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Enregistrement W2167939344 · doi:10.1093/ndt/gfq066

Epidemiology of cardio-renal syndromes: workgroup statements from the 7th ADQI Consensus Conference

2010· review· en· W2167939344 sur OpenAlexaff
Sean M. Bagshaw, D. N. Cruz, Nadia Aspromonte, Luciano Daliento, Federico Ronco, G. Sheinfeld, Stefan D. Anker, Inder S. Anand, Rinaldo Bellomo, Tomás Berl, Ilona Bobek, Andrew Davenport, Mikko Haapio, Hans L. Hillege, Andrew A. House, N. Katz, Alan S. Maisel, Sunil Mankad, Peter A. McCullough, Alexandre Mebazaa, Alberto Palazzuoli, Piotr Ponikowski, Andrew Shaw, Sachin Soni, Giorgio Vescovo, Nereo Zamperetti, P. Zanco, Claudio Ronco

Notice bibliographique

RevueNephrology Dialysis Transplantation · 2010
Typereview
Langueen
DomaineMedicine
ThématiqueDialysis and Renal Disease Management
Établissements canadiensLondon Health Sciences CentreAlberta Hospital EdmontonUniversity of Alberta Hospital
Organismes subventionnairesnon disponible
Mots-clésWorkgroupMedicineConsensus conferenceEpidemiologyIntensive care medicineMEDLINEInternal medicine

Résumé

récupéré en direct d'OpenAlex

Observational and clinical trial data have accrued to show that acute/chronic heart disease can directly contribute to and/or accelerate acute/chronic worsening kidney function and vice versa. A description of the epidemiology of heart–kidney interaction, as defined by the proposed consensus cardio-renal syndrome (CRS) definitions, is a critical initial step towards understanding not only the overall burden of disease for each of the proposed CRS subtypes, but also their natural history, associated morbidity and mortality and potential health resource implications [1]. Importantly, these CRS subtypes may have important discriminating features in terms of predisposing or precipitating events, risk identification, natural history and outcomes. Likewise, a surveillance of the epidemiology is vital for determining whether there exist important gaps in knowledge and for the design of future epidemiologic investigations and clinical trials. Accordingly, this article will summarize the epidemiology of CRS. Refer to supplementary file. This syndrome is characterized by acute worsening of heart function leading to acute kidney injury (AKI) and/or dysfunction. The spectrum of acute cardiac events that may contribute to AKI and the development of acute cardio-renal syndrome (Type 1 CRS) include acute decompensated heart failure (ADHF), acute coronary syndrome (ACS), cardiogenic shock and cardiac surgery-associated low cardiac output syndrome. There is a large body of literature that has examined AKI attributable to acute worsening of heart function, in particular for ADHF and ACS (Tables 2 and 3). Most are retrospective, secondary and/or posthoc analyses from large databases [2–8] or clinical trials of drug therapy [9,10]. Few were prospective [11–15]. Summary of studies fulfilling criteria for Type 1 CRS with a presenting diagnosis of ADHF SCr, serum creatinine; m, months; d, days; CV, cardiovascular; LOS, length of stay. Summary of studies fulfilling criteria for Type 1 CRS with a presenting diagnosis of ADHF SCr, serum creatinine; m, months; d, days; CV, cardiovascular; LOS, length of stay. Summary of studies fulfilling criteria for Type 1 CRS with a presenting diagnosis of ACS WRF, worsening renal function; SCr, serum creatinine; wks, weeks; m, months; CKD, chronic kidney disease; ESKD, end-stage kidney disease. Summary of studies fulfilling criteria for Type 1 CRS with a presenting diagnosis of ACS WRF, worsening renal function; SCr, serum creatinine; wks, weeks; m, months; CKD, chronic kidney disease; ESKD, end-stage kidney disease. The term ‘worsening renal function’ (WRF) has been regularly used to describe the acute and/or sub-acute changes that occur to kidney function following ADHF or ACS (Table 1). The incidence estimates for WRF associated with ADHF and ACS have ranged between 24–45 and 9–19%, respectively. A small single-centre study found that AKI occurred in 48% of paediatric patients admitted for ADHF [16]. The broad range in reported incidence is largely attributable to variations in the definitions of WRF, differences in the observed time-at-risk and the heterogeneity of selected populations being studied (Table 1). Proposed summary of operational definitions to be used when describing the epidemiology of CRS HF, heart failure; LVEF, left ventricular ejection fraction; ESC, European Society of Cardiology; AHA, Alberta Heart Association; ACC, American College of Cardiology; TIA, transient ischaemic attack; SCr, serum creatinine; GFR, glomerular filtration rate. Proposed summary of operational definitions to be used when describing the epidemiology of CRS HF, heart failure; LVEF, left ventricular ejection fraction; ESC, European Society of Cardiology; AHA, Alberta Heart Association; ACC, American College of Cardiology; TIA, transient ischaemic attack; SCr, serum creatinine; GFR, glomerular filtration rate. Many studies used variable durations of observed time-at-risk for ascertainment of WRF. Most commonly, criteria for WRF were fulfilled if the defined changes to kidney function occurred within hospital admission [4,5,15]. This is problematic when considering the variation in duration of hospital stay both between individual patient admissions and between studies. Other studies observed for WRF for 2 weeks [9] and up to 6 months [17]. These variations in observed time-at-risk for WRF have the potential to introduce bias and misclassification. In ADHF, Gottlieb et al. showed that 47% had WRF within 3 days of hospital admission [4], while Cowie et al. found that 50% occurred within 4 days [11]. Both Cowie et al. and Krumholz et al. showed that 70–90% of all WRF had occurred within the first week of hospital admission [5,11]. Likewise, two studies have shown that the time to peak change in serum creatinine (SCr) had occurred within 5 days of hospital admission [13,14]. Goldberg et al. found that 75% of AKI occurring in association with ACS occurred within 3 days after hospital admission [3]. Accordingly, these differences in time to ascertain WRF/AKI will influence the incidence and outcome estimates and unduly influence the generalizability and inference from any given study. Several clinical factors have been shown to be associated with increased risk for WRF including male sex, kidney dysfunction at the time of hospital admission, worsened heart failure (HF) (i.e. NHYA class, left ventricular ejection fraction or pulmonary oedema), tachyarrhythmias and elevated blood pressure at hospital admission. Similarly, several therapy-related factors have shown association with WRF including high-dose diuretic and/or vasodilator therapy [2,5,10,11,14,18]. In both ADHF and acute myocardial infarction (AMI), the development of WRF/AKI has been associated with worse clinical outcomes and higher health care costs [5] (Tables 2 and 3). In ADHF, the presence of AKI confers an increased risk for both short-term and long-term all-cause and cardiovascular mortality [2,4,5,10,11,13–15]. Moreover, there appears to be a biological gradient seen between severity of AKI and risk of death [15]. Two studies have shown that the risk of poor outcome persisted regardless of whether WRF/AKI was transient or sustained [12,13]. Several studies have shown that the development of AKI in association with ADHF prolongs stay in hospital [4,5,11,13,14]. While two studies showed that AKI in ADHF was associated with increased readmission rates [13,14], this was not a universal finding [5,10,11,15]. Similar to ADHF, AKI associated with ACS appears to significantly modify the risk of poor outcome [3,7–9,12]. Importantly, even small acute changes in SCr appear to modify the risk of death [9]. In addition, data have also suggested a greater occurrence of cardiovascular events such as congestive heart failure (CHF), recurrent ACS and stroke and need for re-hospitalization among patients who developed AKI [9]. Newsome et al. reported a greater likelihood and/or rate of progression to end-stage kidney disease (ESKD) in those with ACS complicated by AKI [7]. These data would suggest that the development of AKI in association with ADHF or ACS may further exacerbate cardiac injury and/or function and also contribute to exaggerated declines in kidney function. This would imply that the observed heart–kidney interface in Type 1 CRS may synergistically act to further accelerate injury and/or dysfunction following the initial insult. We suggest the use of an established consensus definition/classification for AKI in clinical practice and future studies enrolling ADHF/ACS patients. We also favour the use of the term AKI rather than WRF. The term AKI better represents the entire spectrum of acute renal failure and would enable integration of Type 1 CRS into the broader context of AKI. We believe there is a need to define a relevant time frame for ascertainment of AKI associated with ADHF and/or ACS. The ideal ‘ascertainment time’ would identify AKI as being most likely attributable to the acute cardiac event rather than due to observed complications of therapy or more chronic processes (where prognosis may differ). We suggest that the diagnosis of AKI in association with ADHF/ACS should be determined within the first 7 days of hospitalization based on data showing that the majority of patients (>90%) would be captured within this time frame. This would permit greater standardization of data across future epidemiologic investigations. Future investigations should evaluate the incidence, temporal profile and outcomes of Type 1 CRS in selected populations (i.e. ADHF, ACS) with the use of established consensus definitions for AKI. Clinical outcomes should include both short-term and long-term mortality along with major morbidity outcomes (i.e. kidney function, progression to ESKD, cardiovascular events, quality of life, health care costs). We also recognize that the current definition for Type 1 CRS only explicitly considers establishing the diagnosis and presence of pathologic heart–kidney interaction. However, there is also the need to acknowledge that, once present, this interaction may synergistically compound existing and/or further accelerate bi-directional injury and/or dysfunction in either organ system. We believe that this requires investigation to better understand the pathophysiology and natural history of patients diagnosed with Type 1 CRS. This syndrome is characterized by chronic abnormalities in cardiac function leading to kidney injury or dysfunction. This subtype indicates a more chronic state of kidney disease complicating chronic heart disease. The term ‘chronic cardiac abnormalities’ encompasses several different conditions including chronic HF, atrial fibrillation, congenital heart disease, constrictive pericarditis and chronic ischaemic heart disease (Table 4). Summary of studies fulfilling the criteria for Type 2 CRS ARIC, Atherosclerosis Risk in Communities Study; ADHF, acute decompensated heart failure; GFRc, GFR estimated by Cockroft–Gault; CATS, Captopril and Thrombolysis Study; CVD, cardiovascular disease; CHS, Cardiovascular Health Study; DIG, Digoxin Investigator Group. Summary of studies fulfilling the criteria for Type 2 CRS ARIC, Atherosclerosis Risk in Communities Study; ADHF, acute decompensated heart failure; GFRc, GFR estimated by Cockroft–Gault; CATS, Captopril and Thrombolysis Study; CVD, cardiovascular disease; CHS, Cardiovascular Health Study; DIG, Digoxin Investigator Group. Chronic heart disease and chronic kidney disease (CKD) frequently co-exist. The clinical circumstances often present a challenge for determining which disease process was primary versus secondary. This challenge is likewise evident when appraising the literature and applying the proposed consensus CRS subtype definitions in a retrospective manner. Several large database studies have assembled patient cohorts based on the presence of one disease (i.e. CHF) while estimating the prevalence/incidence of the other (i.e. kidney dysfunction). For example, in the ADHERE study, evaluating 118 465 ADHF admissions, 27.4, 43.5 and 13.1% of patients were found to have mild, moderate and severe kidney dysfunction at the time of hospital admission, respectively [19]. Increasing severity of dysfunction was found to portend worse clinical outcomes, including ICU admission, mechanical ventilation, length of stay and in-hospital mortality. Similarly, in a secondary analysis of the Digitalis Investigation Group trial, Campbell et al. found that CKD in ambulatory patients with chronic HF (45% of cohort) was associated with increased risk of hospitalization and death [20]. Moreover, there was a biologic gradient in the risk for hospitalization and mortality as glomerular filtration rate (GFR) decreased. These data clearly highlight the common co-existence of heart and kidney dysfunction and associated poor prognosis; however, very few studies are able to clearly separate the occurrence of kidney disease in time from the occurrence of heart disease. Therefore, the current body of literature does not readily allow for clear discrimination between chronic cardio-renal syndrome (Type 2 CRS) and chronic reno-cardiac syndrome (Type 4) CRS (see below). A recent pooled analysis of data from the Atherosclerosis Risk in Communities Study and Cardiovascular Health Study provided further insight into the epidemiology of Type 2 CRS [21]. Patients with baseline cardiovascular disease (CVD) constituted 12.9% of the study population. These patients had a mean baseline SCr 79.6 µmol/L [0.9 mg/dL] and estimated glomerular filtration rate (eGFR) 86.2 mL/min/1.73 m2. After a mean follow-up of 9.3 years, 7.2% of CVD patients had declines in kidney function when defined as a SCr increase of ≥35.4 µmol/L [0.4 mg/dL] and 34% when defined as a decrease in eGFR ≥ 15 mL/min/1.73 m2. During the observational period, 2.3% and 5.6% developed new kidney disease, respectively. By multi-variable analysis, baseline CVD was independently associated with both decline in kidney function and development of new CKD. These data provide compelling evidence for the attributable risk of CVD for declines in kidney function (OR 1.70, 95% CI 1.36–2.31) and CKD (OR 1.75, 95% CI 1.32–2.32) and the concept of Type II CRS. ‘Cyanotic nephropathy’ has long been recognized as a potential of congenital heart disease with congenital heart in the majority of have et al. studied patients into with congenital heart disease this had evidence of kidney dysfunction that was to in and in Patients with had the eGFR and the of moderate or severe GFR Similarly, there was a towards greater kidney dysfunction in patients with more However, kidney dysfunction was even among patients characterized as Importantly, kidney dysfunction had a on mortality for versus We suggest of patients into CRS subtypes based on the initial diagnosis of either CKD or For example, when CVD clearly of CKD, as in congenital heart disease, patients should be as Type 2 CRS. We recognize that clear discrimination of the primary versus secondary process will not be given the of CVD and CKD. In these patients be as both (i.e. Type Future clinical studies need to evaluate the incidence and of kidney by CVD (i.e. congenital heart and The rate of progression of CKD in patients with established CVD and whether interaction also more as as the of on these renal the proposed consensus definitions, would be to between different CRS believe investigations should be for risk of potential of patients with Type 2 CRS who may kidney injury and/or dysfunction in the context of chronic studies should and to further the of heart–kidney interaction. The of chronic heart disease and CKD on mortality and cardiovascular events are other long-term relevant should include quality of and health care This syndrome is characterized by acute worsening of kidney function (i.e. that to acute cardiac injury and/or dysfunction (i.e. conditions to acute reno-cardiac syndrome (Type 3 CRS) would include acute kidney injury other AKI after major AKI after cardiac and any for which AKI directly to acute cardiac dysfunction. The association of AKI and acute cardiac dysfunction with these conditions likely predisposing for development and (i.e. of We also however, that the to Type 3 CRS likely of and/or Similar to CRS subtypes, the epidemiology of Type 3 CRS is for several heterogeneity in predisposing conditions different for variable baseline risk in for the development of acute cardiac dysfunction (i.e. increased in with and failure of clinical studies of AKI to the occurrence of acute cardiac dysfunction as outcomes. Accordingly, incidence estimates and associated clinical outcomes of acute cardiac dysfunction following the development of AKI are largely and an example, a leading of kidney injury following and and on progression of CKD and of health While AKI is most often attributable to the of factors (i.e. disease, kidney may also be The reported incidence is variable on the being CKD, and the of (i.e. and of estimates have been reported in the range of Moreover, the incidence of will likely increase with the broader of for along with of both CKD and The natural history of in patients may an in SCr with to baseline and these patients would not be to the criteria for Type 3 CRS. However, in an estimated AKI to the of renal therapy In these AKI may be associated with of pulmonary and cardiac Importantly, those at risk for may be a Several factors have been found to independently for after including CKD, CVD, HF and of However, the in evaluating the epidemiology of Type 3 CRS attributable to is that few studies have reported the temporal occurrence of cardiovascular events following There are for clinical practice in this consensus definitions for AKI in future epidemiologic studies. We believe the of cardiovascular events as outcomes is to better understand and the epidemiology of Type 3 CRS. primary investigations to factors associated with those at risk or those for acute cardiac dysfunction in AKI and whether these factors may be and/or The Type 4 CRS is a primary CKD to a in cardiac function (i.e. cardiac left ventricular left ventricular and/or an increased risk for cardiovascular events (i.e. myocardial HF, This CRS subtype to cardiac dysfunction and/or disease occurring in to CKD. CKD is into clinical based on changes to GFR and kidney Several observational studies have the cardiovascular event rates and outcomes in selected populations Most were retrospective and/or analyses from large clinical databases or clinical trials. this of the epidemiology of Type 4 CRS is to summarize and estimates due largely to differences in the in the clinical outcomes in the duration of time for ascertainment of study and in the operational definitions used for CKD, cardiac disease and mortality (i.e. all-cause or (Table Summary of studies fulfilling criteria for Type 4 CRS ESKD, end-stage kidney disease; CKD, chronic kidney disease; congestive heart failure; CVD, disease; coronary heart disease; left ventricular CV, cardiovascular; estimated glomerular filtration ADHF, acute decompensated heart Summary of studies fulfilling criteria for Type 4 CRS ESKD, end-stage kidney disease; CKD, chronic kidney disease; congestive heart failure; CVD, disease; coronary heart disease; left ventricular CV, cardiovascular; estimated glomerular filtration ADHF, acute decompensated heart For example, the in these based on the presence and/or severity of CKD, ranged from kidney function to et in a secondary analysis of the found that of patients in the trial had of cardiac disease at baseline and those who have been a duration of had higher of cardiac disease. During of patients were admitted to hospital for were attributable to ischaemic the of cardiac were attributable to ischaemic cardiac disease in this was significantly of death follow-up risk disease in patients is and mortality rates are higher when with and populations Moreover, recent data have to suggest in selected patients with chronic may cardiac injury and contribute to declines in myocardial In those CKD patients not the of CVD with CKD severity The of CVD events and death is also likely further by and presence of In data from the II study, et al. found a CVD of and 12.9% for patients with eGFR and respectively Likewise, in a large et al. found in the of CVD and HF, along with higher risk of cardiac events follow-up associated with the of decline in eGFR mL/min/1.73 This in CVD by severity of CKD also into for risk of and all-cause mortality Several investigations that the presence of CKD the risk for and development of CVD This risk for cardiovascular events and disease in patients with CKD may be the of pathophysiology that in these patients These CKD patients may a with clinical In to a of cardiovascular risk the elevated CVD risk may also a of processes not including elevated chronic in and In broader epidemiologic the exaggerated risk or worsening of CVD in CKD patients may also be by current data from observational studies or secondary analyses may to for or CKD patients have been from clinical trials and as a or and the for and/or in CKD patients or WRF may be such that therapy is not due to of a is that these in may provide for the of cardiac disease and worse clinical outcomes for CKD patients. However, prospective data on CKD are of the epidemiology of Type 4 CRS from the literature is in due to to clearly between the primary versus secondary disease process and the that likely with Type 2 as Moreover, recognize that the current definition for Type 4 CRS only explicitly considers establishing the presence of pathologic heart–kidney interaction and does not explicitly identify and/or for of patients CKD may act to significantly modify the risk of cardiovascular events and accelerate CKD patients with Type 4 CRS have the potential for between CRS This has the potential to in to patients (i.e. Type 2 Type 3 We suggest that CKD patients should be to their baseline (i.e. or with to include a CRS Likewise, as recognize that clear discrimination of the primary versus secondary process will not be in these patients given the of CVD and CKD. In these that patients be as both (i.e. Type Future clinical studies need to evaluate the of CVD and the incidence of CVD events by CKD the temporal to both kidney and cardiac function time and and to further the of interaction in these patients. Likewise, clinical studies are to the incidence of and risk factors for CVD in patients with CKD. We recognize that such patients may in further definition for Type 1 CRS and other CRS In addition, future clinical trials and observational studies need to evaluate the and of CKD and/or This syndrome is characterized by acute or chronic that both cardiac and kidney dysfunction. There is data on the epidemiology of secondary cardio-renal (Type 5 CRS) in due to the large of potential acute and chronic Accordingly, estimates of incidence, risk and associated outcomes for Type 5 CRS are largely and/or and may be Importantly, there is an understanding of the of secondary interaction. whether cardiac and kidney dysfunction in is or whether there is bi-directional interaction that may directly contribute to dysfunction in either organ (i.e. and/or Moreover, there is a of data to when the of such bi-directional interaction that would the criteria for a secondary CRS. We have selected potential acute and chronic conditions that may contribute to Type 5 CRS in Summary of selected potential for acute and chronic Type 5 CRS Summary of selected potential for acute and chronic Type 5 CRS The that may to acute Type 5 CRS is at a rate of and is by an estimated The and estimated to be between and a rate to the mortality for While data have suggested a in the of patients from has increased of patients AKI and have as a major to the development of AKI studies have shown higher morbidity and mortality for those with AKI when to those with either or AKI Similarly, abnormalities in cardiac function are common in patients with The incidence of cardiac dysfunction in is on the being the definition used for the of cardiac dysfunction (i.e. low cardiac output by pulmonary left ventricular dysfunction by severity of and duration of to However, observational data have found that have elevated that often with cardiac function kidney and myocardial dysfunction in are there is a of and epidemiologic studies that have examined for insight on the incidence, risk and associated outcomes for patients with AKI and myocardial who may the criteria for acute Type 5 CRS. There are for clinical practice in this For Type 5 studies are to and recognize the spectrum of acute/chronic that to acute/chronic pathologic heart–kidney interaction. Both and epidemiologic investigations of can be to evaluate the on and temporal changes in both heart and kidney function occurring in to acute/chronic heart and kidney and to whether can be and cardiac disease are and frequently co-exist. A large body of observational and clinical trial data has found that acute/chronic cardiac disease can directly contribute to acute/chronic worsening kidney function and vice versa. The proposed CRS subtypes to are all characterized by important heart–kidney that likely in however, all appear to have important discriminating features in terms of predisposing or precipitating events, risk identification, natural history and outcomes. Type 1 CRS is with incidence estimates of AKI in ADHF or ACS between 24–45 and 9–19%, respectively. the development of Type 1 CRS clearly into higher morbidity and worse clinical Chronic heart disease and CKD are in and frequently co-exist. Accordingly, this for applying the proposed definitions for Type 2 and 4 CRS to the existing literature when the primary versus secondary process be clearly to the incidence and outcome estimates associated with Type 3 CRS are largely and data is on the epidemiology or the of secondary heart–kidney interaction (Type 5 CRS) due to the large of potential Accordingly, the epidemiology of Type 5 CRS is largely and In there is a clear need for prospective studies to the epidemiology of heart–kidney across the CRS subtypes, not only for a better understanding of the overall burden of disease, but also for risk and of potential for or in future investigations. is by a Clinical Investigator from the Alberta for is by a from the Society of of has an from for has an from for has been on the for

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,008
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,011
Score d'incertitude au seuil0,028

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,008
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0040,003
Bibliométrie0,0050,007
Études des sciences et des technologies0,0000,001
Communication savante0,0020,002
Science ouverte0,0020,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,077
Tête enseignante GPT0,366
Écart entre enseignants0,289 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations231
Publié2010
Routes d'admission1
Résumé présentnon

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