均为去标识化数据,机构审查委员会豁免知情同意;本研究遵循STROBE报告规范。数据提取及变量字典见补充方法 eMethods 与 eTable S1。(manuscript.docx)

研究对象

纳入标准:① ≥18岁成人;② ICU首次入科期间满足心源性休克(CS)诊断编码(ICD‑9‑CM: 785.51、998.01;ICD‑10‑CM:** R57.0、T81.11XA**)且发生于入ICU 24小时内。若同一住院存在多次ICU,仅取首次ICU。排除:① ICU停留**<24 h**;② 首日缺失BUN或白蛋白;③ 缺失身高/体重无法计算BMI。最终纳入 1,011例(流程图见图1)。(更严格编码的敏感性分析方案见Supplement)。(manuscript.docx)

暴露(Exposure)

暴露为ICU首24小时最早一次化验计算的 BAR

BAR=BUN(mg/dL)白蛋白(g/dL)  (单位:mg\cdotpg1\text{BAR}=\frac{\text{BUN(mg/dL)}}{\text{白蛋白(g/dL)}}\ \ \text{(单位:mg·g}^{-1}\text{)}

BAR既按连续变量建模,也按**三分位数(T1–T3)**分组分析;具体cut‑off见表/补充材料。(manuscript.docx)

结局(Outcomes)

主要结局为30天全因死亡;次要结局为60/120/365天全因死亡。时间零点为ICU入科;存活/失访者在数据库中最后可确认日期右删截。(manuscript.docx)

协变量

基于临床相关性并避免“前瞻性偏倚”,所有协变量均取自入ICU首24小时

  • 人口学:年龄、性别、种族、BMI;
  • 疾病严重度:SOFA、SAPS II;
  • 合并症:急/慢性肾损伤、COPD、糖尿病、恶性心律失常、脓毒症等(编码算法见eMethods);
  • 生命体征/实验室:心率、SpO₂、血红蛋白、白细胞、葡萄糖、AST、肌酐、钾、INR、乳酸、pH等;
  • 首日治疗/干预:有创机械通气、肾脏替代治疗(CRRT)、血管活性药/常用心血管药物等。
    完整清单与单位/阈值见eTable S1。(manuscript.docx)

数据预处理与缺失值

20%缺失的变量不纳入主模型(如HbA1c、部分脂质、CRP、NT‑proBNP等,仅用于敏感性分析);≤20%缺失的变量采用多重插补(MICE,m=20);主分析基于插补数据集,完全病例分析作为敏感性验证;各变量缺失比例与插补细节见eTable S1–S2。描述性统计按**中位数(IQR)n(%)**呈现。(manuscript.docx)

统计学分析

  1. 描述性比较:BAR三分位组间连续变量用Kruskal–Wallis,分类变量用χ²或Fisher
  2. 生存分析:绘制Kaplan–Meier曲线并行log‑rank检验。
  3. Cox模型(主要分析,分别评估30/60/120/365天):
    • 模型1:仅BAR;
    • 模型2:+ 年龄、性别、种族、BMI;
    • 模型3(完全调整):在模型2基础上加入主要合并症SOFA/SAPS II关键实验室(肌酐、乳酸、INR等)及早期干预(IMV、CRRT等)。
      Schoenfeld残差检验比例风险假设;用限制性立方样条(RCS)评估BAR‑风险的非线性;三分位作趋势检验
  4. 亚组与交互(预设):按人口学、合并症(AMI、主动脉瓣狭窄、恶性心律失常、DM、HTN、AF)、SAPS II分层、CRRT/IMV等绘制森林图并检验乘法交互
  5. 敏感性分析:** 替代变量编码**、极端值修剪完全病例;(预设方案包含“仅限R57.0/785.51严格CS编码”的再分析,详见Supplement)。
    统计检验均为双侧α=0.05;更多实现细节与代码框架见Supplement。(manuscript.docx)

探索性机器学习(Supplement)

为验证BAR对30天死亡的增量信息,我们进行了交叉验证的监督学习作为补充:以与Cox相同的特征集训练若干常见算法,报告PR曲线(平均精度)DCASHAP解释;所有预处理与调参在每个重采样折内完成以避免信息泄漏。由于仅内部验证,该部分定位为探索性,完整流程与超参数见Supplement。(manuscript.docx)


删减与移补清单(便于你在稿件里快速操作)

建议从正文删除或合并为一句:

  • 反复出现的**“Shapiro–Wilk全部P<0.0001 → 用中位数(IQR)/Kruskal–Wallis/χ²”**整段说明(正文保留“连续变量以中位数(IQR)/Kruskal–Wallis,分类变量以n(%) / χ²或Fisher”即可)。(manuscript.docx)
  • 多重插补实施细节(各变量方法、m=20、预测均值匹配等)的长段落;正文只保留“≤20%缺失用MICE,主分析基于插补数据,完全病例作敏感性验证”。(manuscript.docx)
  • 算法清单/调参网格/防泄漏流程SHAP/PR/DCA绘图细节;改为一句“探索性ML,见Supplement”。(manuscript.docx)
  • 培训/认证编号(例如 certification number 13968729)这类与伦理合规相关但非学术必要的信息;如期刊要求可放补充或数据可用性声明。(manuscript.docx)

建议移至Supplement(保留在文内的引用锚点):

  • 变量字典、编码与单位换算表(eTable S1)、缺失比例(eTable S1–S2)、单变量Cox(eTable S4)、Boruta/SHAP细节(eTable S5–S6)、RCS结点选择与PH检验结果(eMethods)。(manuscript.docx)

正文应保留的要点(已体现在上面的精简版):

  • 数据来源、纳排标准、样本量与指数时间(ICU入科);
  • 暴露(BAR定义、时间窗与单位)、结局(四个时点)、协变量类别;
  • Cox层级模型框架、PH检验与RCS、亚组/敏感性思路;
  • 双侧α=0.05与“主分析基于插补数据,完全病例敏感性”。(manuscript.docx)

如果你愿意,我也可以把这份方法学精简稿对照你现有英文版逐句替换成英文,并给你一份带修订痕迹的Word(保留Supplement锚点和图表编号一致)。

질문

请逐句修订并指明原句位置,表达要参照回顾性研究的习惯,尽可能的学术化,并且简练,有侧重点(重点与研究的主题契合)

사고

Revisiting methods

I’m refining the Methods section, ensuring each sentence aligns with STROBE guidelines. Original sentences are clearly marked for easy reference. Progress is steady.

Refining methods

I’m refining the Methods section, ensuring conciseness, academic precision, and thematic alignment. Repeated paragraphs and redundant lines are condensed, preserving crucial details and clear references.

Clarifying the method

I’m crafting a precise "clean version" of the Methods section, emphasizing thematic elements and removing redundant paragraphs. Each sentence is meticulously revised or removed to enhance clarity and focus.

Refining statistical methods

I’m detailing BAR's analysis, assessing nonlinearity, and exploring tertiles. VAR's impact on 30-day mortality and secondary outcomes is examined in this structured framework.

Refining statistical analyses

I’m detailing subgroup, interaction, and sensitivity analyses. Handling missing data transitions to secondary validation with a cross-validated ML pipeline, assessing discrimination and clinical utility.

Refining details

I’m refining the paragraph on data preprocessing and missing data, simplifying variable definitions, handling missing data, and clearly outlining imputation methods and analysis strategies.

Taking a closer look

I’m removing Shapiro–Wilk test repetitions, clarifying hierarchical model adjustments, detailing subgroup interactions and sensitivity analyses, and ensuring consistent notation of BAR units throughout the methods.

Refining citations

I’m ensuring precision in citations, including markers for guiding clarity. The aim is to present revised sentences with a clear rationale for each edit, focusing on thematic coherence.

Reasoned for 9m 6s

답변

下面按Methods各小节,对您稿件中的每一句进行学术化与精炼修订,并标注“原句位置 → 原句 → 建议修订(可直接替换) → 处理与理由”。最后附上整合后的《Methods》终稿,便于您一键粘贴到正文;所有细目来源均出自您上传的稿件。(manuscript.docx)


一、逐句修订对照(按小节与句序编号)

记号示例:“[SD-1]”= Study Design and Data Source 第1句;“[PT-3]”= Participants 第3句;以此类推。
处理类型:保留并改写=Keep‑Revise;合并=Merge;移至补充=Move‑Supp;删除重复=Delete‑Dup。

A. Study Design and Data Source

  • [SD‑1] 原句We conducted a retrospective cohort study using MIMIC‑IV v3.1, a publicly available ICU database from Beth Israel Deaconess Medical Center (2008–2019). (manuscript.docx)
    建议修订We performed a single‑center retrospective cohort study using the de‑identified MIMIC‑IV v3.1 database from Beth Israel Deaconess Medical Center (2008–2019).
    处理与理由:Keep‑Revise;补足“single‑center、de‑identified”,符合回顾性表述习惯,语义更凝练。

  • [SD‑2] 原句The database contains de‑identified data and is approved by the BIDMC IRB with a waiver of informed consent. (manuscript.docx)
    建议修订Use of MIMIC‑IV is approved by the BIDMC IRB with waived informed consent owing to de‑identification.
    处理与理由:Keep‑Revise;并列成分前置原因,学术化。

  • [SD‑3] 原句The current analysis was conducted under certification number 13968729 and follows STROBE guidelines. (manuscript.docx)
    建议修订This analysis adhered to STROBE reporting guidelines.
    处理与理由:Merge/Move‑Supp;证书编号属合规细则,正文可省,移至数据合规/致谢或Supplement更妥,保留“遵循STROBE”。


B. Participants

  • [PT‑1] 原句This study identified adult patients (≥18 years) from the MIMIC‑IV database who had cardiogenic shock, defined by specific ICD‑9‑CM (78551, 99801) or ICD‑10‑CM (R570, T8111XA) codes, within the first 24 hours of ICU admission. (manuscript.docx)
    建议修订We included adults (≥18 years) with cardiogenic shock (CS) identified within 24 hours of ICU admission using prespecified ICD‑9‑CM (785.51, 998.01) and ICD‑10‑CM (R57.0, T81.11XA) codes.
    处理与理由:Keep‑Revise;顺序调整为人群→时间窗→编码;将代码格式标准化(带小数点/零);与主题(CS队列)对齐。

  • [PT‑2] 原句For patients with multiple ICU admissions, only the first ICU stay during the initial hospitalization was included. (manuscript.docx)
    建议修订For individuals with multiple ICU stays, the first ICU admission of the index hospitalization was analyzed.
    处理与理由:Keep‑Revise;更简洁。

  • [PT‑3] 原句Exclusion criteria were: (a) ICU length of stay <24 hours (due to potential incompleteness of clinical data); (b) missing albumin or blood urea nitrogen (BUN) measurements on the first ICU day; and (c) missing height or weight data required for body mass index (BMI) calculation. (manuscript.docx)
    建议修订Exclusions were ICU stay <24 h, missing first‑day BUN or albumin, and missing height/weight precluding BMI calculation.
    处理与理由:Keep‑Revise;删冗语,凸显与暴露(BAR)直接相关的排除项。

  • [PT‑4] 原句A total of 1,011 patients were included (Figure 1). (manuscript.docx)
    建议修订The final cohort comprised 1,011 patients (Figure 1).
    处理与理由:Keep‑Revise;规范数字呈现。


C. Exposure

  • [EX‑1] 原句The index time was defined as the time of first ICU admission. (manuscript.docx)
    建议修订Time zero (index) was ICU admission.
    处理与理由:Keep‑Revise;更精炼。

  • [EX‑2] 原句The primary exposure was the BAR, calculated using the earliest available BUN and albumin values measured within the first 24 hours of ICU admission. (manuscript.docx)
    建议修订The exposure was the blood urea nitrogen‑to‑albumin ratio (BAR) computed from the earliest BUN (mg/dL) and albumin (g/dL) within 24 h of ICU admission.
    处理与理由:Keep‑Revise;补单位,贴合主题。

  • [EX‑3] 原句When multiple measurements existed in this window, we used the earliest valid value for laboratory tests; units were harmonized a priori before computing BAR. (manuscript.docx)
    建议修订If multiple results were available, the earliest valid value was used; units were standardized a priori.
    处理与理由:Keep‑Revise;保留必要性,语序优化。

  • [EX‑4] 原句For analysis, BAR was examined both as a continuous variable (with assessment for nonlinearity) and as ordinal categories (tertiles). (manuscript.docx)
    建议修订BAR was modeled continuously (with nonlinearity assessment) and by tertiles.
    处理与理由:Keep‑Revise;精炼无损信息。


D. Outcomes

  • [OC‑1] 原句The primary outcome was 30‑day all‑cause mortality from the index time. (manuscript.docx)
    建议修订The primary outcome was 30‑day all‑cause mortality from index.
    处理与理由:Keep‑Revise;学术惯式。

  • [OC‑2] 原句Secondary outcomes included all‑cause mortality at 60, 120, and 365 days. (manuscript.docx)
    建议修订Secondary outcomes were 60/120/365‑day all‑cause mortality.
    处理与理由:Keep‑Revise;并列紧凑。

  • [OC‑3] 原句Time zero was defined as ICU admission, and surviving or censored patients were right‑censored at the date of last record in the database. (manuscript.docx)
    建议修订Patients were right‑censored at the last known alive date in MIMIC‑IV.
    处理与理由:Keep‑Revise;避免重复“time zero”。


E. Covariates

  • [CV‑1] 原句Covariates were selected a priori based on clinical relevance and prior literature and were restricted to information available at or before the index time to avoid immortal-time or look-ahead bias. (manuscript.docx)
    建议修订Covariates were pre‑specified from clinical relevance/literature and restricted to baseline (≤24 h) to limit immortal‑time/look‑ahead bias.
    处理与理由:Keep‑Revise;把“≤24h”与方法主题对齐。

  • [CV‑2] 原句(长列表)They included: demographics (age, sex, race), illness severity (SOFA and SAPS II …), comorbidities…, vital signs and laboratory tests…, and critical‑care interventions… (manuscript.docx)
    建议修订Domains included demographics, illness‑severity scores (SOFA, SAPS II), comorbidities, first‑day vitals/laboratories, and early interventions (IMV, renal replacement, vasopressors).
    处理与理由:Keep‑Revise;正文保留“域级别”即可;详表移Supplement。

  • [CV‑3] 原句All continuous covariates were assessed for distributional assumptions and transformed or categorized if needed. (manuscript.docx)
    建议修订Continuous covariates were checked and transformed/categorized as appropriate.
    处理与理由:Keep‑Revise;简化术语。

  • [CV‑4] 原句Detailed variable definitions, code lists, units/conversions, and physiologic plausibility ranges are provided in Supplementary Table S1. (manuscript.docx)
    建议修订Operational definitions, code lists, and unit conventions appear in eTable S1.
    处理与理由:Keep‑Revise;引用统一。

  • [CV‑5] 原句Summary statistics and missing value proportions for all continuous variables are presented in Supplementary Table S1. (manuscript.docx)
    建议修订Baseline summaries and missingness are reported in eTable S1.
    处理与理由:Keep‑Revise;合并措辞,避免与后文重复。


F. Data preprocessing and missing data

  • [MS‑1] 原句Variables with >20% missingness were excluded from primary multivariable models; (including HbA1c, lipid profiles …) were excluded from primary multivariable models and considered only in sensitivity analyses. (manuscript.docx)
    建议修订Variables with >20% missingness were excluded from primary models and considered only in sensitivity analyses (details in eTable S1–S2).
    处理与理由:Keep‑Revise;去掉括号内长清单,放Supplement。

  • [MS‑2] 原句For variables with ≤20% missingness, we performed multiple imputation by chained equations (m=20 …). (manuscript.docx)
    建议修订For ≤20% missingness, we applied multiple imputation by chained equations (m=20) using standard models per variable type; estimates were pooled by Rubin’s rules.
    处理与理由:Keep‑Revise;保留关键信息,删冗句。

  • [MS‑3] 原句The imputation model incorporated the exposure, outcomes, and all baseline covariates (no post-index data). (manuscript.docx)
    建议修订Imputation used pre‑index exposure, outcomes, and baseline covariates only.
    处理与理由:Keep‑Revise;更紧凑。

  • [MS‑4] 原句Primary analyses were conducted on the imputed datasets, with complete‑case analyses performed for sensitivity assessment. (manuscript.docx)
    建议修订Primary estimates derived from imputed datasets; complete‑case analyses served as sensitivity checks.
    处理与理由:Keep‑Revise。

  • [MS‑5] 原句For machine learning analyses, all preprocessing steps … within each resampling fold to prevent information leakage. (manuscript.docx)
    建议修订Preprocessing for exploratory ML was performed within resampling folds to avoid information leakage (Supplement).
    处理与理由:Move‑Supp;正文一句带锚点即可。

  • [MS‑6] 原句(与统计描述重复出现一次):All continuous variables exhibited non‑normal distributions … summarized as medians (IQR) and compared using non‑parametric tests … (manuscript.docx)
    建议修订:** 删除重复**(此信息在“Statistical analysis”已充分表述)。
    处理与理由:Delete‑Dup;避免同段落重复。


G. Statistical analysis

  • [ST‑1] 原句Continuous variables were reported as medians (IQRs) and compared with Kruskal–Wallis tests; categorical variables as counts (%) with χ² or Fisher tests. (manuscript.docx)
    建议修订Baseline characteristics are presented as median (IQR) or n (%) and compared by Kruskal–Wallis or χ²/Fisher tests, as appropriate.
    处理与理由:Keep‑Revise;一次到位,无需再在其他段落重复。

  • [ST‑2] 原句The primary exposure (BAR) was analyzed continuously and by tertiles with tests for trend. (manuscript.docx)
    建议修订BAR was evaluated per unit and by tertiles with trend tests.
    处理与理由:Keep‑Revise。

  • [ST‑3] 原句Time‑to‑event analyses used Kaplan–Meier/log‑rank and Cox proportional‑hazards models at 30, 60, 120, and 365 days with hierarchical adjustment… (manuscript.docx)
    建议修订Time‑to‑event analyses used Kaplan–Meier/log‑rank and Cox models at 30/60/120/365 days, with pre‑specified hierarchical adjustment (Model 1–3).
    处理与理由:Keep‑Revise;与后续模型说明呼应。

  • [ST‑4] 原句Proportional‑hazards assumptions were checked (Schoenfeld). Nonlinearity was evaluated with restricted cubic splines. (manuscript.docx)
    建议修订We tested proportional‑hazards (Schoenfeld) and assessed nonlinearity with restricted cubic splines.
    处理与理由:Keep‑Revise。

  • [ST‑5] 原句Prespecified subgroup/interaction and sensitivity analyses (alternative codings, covariate specifications, extreme‑value trimming, complete‑case) were conducted. (manuscript.docx)
    建议修订Prespecified subgroup/interaction and sensitivity analyses (alternative codings, extreme‑value trimming, complete‑case) were performed.
    处理与理由:Keep‑Revise;删重复语。

  • [ST‑6] 原句Missing‑data handling is described elsewhere; primary estimates used imputed datasets. (manuscript.docx)
    建议修订Primary inference used the imputed datasets (details in eMethods).
    处理与理由:Keep‑Revise;与缺失值段落衔接。

  • [ST‑7] 原句(模型层级与协变量长清单,出现两次)
    建议修订(合并)
    Model 1: BAR only; Model 2: + age, sex, race, BMI; Model 3 (fully adjusted): Model 2 + key comorbidities, SOFA/SAPS II, core laboratories (creatinine, lactate, INR), and early interventions (IMV, CRRT). Collinearity was checked; continuous covariates were modeled flexibly. (manuscript.docx)
    处理与理由:Merge;一次交代,去掉在后段重复的相同句群与过长变量清单(移Supplement)。

  • [ST‑8] 原句As secondary validation, a cross‑validated ML pipeline … discrimination, calibration, and clinical utility. (manuscript.docx)
    建议修订An exploratory, cross‑validated ML pipeline evaluated discrimination, calibration, and decision utility (Supplement).
    处理与理由:Move‑Supp;与主题保持“Cox为主、ML为辅”。

  • [ST‑9] 原句Two‑sided α=0.05. (manuscript.docx)
    建议修订Two‑sided tests with α=0.05 were used.
    处理与理由:Keep‑Revise;规范。


二、整合后的《Methods》精炼终稿(可直接替换正文)

Methods(字数与结构符合回顾性队列常规做法;ML 细节与变量长清单均用 Supplement 锚点承接)

Study Design and Data Source.
We performed a single‑center retrospective cohort study using the de‑identified MIMIC‑IV v3.1 database from Beth Israel Deaconess Medical Center (2008–2019). Use of MIMIC‑IV is approved by the BIDMC IRB with waived informed consent owing to de‑identification. This analysis adhered to STROBE reporting guidelines. (manuscript.docx)

Participants.
We included adults (≥18 years) with cardiogenic shock (CS) identified within 24 hours of ICU admission using prespecified ICD‑9‑CM 785.51/998.01 and ICD‑10‑CM R57.0/T81.11XA codes. For individuals with multiple ICU stays, the first ICU admission of the index hospitalization was analyzed. Exclusions were ICU stay <24 h, missing first‑day BUN or albumin, and missing height/weight for BMI. The final cohort comprised 1,011 patients (Figure 1). (manuscript.docx)

Exposure.
The exposure was the blood urea nitrogen‑to‑albumin ratio (BAR) computed from the earliest BUN (mg/dL) and albumin (g/dL) measured within 24 h of ICU admission; the earliest valid value was used when multiple results were available, with units standardized a priori. BAR was modeled continuously and by tertiles. (manuscript.docx)

Outcomes.
The primary outcome was 30‑day all‑cause mortality. Secondary outcomes were 60/120/365‑day all‑cause mortality. Time origin was ICU admission; patients were right‑censored at the last known alive date in MIMIC‑IV. (manuscript.docx)

Covariates.
Covariates were pre‑specified from clinical relevance and literature and restricted to baseline (≤24 h) to limit immortal‑time/look‑ahead bias. Domains included demographics, illness‑severity scores (SOFA, SAPS II), comorbidities, first‑day vitals/laboratories, and early interventions (IMV, renal replacement, vasopressors). Operational definitions, code lists, unit conventions, and missingness summaries are provided in eTable S1–S2. (manuscript.docx)

Data Preprocessing and Missing Data.
Variables with >20% missingness were excluded from primary models and analyzed only in sensitivity analyses. For variables with ≤20% missingness, we used multiple imputation by chained equations (m=20) according to variable type; estimates were pooled by Rubin’s rules. Primary inference used the imputed datasets; complete‑case results served as sensitivity checks (details in eMethods/eTable S2). (manuscript.docx)

Statistical Analysis.
Baseline characteristics are presented as median (IQR) or n (%) and compared by Kruskal–Wallis or χ²/Fisher tests, as appropriate. Time‑to‑event analyses used Kaplan–Meier/log‑rank and Cox models at 30/60/120/365 days. Model 1 included BAR only; Model 2 adjusted for age, sex, race, and BMI; Model 3 additionally adjusted for key comorbidities, SOFA/SAPS II, core laboratories (creatinine, lactate, INR), and early interventions (IMV, CRRT). We tested proportional‑hazards (Schoenfeld), assessed nonlinearity with restricted cubic splines, and performed prespecified subgroup/interaction and sensitivity analyses (alternative codings, extreme‑value trimming, complete‑case). Two‑sided α=0.05 was used. An exploratory, cross‑validated ML pipeline evaluated discrimination, calibration, and decision utility (Supplement). (manuscript.docx)


三、删改与移补清单(便于排版与响应审稿意见)

  1. 删除重复:将“Shapiro–Wilk均P<0.0001,因此以中位数(IQR)/Kruskal–Wallis、χ²或Fisher”这类描述性统计语句在Methods中保留一次(见 Statistical Analysis 首句),其余位置删去。(manuscript.docx)
  2. 合并模型说明:模型层级与协变量清单在“Statistical Analysis”集中一次性交代,避免在后段再次出现同样的长段落。(manuscript.docx)
  3. 移至补充材料
    • 变量长清单、单位换算与缺失比例(eTable S1–S2);
    • 多重插补的建模细节与参数(eMethods);
    • 机器学习的算法、调参、重采样与图(eFigures/eTables)。(manuscript.docx)
  4. 可移出正文的信息:认证编号“13968729”——留在“Data availability/Compliance”或Supplement即可,不必占正文。(manuscript.docx)

四、与研究主题的“侧重点”对齐提示

  • 暴露定义(BAR)与时间窗(首24h)结局(30天为主,60/120/365天为次)Cox为主+RCS检验非线性三处加粗/首句呈现,形成主题“早期BAR—多时点死亡”的清晰主线。
  • ML仅作“探索性补充”,正文一句带锚点即可,避免喧宾夺主。(manuscript.docx)

如需,我可以把上述《Methods》终稿按您目标期刊的字数/格式(如心内科/重症领域期刊的字数上限、图表位次、Supplement命名)再做一次版面级微调,并在Word中套用修订痕迹(Track Changes),方便与合作者沟通。

질문

image.pngimage.png

Continuous variables conforming to a normal distribution were presented as mean and standard deviation, whereas the others were reported as median and interquartile range. Categorical variables were expressed as percentages. All analyses were run in R Studio (version 4.4.1), with a significance threshold at p < 0.005 in the Bonferroni-adjusted subgroup analysis, while a significance threshold of p < 0.05 was used for the rest of the analysis. First, BAR levels were analyzed across the low, intermediate, and high-risk groups, which were categorized according to the tertiles of Acute Physiology Score III (APS III) and Sequential Organ Failure Assessment (SOFA).
Moreover, Kaplan-Meier survival curves stratified by BAR tertiles were employed to evaluate the risk of allcause mortality. To minimize confounding bias, BAR tertiles were treated as a categorical characteristic (T1 as the reference), a rank variable (one-tertile increment), and a continuous characteristic (per unit increase) in Cox proportional hazards models. These models, adjusted for various confounders, were used to calculate the hazard ratio (HR) for all-cause mortality, and a linear trend test was applied. Confounders were considered based on previous research and clinical experience, including demographics, markers of inflammation and anemia, liver and kidney function, therapy-related factors (drugs and devices), and disease severity (as indicated by SOFA and APS III scores). In Model 0, only BAR was included. In Model 1, age, gender, neutrophil, hemoglobin, total bilirubin, and creatinine levels were adjusted. Model 2 was further adjusted for inotropes or vasopressors, ventilation, and CRRT. In Model 3, the SOFA and APS III scores were additionally included. Additionally, these analyses were reproduced in patients with LVEF data. Specifically, LVEF was included in the analysis as a possible confounding factor. Furthermore, restricted cubic spline (RCS) analysis was employed to investigate the dose-response effect of BAR on mortality, with threshold effect analysis performed as necessary across all the patients. Similarly, this analysis was replicated in patients with LVEF data. Subgroup analysis and interaction testing were conducted using Model 3 to assess the prognostic value of BAR across different patient populations. These analyses considered factors such as age (≤ 65 vs. >65 years), gender, presence of hypertension or diabetes, use of inotropes or vasopressors, ventilation, and CRRT. Interaction terms, including serum creatinine × BAR, BUN × BAR, ALT × BAR, and ALP × BAR, were added to the models to evaluate the continuous interaction between these variables and BAR, with the results visualized using RCS. In addition, differences in predictive power were compared between BAR, BUN, and albumin, using receiver operating characteristic (ROC) curves and the DeLong test. Finally, to verify the robustness of the findings, relative risks (RRs) for BAR tertiles across both 6-month and 1-year periods were calculated using modified Poisson regression.
参照这个写作习惯(不要参考具体内容),修改我的手稿的写作表达

사고

Rewritten method expressions

I’m focusing on aligning the manuscript's "Statistical analysis" style with the provided habit, ensuring clarity and conciseness without duplicating specific content.

Polishing manuscript sections

I’m honing the manuscript by refining Method sections, maintaining clarity and conciseness, and adhering to the provided writing style while including necessary citations and translations.

Crafting the replacement

I’m transforming the "Statistical analysis" section into a concise, academic style, maintaining the user's style habits and including citations and optional translations for clarity.

Reasoned for 4m 9s

답변

下面给你两部分内容:
A)把你“Statistical analysis / 数据处理与统计学”逐条改写为更学术、简练且有侧重的表达(可直接替换到手稿里);
B)给出“原句位置 → 建议替换句 → 处理理由”的对应清单,便于你在文档中定位和逐句替换。改写仅改变表达,不改变你原有的分析方案与结论。改写依据为你当前手稿 Methods 与 Statistical analysis 段落。(manuscript.docx)


A)可直接替换的精炼版本(英文)

Statistical analysis
All analyses were performed in R (R Foundation). Baseline characteristics are summarized as median (IQR) for continuous variables and n (%) for categorical variables; group comparisons used Kruskal–Wallis and χ²/Fisher tests, as appropriate. Two‑sided p < 0.05 denoted statistical significance. (manuscript.docx)

We evaluated the prognostic association between BAR measured within 24 h of ICU admission and all‑cause mortality at 30/60/120/365 days in three steps. First, Kaplan–Meier curves with log‑rank tests compared survival across prespecified BAR tertiles (T1–T3). Second, Cox proportional‑hazards models quantified the association treating BAR as (i) tertiles (T1 reference), (ii) an ordinal variable (per‑tertile increase), and (iii) a continuous variable (per 1 mg·g⁻¹ increase). A hierarchical adjustment strategy was prespecified: Model 1 (BAR only); Model 2 (+ age, sex, race, BMI); Model 3 (+ key comorbidities, illness‑severity scores SOFA/SAPS II, core laboratories creatinine, lactate, INR, and early interventions IMV/CRRT). Trend tests treated tertiles as ordered categories. Proportional‑hazards assumptions were checked using Schoenfeld residuals, and the functional form of continuous BAR was examined with restricted cubic splines. Third, prespecified subgroup and interaction analyses assessed heterogeneity across demographic and clinical strata (e.g., age, sex, comorbidities, SAPS II strata, IMV/CRRT). (manuscript.docx)

Missing data were handled as follows: variables with >20% missingness were excluded from primary multivariable models and considered only in sensitivity analyses; variables with ≤20% missingness underwent multiple imputation by chained equations (m = 20) restricted to pre‑index information (exposure, outcomes, baseline covariates). Estimates were pooled by Rubin’s rules. Primary inference used the imputed datasets; complete‑case analyses, alternative codings, and extreme‑value trimming served as sensitivity checks (details in Supplement). (manuscript.docx)

An exploratory, cross‑validated machine‑learning pipeline for 30‑day mortality (algorithms, discrimination/calibration, and decision‑curve analysis) is described in the Supplement; all preprocessing occurred within resampling folds to avoid information leakage. (manuscript.docx)

上述文本采用与您给出的“写作习惯示例”一致的节奏(First/Second/Third、分层模型、先主后次、先统计主线后补充说明),但不引入示例中的具体设定(如特定的Bonferroni阈值或APS‑III分层)。侧重点始终围绕“ICU首日BAR → 多时点死亡”。


B)逐句定位与替换清单(原句位置 → 建议替换句 → 理由)

记号说明:

  • [SA‑x] = Methods ▸ Statistical analysis 第 x 句/句群;
  • [MD‑x] = Methods ▸ Data preprocessing and missing data 第 x 句/句群。
    位置标注以你稿件当前版本为准。均来自同一文件。(manuscript.docx)
  1. [SA‑1] 原句:“Continuous variables were reported as medians (IQRs) … categorical variables as counts (%) with χ² or Fisher tests.”
    替换:** “Baseline characteristics are summarized as median (IQR) for continuous variables and n (%) for categorical variables; group comparisons used Kruskal–Wallis and χ²/Fisher tests, as appropriate.”**
    理由:合并叙述、去除重复,语序更紧凑。(manuscript.docx)

  2. [SA‑2] 原句:“The primary exposure (BAR) was analyzed continuously and by tertiles with tests for trend.”
    替换:** “BAR was modeled as tertiles (T1 reference), as an ordinal variable (per‑tertile increase), and as a continuous variable (per 1 mg·g⁻¹ increase), with trend tests for ordered categories.”**
    理由:与后续分层模型衔接,突出三种建模视角。(manuscript.docx)

  3. [SA‑3] 原句:“Time‑to‑event analyses used Kaplan–Meier/log‑rank and Cox … with hierarchical adjustment …”
    替换:** “We used Kaplan–Meier with log‑rank for unadjusted comparisons and Cox models at 30/60/120/365 days with prespecified hierarchical adjustment (Model 1–3).”**
    理由:保留核心方法并压缩描述。(manuscript.docx)

  4. [SA‑4] 原句:“Proportional‑hazards assumptions were checked (Schoenfeld). Nonlinearity was evaluated with restricted cubic splines.”
    替换:** “Proportional‑hazards were tested using Schoenfeld residuals; nonlinearity of continuous BAR was assessed with restricted cubic splines.”**
    理由:术语标准化、主语一致。(manuscript.docx)

  5. [SA‑5] 原句:“Prespecified subgroup/interaction and sensitivity analyses … were conducted.”
    替换:** “Prespecified subgroup and interaction analyses assessed heterogeneity across demographic and clinical strata; sensitivity analyses included alternative codings, extreme‑value trimming, and complete‑case estimation.”**
    理由:明确目的(heterogeneity),并列结构更清晰。(manuscript.docx)

  6. [SA‑6] 原句:“Missing‑data handling is described elsewhere; primary estimates used imputed datasets.”
    替换:** “Primary inference used the imputed datasets; details of missing‑data handling appear in the Supplement.”**
    理由:与“Missing data”段落前后呼应。(manuscript.docx)

  7. [SA‑7] 原句(模型清单):“… hierarchical adjustment (none; age/sex/race; +SOFA, SAPS II, key comorbidities, creatinine, lactate, INR, invasive ventilation, renal replacement).”
    替换:** “Model 1: BAR only; Model 2: + age, sex, race, BMI; Model 3: + key comorbidities, SOFA/SAPS II, core laboratories (creatinine, lactate, INR), and early interventions (IMV/CRRT).”**
    理由:按“从少到多”明确三层模型,术语统一。(manuscript.docx)

  8. [SA‑8] 原句:“As secondary validation, a cross‑validated ML pipeline … assessed discrimination, calibration, and clinical utility.”
    替换:** “An exploratory, cross‑validated machine‑learning pipeline for 30‑day mortality (algorithms, discrimination/calibration, decision‑curve analysis) is detailed in the Supplement; all preprocessing occurred within resampling folds to avoid leakage.”**
    理由:定性为“exploratory”,保留关键信息并外移细节。(manuscript.docx)

  9. [SA‑9] 原句:“Two‑sided α=0.05.”
    替换:** “Two‑sided p < 0.05 denoted statistical significance.”**
    理由:期刊常用写法。(manuscript.docx)

  10. [MD‑1] 原句:“Variables with >20% missingness were excluded … considered only in sensitivity analyses.”
    替换:** “Variables with >20% missingness were excluded from primary multivariable models and analyzed only in sensitivity analyses.”**
    理由:压缩重复成分。(manuscript.docx)

  11. [MD‑2] 原句:“For variables with ≤20% missingness, we performed multiple imputation by chained equations (m=20 … predictive mean matching … logistic … polytomous …).”
    替换:** “Variables with ≤20% missingness were multiply imputed using chained equations (m = 20) restricted to pre‑index information; estimates were pooled by Rubin’s rules.”**
    理由:保留必要要点,技术细节移补充材料。(manuscript.docx)

  12. [MD‑3] 原句:“Primary analyses were conducted on the imputed datasets, with complete‑case analyses performed for sensitivity assessment.”
    替换:** “Primary inference used the imputed datasets; complete‑case analyses served as sensitivity checks.”**
    理由:学术化、精炼。(manuscript.docx)

  13. [SA/MD‑重复] 原句:“All continuous variables exhibited non‑normal distributions… summarized as medians (IQR) … compared using non‑parametric tests …”
    处理:** 删除重复**(保留在“Statistical analysis”第一句的总体说明即可)。
    理由:避免冗余、符合期刊对 Methods 简洁性的要求。(manuscript.docx)


小提示(与“写作习惯示例”保持风格一致)

  • 步骤词增强逻辑:First/Second/Third
  • 先交代主线分析(BAR→KM→Cox→RCS),再提补充/敏感性(subgroup、sensitivity、ML);
  • 模型用Model 1–3明示递进;统计阈值统一为two‑sided p < 0.05(若你要做严格多重校正,可在 Supplement 标注 Bonferroni/FDR 的备用阈值)。

如需,我可以把以上替换句直接套进你的Word并打上修订痕迹(Track Changes),保证与正文、表图编号和 Supplement 锚点完全一致。

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