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        認(rèn)知損傷與老年人全死因死亡率關(guān)系的Meta分析

        2021-04-12 00:00:00王宇鞏秀珍翟鴻瑞姜文潔

        [摘要]"目的 評估老年人認(rèn)知功能損傷與全死因死亡率的相關(guān)性。方法 在PubMed、Web of Science、萬方和中國知網(wǎng)中檢索自建庫至2019年12月期間發(fā)表的關(guān)于簡易精神狀態(tài)量表(MMSE)評估的認(rèn)知功能損傷與全死因死亡率關(guān)聯(lián)的研究文獻(xiàn),提取符合納入標(biāo)準(zhǔn)的文獻(xiàn)數(shù)據(jù)并進(jìn)行Meta分析。采用固定或隨機(jī)效應(yīng)模型計算風(fēng)險比(HR)及其95%置信區(qū)間(CI),使用限制性立方樣條評估劑量-反應(yīng)關(guān)系。結(jié)果 共納入42項隊列研究,全死因死亡風(fēng)險與認(rèn)知功能損傷之間的關(guān)聯(lián)具有統(tǒng)計學(xué)意義(HR=1.64,95%CI=1.51~1.78);對最輕程度的認(rèn)知損傷進(jìn)行單獨合并以最大程度排除癡呆影響,結(jié)果同樣具有統(tǒng)計學(xué)意義(HR=1.33,95%CI=1.24~1.43)。經(jīng)MMSE檢測的認(rèn)知功能損傷與全死因死亡風(fēng)險之間有線性劑量-反應(yīng)關(guān)系(P=0.06)。與正常認(rèn)知相比,MMSE評分每降低1分,全死因死亡風(fēng)險增加4%(HR=1.04,Plt;0.001)。結(jié)論 經(jīng)MMSE篩查的認(rèn)知功能損傷可能是老年人全死因死亡的重要預(yù)測指標(biāo)。

        [關(guān)鍵詞]"認(rèn)知功能障礙;死亡率;老年人;Meta分析

        [中圖分類號]"R749.1

        [文獻(xiàn)標(biāo)志碼]"A

        [文章編號]"2096-5532(2021)04-0544-07

        認(rèn)知功能損傷是癡呆和輕度認(rèn)知障礙(MCI)最關(guān)鍵的診斷標(biāo)準(zhǔn)之一,可能反映出了不健康的生活方式、共病狀態(tài)和整體老化等[1]。不佳的認(rèn)知表現(xiàn)與多種不良結(jié)局有關(guān),例如衰弱、跌倒和入院率增高等。然而,認(rèn)知損傷與死亡是否獨立相關(guān)仍有爭議,尚未被推薦用于全死因死亡率的風(fēng)險評估。這可能是由于:①認(rèn)知功能障礙常與癡呆共存,可能不是一個獨立的預(yù)測指標(biāo);②在現(xiàn)有研究中,不良認(rèn)知功能的死亡率風(fēng)險大小不一致,尤其是輕度認(rèn)知損害。雖然既往有系統(tǒng)綜述顯示,患有認(rèn)知功能障礙的老年人全死因死亡率增加,但目前仍然缺乏定量評估和劑量-反應(yīng)關(guān)系研究[2]。本文對認(rèn)知功能損傷和全死因死亡率的關(guān)聯(lián)進(jìn)行了Meta分析。由于認(rèn)知受損的定義不同影響了研究之間的可比性,因此本文選擇了臨床使用最廣泛的簡易精神狀態(tài)檢查量表(MMSE)以及包含MMSE的組合量表作為篩選工具[3],以系統(tǒng)地評估老年人認(rèn)知功能損傷與全死因死亡率風(fēng)險之間的關(guān)聯(lián)和潛在劑量-反應(yīng)關(guān)系。

        1"資料與方法

        1.1"文獻(xiàn)檢索

        檢索PubMed、Web of Science、萬方和中國知網(wǎng)等數(shù)據(jù)庫中的中英文文獻(xiàn),時間為建庫至2019年12月。英文檢索詞為“cognition”(或“cognitive function”、“cognitive”、“neuropsychology”、“neuropsychological”)和“mortality”(或“death”)和“prospective”(或“cohort”、“nested case-control study”、“case-cohort study”、“l(fā)ongitudinal”、“follow up”、“follow-up”)和“old”(或“aged”、“aging”、“ageing”、“elder”、“geriatric”、“senior”、“community”、“ge-neral population”);中文檢索詞為“認(rèn)知”和“死亡”和“前瞻性”。閱讀文題和摘要后排除無關(guān)文獻(xiàn),閱讀全文后根據(jù)納入和排除標(biāo)準(zhǔn)進(jìn)一步篩選出相關(guān)文章,并對入選文獻(xiàn)中的參考文獻(xiàn)進(jìn)行了手工檢索。文獻(xiàn)篩檢由兩人獨立進(jìn)行。如意見不一,則通過討論達(dá)成共識。

        1.2"納入和排除標(biāo)準(zhǔn)

        文獻(xiàn)的納入標(biāo)準(zhǔn)為:①原創(chuàng)前瞻性觀察研究(包括隊列研究、巢式病例對照研究和病例隊列研究);②研究對象為老年人群(≥60歲);③暴露為基線時使用MMSE評估的認(rèn)知功能;④結(jié)局為全死因死亡;⑤提供相對危險度(RR)或危險比(HR)及其95%置信區(qū)間(CI),或可經(jīng)計算得出;⑥如果同一人群數(shù)據(jù)在多個研究中重復(fù)出現(xiàn),則選擇最為詳盡的數(shù)據(jù)。排除標(biāo)準(zhǔn)為:①研究對象為特定疾病人群;②數(shù)據(jù)或隊列重復(fù);③未調(diào)整混雜因素。

        1.3"數(shù)據(jù)提取

        由兩位研究員使用統(tǒng)一的數(shù)據(jù)收集表,獨立提取數(shù)據(jù),包括第一作者姓名、出版年份、研究對象的年齡和性別、隨訪時間、總樣本量和死亡人數(shù)、基線認(rèn)知功能的測量方法、正常認(rèn)知功能的截斷值、HR和95%CI,以及所調(diào)整的潛在混雜因素。劑量-反應(yīng)分析數(shù)據(jù)包括MMSE評分每個等級(至少3個劑量等級)的研究對象(觀察人年數(shù))、死亡人數(shù)、HR與95%CI。每個等級MMSE評分的中位水平被用來估計相應(yīng)HR的劑量-反應(yīng)關(guān)系。提取調(diào)整因素最多的HR,以最大程度上對潛在混雜因素進(jìn)行控制。使用紐爾斯卡-渥太華量表(NOS)從選擇性、可比性和結(jié)局方面評估納入文獻(xiàn)各隊列研究的質(zhì)量。

        1.4"統(tǒng)計分析方法

        采用STATA 15.0軟件進(jìn)行統(tǒng)計分析。用HR值及其95%CI的倒數(shù)逆方差的加權(quán)平均數(shù)估計認(rèn)知功能受損與全死因死亡率之間的關(guān)系。采用I2評價研究間的異質(zhì)性,以25%、50%和75%的I2值分別代表低、中、高異質(zhì)性。異質(zhì)性較?。↖2lt;50%)時采用固定效應(yīng)模型(FEM)合并效應(yīng)量,而異質(zhì)性處于中至重度(I2≥50%)時則采用隨機(jī)效應(yīng)模型(REM)合并效應(yīng)量,同時繪制森林圖。按地區(qū)、年齡、隨訪時間、樣本量、研究質(zhì)量和15個協(xié)變量(基線癡呆、基線虛弱、收入、體質(zhì)量指數(shù)、抑郁、體育活動、教育、日?;顒?、血壓、血清膽固醇、吸煙、飲酒、糖尿病、心血管疾病、癌癥)等進(jìn)行亞組分析。使用Meta回歸探討潛在的異質(zhì)性來源。使用影響性分析評估單一研究是否會顯著影響評估結(jié)果。以I2gt;50%為標(biāo)準(zhǔn)進(jìn)行敏感度分析,驗證結(jié)論的穩(wěn)健性。使用漏斗圖和Egger檢驗法評估發(fā)表偏倚。

        采用兩階段的REM進(jìn)行劑量-反應(yīng)關(guān)系Meta分析:在第一階段,應(yīng)用3節(jié)點的限制性立方樣條模型和廣義最小二乘回歸模型來分析劑量-反應(yīng)關(guān)系;第二階段,使用最大似然法合并效應(yīng)值。

        并對第二個樣條的回歸系數(shù)β2進(jìn)行顯著性檢驗以判斷劑量-反應(yīng)關(guān)系的非線性部分。以27分(正常認(rèn)知范圍的中間值[3])為參考值,評價較低MMSE評分與老年人全死因死亡率之間的劑量-反應(yīng)關(guān)系。所有檢驗均為雙側(cè)檢驗,以Plt;0.05為差異有統(tǒng)計學(xué)意義。

        2"結(jié)"果

        2.1"納入文獻(xiàn)特征

        經(jīng)文獻(xiàn)檢索和篩選,共納入38篇文獻(xiàn)[4-41],其中4篇文獻(xiàn)僅按照性別分層分析[13,16,20,41]。共計42個研究,包含了95 064例參與者,其中有29 269例在隨訪期內(nèi)死亡。文獻(xiàn)檢索的過程見圖1。

        本文42項研究中,14項源于亞洲、15項源于歐洲、10項源于北美、1項源于南美洲、2項源于澳大利亞;隨訪時間為1.25~20.00年,隨訪時間gt;10.00年研究有12項;參加者人數(shù)205~12 552人;研究質(zhì)量評分范圍為6~9星。納入研究的基線特征信息見表1。

        2.2"認(rèn)知功能損傷與全死因死亡率的Meta分析

        與認(rèn)知功能正常者相比,不同程度的損傷與總死亡風(fēng)險增加之間的關(guān)聯(lián)有統(tǒng)計學(xué)意義(n=42;HR=1.64,95%CI=1.51~1.78;I2=81.3%;REM),該關(guān)聯(lián)在80歲以上的高齡老人中同樣存在(n=8;HR=1.53,95%CI=1.19~1.97;I2=86.6%)。為最大程度排除癡呆影響,本文對最輕程度的認(rèn)知損傷研究進(jìn)行單獨合并,結(jié)果仍具有統(tǒng)計學(xué)意義(n=20;HR=1.33,95%CI=1.24~1.43;I2=66.3%;REM)。對不同地區(qū)的文獻(xiàn)分析表明,北美洲(n=10;HR=1.58,95%CI=1.33~1.89)、南美洲(n=1;HR=1.91,95%CI=1.83~2.00)、歐洲(n=15;HR=1.63,95%CI=1.40~1.89)、亞洲(n=14;HR=1.67,95%CI=1.39~2.01)和澳大利亞(n=2;HR=1.65,95%CI=1.34~2.03)研究顯示認(rèn)知損傷與全死因死亡率的增加均相關(guān)。見圖2、3。

        當(dāng)研究排除或調(diào)整了基線癡呆時,認(rèn)知功能損傷與死亡率之間的關(guān)聯(lián)仍具有統(tǒng)計學(xué)意義(n=6;HR=1.44,95%CI=1.29~1.59)。在不調(diào)整基線癡呆的研究中,合并HR為1.69(n=36;95%CI=1.54~1.85)。見表2。

        2.3"劑量-反應(yīng)關(guān)系

        在劑量-反應(yīng)關(guān)系分析中,使用了10項研究的數(shù)據(jù)[4,10,18-19,24,26,29-30,32,34],共包含了12 010例死亡病例。由MMSE測量的認(rèn)知功能狀態(tài)與全死因死亡風(fēng)險之間呈線性關(guān)系(P=0.06)。見圖4。與參考值27分相比,全死因死亡的風(fēng)險隨著認(rèn)知功能的降低而顯著增加,MMSE每降低1分,死亡風(fēng)險增加4%(HR=1.04,Plt;0.001)。

        2.4"異質(zhì)性來源和敏感度分析

        本研究結(jié)果顯示,各研究間有較高的異質(zhì)性(I2=81.3%)?;€是否調(diào)整衰弱(P=0.005)和基線血脂水平是異質(zhì)性來源(P=0.023)。鑒于從研究變量層面不能充分解釋異質(zhì)性,為了評估結(jié)果的穩(wěn)健性,本文以I2gt;50%為標(biāo)準(zhǔn)進(jìn)行敏感度分析。在排除了9項導(dǎo)致較大異質(zhì)性的研究后,認(rèn)知功能損害所導(dǎo)致的全死因死亡風(fēng)險為1.56(95%CI=1.45~1.66;I2=45.9%;REM;n=33),異質(zhì)性I2顯著降低,而合并HR無明顯變化。影響性分析結(jié)果顯示,沒有單個研究對總合并效應(yīng)值產(chǎn)生顯著影響。

        2.5"發(fā)表偏倚

        漏斗圖顯示,各研究在總HR值的兩側(cè)分布基本對稱,Egger檢驗也未發(fā)現(xiàn)發(fā)表偏倚(P=0.205)。見圖5。

        3"討"論

        本文對納入的42項研究進(jìn)行了Meta分析。結(jié)果顯示,基線整體認(rèn)知功能可能是老年人群中全死因死亡的中等強(qiáng)度預(yù)測因子,即使是最輕微的認(rèn)知受損也與死亡率增加顯著相關(guān)。全死因死亡率與認(rèn)知功能呈線性關(guān)系,MMSE每降低1分,全死因死亡率增加4%。

        本文納入文獻(xiàn)充分考慮到了潛在的混雜因素。年齡是所有研究中最重要的混雜因素。在納入的42項研究中,37項研究調(diào)整了年齡,3項研究使用了出生隊列[13,21,30],1項研究的研究對象基線年齡限制在75~83歲[16],1項研究的基線年齡限制在65歲及以上[35]。5項研究對基線診斷的癡呆進(jìn)行了調(diào)整或排除[12,27,34,36,39]。1項研究排除了MMSE評分低于18分的參與者[22],這相當(dāng)于排除了基線癡呆。大多數(shù)研究對研究對象的受教育程度進(jìn)行了調(diào)整,或在確定認(rèn)知功能的正常截斷值時,充分考慮了研究人群的受教育水平。其他混雜因素(如收入、體質(zhì)量指數(shù)、抑郁癥等)在部分研究中進(jìn)行了調(diào)整。

        認(rèn)知功能損傷與死亡率風(fēng)險增加相關(guān)的機(jī)制尚不明確,目前可能的機(jī)制有以下幾種。①認(rèn)知功能障礙可能是癡呆和MCI的表現(xiàn)。既往綜述顯示,癡呆和MCI病人死亡風(fēng)險增加[2,42]。②認(rèn)知損害可能反映了藥物的副作用或病人對一些慢性疾?。ㄈ缣悄虿?、高血壓等)的控制不佳[43]。③認(rèn)知損傷也可能反映了“終末衰退”,一些研究發(fā)現(xiàn),當(dāng)人接近死亡時,整體認(rèn)知功能下降[44]。④認(rèn)知功能可能影響健康素養(yǎng),認(rèn)知缺陷的人群可能在日常生活中難以獲取正確的醫(yī)療保健信息以促進(jìn)和維持健康,從而進(jìn)一步縮短了壽命[45]。

        本研究有以下優(yōu)點:①本文Meta分析包含了大量的樣本,結(jié)果更具代表性;②本文納入的所有研究都是隊列研究,能滿足時序性因果推論的標(biāo)準(zhǔn)且減少回憶偏差和選擇偏差的影響;③本文定量地評估了最輕度認(rèn)知障礙與全死因死亡率之間的關(guān)系,以盡量減少癡呆對結(jié)果的影響;④本文使用限制性立方樣條模型進(jìn)行了劑量-反應(yīng)分析,進(jìn)一步支持了因果關(guān)系的存在。

        本研究仍然存在一些局限性。①僅考慮了基線認(rèn)知功能,而沒有探討認(rèn)知功能隨時間變化對死亡產(chǎn)生的影響,可能會低估認(rèn)知功能與死亡之間的關(guān)聯(lián)。②只分析了整體認(rèn)知功能與全死因死亡率之間的關(guān)系,而沒有研究各認(rèn)知域與死亡的獨立關(guān)聯(lián)。③盡管提取了對潛在混雜因素最大程度控制的HR值,但所納入的研究對協(xié)變量的調(diào)整程度仍然不盡相同。④本研究中存在著較大的異質(zhì)性,且該異質(zhì)性不能通過亞組分析和Meta回歸得到充分解釋。在敏感度分析中,以I2gt;50%為標(biāo)準(zhǔn),發(fā)現(xiàn)有9項研究對異質(zhì)性有顯著影響[5,10,11,15,28,35,37-38,40]。去除這9項研究后,異質(zhì)性降至45.9%,結(jié)果仍然有統(tǒng)計學(xué)意義,從而證明了結(jié)論的穩(wěn)健性。

        綜上所述,使用MMSE量表所評估的基線認(rèn)知功能可能是老年人群全死因死亡增加的獨立預(yù)測指標(biāo)。對老年人進(jìn)行定期的認(rèn)知功能篩查是非常有必要的。未來研究需進(jìn)一步探討老年人全死因死亡的綜合預(yù)測因素,以形成一套包含認(rèn)知功能測量的高效篩查工具,及時識別高危人群,為臨床醫(yī)生和衛(wèi)生政策的制定者提供依據(jù)。

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