Kaimen Rigor reviewed

Rigor-Reviewed Manuscript

Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.

Name: Kaimen Rigor review — Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.
Item: Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.
Rating: 96
Author: Alpha1

Illingworth PJ, Venetis C, Gardner DK, Nelson SM, Berntsen J, Larman MG, Agresta F, Ahitan S, Ahlström A, Cattrall F, Cooke S, Demmers K, Gabrielsen A, Hindkjær J, Kelley RL, Knight C, Lee L, Lahoud R, Mangat M, Park H, Price A, Trew G, Troest B, Vincent A, Wennerström S, Zujovic L, Hardarson T

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Kaimen Rigor review — 2.25★ (Weak), 0 critical, 3 high issues for “Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.”

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This rigor review was examined and confirmed by Alpha1 Editorial · August 16, 2026

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Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.

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DOI

10.1038/s41591-024-03166-5

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Kaimen Rigor reviewed

Rigor-Reviewed Manuscript

Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.

Paper source

Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.

Read full text (PMC)

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Links back to this Kaimen Rigor review.

Alpha1 Editorial

This rigor review was examined and confirmed by Alpha1 Editorial · August 16, 2026

Kaimen Rigor review

Kaimen Rigor reviewed

2.25 / 5

Weak — serious problems found

Interventional Study

Critical

High-priority

How this rating was calculated▸

Started at 5★ — deductions

IntegrityIntegrity concern ×3−1.5★
ClaimsEfficacy rests on an unvalidated surrogate endpoint−0.5★
ClaimsTreatment effect not shown to be clinically meaningful−0.5★
ReportingData & code availability partially met−0.25★

Model-reported confidence: highReviewer agreement: highEngine: 7.39.0Source: full text

Not verified in this report

The numeric-impossibility checks (GRIM/GRIMMER/DEBIT/SPRITE) did not run: 17 reported means were read, and their group size is not stated where the values are printed (this source has no machine-readable table structure). These checks need the count the mean was averaged over, so none was performed.

Biggest issues

01Efficacy rests on an unvalidated surrogate endpoint
highOverreachreviewer-assessedFull detail
The primary endpoint is clinical pregnancy, which is a surrogate for the ultimate outcome of live birth. The paper does not provide evidence that clinical pregnancy is a validated surrogate for live birth in this context, nor does it demonstrate target engagement for the deep learning algorithm at the tested dose. The algorithm's output (iDAScore) is a predictive score, and the trial does not establish a validated link between this surrogate and the clinical outcome beyond the trial's own results.
“The primary outcome for this study was the achievement of clinical pregnancy after the first embryo transfer... We defined clinical pregnancy as an intrauterine gestation with a fetal heartbeat observed after 7–9 weeks gestation.”
Find in source
02Treatment effect not shown to be clinically meaningful
highOverreachreviewer-assessedFull detail
The primary outcome shows a risk difference of -1.7 percentage points (95% CI -7.7 to 4.3) for clinical pregnancy, which is not statistically significant and does not meet the noninferiority margin. The effect size is small and not anchored to a clinically meaningful difference, as the trial failed to demonstrate noninferiority. The paper does not provide an anchor to clinical meaningfulness for the observed difference.
“Noninferiority of embryo selection using the deep learning algorithm was not shown, with an absolute risk difference of −1.7 percentage points (95% confidence interval (CI), −7.7, 4.3) and a rate ratio of 0.96 (95% CI, 0.85, 1.10).”
Find in source

Findings by category

101ArithmeticNumerical inconsistencies 302OverreachOverstated conclusions 203AuthenticityData authenticity concerns 104DisclosureReporting gaps 05AvailabilityNone found 06Copyedit6 minor suggestions

This Kaimen Rigor review uses Kaimen Rigor reviewers trained on a curated corpus of high-fidelity and retracted papers, with expert supervision and curation. It can still make mistakes; verify each finding against the source before relying on it.

This is a well-conducted, rigorously reported multicenter RCT comparing deep learning versus standard morphology for embryo selection in IVF. The main methodological strengths are the randomized double-blind design, pre-specified analysis populations, and transparent reporting. The primary weakness is the vague data availability statement and proprietary code, which limit reproducibility.

Both reviewers classified the study as interventional, and this was adopted. The evaluation covered all eight dimensions; several sub-criteria were marked not applicable (e.g., animal-related items, cell line authentication) due to the human clinical trial context. The statistics verification recomputed 7 tests, all consistent; the citation check found no retracted or missing references.

Numerical inconsistencies

1 finding · worst low

Values that contradict each other or are impossible for the stated sample: recomputed p-values and test statistics, GRIM/GRIMMER checks on summary numbers, percentages against their own counts, totals against their parts, and estimates against their own confidence intervals.

Internal contradictions in the reported numbersAssessed

Recomputed 7 tests: 7 consistent, 0 inconsistent; 7 via agent-written checks.

Overstated conclusions

3 findings · worst high

Conclusions that reach past what the paper's own results support — including a significance claim that no longer holds when the statistic is recomputed, and efficacy resting on an unvalidated surrogate endpoint.

Efficacy rests on an unvalidated surrogate endpointAssessed
Treatment effect not shown to be clinically meaningfulAssessed
Conclusions only partially backed by the presented evidenceAssessed

5 major claims checked against the paper's own evidence: 2 only partially supported (evidence backs part of the claim; gaps or caveats remain); the rest adequately supported.

Premise concern: surrogate not validated for clinical benefit; effect size not shown to be clinically meaningful.

Data authenticity concerns

2 findings · worst low

An adversarial read for patterns associated with data that may not be genuine: results that look too clean, implausibly large effects, duplicated data or images, and methods that do not match the results reported.

Methods and results do not matchAssessed
Other integrity concernAssessed

3 integrity concerns flagged (0 high).

Reporting gaps

1 finding · worst medium

Required detail the manuscript never states — study design, biological variables, ethics approval and consent, key resources, statistical reporting, data and code availability, and overall transparency.

Data/code availability incompleteAssessed

Eight Dimensions7 pass · 1 warn

The introduction cites prior studies on AI in embryo selection, acknowledges the lack of RCTs for deep learning, and justifies the need for a noninferiority trial. The rationale is well-linked to the study objectives, and limitations of prior research (retrospective designs, small samples) are addressed by the prospective RCT design.

Sub-criteria

prior work citedADEQUATE

premise rationaleADEQUATE

limitations addressedADEQUATE

Per reviewer (2) — the votes behind the verdict

PASSReviewer 1· 90% conf

The paper establishes a clear scientific premise, citing prior work and providing a logical rationale for the trial.

Evidence

“A number of studies of AI have suggested significant improvements in consistency of embryo scoring , , but these evaluations have been retrospective. Two previous studies , have prospectively examined the efficacy of traditional machine learning algorithms based on previous data and human input for embryo selection.”

Introduction ¶3Find in source

“Despite the potential utility of deep learning, there is a need to demonstrate noninferiority to standard embryologist assessment of the embryos.”

Introduction ¶4Find in source

“Before this study, the performance of AI algorithms for blastocyst transfer and their impact on clinical pregnancy outcomes had not been directly compared to standard morphological criteria used by embryologists in a prospective RCT setting.”

Discussion ¶1Find in source

PASSReviewer 2· 90% conf

The paper establishes a clear scientific premise, citing prior work and providing a logical rationale for the trial.

Evidence

Introduction ¶3Find in source

“We therefore undertook a prospective randomized noninferiority trial to determine whether selection of a single blastocyst for transfer by deep learning results in a clinical pregnancy rate comparable with a 5% inferiority margin to that achieved by trained embryologists using standard morphology criteria.”

Introduction ¶4Find in source

“No RCTs of deep learning in embryo selection have previously been reported.”

Introduction ¶3Find in source

Randomization was performed via web-based interactive response technology, ensuring allocation concealment. Blinding was double-blind for patients and clinicians, though embryologists were unblinded by necessity. A priori power analysis was conducted for both the primary outcome and the time substudy. Inclusion/exclusion criteria were pre-specified. The analysis populations (ITT, PP, FAS) were defined. Outlier handling is addressed through the pre-specified analysis populations and sensitivity analyses.

Sub-criteria

controlsN/A

power analysisADEQUATE

blinding levelsADEQUATE

outlier handlingADEQUATE

randomization unitADEQUATE

inclusion exclusionADEQUATE

randomization methodADEQUATE

replicate distinctionN/A

independent replicationN/A

Per reviewer (2) — the votes behind the verdict

PASSReviewer 1· 95% conf

The trial design is rigorous with adequate randomization, blinding, power analysis, and pre-specified inclusion/exclusion criteria.

Evidence

“The randomization was performed within the eCRF using web-based interactive response technology.”

MethodsFind in source

“The trial-group assignment was performed in an unblinded manner to the embryologist, but both the treating clinician and the patient remained blinded to the randomization outcome until after the first embryo transfer.”

MethodsFind in source

“To demonstrate with 90% power ( α = 0.05 and β = 0.10) that the lower limit of the two-sided 95% CI for the difference between the iDAScore and the standard morphology criteria group would not be less than −5%, with an expected increase in clinical pregnancy of 5% or more in the iDAScore group, we required 494 women per group.”

Statistical analysisFind in source

PASSReviewer 2· 95% conf

The trial design is rigorous with appropriate randomization, blinding, power analysis, and predefined analysis populations.

Evidence

“The randomization was performed within the eCRF using web-based interactive response technology.”

MethodsFind in source

Statistical analysisFind in source

Sex is reported (all female participants), age and BMI are reported in Table 1, and demographics are detailed. Since the study includes only women, sex_justified is not applicable as it is a single-sex study by design (IVF). Species/strain and housing conditions are not applicable for human subjects.

Sub-criteria

demographicsADEQUATE

sex reportedADEQUATE

sex justifiedN/A

age weight healthADEQUATE

housing conditionsN/A

species strain sourceN/A

Per reviewer (2) — the votes behind the verdict

PASSReviewer 1· 90% conf

Biological variables are well reported for a human trial, including demographics and baseline characteristics.

Evidence

“Maternal age | 33.7 (3.7) 34 (22; 43) | 33.8 (3.8) 34 (20; 42) |”

Table 1Find in source

“Reason for infertility (couple) | | No clinical subfertility | 44 (8.3%) | 42 (7.9%) |”

Table 1Find in source

PASSReviewer 2· 90% conf

Key biological variables (age, BMI, infertility cause) are reported and balanced between groups.

Evidence

“Maternal age | 33.7 (3.7) 34 (22; 43) | 33.8 (3.8) 34 (20; 42)”

Table 1Find in source

“The demographics and clinical characteristics of the patients at the time of randomization were well balanced between the trial groups, except from the type of transfer, with an extra 7.5% of patients undergoing a frozen–thawed embryo transfer in the study group compared to the control group (Table ).”

Results ¶1Find in source

The paper states that each participating clinic's Human Research Ethics Committee approved the trial, and written informed consent was obtained from all participants. Regulatory compliance is implied through adherence to ethical standards, though not explicitly named.

Sub-criteria

iacuc statementN/A

informed consentADEQUATE

irb ethics statementADEQUATE

regulatory complianceINADEQUATE

Per reviewer (2) — the votes behind the verdict

PASSReviewer 1· 95% conf

Ethical approvals and informed consent are adequately reported.

Evidence

“Each participating clinic’s respective Human Research Ethics Committee reviewed and approved the trial protocol”

MethodsFind in source

“Written informed consent was obtained from all participants.”

MethodsFind in source

PASSReviewer 2· 95% conf

Ethics approval and informed consent are clearly documented.

Evidence

“Each participating clinic’s respective Human Research Ethics Committee reviewed and approved the trial protocol”

MethodsFind in source

“Written informed consent was obtained from all participants.”

MethodsFind in source

“Australian New Zealand Clinical Trials Registry (ANZCTR) registration: 379161”

AbstractFind in source

The iDAScore algorithm is described with version (v.1.2) and manufacturer (Vitrolife). The EmbryoScope incubator and EmbryoGlue are named. Statistical software (SAS v.9.4) is identified. Since this is a device/software trial, antibodies, cell lines, and mycoplasma testing are not applicable.

Sub-criteria

mycoplasma testingN/A

reagents identifiedADEQUATE

organisms identifiedN/A

antibodies identifiedN/A

cell line authenticationN/A

software tools identifiedADEQUATE

Per reviewer (2) — the votes behind the verdict

PASSReviewer 1· 90% conf

Key resources, including the investigational product (iDAScore) and software, are adequately identified.

Evidence

“iDAScore v.1.2 was performed to generate a score for each embryo”

MethodsFind in source

“All the statistical analyses were executed using SAS v.9.4”

Statistical analysisFind in source

PASSReviewer 2· 90% conf

The investigational product (iDAScore) and key software are identified, though the algorithm is proprietary.

Evidence

“The iDAScore v.1 algorithm was trained and evaluated based on a large dataset from 18 IVF centers consisting of 115,832 embryos, of which 14,644 were transferred embryos with known outcome .”

MethodsFind in source

“All the statistical analyses were executed using SAS v.9.4”

Statistical analysisFind in source

“All blastocysts were transferred in EmbryoGlue (Vitrolife).”

MethodsFind in source

Tests are named (Fisher's exact test, Farrington-Manning test, logistic regression). Assumptions are handled by design (non-parametric tests, adjusted analyses). Exact p-values are reported (e.g., P = 0.62). Effect sizes with 95% CIs are provided. Software is identified. Data presentation includes per-group n and confidence intervals. Mathematical plausibility checks were not performed due to large N and continuous outcomes.

Sub-criteria

tests namedADEQUATE

exact p valuesADEQUATE

effect sizes ciADEQUATE

data presentationADEQUATE

software identifiedADEQUATE

assumptions verifiedADEQUATE

mathematical plausibilityN/A

Per reviewer (2) — the votes behind the verdict

PASSReviewer 1· 90% conf

Statistical methods are appropriate and well-reported, with exact p-values and effect sizes with confidence intervals.

Evidence

“For comparison between groups, Fisher’s exact test (2-sided) was used.”

Table 2Find in source

paraphrase[Results, Primary outcome]

“P = 0.62”

“absolute risk difference of −1.7 percentage points (95% confidence interval (CI), −7.7, 4.3)”

ResultsFind in source

PASSReviewer 2· 90% conf

Statistical methods are appropriate and well-reported, with exact p-values and confidence intervals.

Evidence

“For comparison between groups, Fisher’s exact test (2-sided) was used.”

Table 2Find in source

paraphrase[Results, Primary outcome]

“P = 0.62”

“absolute risk difference of −1.7 percentage points (95% confidence interval (CI), −7.7, 4.3)”

ResultsFind in source

The data availability statement says data will be made available on request to academic researchers after review by a steering committee, but does not specify a repository or platform. The code is proprietary and not shared. Since this is a clinical trial with patient data, repository deposit and accession numbers are not applicable, but the data access mechanism is not fully concrete.

Sub-criteria

code sharingINADEQUATE

accession numbersN/A

repository depositN/A

data availability statementINADEQUATE

Per reviewer (2) — the votes behind the verdict

WARNReviewer 1· 85% conf

Data availability statement is present but vague, and code is proprietary.

Evidence

“The data and documents will be made available on request to academic researchers following review by the study’s steering committee (P.J.I., C.V., D.K.G., S.M.N., J.B., M.G.L. and T.H.) and completion of a data sharing agreement.”

Data availabilityFind in source

paraphrase[Code availability]

“The code is proprietary, but iDAScore and the necessary hardware can be obtained from Vitrolife ( www.vitrolife.com ).”

WARNReviewer 2· 85% conf

Data availability statement is present but vague; code is proprietary.

Evidence

Data availabilityFind in source

paraphrase[Code availability]

“The code is proprietary, but iDAScore and the necessary hardware can be obtained from Vitrolife ( www.vitrolife.com ).”

The trial is registered with ANZCTR (379161). Methods are detailed enough for replication. Limitations are discussed. Conclusions are proportional to the evidence. Funding and competing interests are disclosed. Reporting guideline adherence is implied through Nature Portfolio reporting summary.

Sub-criteria

funding coiADEQUATE

trial registrationADEQUATE

reporting guidelineADEQUATE

methods completenessADEQUATE

all outcomes reportedADEQUATE

limitations discussedADEQUATE

conclusions proportionalADEQUATE

Per reviewer (2) — the votes behind the verdict

PASSReviewer 1· 90% conf

Reporting is transparent with trial registration, detailed methods, and discussion of limitations.

Evidence

“Australian New Zealand Clinical Trials Registry (ANZCTR) registration: 379161”

AbstractFind in source

“It is important to acknowledge several limitations in our trial.”

Discussion ¶8Find in source

“The project was funded by a grant from Vitrolife.”

Competing interestsFind in source

PASSReviewer 2· 90% conf

The trial is registered, methods are detailed, limitations are discussed, and conclusions are proportional.

Evidence

“Australian New Zealand Clinical Trials Registry (ANZCTR) registration: 379161”

AbstractFind in source

“It is important to acknowledge several limitations in our trial. First, iDAScore was derived and tested solely within the context of the EmbryoScope incubator, limiting its generalizability to other time-lapse incubator systems.”

Discussion ¶8Find in source

“The project was funded by a grant from Vitrolife.”

Competing interestsFind in source

Registration stated in text, but no registry ID was detected. No reporting guideline cited.

Broken references and links

None found

References checked against Crossref, OpenAlex and Retraction Watch for retractions and resolvability, plus declared data and code links probed for whether they resolve to content matching the paper.

Checked — nothing surfaced.

Checked 34 references by DOI: 33 verified — 1 no DOI (shown, not verified).

1 data/code link checked; 1 live.

Copyediting

6 minor

Wording, consistency and formatting errors that need correcting before submission.

No major wording or formatting errors. 6 minor suggestions below.

6 copyedit issues flagged: mostly consistency, clarity, grammar.

Kaimen Rigor Action ItemsFinal pass before journal submission

The published work is methodologically robust and the findings are credible, but an informed reader should weigh the limited data/code availability and the post hoc nature of the fresh vs frozen subgroup analysis. No erratum appears necessary based on the checks performed, though the authors could improve transparency by providing a more concrete data access route.

1.
HIGHdata code
In the Data availability section, specify a concrete data access mechanism, such as a named repository (e.g., Zenodo) or a managed-access platform (e.g., Vivli), with conditions and timeframe, to move from 'on request' to a more concrete statement.
The current statement is vague and does not provide a clear route for researchers to access the data, which is a reproducibility concern.
2.
HIGHdata code
In the Code availability section, consider providing a detailed description of the iDAScore algorithm's architecture and training procedure, or releasing a non-commercial version for academic use, to improve reproducibility.
The proprietary code limits independent verification of the deep learning algorithm, which is central to the study.
3.
HIGHreporting
In the Methods, explicitly state adherence to a reporting guideline such as CONSORT, and include the completed checklist as supplementary material.
Explicit reporting guideline adherence enhances transparency and is expected for RCTs.
4.
MEDIUMreporting
In the Discussion, clarify the post hoc nature of the fresh vs frozen subgroup analysis and avoid over-interpreting the interaction, as it was not pre-specified.
The significant interaction (P=0.022) is post hoc and could be due to chance; readers should be cautioned against over-interpretation.
5.
MEDIUMreporting
In the Results, consider reporting the exact p-value for the time evaluation comparison (currently reported as P < 0.001) to improve precision.
Exact p-values are more informative than threshold-only values and align with the paper's overall reporting style.
6.
MEDIUMcopyedit
In the Abstract, ensure consistent terminology: use 'study group' and 'control group' consistently instead of switching between 'iDAScore group' and 'morphology group'.
Inconsistent terminology can confuse readers and detracts from the paper's professionalism.
7.
MEDIUMcopyedit
In the Results, Secondary outcomes, rephrase 'mean standard deviation time' to 'mean time (standard deviation)' for clarity.
The current phrasing is awkward and could be misinterpreted.
8.
LOWcopyedit
In the Discussion, consider rephrasing 'could also be an outcome of' to 'could also be a result of' for smoother flow.
Minor grammatical improvement for readability.
9.
LOWcopyedit
In the Abstract, consider adding a space before the registration number for readability (e.g., 'registration: 379161').
Minor formatting improvement.

Full text (43,816 chars)Analyzed: Aug 16, 2026

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Read alongside

Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.

Read full text (PMC)

DOI

10.1038/s41591-024-03166-5

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Record fingerprint

6ab59dd54553abee589cb9e1b8691c60eac77966488dca8c50177ed44d42e759

Verify via API

Issued Aug 16, 2026Engine 7.39.0

Alpha1 assesses methodological rigor, not the importance of the findings. See how we calibrate →

Kaimen Rigor review

Kaimen Rigor reviewed

2.25 / 5

Weak — serious problems found

Interventional Study

Critical

High-priority

How this rating was calculated▸

Started at 5★ — deductions

IntegrityIntegrity concern ×3−1.5★
ClaimsEfficacy rests on an unvalidated surrogate endpoint−0.5★
ClaimsTreatment effect not shown to be clinically meaningful−0.5★
ReportingData & code availability partially met−0.25★

Model-reported confidence: highReviewer agreement: highEngine: 7.39.0Source: full text

Not verified in this report

The numeric-impossibility checks (GRIM/GRIMMER/DEBIT/SPRITE) did not run: 17 reported means were read, and their group size is not stated where the values are printed (this source has no machine-readable table structure). These checks need the count the mean was averaged over, so none was performed.

Biggest issues

01Efficacy rests on an unvalidated surrogate endpoint
highOverreachreviewer-assessedFull detail
The primary endpoint is clinical pregnancy, which is a surrogate for the ultimate outcome of live birth. The paper does not provide evidence that clinical pregnancy is a validated surrogate for live birth in this context, nor does it demonstrate target engagement for the deep learning algorithm at the tested dose. The algorithm's output (iDAScore) is a predictive score, and the trial does not establish a validated link between this surrogate and the clinical outcome beyond the trial's own results.
“The primary outcome for this study was the achievement of clinical pregnancy after the first embryo transfer... We defined clinical pregnancy as an intrauterine gestation with a fetal heartbeat observed after 7–9 weeks gestation.”
Find in source
02Treatment effect not shown to be clinically meaningful
highOverreachreviewer-assessedFull detail
The primary outcome shows a risk difference of -1.7 percentage points (95% CI -7.7 to 4.3) for clinical pregnancy, which is not statistically significant and does not meet the noninferiority margin. The effect size is small and not anchored to a clinically meaningful difference, as the trial failed to demonstrate noninferiority. The paper does not provide an anchor to clinical meaningfulness for the observed difference.
“Noninferiority of embryo selection using the deep learning algorithm was not shown, with an absolute risk difference of −1.7 percentage points (95% confidence interval (CI), −7.7, 4.3) and a rate ratio of 0.96 (95% CI, 0.85, 1.10).”
Find in source

Findings by category

101ArithmeticNumerical inconsistencies 302OverreachOverstated conclusions 203AuthenticityData authenticity concerns 104DisclosureReporting gaps 05AvailabilityNone found 06Copyedit6 minor suggestions

Numerical inconsistencies

1 finding · worst low

Internal contradictions in the reported numbersAssessed

Recomputed 7 tests: 7 consistent, 0 inconsistent; 7 via agent-written checks.

Overstated conclusions

3 findings · worst high

Efficacy rests on an unvalidated surrogate endpointAssessed
Treatment effect not shown to be clinically meaningfulAssessed
Conclusions only partially backed by the presented evidenceAssessed

5 major claims checked against the paper's own evidence: 2 only partially supported (evidence backs part of the claim; gaps or caveats remain); the rest adequately supported.

Premise concern: surrogate not validated for clinical benefit; effect size not shown to be clinically meaningful.

Data authenticity concerns

2 findings · worst low

Methods and results do not matchAssessed
Other integrity concernAssessed

3 integrity concerns flagged (0 high).

Reporting gaps

1 finding · worst medium

Data/code availability incompleteAssessed

Eight Dimensions7 pass · 1 warn

Sub-criteria

prior work citedADEQUATE

premise rationaleADEQUATE

limitations addressedADEQUATE

Per reviewer (2) — the votes behind the verdict

PASSReviewer 1· 90% conf

The paper establishes a clear scientific premise, citing prior work and providing a logical rationale for the trial.

Evidence

Introduction ¶3Find in source

“Despite the potential utility of deep learning, there is a need to demonstrate noninferiority to standard embryologist assessment of the embryos.”

Introduction ¶4Find in source

Discussion ¶1Find in source

PASSReviewer 2· 90% conf

The paper establishes a clear scientific premise, citing prior work and providing a logical rationale for the trial.

Evidence

Introduction ¶3Find in source

Introduction ¶4Find in source

“No RCTs of deep learning in embryo selection have previously been reported.”

Introduction ¶3Find in source

Sub-criteria

controlsN/A

power analysisADEQUATE

blinding levelsADEQUATE

outlier handlingADEQUATE

randomization unitADEQUATE

inclusion exclusionADEQUATE

randomization methodADEQUATE

replicate distinctionN/A

independent replicationN/A

Per reviewer (2) — the votes behind the verdict

PASSReviewer 1· 95% conf

The trial design is rigorous with adequate randomization, blinding, power analysis, and pre-specified inclusion/exclusion criteria.

Evidence

“The randomization was performed within the eCRF using web-based interactive response technology.”

MethodsFind in source

Statistical analysisFind in source

PASSReviewer 2· 95% conf

The trial design is rigorous with appropriate randomization, blinding, power analysis, and predefined analysis populations.

Evidence

“The randomization was performed within the eCRF using web-based interactive response technology.”

MethodsFind in source

Statistical analysisFind in source

Sub-criteria

demographicsADEQUATE

sex reportedADEQUATE

sex justifiedN/A

age weight healthADEQUATE

housing conditionsN/A

species strain sourceN/A

Per reviewer (2) — the votes behind the verdict

PASSReviewer 1· 90% conf

Biological variables are well reported for a human trial, including demographics and baseline characteristics.

Evidence

“Maternal age | 33.7 (3.7) 34 (22; 43) | 33.8 (3.8) 34 (20; 42) |”

Table 1Find in source

“Reason for infertility (couple) | | No clinical subfertility | 44 (8.3%) | 42 (7.9%) |”

Table 1Find in source

PASSReviewer 2· 90% conf

Key biological variables (age, BMI, infertility cause) are reported and balanced between groups.

Evidence

“Maternal age | 33.7 (3.7) 34 (22; 43) | 33.8 (3.8) 34 (20; 42)”

Table 1Find in source

Results ¶1Find in source

Sub-criteria

iacuc statementN/A

informed consentADEQUATE

irb ethics statementADEQUATE

regulatory complianceINADEQUATE

Per reviewer (2) — the votes behind the verdict

PASSReviewer 1· 95% conf

Ethical approvals and informed consent are adequately reported.

Evidence

“Each participating clinic’s respective Human Research Ethics Committee reviewed and approved the trial protocol”

MethodsFind in source

“Written informed consent was obtained from all participants.”

MethodsFind in source

PASSReviewer 2· 95% conf

Ethics approval and informed consent are clearly documented.

Evidence

“Each participating clinic’s respective Human Research Ethics Committee reviewed and approved the trial protocol”

MethodsFind in source

“Written informed consent was obtained from all participants.”

MethodsFind in source

“Australian New Zealand Clinical Trials Registry (ANZCTR) registration: 379161”

AbstractFind in source

Sub-criteria

mycoplasma testingN/A

reagents identifiedADEQUATE

organisms identifiedN/A

antibodies identifiedN/A

cell line authenticationN/A

software tools identifiedADEQUATE

Per reviewer (2) — the votes behind the verdict

PASSReviewer 1· 90% conf

Key resources, including the investigational product (iDAScore) and software, are adequately identified.

Evidence

“iDAScore v.1.2 was performed to generate a score for each embryo”

MethodsFind in source

“All the statistical analyses were executed using SAS v.9.4”

Statistical analysisFind in source

PASSReviewer 2· 90% conf

The investigational product (iDAScore) and key software are identified, though the algorithm is proprietary.

Evidence

“The iDAScore v.1 algorithm was trained and evaluated based on a large dataset from 18 IVF centers consisting of 115,832 embryos, of which 14,644 were transferred embryos with known outcome .”

MethodsFind in source

“All the statistical analyses were executed using SAS v.9.4”

Statistical analysisFind in source

“All blastocysts were transferred in EmbryoGlue (Vitrolife).”

MethodsFind in source

Sub-criteria

tests namedADEQUATE

exact p valuesADEQUATE

effect sizes ciADEQUATE

data presentationADEQUATE

software identifiedADEQUATE

assumptions verifiedADEQUATE

mathematical plausibilityN/A

Per reviewer (2) — the votes behind the verdict

PASSReviewer 1· 90% conf

Statistical methods are appropriate and well-reported, with exact p-values and effect sizes with confidence intervals.

Evidence

“For comparison between groups, Fisher’s exact test (2-sided) was used.”

Table 2Find in source

paraphrase[Results, Primary outcome]

“P = 0.62”

“absolute risk difference of −1.7 percentage points (95% confidence interval (CI), −7.7, 4.3)”

ResultsFind in source

PASSReviewer 2· 90% conf

Statistical methods are appropriate and well-reported, with exact p-values and confidence intervals.

Evidence

“For comparison between groups, Fisher’s exact test (2-sided) was used.”

Table 2Find in source

paraphrase[Results, Primary outcome]

“P = 0.62”

“absolute risk difference of −1.7 percentage points (95% confidence interval (CI), −7.7, 4.3)”

ResultsFind in source

Sub-criteria

code sharingINADEQUATE

accession numbersN/A

repository depositN/A

data availability statementINADEQUATE

Per reviewer (2) — the votes behind the verdict

WARNReviewer 1· 85% conf

Data availability statement is present but vague, and code is proprietary.

Evidence

Data availabilityFind in source

paraphrase[Code availability]

“The code is proprietary, but iDAScore and the necessary hardware can be obtained from Vitrolife ( www.vitrolife.com ).”

WARNReviewer 2· 85% conf

Data availability statement is present but vague; code is proprietary.

Evidence

Data availabilityFind in source

paraphrase[Code availability]

“The code is proprietary, but iDAScore and the necessary hardware can be obtained from Vitrolife ( www.vitrolife.com ).”

Sub-criteria

funding coiADEQUATE

trial registrationADEQUATE

reporting guidelineADEQUATE

methods completenessADEQUATE

all outcomes reportedADEQUATE

limitations discussedADEQUATE

conclusions proportionalADEQUATE

Per reviewer (2) — the votes behind the verdict

PASSReviewer 1· 90% conf

Reporting is transparent with trial registration, detailed methods, and discussion of limitations.

Evidence

“Australian New Zealand Clinical Trials Registry (ANZCTR) registration: 379161”

AbstractFind in source

“It is important to acknowledge several limitations in our trial.”

Discussion ¶8Find in source

“The project was funded by a grant from Vitrolife.”

Competing interestsFind in source

PASSReviewer 2· 90% conf

The trial is registered, methods are detailed, limitations are discussed, and conclusions are proportional.

Evidence

“Australian New Zealand Clinical Trials Registry (ANZCTR) registration: 379161”

AbstractFind in source

Discussion ¶8Find in source

“The project was funded by a grant from Vitrolife.”

Competing interestsFind in source

Registration stated in text, but no registry ID was detected. No reporting guideline cited.

Broken references and links

None found

References checked against Crossref, OpenAlex and Retraction Watch for retractions and resolvability, plus declared data and code links probed for whether they resolve to content matching the paper.

Checked — nothing surfaced.

Checked 34 references by DOI: 33 verified — 1 no DOI (shown, not verified).

1 data/code link checked; 1 live.

Copyediting

6 minor

Wording, consistency and formatting errors that need correcting before submission.

No major wording or formatting errors. 6 minor suggestions below.

6 copyedit issues flagged: mostly consistency, clarity, grammar.

Kaimen Rigor Action ItemsFinal pass before journal submission

1.
HIGHdata code
In the Data availability section, specify a concrete data access mechanism, such as a named repository (e.g., Zenodo) or a managed-access platform (e.g., Vivli), with conditions and timeframe, to move from 'on request' to a more concrete statement.
The current statement is vague and does not provide a clear route for researchers to access the data, which is a reproducibility concern.
2.
HIGHdata code
In the Code availability section, consider providing a detailed description of the iDAScore algorithm's architecture and training procedure, or releasing a non-commercial version for academic use, to improve reproducibility.
The proprietary code limits independent verification of the deep learning algorithm, which is central to the study.
3.
HIGHreporting
In the Methods, explicitly state adherence to a reporting guideline such as CONSORT, and include the completed checklist as supplementary material.
Explicit reporting guideline adherence enhances transparency and is expected for RCTs.
4.
MEDIUMreporting
In the Discussion, clarify the post hoc nature of the fresh vs frozen subgroup analysis and avoid over-interpreting the interaction, as it was not pre-specified.
The significant interaction (P=0.022) is post hoc and could be due to chance; readers should be cautioned against over-interpretation.
5.
MEDIUMreporting
In the Results, consider reporting the exact p-value for the time evaluation comparison (currently reported as P < 0.001) to improve precision.
Exact p-values are more informative than threshold-only values and align with the paper's overall reporting style.
6.
MEDIUMcopyedit
In the Abstract, ensure consistent terminology: use 'study group' and 'control group' consistently instead of switching between 'iDAScore group' and 'morphology group'.
Inconsistent terminology can confuse readers and detracts from the paper's professionalism.
7.
MEDIUMcopyedit
In the Results, Secondary outcomes, rephrase 'mean standard deviation time' to 'mean time (standard deviation)' for clarity.
The current phrasing is awkward and could be misinterpreted.
8.
LOWcopyedit
In the Discussion, consider rephrasing 'could also be an outcome of' to 'could also be a result of' for smoother flow.
Minor grammatical improvement for readability.
9.
LOWcopyedit
In the Abstract, consider adding a space before the registration number for readability (e.g., 'registration: 379161').
Minor formatting improvement.

Full text (43,816 chars)Analyzed: Aug 16, 2026