#1122 Anaemia in CKD and cardiovascular risk; all cut from the same cloth? Article Swipe
Lisa Le Gall
,
Jérôme Harambat
,
Christian Combe
,
Natália Alencar de Pinho
,
Bénédicte Stengel
,
Céline Lange
,
Karen Leffondré
,
Mathilde Prezelin‐Reydit
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1093/ndt/gfae069.670
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1093/ndt/gfae069.670
Background and Aims Anaemia in chronic kidney disease (CKD) has been repeatedly associated with increased cardiovascular morbidity and mortality, but most studies have not investigated its longitudinal association by sex and age. Our aim was to study the association between haemoglobin (Hb) current value and the hazard of major adverse cardiovascular event (MACE) in specific subgroups of CKD patients defined by age and sex. Because erythropoiesis-stimulating agents (ESA) are incriminated to modify the effect of Hb level on the hazard of event for high level of Hb, we have here only focused in non-ESA users CKD patients. Method We used data from the CKD-REIN cohort, which included 3033 patients with moderate to severe CKD from 40 nationally representative nephrology clinics in France between 2013 and 2016. We included patients with at least one Hb, estimated glomerular filtration rate (eGFR), transferrin saturation (TSAT) or ferritin measurement. We studied all Hb measurements available until a first MACE defined as the first event among cardio-vascular death, myocardial infarction, stroke or hospitalization for acute heart failure; initiation of kidney replacement therapy; death from other causes; or initiation of ESA therapy, whichever came first. First, we estimated the individual trajectories of Hb, eGFR, TSAT, ferritin using multivariate share random effect joint model. Then, we estimated the association between Hb current value and MACE using a cause specific multivariate Cox model in 4 specific subgroups separately: women ≤ and >70 years, men ≤ and >70 years. All models were adjusted on current value of eGFR, TSAT, Ferritin, and baseline value of albumin-to-creatinine ratio, age, CKD aetiology, heart failure past history, alcohol consumption, iron treatment, antithrombotic and anticoagulant. When appropriate, spline functions were used for continuous variables to account for potential non-linear effects. Reference value of Hb for computing hazard ratio was 12 g/dL in women, and 13 in men according to current definition of anaemia. Results A total of 2742 patients were included in the analysis (median eGFR 33 ml/min/1.73 m2, median age at inclusion 69 years) together with 28423 Hb measurements (median of 13 per patient) collected during a median follow-up of 5.0 years. There were 551 women ≤70 (median Hb 12.4 g/dL, 34 (6.2%) MACE), 349 women > 70 (12.2 g/dL, 61 (17.5%) MACE), 1009 men ≤ 70 (13.4 g/dL, 104 (10.3%) MACE) and 833 men > 70 (13.0 g/dL, 163 (19.6%) MACE). No statistical significant association was found in males whatever their age (Hazard ratio of MACE for each 1 g/dL increase in Hb 1.0 (95% CI 0.9-1.1) in men < 70 and 0.9 (95% CI 0.8-1.1) in men > 70). For women, the hazard of MACE raised as the Hb values decreased, with a more pronounced increase in women > 70 (Fig. 1). For example, the hazard ratio for a Hb value of 10 g/dL compared to the reference was 2.0 (95% CI 0.9-4.7) in women < 70 and 3.3 (95% CI 1.5-7.2) in women > 70. Conclusion In non-ESA users CKD patients, anaemia is associated with the occurrence of MACE in females, especially those older than 70 years. These results raise question about a one-size-fits-all approach in the interpretation of low values of haemoglobin and anaemia management. It also suggests to evaluate the effect of anaemia therapies in men and women separately.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/ndt/gfae069.670
- https://academic.oup.com/ndt/article-pdf/39/Supplement_1/gfae069-0670-1122/57793749/gfae069-0670-1122.pdf
- OA Status
- bronze
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4398233989
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4398233989Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1093/ndt/gfae069.670Digital Object Identifier
- Title
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#1122 Anaemia in CKD and cardiovascular risk; all cut from the same cloth?Work title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-05-01Full publication date if available
- Authors
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Lisa Le Gall, Jérôme Harambat, Christian Combe, Natália Alencar de Pinho, Bénédicte Stengel, Céline Lange, Karen Leffondré, Mathilde Prezelin‐ReyditList of authors in order
- Landing page
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https://doi.org/10.1093/ndt/gfae069.670Publisher landing page
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https://academic.oup.com/ndt/article-pdf/39/Supplement_1/gfae069-0670-1122/57793749/gfae069-0670-1122.pdfDirect link to full text PDF
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YesWhether a free full text is available
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bronzeOpen access status per OpenAlex
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https://academic.oup.com/ndt/article-pdf/39/Supplement_1/gfae069-0670-1122/57793749/gfae069-0670-1122.pdfDirect OA link when available
- Concepts
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Medicine, Internal medicine, Hazard ratio, Kidney disease, Mace, Transferrin saturation, Renal function, Proportional hazards model, Myocardial infarction, Cohort, Ferritin, Cardiology, Heart failure, Anemia, Iron deficiency, Confidence interval, Percutaneous coronary interventionTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.g/dL | 297, 408, 463 |
| abstract_inverted_index.have | 23, 89 |
| abstract_inverted_index.here | 90 |
| abstract_inverted_index.high | 84 |
| abstract_inverted_index.iron | 267 |
| abstract_inverted_index.more | 443 |
| abstract_inverted_index.most | 21 |
| abstract_inverted_index.only | 91 |
| abstract_inverted_index.past | 263 |
| abstract_inverted_index.rate | 138 |
| abstract_inverted_index.sex. | 64 |
| abstract_inverted_index.than | 505 |
| abstract_inverted_index.used | 100, 277 |
| abstract_inverted_index.were | 243, 276, 316, 351 |
| abstract_inverted_index.with | 14, 110, 130, 333, 441, 495 |
| abstract_inverted_index.(12.2 | 366 |
| abstract_inverted_index.(13.0 | 385 |
| abstract_inverted_index.(13.4 | 375 |
| abstract_inverted_index.(CKD) | 9 |
| abstract_inverted_index.(ESA) | 68 |
| abstract_inverted_index.(Fig. | 450 |
| abstract_inverted_index.2016. | 126 |
| abstract_inverted_index.28423 | 334 |
| abstract_inverted_index.MACE) | 379 |
| abstract_inverted_index.TSAT, | 199, 250 |
| abstract_inverted_index.Then, | 208 |
| abstract_inverted_index.There | 350 |
| abstract_inverted_index.These | 508 |
| abstract_inverted_index.about | 512 |
| abstract_inverted_index.acute | 170 |
| abstract_inverted_index.among | 161 |
| abstract_inverted_index.cause | 221 |
| abstract_inverted_index.death | 178 |
| abstract_inverted_index.eGFR, | 198, 249 |
| abstract_inverted_index.event | 52, 82, 160 |
| abstract_inverted_index.first | 154, 159 |
| abstract_inverted_index.found | 395 |
| abstract_inverted_index.g/dL, | 358, 367, 376, 386 |
| abstract_inverted_index.heart | 171, 261 |
| abstract_inverted_index.joint | 206 |
| abstract_inverted_index.least | 132 |
| abstract_inverted_index.level | 77, 85 |
| abstract_inverted_index.major | 49 |
| abstract_inverted_index.males | 397 |
| abstract_inverted_index.model | 225 |
| abstract_inverted_index.older | 504 |
| abstract_inverted_index.other | 180 |
| abstract_inverted_index.raise | 510 |
| abstract_inverted_index.ratio | 294, 402, 456 |
| abstract_inverted_index.share | 203 |
| abstract_inverted_index.study | 37 |
| abstract_inverted_index.their | 399 |
| abstract_inverted_index.those | 503 |
| abstract_inverted_index.total | 312 |
| abstract_inverted_index.until | 152 |
| abstract_inverted_index.users | 95, 489 |
| abstract_inverted_index.using | 201, 219 |
| abstract_inverted_index.value | 44, 216, 247, 254, 288, 460 |
| abstract_inverted_index.which | 106 |
| abstract_inverted_index.women | 231, 353, 363, 447, 474, 483, 540 |
| abstract_inverted_index.≤70 | 354 |
| abstract_inverted_index.(6.2%) | 360 |
| abstract_inverted_index.(MACE) | 53 |
| abstract_inverted_index.(TSAT) | 142 |
| abstract_inverted_index.First, | 190 |
| abstract_inverted_index.France | 122 |
| abstract_inverted_index.MACE), | 361, 370 |
| abstract_inverted_index.MACE). | 389 |
| abstract_inverted_index.Method | 98 |
| abstract_inverted_index.agents | 67 |
| abstract_inverted_index.death, | 163 |
| abstract_inverted_index.during | 343 |
| abstract_inverted_index.effect | 74, 205, 533 |
| abstract_inverted_index.first. | 189 |
| abstract_inverted_index.hazard | 47, 80, 293, 432, 455 |
| abstract_inverted_index.kidney | 7, 175 |
| abstract_inverted_index.median | 326, 345 |
| abstract_inverted_index.model. | 207 |
| abstract_inverted_index.models | 242 |
| abstract_inverted_index.modify | 72 |
| abstract_inverted_index.raised | 435 |
| abstract_inverted_index.random | 204 |
| abstract_inverted_index.ratio, | 257 |
| abstract_inverted_index.severe | 113 |
| abstract_inverted_index.spline | 274 |
| abstract_inverted_index.stroke | 166 |
| abstract_inverted_index.values | 439, 521 |
| abstract_inverted_index.women, | 299, 430 |
| abstract_inverted_index.years) | 331 |
| abstract_inverted_index.years, | 235 |
| abstract_inverted_index.years. | 240, 349, 507 |
| abstract_inverted_index.(10.3%) | 378 |
| abstract_inverted_index.(17.5%) | 369 |
| abstract_inverted_index.(19.6%) | 388 |
| abstract_inverted_index.(Hazard | 401 |
| abstract_inverted_index.(eGFR), | 139 |
| abstract_inverted_index.(median | 321, 337, 355 |
| abstract_inverted_index.Anaemia | 4 |
| abstract_inverted_index.Because | 65 |
| abstract_inverted_index.Results | 310 |
| abstract_inverted_index.account | 282 |
| abstract_inverted_index.adverse | 50 |
| abstract_inverted_index.alcohol | 265 |
| abstract_inverted_index.anaemia | 492, 525, 535 |
| abstract_inverted_index.between | 40, 123, 213 |
| abstract_inverted_index.causes; | 181 |
| abstract_inverted_index.chronic | 6 |
| abstract_inverted_index.clinics | 120 |
| abstract_inverted_index.cohort, | 105 |
| abstract_inverted_index.current | 43, 215, 246, 306 |
| abstract_inverted_index.defined | 60, 156 |
| abstract_inverted_index.disease | 8 |
| abstract_inverted_index.failure | 262 |
| abstract_inverted_index.focused | 92 |
| abstract_inverted_index.non-ESA | 94, 488 |
| abstract_inverted_index.results | 509 |
| abstract_inverted_index.studied | 147 |
| abstract_inverted_index.studies | 22 |
| abstract_inverted_index.&gt; | 364, 383, 427, 448, 484 |
| abstract_inverted_index.&lt; | 418, 475 |
| abstract_inverted_index.0.8-1.1) | 424 |
| abstract_inverted_index.0.9-1.1) | 415 |
| abstract_inverted_index.0.9-4.7) | 472 |
| abstract_inverted_index.1.5-7.2) | 481 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.CKD-REIN | 104 |
| abstract_inverted_index.adjusted | 244 |
| abstract_inverted_index.anaemia. | 309 |
| abstract_inverted_index.analysis | 320 |
| abstract_inverted_index.approach | 515 |
| abstract_inverted_index.baseline | 253 |
| abstract_inverted_index.compared | 464 |
| abstract_inverted_index.effects. | 286 |
| abstract_inverted_index.evaluate | 531 |
| abstract_inverted_index.example, | 453 |
| abstract_inverted_index.failure; | 172 |
| abstract_inverted_index.females, | 501 |
| abstract_inverted_index.ferritin | 144, 200 |
| abstract_inverted_index.history, | 264 |
| abstract_inverted_index.included | 107, 128, 317 |
| abstract_inverted_index.increase | 409, 445 |
| abstract_inverted_index.moderate | 111 |
| abstract_inverted_index.patient) | 341 |
| abstract_inverted_index.patients | 59, 109, 129, 315 |
| abstract_inverted_index.question | 511 |
| abstract_inverted_index.specific | 55, 222, 228 |
| abstract_inverted_index.suggests | 529 |
| abstract_inverted_index.therapy, | 186 |
| abstract_inverted_index.therapy; | 177 |
| abstract_inverted_index.together | 332 |
| abstract_inverted_index.whatever | 398 |
| abstract_inverted_index.Ferritin, | 251 |
| abstract_inverted_index.Reference | 287 |
| abstract_inverted_index.according | 304 |
| abstract_inverted_index.available | 151 |
| abstract_inverted_index.collected | 342 |
| abstract_inverted_index.computing | 292 |
| abstract_inverted_index.estimated | 135, 192, 210 |
| abstract_inverted_index.follow-up | 346 |
| abstract_inverted_index.functions | 275 |
| abstract_inverted_index.inclusion | 329 |
| abstract_inverted_index.increased | 15 |
| abstract_inverted_index.morbidity | 17 |
| abstract_inverted_index.patients, | 491 |
| abstract_inverted_index.patients. | 97 |
| abstract_inverted_index.potential | 284 |
| abstract_inverted_index.reference | 467 |
| abstract_inverted_index.subgroups | 56, 229 |
| abstract_inverted_index.therapies | 536 |
| abstract_inverted_index.variables | 280 |
| abstract_inverted_index.whichever | 187 |
| abstract_inverted_index.&gt;70 | 234, 239 |
| abstract_inverted_index.Background | 1 |
| abstract_inverted_index.Conclusion | 486 |
| abstract_inverted_index.aetiology, | 260 |
| abstract_inverted_index.associated | 13, 494 |
| abstract_inverted_index.continuous | 279 |
| abstract_inverted_index.decreased, | 440 |
| abstract_inverted_index.definition | 307 |
| abstract_inverted_index.especially | 502 |
| abstract_inverted_index.filtration | 137 |
| abstract_inverted_index.glomerular | 136 |
| abstract_inverted_index.individual | 194 |
| abstract_inverted_index.initiation | 173, 183 |
| abstract_inverted_index.mortality, | 19 |
| abstract_inverted_index.myocardial | 164 |
| abstract_inverted_index.nationally | 117 |
| abstract_inverted_index.nephrology | 119 |
| abstract_inverted_index.non-linear | 285 |
| abstract_inverted_index.occurrence | 497 |
| abstract_inverted_index.pronounced | 444 |
| abstract_inverted_index.repeatedly | 12 |
| abstract_inverted_index.saturation | 141 |
| abstract_inverted_index.treatment, | 268 |
| abstract_inverted_index.association | 28, 39, 212, 393 |
| abstract_inverted_index.haemoglobin | 41, 523 |
| abstract_inverted_index.infarction, | 165 |
| abstract_inverted_index.management. | 526 |
| abstract_inverted_index.ml/min/1.73 | 324 |
| abstract_inverted_index.replacement | 176 |
| abstract_inverted_index.separately. | 541 |
| abstract_inverted_index.separately: | 230 |
| abstract_inverted_index.significant | 392 |
| abstract_inverted_index.statistical | 391 |
| abstract_inverted_index.transferrin | 140 |
| abstract_inverted_index.appropriate, | 273 |
| abstract_inverted_index.consumption, | 266 |
| abstract_inverted_index.incriminated | 70 |
| abstract_inverted_index.investigated | 25 |
| abstract_inverted_index.longitudinal | 27 |
| abstract_inverted_index.measurement. | 145 |
| abstract_inverted_index.measurements | 150, 336 |
| abstract_inverted_index.multivariate | 202, 223 |
| abstract_inverted_index.trajectories | 195 |
| abstract_inverted_index.anticoagulant. | 271 |
| abstract_inverted_index.antithrombotic | 269 |
| abstract_inverted_index.cardiovascular | 16, 51 |
| abstract_inverted_index.interpretation | 518 |
| abstract_inverted_index.representative | 118 |
| abstract_inverted_index.cardio-vascular | 162 |
| abstract_inverted_index.hospitalization | 168 |
| abstract_inverted_index.one-size-fits-all | 514 |
| abstract_inverted_index.albumin-to-creatinine | 256 |
| abstract_inverted_index.erythropoiesis-stimulating | 66 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 8 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.5799999833106995 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.13418773 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |