Evidence from individual trials comparing Mediterranean to low-fat diets to modify cardiovascular risk factors remains preliminary.
Methods
We systematically searched MEDLINE, EMBASE, Biosis, Web of Science, and the Cochrane Central Register of Controlled Trials from their inception until January 2011, as well as contacted experts in the field, to identify randomized controlled trials comparing Mediterranean to low-fat diets in overweight/obese individuals, with a minimum follow-up of 6 months, reporting intention-to-treat data on cardiovascular risk factors. Two authors independently assessed trial eligibility and quality.
Results
We identified 6 trials, including 2650 individuals (50% women) fulfilling our inclusion criteria. Mean age of enrolled patients ranged from 35 to 68 years, mean body mass index from 29 to 35 kg/m2. After 2 years of follow-up, individuals assigned to a Mediterranean diet had more favorable changes in weighted mean differences of body weight (−2.2 kg; 95% confidence interval [CI], −3.9 to −0.6), body mass index (−0.6 kg/m2; 95% CI, −1 to −0.1), systolic blood pressure (−1.7 mm Hg; 95% CI, −3.3 to −0.05), diastolic blood pressure (−1.5 mm Hg; 95% CI, −2.1 to −0.8), fasting plasma glucose (−3.8 mg/dL, 95% CI, −7 to −0.6), total cholesterol (−7.4 mg/dL; 95% CI, −10.3 to −4.4), and high-sensitivity C-reactive protein (−1.0 mg/L; 95% CI, −1.5 to −0.5). The observed heterogeneity across individual trials could, by and large, be eliminated by restricting analyses to trials with balanced co-interventions or trials with restriction of daily calorie intake in both diet groups.
Conclusion
Mediterranean diets appear to be more effective than low-fat diets in inducing clinically relevant long-term changes in cardiovascular risk factors and inflammatory markers.
2012年4月25日の記事では地中海料理が心血管危険因子を減少させるという内容でした．死亡や心筋梗塞・脳卒中などの臨床転帰については評価していませんでした．今回は PREDIMED study というより大規模な試験の結果幾つかの論文が発表され，そのメタ解析を行った論文を紹介します．残念ながら臨床転帰について評価した論文が1つしかなかったため，臨床転帰についてのエビデンスは得られていません．
我々は MEDLINE, EMBASE, Biosis, Web of Science, Cochrane Central Register of Controlled Trial を 2011 年1月まで全体的に調査し，その道の専門家に接触し，太り過ぎ又は肥満の人の地中海料理と低脂肪食との無作為化比較試験を同定し，最低6ヶ月間経過観察し，心血管危険因子の治療目的のデータを報告したものについて．2名の著者が別々に試験の有用性と品質を評価した．
This article has reported the association between dietary fiber intakes and the risk of cardiovascular disease, that it has been shown that total fiber intakes, cereal fiber intakes and fruit fiber intakes have inverse association, in contrast, vegetable fiber has no association.
In the Dietary Reference Intakes for Japanese 2015 edition, they have described “If they would intake 24 g/d or greater of dietary fiber, they could avoid the risk of coronary death.”, but I couldn’t find the describe in the original article.
Mark A. Pereira, PhD; Eilis O’Reilly, MSc; Katarina Augustsson, PhD; Gary E. Fraser, MBChB, PhD; Uri Goldbourt, PhD; Berit L. Heitmann, PhD; Goran Hallmans, MD, PhD; Paul Knekt, PhD; Simin Liu, MD, ScD; Pirjo Pietinen, DSc; Donna Spiegelman, ScD; June Stevens, MS, PhD; Jarmo Virtamo, MD; Walter C. Willett, MD; Alberto Ascherio, MD
Background Few epidemiologic studies of dietary fiber intake and risk of coronary heart disease have compared fiber types (cereal, fruit, and vegetable) or included sex-specific results. The purpose of this study was to conduct a pooled analysis of dietary fiber and its subtypes and risk of coronary heart disease.
Methods We analyzed the original data from 10 prospective cohort studies from the United States and Europe to estimate the association between dietary fiber intake and the risk of coronary heart disease.
Results Over 6 to 10 years of follow-up, 5249 incident total coronary cases and 2011 coronary deaths occurred among 91 058 men and 245 186 women. After adjustment for demographics, body mass index, and lifestyle factors, each 10-g/d increment of energy-adjusted and measurement error–corrected total dietary fiber was associated with a 14% (relative risk [RR], 0.86; 95% confidence interval [CI], 0.78-0.96) decrease in risk of all coronary events and a 27% (RR, 0.73; 95% CI, 0.61-0.87) decrease in risk of coronary death. For cereal, fruit, and vegetable fiber intake (not error corrected), RRs corresponding to 10-g/d increments were 0.90 (95% CI, 0.77-1.07), 0.84 (95% CI, 0.70-0.99), and 1.00 (95% CI, 0.88-1.13), respectively, for all coronary events and 0.75 (95% CI, 0.63-0.91), 0.70 (95% CI, 0.55-0.89), and 1.00 (95% CI, 0.82-1.23), respectively, for deaths. Results were similar for men and women.
Conclusion Consumption of dietary fiber from cereals and fruits is inversely associated with risk of coronary heart disease.
Mark A. Pereira, PhD; Eilis O’Reilly, MSc; Katarina Augustsson, PhD; Gary E. Fraser, MBChB, PhD; Uri Goldbourt, PhD; Berit L. Heitmann, PhD; Goran Hallmans, MD, PhD; Paul Knekt, PhD; Simin Liu, MD, ScD; Pirjo Pietinen, DSc; Donna Spiegelman, ScD; June Stevens, MS, PhD; Jarmo Virtamo, MD; Walter C. Willett, MD; Alberto Ascherio, MD
最低 10 件の前向きコホート試験で食物繊維と心血管疾患発生との関係を精査した．それらの試験のうち一つを除いて全て負の相関を報告していた．方法および解析技術の相違により繊維摂取総量および繊維の種類（由来が穀物か果実か野菜かおよび水溶性か否か）のこの相関の強度は不明のままであった．更に，4編のみの試験では男性を除外して女性における所見を報告していた．他の生活スタイル因子によるネガティブな刊行バイアスおよび残差交絡の可能性が残っている．ゆえに我々は米国およびヨーロッパにおける 10 件の前向きコホート試験から系統的解析を行った．それには Pooling Project of Cohort Studies on Diet and Coronary Disease を含んでいた．
方法
このプール解析には下記の適合基準を適用した．すなわち，最低 150 例の冠動脈疾患発症例を有する前向き試験，日常の食事摂取の評価，および食事評価法の検証試験またはそれに近い関連する機器．文献検索およびその道の専門家への質問を通じて 14 の試験が適合基準に合致するとして同定され，11 試験の研究者がプロジェクトにおけるデータの提供に賛同した．1 編の試験は食物繊維摂取量のデータを有していないため除外された．利用できる 3 編の試験の研究者は，皆米国からの報告だったのだが，試験への参加に賛同しなかった．残った試験を Table 1 に示す．Nurses’ Health Study (NHS) の経験の解析のための観察期間は，食事摂取を繰り返し評価していることと長期間の観察期間という利点から2つの期間に分割した．1980-1986 年の観察期間は Nurses’ Health Study A (NHSa) と呼ばれ，1986 年まで心血管疾患を発症しなかった女性の 1986-1996 年の観察期間は Nurses’ Health Study B (NHSb) と呼ばれた．生存期間の underlying theory に基づき，異なる期間における人-期間のブロックは，同じ人に由来したとしても統計的に独立であった．ゆえに，これらの2つの期間からのプール推定値は一つの期間を用いたのと等価であり，1980 年と比較して 1986 年における強化された曝露評価における利点を有している．
食事評価
いずれの試験においても食物摂取頻度アンケートまたは食事履歴計器によるベースラインの食事を計測していた．Adventist Health Study (AHS) においては原食物繊維だけを評価していた．そのため，このコホートにおいては食物繊維総量の近似のため原食物繊維に 3.5 を掛け算した．これは他の試験から得られた原食物繊維の食物繊維総量に対する比である．食物繊維総量に加え，我々は 3 つの食品群からの繊維摂取量を調査した．それには穀物（全粒穀物），果実および野菜が含まれ，不溶性食物繊維（ヘミセルロース，セルロースおよびリグニン）および水溶性食物繊維（ペクチン，ガム質および粘液質）も含まれる．穀物，果実および野菜由来の繊維は AHS および Glostrup Population Study (GPS) 以外のすべての試験で利用可能であった．広い種類の食品が各々の繊維の種類に寄与しており，ある種の食物は多くの試験において相対的に寄与していた．トウモロコシやエンドウなどのでんぷん質の野菜はすべての試験において野菜の繊維に実質的に寄与していた．Finish Mobile Clinic Health Examination Survey (FMC) および Vasterbotten Intervention Program (VIP) のみがバレイショの繊維を野菜の繊維に含めており，これら 2 編の試験においてはバレイショの繊維は野菜の繊維の一般的形態であった．6 編の試験のみが不溶性食物繊維および水溶性食物繊維の推定値を有していたが，食品成分表に基づいてこれらの繊維の種類を推定する標準的方法がなかったため，結果の解釈は注意深くあるべきである．
The Japanese Society for Dialysis Therapy (JSDT) recommends PCR as an indicator of protein intake. Otherwise K/DOQQI recommends nPNA. If you calculate Kt/V with Daugirdas’ method, you can also define nPNA.
In Japan, Shinzato’s fomula for calculating Kt/V, an indicator of efficiency of dialysis, is recommended by JSDT. Since integral equation is used to solve Shinzato’s method, you couldn’t solve algebraically. In K/DOQQI, it is usual to solve Kt/V with Daugirdas’ method. Shinzato has described that Daugirdas’ Kt/V is similar to Shinzato’s Kt/V.
Malnutrition in elder people increases the risk of death. Geriatric Nutrition Risk Index (GNRI) is the tool to detect malnutrition easily in hemodialysis patients, too. The definition is as following;
where ideal body weight is given by multiplying 22 the square of height. But body weight should be replaced with ideal body weight if body weight is greater than ideal body weight. Then the second term is equal to 1.
Table is defined as following procedure. It is based on the survey list of the Japanese Society for Dialysis Therapy in 2013.
CREATE TABLE dbo.T_JSDT(
ID nchar(8) NOT NULL,
DATE_Survey date NOT NULL,
Diabetes nchar(1) NOT NULL,
Myocardial_Infarction nchar(1) NOT NULL,
Cerebral_Hemorrhage nchar(1) NOT NULL,
Cerebral_Infarction nchar(1) NOT NULL,
Amputation nchar(1) NOT NULL,
Femoral_Fracture nchar(1) NOT NULL,
EPS nchar(1) NOT NULL,
Hypertensive_Agents nchar(1) NOT NULL,
Smoke nchar(1) NOT NULL,
Therapy_Mode nchar(10) NOT NULL,
Combination_PD nchar(1) NOT NULL,
History_PD nchar(1) NOT NULL,
Transplantation_COUNT nchar(1) NOT NULL,
DIalysis_COUNT int NULL,
Dialysis_Duration int NULL,
QB int NULL,
Height decimal(4, 1) NOT NULL,
preWeight decimal(4, 1) NOT NULL,
postWeight decimal(4, 1) NULL,
preBUN decimal(4, 1) NOT NULL,
postBUN decimal(4, 1) NULL,
preCre decimal(5, 2) NOT NULL,
postCre decimal(5, 2) NULL,
Albumin decimal(3, 1) NOT NULL,
CRP decimal(4, 2) NOT NULL,
Ca decimal(3, 1) NOT NULL,
IP decimal(3, 1) NOT NULL,
Hemoglobin decimal(3, 1) NOT NULL,
TIBC decimal(3, 0) NULL,
Fe decimal(3, 0) NULL,
Ferritin decimal(5, 1) NULL,
TCHO decimal(3, 0) NOT NULL,
HDLC decimal(3, 0) NOT NULL,
PTH_mode nchar(1) NOT NULL,
PTH decimal(4, 0) NULL,
HbA1c decimal(3, 1) NULL,
GA decimal(3, 1) NULL,
SBP decimal(3, 0) NOT NULL,
DBP decimal(3, 0) NOT NULL,
HR decimal(3, 0) NOT NULL,
KtV_JSDT decimal(3, 2) NULL,
nPCR_JSDT decimal(3, 2) NULL,
[%CRE] decimal(4, 1) NULL,
CONSTRAINT PK_T_JSDT PRIMARY KEY (ID, DATE_Survey)
We need height, body weight and albumin in the table. Execute following procedure to create function.
CREATE FUNCTION Function_GNRI
(@Albumin dec(3, 1), @Height dec(4, 1), @Weight dec(4, 1))
RETURNS DEC(5, 2)
AS
BEGIN
DECLARE @GNRI DEC(5,2)
SELECT @GNRI = 14.89 * @Albumin + 41.7 * CASE WHEN @Weight > ( 22 * POWER(@Height/100, 2)) THEN ( 22 * POWER(@Height/100, 2)) ELSE @Weight END / ( 22 * POWER(@Height/100, 2))
RETURN @GNRI
END
Execute following query to calculate GNRI.
WITH CTE AS
(SELECT J.ID AS ID
, J.DATE_Survey AS DATE_Survey
, J.Albumin AS ALB
, J.Height AS Height
, CASE WHEN J.postWeight IS NULL THEN J.preWeight ELSE J.postWeight END AS Weight
FROM dbo.T_JSDT AS J
), CTE_GNRI AS
(SELECT CTE.ID AS ID
, CTE.DATE_Survey AS DATE_Survey
, dbo.Function_GNRI(CTE.ALB, CTE.Height, CTE.Weight) AS GNRI
FROM CTE)
SELECT * FROM CTE_GNRI;
CREATE TABLE dbo.T_JSDT(
ID nchar(8) NOT NULL,
DATE_Survey date NOT NULL,
Diabetes nchar(1) NOT NULL,
Myocardial_Infarction nchar(1) NOT NULL,
Cerebral_Hemorrhage nchar(1) NOT NULL,
Cerebral_Infarction nchar(1) NOT NULL,
Amputation nchar(1) NOT NULL,
Femoral_Fracture nchar(1) NOT NULL,
EPS nchar(1) NOT NULL,
Hypertensive_Agents nchar(1) NOT NULL,
Smoke nchar(1) NOT NULL,
Therapy_Mode nchar(10) NOT NULL,
Combination_PD nchar(1) NOT NULL,
History_PD nchar(1) NOT NULL,
Transplantation_COUNT nchar(1) NOT NULL,
DIalysis_COUNT int NULL,
Dialysis_Duration int NULL,
QB int NULL,
Height decimal(4, 1) NOT NULL,
preWeight decimal(4, 1) NOT NULL,
postWeight decimal(4, 1) NULL,
preBUN decimal(4, 1) NOT NULL,
postBUN decimal(4, 1) NULL,
preCre decimal(5, 2) NOT NULL,
postCre decimal(5, 2) NULL,
Albumin decimal(3, 1) NOT NULL,
CRP decimal(4, 2) NOT NULL,
Ca decimal(3, 1) NOT NULL,
IP decimal(3, 1) NOT NULL,
Hemoglobin decimal(3, 1) NOT NULL,
TIBC decimal(3, 0) NULL,
Fe decimal(3, 0) NULL,
Ferritin decimal(5, 1) NULL,
TCHO decimal(3, 0) NOT NULL,
HDLC decimal(3, 0) NOT NULL,
PTH_mode nchar(1) NOT NULL,
PTH decimal(4, 0) NULL,
HbA1c decimal(3, 1) NULL,
GA decimal(3, 1) NULL,
SBP decimal(3, 0) NOT NULL,
DBP decimal(3, 0) NOT NULL,
HR decimal(3, 0) NOT NULL,
KtV_JSDT decimal(3, 2) NULL,
nPCR_JSDT decimal(3, 2) NULL,
[%CRE] decimal(4, 1) NULL,
CONSTRAINT PK_T_JSDT PRIMARY KEY (ID, DATE_Survey)
上記テーブルの中で必要な項目は身長，体重，アルブミン値です．下記プロシージャを実行して関数を作成します．実体重が理想体重を上回る場合には実体重を理想体重に置き換えるという条件は CASE 式の中で評価します．
CREATE FUNCTION Function_GNRI
(@Albumin dec(3, 1), @Height dec(4, 1), @Weight dec(4, 1))
RETURNS DEC(5, 2)
AS
BEGIN
DECLARE @GNRI DEC(5,2)
SELECT @GNRI = 14.89 * @Albumin + 41.7 * CASE WHEN @Weight > ( 22 * POWER(@Height/100, 2)) THEN ( 22 * POWER(@Height/100, 2)) ELSE @Weight END / ( 22 * POWER(@Height/100, 2))
RETURN @GNRI
END
WITH CTE AS
(SELECT J.ID AS ID
, J.DATE_Survey AS DATE_Survey
, J.Albumin AS ALB
, J.Height AS Height
, CASE WHEN J.postWeight IS NULL THEN J.preWeight ELSE J.postWeight END AS Weight
FROM dbo.T_JSDT AS J
), CTE_GNRI AS
(SELECT CTE.ID AS ID
, CTE.DATE_Survey AS DATE_Survey
, dbo.Function_GNRI(CTE.ALB, CTE.Height, CTE.Weight) AS GNRI
FROM CTE)
SELECT * FROM CTE_GNRI;
Nutrition rehabilitation in hemodialysis patients is one of the hottest topics. They have reported that resistance exercise has resulted to muscle strength, but the lack of functional capacity. Although this trial has high evidence with RCT, the number of participants may be too small to determine statistically significant.
Anabolic exercise in haemodialysis patients: a randomised controlled pilot study
Danielle L. Kirkman, Paul Mullins, Naushad A. Junglee, Mick Kumwenda, Mahdi M. Jibani, Jamie H. Macdonald
Abstract
Background
The anabolic response to progressive resistance exercise training (PRET) in haemodialysis patients is unclear. This pilot efficacy study aimed to determine whether high-intensity intradialytic PRET could reverse atrophy and consequently improve strength and physical function in haemodialysis patients. A second aim was to compare any anabolic response to that of healthy participants completing the same program.
Methods
In a single blind controlled study, 23 haemodialysis patients and 9 healthy individuals were randomly allocated to PRET or an attention control (SHAM) group. PRET completed high-intensity exercise leg extensions using novel equipment. SHAM completed low-intensity lower body stretching activities using ultra light resistance bands. Exercises were completed thrice weekly for 12 weeks, during dialysis in the haemodialysis patients. Outcomes included knee extensor muscle volume by magnetic resonance imaging, knee extensor strength by isometric dynamometer and lower body tests of physical function. Data were analysed by a per protocol method using between-group comparisons.
Results
PRET elicited a statistically and clinically significant anabolic response in haemodialysis patients (PRET—SHAM, mean difference [95 % CI]: 193[63 to 324] cm3) that was very similar to the response in healthy participants (PRET—SHAM, 169[−41 to 379] cm3). PRET increased strength in both haemodialysis patients and healthy participants. In contrast, PRET only enhanced lower body functional capacity in the healthy participants.
Conclusions
Intradialytic PRET elicited a normal anabolic and strength response in haemodialysis patients. The lack of a change in functional capacity was surprising and warrants further investigation.
Danielle L. Kirkman, Paul Mullins, Naushad A. Junglee, Mick Kumwenda, Mahdi M. Jibani, Jamie H. Macdonald
要旨
背景
透析患者における漸増レジスタンス運動 (PRET) への反応は不明確である．このパイロット有効性研究は，透析患者において透析の間での強度の PRET が萎縮を逆転できるか，また結果的に筋力と身体機能を改善することができるか否かを定義することを目的とする．2番目の目的は蛋白同化反応と，同様のプログラムを完遂した健康な参加者の反応とを比較することである．
PRET は透析患者において統計的および臨床的に有意に蛋白同化反応を惹起し (PRET—SHAM, mean difference [95 % CI]: 193[63 to 324] cm3), 健常な参加者においても同様であった (PRET—SHAM, 169[−41 to 379] cm3). PRET は透析患者においても健常者においても筋力を増強させた．対照的に, PRET は健常者においてのみ下半身の身体機能を増強させただけであった．
結論
透析患者において透析中の PRET は正常な蛋白同化と筋力増強を惹起した．身体機能に変化がなかったことは驚くべきものであり，さらなる調査が必要と考えられた．
Differential diagnosis between Castleman’s disease and systemic IgG4-related lymphadenopathy is described in this article. In their patients, systemic IgG4-related lymphadenopathy showed pathologic features only partially overlapping those of multicentric Castleman’s disease. Serum data, especially CRP and IL-6 are useful for differentiating the two.
Systemic IgG4-related lymphadenopathy: a clinical and pathologic comparison to multicentric Castleman’s disease
IgG4-related disease sometimes involves regional and/or systemic lymph nodes, and often clinically and/or histologically mimics multicentric Castleman’s disease or malignant lymphoma. In this study, we examined clinical and pathologic findings of nine patients with systemic IgG4-related lymphadenopathy. None of these cases were associated with human herpes virus-8 or human immunodeficiency virus infection, and there was no T-cell receptor or immunoglobulin gene rearrangement. Histologically, systemic IgG4-related lymphadenopathy was classified into two types by the infiltration pattern of IgG4-positive cells: interfollicular plasmacytosis type and intra-germinal center plasmacytosis type. The interfollicular plasmacytosis type showed either Castleman’s disease-like features or atypical lymphoplasmacytic and immunoblastic proliferation-like features. By contrast, the intra-germinal center plasmacytosis type showed marked follicular hyperplasia, and infiltration of IgG4-positive cells mainly into the germinal centers, and some cases exhibited features of progressively transformed germinal centers. Interestingly, eight of our nine (89%) cases showed eosinophil infiltration in the affected lymph nodes, and examined patients showed high elevation of serum IgE. Laboratory examinations revealed elevation of serum IgG4 and soluble interleukin-2 receptors. However, the levels of interleukin-6, C-reactive protein, and lactate dehydrogenase were within normal limits or only slightly elevated in almost all patients. One patient showed a high interleukin-6 level whereas C-reactive protein was within the normal limit. Autoantibodies were examined in five patients and detected in four. Compared with the previously reported cases of multicentric Castleman’s disease, our patients with systemic IgG4-related lymphadenopathy were significantly older and had significantly lower C-reactive protein and interleukin-6 levels. In conclusion, in our systemic IgG4-related lymphadenopathy showed pathologic features only partially overlapping those of multicentric Castleman’s disease, and serum data (especially C-reactive protein and interleukin-6) are useful for differentiating the two. Our findings of eosinophil infiltration in the affected tissue and elevation of serum IgE may suggest an allergic mechanism in the pathogenesis of systemic IgG4-related lymphadenopathy.
Outcome of PREDIMED Study has been published in the New England Journal of Medicine that examined primary prevention of cardiovascular disease with Mediterranean diet. The result has been shown that Mediterranean diet with extra-virgin olive oil or mixed nuts has better prognosis than reduction of lipid. It is considered that alpha linolenic acid rich Mediterranean diet, a component of walnuts, influences oxidative stress, inflammation or endothelial dysfunction.
Primary Prevention of Cardiovascular Disease with a Mediterranean Diet
Ramón Estruch, M.D., Ph.D., Emilio Ros, M.D., Ph.D., Jordi Salas-Salvadó, M.D., Ph.D., Maria-Isabel Covas, D.Pharm., Ph.D., Dolores Corella, D.Pharm., Ph.D., Fernando Arós, M.D., Ph.D., Enrique Gómez-Gracia, M.D., Ph.D., Valentina Ruiz-Gutiérrez, Ph.D., Miquel Fiol, M.D., Ph.D., José Lapetra, M.D., Ph.D., Rosa Maria Lamuela-Raventos, D.Pharm., Ph.D., Lluís Serra-Majem, M.D., Ph.D., Xavier Pintó, M.D., Ph.D., Josep Basora, M.D., Ph.D., Miguel Angel Muñoz, M.D., Ph.D., José V. Sorlí, M.D., Ph.D., José Alfredo Martínez, D.Pharm, M.D., Ph.D., and Miguel Angel Martínez-González, M.D., Ph.D., for the PREDIMED Study Investigators
Observational cohort studies and a secondary prevention trial have shown an inverse association between adherence to the Mediterranean diet and cardiovascular risk. We conducted a randomized trial of this diet pattern for the primary prevention of cardiovascular events.
Methods
In a multicenter trial in Spain, we randomly assigned participants who were at high cardiovascular risk, but with no cardiovascular disease at enrollment, to one of three diets: a Mediterranean diet supplemented with extra-virgin olive oil, a Mediterranean diet supplemented with mixed nuts, or a control diet (advice to reduce dietary fat). Participants received quarterly individual and group educational sessions and, depending on group assignment, free provision of extra-virgin olive oil, mixed nuts, or small nonfood gifts. The primary end point was the rate of major cardiovascular events (myocardial infarction, stroke, or death from cardiovascular causes). On the basis of the results of an interim analysis, the trial was stopped after a median follow-up of 4.8 years.
Results
A total of 7447 persons were enrolled (age range, 55 to 80 years); 57% were women. The two Mediterranean-diet groups had good adherence to the intervention, according to self-reported intake and biomarker analyses. A primary end-point event occurred in 288 participants. The multivariable-adjusted hazard ratios were 0.70 (95% confidence interval [CI], 0.54 to 0.92) and 0.72 (95% CI, 0.54 to 0.96) for the group assigned to a Mediterranean diet with extra-virgin olive oil (96 events) and the group assigned to a Mediterranean diet with nuts (83 events), respectively, versus the control group (109 events). No diet-related adverse effects were reported.
Conclusions
Among persons at high cardiovascular risk, a Mediterranean diet supplemented with extra-virgin olive oil or nuts reduced the incidence of major cardiovascular events.
地中海食による心血管疾患の予防効果を検討した PREDIMED Study の成果が New England Journal に掲載されました．単に脂質を制限するよりもオリーブオイルやナッツを摂取したほうが心血管疾患の一次予防に有効であったとする結果です．地中海食には胡桃の成分であるαリノレン酸が豊富に含まれており，酸化ストレスや炎症，内皮機能障害などに影響するからではないかと考察しています．
地中海食による心血管疾患の一次予防
Ramón Estruch, M.D., Ph.D., Emilio Ros, M.D., Ph.D., Jordi Salas-Salvadó, M.D., Ph.D., Maria-Isabel Covas, D.Pharm., Ph.D., Dolores Corella, D.Pharm., Ph.D., Fernando Arós, M.D., Ph.D., Enrique Gómez-Gracia, M.D., Ph.D., Valentina Ruiz-Gutiérrez, Ph.D., Miquel Fiol, M.D., Ph.D., José Lapetra, M.D., Ph.D., Rosa Maria Lamuela-Raventos, D.Pharm., Ph.D., Lluís Serra-Majem, M.D., Ph.D., Xavier Pintó, M.D., Ph.D., Josep Basora, M.D., Ph.D., Miguel Angel Muñoz, M.D., Ph.D., José V. Sorlí, M.D., Ph.D., José Alfredo Martínez, D.Pharm, M.D., Ph.D., and Miguel Angel Martínez-González, M.D., Ph.D., for the PREDIMED Study Investigators
Malnutrition is a common complication in haemodialysis patients. Recently, the Geriatric Nutritional Risk Index (GNRI) has been reported as a simple and accurate tool to assess nutritional status of haemodialysis patients. Our objective was to examine the association between GNRI and mortality in chronic haemodialysis patients.
Methods
We examined the GNRI of 490 maintenance haemodialysis patients (60 ± 12 years, 293 males and 197 females) and followed up these patients for 60 months. Predictors for all-cause death were examined using Kaplan–Meier analysis and Cox proportional analyses.
Results
The GNRI was 98.0 ± 6.0, and was significantly and negatively correlated with age and haemodialysis duration. During the 60-month follow-up period, 129 patients died. According to the highest positive likelihood and risk ratios, the cutoff value of GNRI for mortality was set at 90. Kaplan–Meier analysis revealed that patients with a GNRI <90 (n = 50) had a significantly lower survival rate, compared to those with GNRI ≥90 (n = 440) (log-rank test, P < 0.0001). Multivariate Cox proportional hazards analyses demonstrated that GNRI was a significant predictor for mortality [hazard ratio (HR) 0.962, 95% confidence interval (CI) 0.931–0.995, P < 0.05], after adjustment for age, gender, C-reactive protein, presence of diabetes and haemodialysis duration.
Conclusions
These results demonstrated that GNRI is a significant predictor for mortality in haemodialysis patients. The simple method of GNRI is considered to be a clinically useful marker for the assessment of nutritional status in haemodialysis patients.
This article has described about the relation between the Mediterranean-style diet score (MeDi score) and risk of ischemic stroke, myocardial infarction, and vascular death on blacks and Hispanics in the United States. Although there is no relation between Mediterranean-style diet and stroke because population was too small, this is the first study that is multiethnic, population based, prospective cohort study in the United States.
Mediterranean-style diet and risk of ischemic stroke, myocardial infarction, and vascular death: the Northern Manhattan Study
Hannah Gardener, Clinton B Wright, Yian Gu, Ryan T Demmer, Bernadette Boden-Albala, Mitchell SV Elkind, Ralph L Sacco, and Nikolaos Scarmeas
A dietary pattern common in regions near the Mediterranean appears to reduce risk of all-cause mortality and ischemic heart disease. Data on blacks and Hispanics in the United States are lacking, and to our knowledge only one study has examined a Mediterranean-style diet (MeDi) in relation to stroke.
Objective:
In this study, we examined an MeDi in relation to vascular events.
Design:
The Northern Manhattan Study is a population-based cohort to determine stroke incidence and risk factors (mean ± SD age of participants: 69 ± 10 y; 64% women; 55% Hispanic, 21% white, and 24% black). Diet was assessed at baseline by using a food-frequency questionnaire in 2568 participants. A higher score on a 0–9 scale represented increased adherence to an MeDi. The relation between the MeDi score and risk of ischemic stroke, myocardial infarction (MI), and vascular death was assessed with Cox models, with control for sociodemographic and vascular risk factors.
Results:
The MeDi-score distribution was as follows: 0–2 (14%), 3 (17%), 4 (22%), 5 (22%), and 6–9 (25%). Over a mean follow-up of 9 y, 518 vascular events accrued (171 ischemic strokes, 133 MIs, and 314 vascular deaths). The MeDi score was inversely associated with risk of the composite outcome of ischemic stroke, MI, or vascular death (P-trend = 0.04) and with vascular death specifically (P-trend = 0.02). Moderate and high MeDi scores were marginally associated with decreased risk of MI. There was no association with ischemic stroke.
Conclusions:
Higher consumption of an MeDi was associated with decreased risk of vascular events. Results support the role of a diet rich in fruit, vegetables, whole grains, fish, and olive oil in the promotion of ideal cardiovascular health.
結論として，我々はより大規模な地中海料理の消費と血管イベント，特に血管死のリスクの軽減との関係を示した．地中海料理と虚血性脳卒中との相関を支持するエビデンスは得られなかった．我々の知る限り，男性と女性，同じ国に住む多民族人口を含めた試験としては，本試験は合衆国における最初のものである．我々の結果は，理想的な心血管の健康を達成するという2020 AHA の新しい目標を支持するものである．地中海料理パターンは AHA の推奨する食事の幾つかの方法に合致するからである．地中海料理と血管疾患，特に脳卒中との関連を解明するにはより大規模な人口における追加試験が必要である．致死的事象と非致死的事象の相対関係はさらなる試験に値する．
![\displaystyle \mathrm{Kt/V} = - LN( R - 0.08 \times t ) + \left[ 4 - \left( 3.5 \times R \right) \right] \times\frac{\mathrm{UF}}{\mathrm{W}}\\ = - LN \left( \frac{\mathrm{postBUN}}{\mathrm{preBUN}} - 0.008 \times t \right) + \left[ 4 - \left( 3.5 \times \frac{\mathrm{postBUN}}{\mathrm{preBUN}} \right) \right] \times \frac{\mathrm{preWeight} - \mathrm{postWeight}}{\mathrm{postWeight}} \cdots(1)](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle+%5Cmathrm%7BKt%2FV%7D+%3D+-+LN%28+R+-+0.08+%5Ctimes+t+%29+%2B+%5Cleft%5B+4+-+%5Cleft%28+3.5+%5Ctimes+R+%5Cright%29+%5Cright%5D+%5Ctimes%5Cfrac%7B%5Cmathrm%7BUF%7D%7D%7B%5Cmathrm%7BW%7D%7D%5C%5C++%3D+-+LN+%5Cleft%28+%5Cfrac%7B%5Cmathrm%7BpostBUN%7D%7D%7B%5Cmathrm%7BpreBUN%7D%7D+-+0.008+%5Ctimes+t+%5Cright%29+%2B+%5Cleft%5B+4+-+%5Cleft%28+3.5+%5Ctimes+%5Cfrac%7B%5Cmathrm%7BpostBUN%7D%7D%7B%5Cmathrm%7BpreBUN%7D%7D+%5Cright%29+%5Cright%5D+%5Ctimes+%5Cfrac%7B%5Cmathrm%7BpreWeight%7D+-+%5Cmathrm%7BpostWeight%7D%7D%7B%5Cmathrm%7BpostWeight%7D%7D+%5Ccdots%281%29&bg=T&fg=000000&s=0 "\displaystyle \mathrm{Kt/V} = - LN( R - 0.08 \times t ) + \left[ 4 - \left( 3.5 \times R \right) \right] \times\frac{\mathrm{UF}}{\mathrm{W}}\\ = - LN \left( \frac{\mathrm{postBUN}}{\mathrm{preBUN}} - 0.008 \times t \right) + \left[ 4 - \left( 3.5 \times \frac{\mathrm{postBUN}}{\mathrm{preBUN}} \right) \right] \times \frac{\mathrm{preWeight} - \mathrm{postWeight}}{\mathrm{postWeight}} \cdots(1)")
![\displaystyle \mathrm{Ce} = \mathrm{Cs} Exp\left( - \frac{\mathrm{Kt}}{\mathrm{V}} \right) + \frac{\mathrm{G}}{\mathrm{K}}\left[ 1 - Exp\left( - \frac{\mathrm{Kt}}{\mathrm{V}} \right) \right] \cdots(3)](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle+%5Cmathrm%7BCe%7D+%3D+%5Cmathrm%7BCs%7D+Exp%5Cleft%28+-+%5Cfrac%7B%5Cmathrm%7BKt%7D%7D%7B%5Cmathrm%7BV%7D%7D+%5Cright%29+%2B+%5Cfrac%7B%5Cmathrm%7BG%7D%7D%7B%5Cmathrm%7BK%7D%7D%5Cleft%5B+1+-+Exp%5Cleft%28+-+%5Cfrac%7B%5Cmathrm%7BKt%7D%7D%7B%5Cmathrm%7BV%7D%7D+%5Cright%29+%5Cright%5D+%5Ccdots%283%29&bg=T&fg=000000&s=0 "\displaystyle \mathrm{Ce} = \mathrm{Cs} Exp\left( - \frac{\mathrm{Kt}}{\mathrm{V}} \right) + \frac{\mathrm{G}}{\mathrm{K}}\left[ 1 - Exp\left( - \frac{\mathrm{Kt}}{\mathrm{V}} \right) \right] \cdots(3)")
![\displaystyle \mathrm{Kt/V} = - LN( R - 0.008 \times t ) + \left[ 4 - \left( 3.5 \times R \right) \right] \times\frac{\mathrm{UF}}{\mathrm{W}}\\ = - LN \left( \frac{\mathrm{postBUN}}{\mathrm{preBUN}} - 0.008 \times t \right) + \left[ 4 - \left( 3.5 \times \frac{\mathrm{postBUN}}{\mathrm{preBUN}} \right) \right] \times \frac{\mathrm{preWeight} - \mathrm{postWeight}}{\mathrm{postWeight}} \cdots(1)](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle+%5Cmathrm%7BKt%2FV%7D+%3D+-+LN%28+R+-+0.008+%5Ctimes+t+%29+%2B+%5Cleft%5B+4+-+%5Cleft%28+3.5+%5Ctimes+R+%5Cright%29+%5Cright%5D+%5Ctimes%5Cfrac%7B%5Cmathrm%7BUF%7D%7D%7B%5Cmathrm%7BW%7D%7D%5C%5C++%3D+-+LN+%5Cleft%28+%5Cfrac%7B%5Cmathrm%7BpostBUN%7D%7D%7B%5Cmathrm%7BpreBUN%7D%7D+-+0.008+%5Ctimes+t+%5Cright%29+%2B+%5Cleft%5B+4+-+%5Cleft%28+3.5+%5Ctimes+%5Cfrac%7B%5Cmathrm%7BpostBUN%7D%7D%7B%5Cmathrm%7BpreBUN%7D%7D+%5Cright%29+%5Cright%5D+%5Ctimes+%5Cfrac%7B%5Cmathrm%7BpreWeight%7D+-+%5Cmathrm%7BpostWeight%7D%7D%7B%5Cmathrm%7BpostWeight%7D%7D+%5Ccdots%281%29&bg=T&fg=000000&s=0 "\displaystyle \mathrm{Kt/V} = - LN( R - 0.008 \times t ) + \left[ 4 - \left( 3.5 \times R \right) \right] \times\frac{\mathrm{UF}}{\mathrm{W}}\\ = - LN \left( \frac{\mathrm{postBUN}}{\mathrm{preBUN}} - 0.008 \times t \right) + \left[ 4 - \left( 3.5 \times \frac{\mathrm{postBUN}}{\mathrm{preBUN}} \right) \right] \times \frac{\mathrm{preWeight} - \mathrm{postWeight}}{\mathrm{postWeight}} \cdots(1)")
