Corrigendum. ICSI does not improve reproductive outcomes in autologous ovarian response cycles with non-male factor subfertility
Notice bibliographique
Résumé
Hum Reprod 2020:35: pp. 583–594 The authors would like to apologise for the errors in Table 1, Table 3 and the manuscript of the above article. The errors, unfortunately, occurred in the process of transcribing the data across three platforms (Microsoft Excel, SPPS and then on to Microsoft Word). This has now been rechecked by three different individuals to avoid further transcription errors. Amendments have also been made to Table 4 to further clarify its intention. Distribution of IVF and ICSI cycles in poor ovarian response according to female age groups, number of previous ART cycles, number of previous live birth(s) through ART, oocyte yield, stage of transfer, number of embryos transferred and a sub-analysis of all ovarian response categories. 1466 31742 18556 (55%) 1357 591 (2%) 0.107 0.504 62641 33436 (12%) 29205 (10%) 15892 8067 (33%) 7825 (34%) 1466 31742 18556 (55%) 1357 591 (2%) 0.107 0.504 62641 33436 (12%) 29205 (10%) 15892 8067 (33%) 7825 (34%) Multivariable logistic regression–adjusted for female age, number of previous ART cycles, number of previous live births through ART, oocyte yield. The data is expressed as whole numbers and percentages. The adjusted Odds Ratio (aOR) is displayed as the odds of performing ICSI over IVF for each of the variables. Distribution of IVF and ICSI cycles in poor ovarian response according to female age groups, number of previous ART cycles, number of previous live birth(s) through ART, oocyte yield, stage of transfer, number of embryos transferred and a sub-analysis of all ovarian response categories. 1466 31742 18556 (55%) 1357 591 (2%) 0.107 0.504 62641 33436 (12%) 29205 (10%) 15892 8067 (33%) 7825 (34%) 1466 31742 18556 (55%) 1357 591 (2%) 0.107 0.504 62641 33436 (12%) 29205 (10%) 15892 8067 (33%) 7825 (34%) Multivariable logistic regression–adjusted for female age, number of previous ART cycles, number of previous live births through ART, oocyte yield. The data is expressed as whole numbers and percentages. The adjusted Odds Ratio (aOR) is displayed as the odds of performing ICSI over IVF for each of the variables. Clinical pregnancy, live birth, singleton and multiple birth rate per treatment cycle in all ovarian response for IVF and ICSI cycles distributed by the variables female age, number of previous ART cycles, number of previous live births through ART, oocyte yield and stage of embryo transfer expressed in whole numbers and as a percentage. 17352 (9.4) 57704 (39.9) 50692 (35.1) 34905 (24.2) 15787 (10.9) 4947 (14.8) 17352 (9.4) 57704 (39.9) 50692 (35.1) 34905 (24.2) 15787 (10.9) 4947 (14.8) Clinical pregnancy, live birth, singleton and multiple birth rate per treatment cycle in all ovarian response for IVF and ICSI cycles distributed by the variables female age, number of previous ART cycles, number of previous live births through ART, oocyte yield and stage of embryo transfer expressed in whole numbers and as a percentage. 17352 (9.4) 57704 (39.9) 50692 (35.1) 34905 (24.2) 15787 (10.9) 4947 (14.8) 17352 (9.4) 57704 (39.9) 50692 (35.1) 34905 (24.2) 15787 (10.9) 4947 (14.8) The odds ratio of IVF vs ICSI for clinical pregnancy and live birth outcome subcategorised by 5-year intervals from 2002 up to 2016 for poor ovarian response cohort and by oocyte yield for 1998 to 2016, with 99.5% and 95% confidence intervals and p-values respectively. IVF (n=11,651) ICSI (n=11,362) 1.04 (0.93 – 1.16) 1 0.354 1.03 (0.91 – 1.16) 1 0.500 IVF (n=10,743) ICSI (n=9,836) 1.13 (0.99 – 1.28) 1 0.010 1.14 (0.99 – 1.30) 1 0.006 IVF (n=7,293) ICSI (n=5,837) 1.04 (0.89 – 1.22) 1 0.473 1.04 (0.87 – 1.23) 1 0.573 IVF (n=33,436) ICSI (n=29,205) 1.04 (0.97 – 1.12) 1 0.102 1.03 (0.96 – 1.11) 1 0.261 IVF (n=115,639) ICSI (n=123,497) 1.02 (0.99 – 1.05) 1 0.014 1.03 (0.99 – 1.05) 1 0.012 IVF (n=78,504) ICSI (n=91,284) 0.99 (0.96 – 1.02) 1 0.314 0.99 (0.96 – 1.02) 1 0.261 IVF (n=27,829) ICSI (n=33,452) 0.97 (0.92 – 1.02) 1 0.048 0.98 (0.93 – 1.03) 1 0.286 IVF (n=10,750) ICSI (n=12,736) 0.97 (0.90 – 1.06) 1 0.368 0.98 (0.90 – 1.07) 1 0.480 IVF (n=6,275) ICSI (n=6,998) 0.88 (0.77 – 1.00) 1 0.005 0.88 (0.77 – 1.01) 1 0.011 *aOR (95% CI) Clinical Pregnancy *aOR (95% CI) Live Birth IVF (n=18,556) ICSI (n=13,186) 1.05 (0.96 – 1.16) 1 0.126 1.03 (0.93 – 1.14) 1 0.451 IVF (n=66,863) ICSI (n=58,320) 1.04 (1.00 – 1.07) 1 0.005 1.04 (1.00 – 1.08) 1 0.005 IVF (n=47,008) ICSI (n=44,926) 0.99 (0.96 – 1.03) 1 0.671 1.00 (0.96 – 1.04) 1 0.968 IVF (n=17,386) ICSI (n=17,252) 0.97 (0.91 – 1.04) 1 0.187 1.00 (0.93 – 1.07) 1 0.997 IVF (n=6,967) ICSI (n=6,882) 1.02 (0.92 – 1.14) 1 0.530 1.02 (0.92 – 1.14) 1 0.548 IVF (n=4,270) ICSI (n=4,084) 0.91 (0.77 – 1.07) 1 0.109 0.92 (0.78 – 1.09) 1 0.156 IVF (n=11,651) ICSI (n=11,362) 1.04 (0.93 – 1.16) 1 0.354 1.03 (0.91 – 1.16) 1 0.500 IVF (n=10,743) ICSI (n=9,836) 1.13 (0.99 – 1.28) 1 0.010 1.14 (0.99 – 1.30) 1 0.006 IVF (n=7,293) ICSI (n=5,837) 1.04 (0.89 – 1.22) 1 0.473 1.04 (0.87 – 1.23) 1 0.573 IVF (n=33,436) ICSI (n=29,205) 1.04 (0.97 – 1.12) 1 0.102 1.03 (0.96 – 1.11) 1 0.261 IVF (n=115,639) ICSI (n=123,497) 1.02 (0.99 – 1.05) 1 0.014 1.03 (0.99 – 1.05) 1 0.012 IVF (n=78,504) ICSI (n=91,284) 0.99 (0.96 – 1.02) 1 0.314 0.99 (0.96 – 1.02) 1 0.261 IVF (n=27,829) ICSI (n=33,452) 0.97 (0.92 – 1.02) 1 0.048 0.98 (0.93 – 1.03) 1 0.286 IVF (n=10,750) ICSI (n=12,736) 0.97 (0.90 – 1.06) 1 0.368 0.98 (0.90 – 1.07) 1 0.480 IVF (n=6,275) ICSI (n=6,998) 0.88 (0.77 – 1.00) 1 0.005 0.88 (0.77 – 1.01) 1 0.011 *aOR (95% CI) Clinical Pregnancy *aOR (95% CI) Live Birth IVF (n=18,556) ICSI (n=13,186) 1.05 (0.96 – 1.16) 1 0.126 1.03 (0.93 – 1.14) 1 0.451 IVF (n=66,863) ICSI (n=58,320) 1.04 (1.00 – 1.07) 1 0.005 1.04 (1.00 – 1.08) 1 0.005 IVF (n=47,008) ICSI (n=44,926) 0.99 (0.96 – 1.03) 1 0.671 1.00 (0.96 – 1.04) 1 0.968 IVF (n=17,386) ICSI (n=17,252) 0.97 (0.91 – 1.04) 1 0.187 1.00 (0.93 – 1.07) 1 0.997 IVF (n=6,967) ICSI (n=6,882) 1.02 (0.92 – 1.14) 1 0.530 1.02 (0.92 – 1.14) 1 0.548 IVF (n=4,270) ICSI (n=4,084) 0.91 (0.77 – 1.07) 1 0.109 0.92 (0.78 – 1.09) 1 0.156 Clinical pregnancy and live birth outcome adjusted for female age, number of previous ART cycles, number of previous live birth(s) through ART, oocyte yield, stage of transfer, method of fertilisation and number of embryos transferred. Clinical pregnancy and live birth outcome adjusted for female age, oocyte yield, stage of transfer, method of fertilisation and number of embryos transferred. The odds ratio of IVF vs ICSI for clinical pregnancy and live birth outcome subcategorised by 5-year intervals from 2002 up to 2016 for poor ovarian response cohort and by oocyte yield for 1998 to 2016, with 99.5% and 95% confidence intervals and p-values respectively. IVF (n=11,651) ICSI (n=11,362) 1.04 (0.93 – 1.16) 1 0.354 1.03 (0.91 – 1.16) 1 0.500 IVF (n=10,743) ICSI (n=9,836) 1.13 (0.99 – 1.28) 1 0.010 1.14 (0.99 – 1.30) 1 0.006 IVF (n=7,293) ICSI (n=5,837) 1.04 (0.89 – 1.22) 1 0.473 1.04 (0.87 – 1.23) 1 0.573 IVF (n=33,436) ICSI (n=29,205) 1.04 (0.97 – 1.12) 1 0.102 1.03 (0.96 – 1.11) 1 0.261 IVF (n=115,639) ICSI (n=123,497) 1.02 (0.99 – 1.05) 1 0.014 1.03 (0.99 – 1.05) 1 0.012 IVF (n=78,504) ICSI (n=91,284) 0.99 (0.96 – 1.02) 1 0.314 0.99 (0.96 – 1.02) 1 0.261 IVF (n=27,829) ICSI (n=33,452) 0.97 (0.92 – 1.02) 1 0.048 0.98 (0.93 – 1.03) 1 0.286 IVF (n=10,750) ICSI (n=12,736) 0.97 (0.90 – 1.06) 1 0.368 0.98 (0.90 – 1.07) 1 0.480 IVF (n=6,275) ICSI (n=6,998) 0.88 (0.77 – 1.00) 1 0.005 0.88 (0.77 – 1.01) 1 0.011 *aOR (95% CI) Clinical Pregnancy *aOR (95% CI) Live Birth IVF (n=18,556) ICSI (n=13,186) 1.05 (0.96 – 1.16) 1 0.126 1.03 (0.93 – 1.14) 1 0.451 IVF (n=66,863) ICSI (n=58,320) 1.04 (1.00 – 1.07) 1 0.005 1.04 (1.00 – 1.08) 1 0.005 IVF (n=47,008) ICSI (n=44,926) 0.99 (0.96 – 1.03) 1 0.671 1.00 (0.96 – 1.04) 1 0.968 IVF (n=17,386) ICSI (n=17,252) 0.97 (0.91 – 1.04) 1 0.187 1.00 (0.93 – 1.07) 1 0.997 IVF (n=6,967) ICSI (n=6,882) 1.02 (0.92 – 1.14) 1 0.530 1.02 (0.92 – 1.14) 1 0.548 IVF (n=4,270) ICSI (n=4,084) 0.91 (0.77 – 1.07) 1 0.109 0.92 (0.78 – 1.09) 1 0.156 IVF (n=11,651) ICSI (n=11,362) 1.04 (0.93 – 1.16) 1 0.354 1.03 (0.91 – 1.16) 1 0.500 IVF (n=10,743) ICSI (n=9,836) 1.13 (0.99 – 1.28) 1 0.010 1.14 (0.99 – 1.30) 1 0.006 IVF (n=7,293) ICSI (n=5,837) 1.04 (0.89 – 1.22) 1 0.473 1.04 (0.87 – 1.23) 1 0.573 IVF (n=33,436) ICSI (n=29,205) 1.04 (0.97 – 1.12) 1 0.102 1.03 (0.96 – 1.11) 1 0.261 IVF (n=115,639) ICSI (n=123,497) 1.02 (0.99 – 1.05) 1 0.014 1.03 (0.99 – 1.05) 1 0.012 IVF (n=78,504) ICSI (n=91,284) 0.99 (0.96 – 1.02) 1 0.314 0.99 (0.96 – 1.02) 1 0.261 IVF (n=27,829) ICSI (n=33,452) 0.97 (0.92 – 1.02) 1 0.048 0.98 (0.93 – 1.03) 1 0.286 IVF (n=10,750) ICSI (n=12,736) 0.97 (0.90 – 1.06) 1 0.368 0.98 (0.90 – 1.07) 1 0.480 IVF (n=6,275) ICSI (n=6,998) 0.88 (0.77 – 1.00) 1 0.005 0.88 (0.77 – 1.01) 1 0.011 *aOR (95% CI) Clinical Pregnancy *aOR (95% CI) Live Birth IVF (n=18,556) ICSI (n=13,186) 1.05 (0.96 – 1.16) 1 0.126 1.03 (0.93 – 1.14) 1 0.451 IVF (n=66,863) ICSI (n=58,320) 1.04 (1.00 – 1.07) 1 0.005 1.04 (1.00 – 1.08) 1 0.005 IVF (n=47,008) ICSI (n=44,926) 0.99 (0.96 – 1.03) 1 0.671 1.00 (0.96 – 1.04) 1 0.968 IVF (n=17,386) ICSI (n=17,252) 0.97 (0.91 – 1.04) 1 0.187 1.00 (0.93 – 1.07) 1 0.997 IVF (n=6,967) ICSI (n=6,882) 1.02 (0.92 – 1.14) 1 0.530 1.02 (0.92 – 1.14) 1 0.548 IVF (n=4,270) ICSI (n=4,084) 0.91 (0.77 – 1.07) 1 0.109 0.92 (0.78 – 1.09) 1 0.156 Clinical pregnancy and live birth outcome adjusted for female age, number of previous ART cycles, number of previous live birth(s) through ART, oocyte yield, stage of transfer, method of fertilisation and number of embryos transferred. Clinical pregnancy and live birth outcome adjusted for female age, oocyte yield, stage of transfer, method of fertilisation and number of embryos transferred. We would like to emphasise that the transcription errors had no impact on the message of the publication and its academic value. Whilst the ‘n’ numbers were affected, the odds ratio and confidence interval calculations were not, thus preserving the overall scientific impact of the findings from the study.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,046 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,059 | 0,037 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».