Klinička praksa temeljena na dokazima: pregled prijetnji valjanosti dokaza i kako ih spriječiti

Using the best quality of clinical research evidence is essential for choosing the right treatment for patients. How to identify the best research evidence is, however, difficult. In this narrative review we summarise these threats and describe how to minimise them. Pertinent literature was considered through literature searches combined with personal files. Treatments should generally not be chosen based only on evidence from observational studies or single randomised clinical trials. Systematic reviews with meta-analysis of all identifiable randomised clinical trials with Grading of Recommendations Assessment, Development and Evaluation (GRADE) assessment represent the highest level of evidence. Even though systematic reviews are trust worthier than other types of evidence, all levels of the evidence hierarchy are under threats from systematic errors (bias); design errors (abuse of surrogate outcomes, composite outcomes, etc.); and random errors (play of chance). Clinical research infrastructures may help in providing larger and better conducted trials. Trial Sequential Analysis may help in deciding when there is sufficient evidence in meta-analyses. If threats to the validity of clinical research are carefully considered and minimised, research results will be more valid and this will benefit patients and heath care systems.Primjena najkvalitetnijih dokaza kliničkih istraživanja ključna je u odabiru ispravnog liječenja pacijenata. No, način na koji će se odabrati najbolji dokazi predstavlja često poteškoću. Ovim preglednim člankom prikazujemo opasnosti navedenog odabira, kao i načine kako ih umanjiti. Relevantni izvori razmatrani su pretragom literature u kombinaciji s osobnim datotekama. Izbor liječenja uglavnom se ne bi smio temeljiti isključivo na opservacijskim ili pojedinačnim randomiziranim kliničkim studijama. Sustavni pregledi s metaanalizom svih identificiranih randomiziranih kliničkih studija procijenjenih sustavom stupnjevanja procjene, razvoja i evaluacije preporuka (engl. Grading of Recommendations Assessment, Development and Evaluation; GRADE) predstavljaju najvišu razinu dokaza. Iako su sustavni pregledi pouzdaniji od drugih vrsta dokaza, sve razine hijerarhije dokaza ugrožene su sustavnim pogreškama (engl. bias); pogreškama dizajna studije (zloupotreba surogatnih ishoda, složenih ishoda itd.) i slučajnim pogreškama (igra slučaja). Kliničke istraživačke infrastrukture mogu pomoći u pružanju većih i adekvatnije provedenih ispitivanja. Sekvencijska analiza studija može pomoći pri odlučivanju kada postoji dovoljna razina dokaza u metaanalizama. Ako se prijetnje valjanosti kliničkih istraživanja pažljivo razmatraju i minimiziraju, rezultati istraživanja bit će vrjedniji i korisniji pacientima i zdravstvenim sustavima

Quality of Beverage Intake and Cardiometabolic and Kidney Outcomes: Insights From the STANISLAS Cohort

Background and Aims: Beverages are an important aspect of diet, and their quality can possibly affect health. The Healthy Beverage Index (HBI) has been developed to take into account these effects. This study aimed to highlight the relationships between health and beverage quality by assessing the association of the HBI and its components with kidney and cardiometabolic (CM) outcomes in an initially healthy population-based familial cohort. Methods: This study included 1,271 participants from the STANISLAS cohort. The HBI, which includes 10 components of habitual beverage consumption, was calculated. Associations of the HBI and its components with estimated glomerular filtration rate (eGFR), albuminuria, hypertriglyceridemic waist (HTG waist), metabolic syndrome (MetS), carotid-femoral pulse wave velocity (cfPWV), carotid intima-media thickness (cIMT), and left ventricular mass (LV mass) were analyzed using multivariable linear or logistic regression models. Results: The median HBI score was 89.7 (78.6–95) out of 100 points. While the overall HBI score was not significantly associated with any of the studied outcomes, individual HBI components were found differently associated with the outcomes. cfPWV and cIMT were lower in participants who did not meet the full-fat milk criteria (p = 0.03 and 0.001, respectively). In men, higher cfPWV was observed for the “low Fat milk” (p = 0.06) and “alcohol” (p = 0.03) non-adherence criteria. Odds of HTG waist were higher with the non-adherence to sugar-sweetened beverages criteria (p < 0.001). eGFR was marginally higher with non-adherence to the coffee/tea criteria (p = 0.047). Conclusions: In this initially healthy population, HBI components were differently associated with kidney and cardiometabolic outcomes, despite a good overall HBI score. Our results highlight specific impacts of different beverage types and suggest that beverages could have an impact on kidney and cardiometabolic health

Functional metagenomics: construction and high-throughput screening of fosmid libraries for discovery of novel carbohydrate-active enzymes

Activity-based metagenomics is one of the most efficient approaches to boost the discovery of novel biocatalysts from the huge reservoir of uncultivated bacteria. In this chapter, we describe a highly generic procedure of metagenomic library construction and high-throughput screening for carbohydrate-active enzymes. Applicable to any bacterial ecosystem, it enables the swift identification of functional enzymes that are highly efficient, alone or acting in synergy, to break down polysaccharides and oligosaccharides

Effect of statins on the incidence of cardiovascular evenrs after kidney transplantation

International audienceAbstract Background and Aims Based on intervention thresholds [1], statins are recommended in kidney transplant recipients (KTRs) who are at high risk for major cardiovascular (CV) events. However, in this population, evidence of statin effectiveness is sparse and non-conclusive. The objective of this study is to assess the effect of statins on CV events in KTRs. Method 613 consecutive KTRs from a single-center cohort were retrospectively included between 2006 and 2019. Exposure to statins (indicated in primary or secondary CV prevention) and atherosclerotic CV events during the study period were comprehensively documented. The primary outcome was the incidence of CV events in all statin users compared to that of non-users, based on the Cardiovascular and Stroke Endpoint Definitions for Clinical Trials [2]. In this study, only atherosclerotic events were selected (peripheral vascular stenosis, stroke, myocardial infarction, angina pectoris and transitional ischemic attack). The secondary outcomes were the incidence of CV events (i) in KTRs using statins indicated in primary CV prevention and (ii) in KTRs using statins indicated in secondary CV prevention compared to that of non-users. Cox proportional hazard models including statin exposure as a time-dependent covariate and fitted with inverse probability treatment weighting (IPTW) were used, as well as a multivariable Cox proportional hazard model. Results During a median [interquartile range (IQR)] follow-up period of 4.6 [2.7–10.0] years, CV events occurred in 88 KTRs: 48 (55.5%) KTRs had peripheral vascular stenosis, 24 (27.3%) had myocardial infarction, 12 (13.6%) had stroke, three (3.5%) had angina pectoris and one (1.1%) had a transitional ischemic attack. The incidence of CV events was 24.8 per 1000 person-years. In the Cox models fitted with IPTW, exposure to statins, regardless of the indication or indicated in primary and secondary CV prevention, was not associated with a decrease in CV events: Hazard Ratio (HR) [95% confidence interval (CI)]: 1.22 [0.73–2.03] (P = .435), HR: 1.12 [0.66–1.89] (P = .672), and HR: 2.78 [1.19–6.53] (P = .018), respectively. In the multivariable Cox model, diabetes mellitus was strongly associated with CV events (HR: 4.39 [2.79–6.90], p&lt;0.001), and statin exposure was not (HR: 1.25 [0.78–2.03]). In a subgroup of KTRs exposed to statins after kidney transplantation but not before (n=314), the median [IQR] levels of LDL-c was 3.48 [2.89–4.08] mmol/L when starting statins and 2.74 [2.14–3.35] mmol/L after one year of statin exposure, i.e. a significant decrease of 0.74 [0.60–0.85] mmol/L (p&lt;0.001). The median [IQR] levels of triglyceride was 1.99 [1.47–2.91] mmol/L when starting statins and 1.72 [1.20–2.50] mmol/L after one year of statin exposure, i.e. a significant decrease of 0.27 [0.17–0.42] mmol/l (p&lt;0.001). There were no significant changes in HDL-c levels. Conclusion Despite an improvement in the lipid profile including a reduction of LDL-c and triglyceride levels, statin exposure was not associated with a decrease in CV events in a long-term KTR cohort. Other CV risk factors than dyslipidemia, such as diabetes mellitus, were more likely related to such events

Le Courrier

06 mars 18511851/03/06 (N65)