ReviewJBRA assisted reproduction2020
Sperm selection in IVF: the long and winding road from bench to bedside.
Review in JBRA assisted reproduction, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Clinical Outcomes of ICSI Using Advanced Quantitative Phase Microscopy.Bioengineering (Basel, Switzerland) · 2026Article
- D-Mannose-Mediated metabolic pathways sustain the molecular signatures of sperm function and fertilization.Journal of advanced research · 2025Article
- A Narrative Review on the Sperm Selection Methods in Assisted Reproductive Technology: Out with the New, the Old Is Better?Journal of clinical medicine · 2025Review
- Current and Future Applications of Artificial Intelligence to Diagnose and Treat Male Infertility.Advances in experimental medicine and biology · 2025Review
- Advanced Sperm Selection Techniques for Assisted Reproduction.Journal of personalized medicine · 2024Review
- 'Intracytoplasmic sperm injection (ICSI) paradox' and 'andrological ignorance': AI in the era of fourth industrial revolution to navigate the blind spots.Reproductive biology and endocrinology : RB&E · 2024Article
- Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics.The world journal of men's health · 2024Review
- In Contemporary Reproductive Medicine Human Beings are Not Yet Dispensable.Journal of obstetrics and gynaecology of India · 2023Article
- A Dual Architecture Fusion and AutoEncoder for Automatic Morphological Classification of Human Sperm.Sensors (Basel, Switzerland) · 2023Article
- New horizons in human sperm selection for assisted reproduction.Frontiers in endocrinology · 2023Review
- The Conceivable Functions of Protein Ubiquitination and Deubiquitination in Reproduction.Frontiers in physiology · 2022Review
- Advancements in Microfluidic Systems for the Study of Female Reproductive Biology.Endocrinology · 2021Review
- Sialic Acids and Tetraspanins: An Insight into their Potential as Indicators of Human Sperm Quality.American journal of men's healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spermatozoa wage battle to conquer fertilization but the traits needed to succeed remain elusive. The natural advantageous qualities that enable only a few selected sperm cells to reach the site of fertilization remain unknown. Although in vitro fertilization (IVF) facilitates the job of spermatozoa, a universally acceptable means of sperm selection is yet to be developed. No objective or reliable sperm quality indicators have been established and sperm selection is, to a great extent, based on subjective qualitative evaluation. The best method for sperm selection in IVF presents several challenges: intrinsic sperm qualities cannot be evaluated and the ideal endpoint for these studies is debatable. An ideal method for sperm selection in ART should be noninvasive and cost-effective, and allow the identification of high-quality spermatozoa and yield better outcomes in terms of pregnancy and live birth rates. This narrative review included 85 papers and focused on the new available methods and technologies that might shed some light on sperm selection in IVF. It discusses the available data on microfluidic devices, omics profiling, micronuclei studies, sperm plasma membrane markers, and other techniques, such as Magnetic Activated Cell Sorting (MACS), Raman micro-spectroscopy, and artificial intelligence systems. The new techniques herein reviewed offer fresh approaches to an old problem, for which a definite solution has yet to cross the bridge from bench to IVF clinics around the world, since clinical usefulness and application remain unproven.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.