Semen parameters on the day of oocyte retrieval predict low fertilization during conventional insemination IVF cycles

The effects of repeated freezing and thawing on bovine sperm morphometry and function

Refreezing the remaining genetic resources after in vitro fertilization (IVF) can conserve genetic materials. However, the precise damage inflicted by repeated freezing and thawing on bovine sperm and its underlying mechanism remain largely unexplored. Thus, this study investigates the impact of repeated freeze-thaw cycles on sperm. Our findings indicate that such cycles significantly reduce sperm viability and motility. Furthermore, the integrity of the sperm plasma membrane and acrosome is compromised during this process, exacerbating the advanced apoptosis triggered by oxidative stress. Additionally, transmission electron microscopy exposed severe damage to the plasma membranes of both the sperm head and tail. Notably, the "9 + 2" structure of the tail was disrupted, along with a significant decrease in the level of the axonemal protein DNAH10, leading to reduced sperm motility. IVF outcomes revealed that repeated freeze-thaw cycles considerably impair sperm fertilization capability, ultimately reducing the blastocyst rate. In summary, our research demonstrates that repeated freeze-thaw cycles lead to a decline in sperm viability and motility, attributed to oxidative stress-induced apoptosis and DNAH10-related dynamic deficiency. As a result, the utility of semen is compromised after repeated freezing.

Day 2 versus day 3 embryo transfer in patients with in vitro fertilization and only one zygote with two pronuclei

OBJECTIVE

This study aimed to compare the pregnancy outcomes of Day 2 (D2) fresh embryo transfer and D3 fresh embryo transfer in women with only one zygote with two pronuclei (2PN).

METHODS

Data on 432 in vitro fertilization-embryo transfer cycles with only one 2PN zygote from January 2016 to January 2022 were retrospectively collected. A total of 302 fresh embryo transfers on D2 (n = 193) and D3 (n = 109) were analyzed, and pregnancy outcomes were compared.

RESULTS

The patients' characteristics were not different between D2 and D3 embryo transfer. There were no significant differences in the rates of clinical pregnancy, early abortion, or live birth between D2 and D3 embryo transfer. A multivariate logistic regression model controlling for age, the fertilization method, the number of oocytes harvested, and the number of high-quality embryos transferred showed that the live birth rate was similar between D2 and D3 embryo transfer.

CONCLUSION

In in vitro fertilization-embryo transfer cycles with only one 2PN zygote, D2 fresh embryo transfer may provide similar pregnancy outcomes to those of D3 embryo transfer. D2 embryo transfer may be an option because of the risk of cycle cancellation due to the absence of viable embryos on D3.

Total Fertilization Failure: A Single Center Analysis

Our main objective was to identify the male and female parameters associated with total fertilization failure (TFF) in IVF with nonmasculine indications. The present work, IRB equivalent INS 63209, is a case-control study that evaluated all cases with TFF after conventional IVF at the Center for Human Reproduction from January 2010 to December 2019 (n = 154). As a control group, we analyzed all patients who did not experience fertilization failure after conventional IVF in the same period (n = 475). We evaluated various parameters, both male and female, assessed during infertility treatment, and only cases without masculine etiology (normal seminal parameters) were included. Ages (female and male) were not different between the groups. Moreover, AMH (anti-Müllerian hormone), semen volume, preprocessing concentration and preprocessing motility were not significantly different (P > 0.05). However, the number of collected oocytes (study versus control groups, median [25-75 interquartile]: 2 [1-5] and 5 [3-8]); MII (2 [1-4] and 5 [2-7]); and postprocessing motility (85 [70-90] and 90 [80-95]) were significantly different between both groups (P < 0.05). Furthermore, a logistic regression analysis including all significant data demonstrated that the number of collected oocytes was significantly related to IVF failure. Patients with fewer than 5 oocytes had an OR of - 1.37 (- 0.938 to - 1.827) for TFF after conventional IVF. Our results showed that a lower follicular response to controlled ovarian stimulation, evidenced by a decreased number of collected oocytes, was the most important parameter associated with IVF failure in nonmasculine infertility.

Development and validation of a conventional in vitro total fertilization failure prediction model

BACKGROUND

Conventional total fertilization failure (TFF) is a challenging problem for clinicians. The predictive model developed in this study aims to predict the individual probability of conventional in vitro total fertilization failure.

METHODS

The prediction model was developed based on 1635 patients who underwent first-attempt in vitro fertilization (IVF) cycles from January 2018 to January 2020. Total fertilization failure and normal fertilization occurred in 218 and 1417 cycles, respectively. Multivariate logistic regression analyses were used to develop the prediction model. Performance of our model was evaluated using calibration (Hosmer-Lemeshow test) and discrimination (area under the receiver operating characteristic curve [AUC]).

RESULTS

Thirteen risk factors for TFF were included in the prediction model, as follows: female age; female body mass index; infertility duration; number of oocytes retrieved; stimulation protocol; infertility etiology; infertility diagnosis; male age; sperm concentration; total sperm motility; normal sperm morphology percentage; swim-up sperm motility; and swim-up sperm concentration. The AUC of our model was 0.815 (95% CI: 0.783-0.846), indicating satisfactory discrimination performance.

CONCLUSION

Considering female and male factors (especially sperm parameters), we established a model that predicts the probability of TFF in conventional IVF procedures that will be helpful in the laboratory supporting IVF to facilitate physicians in determining optimal treatment.

Machine learning-based clustering to identify the combined effect of the DNA fragmentation index and conventional semen parameters on in vitro fertilization outcomes

BACKGROUND

Previous studies have demonstrated an association between male sperm quality and assisted reproduction outcomes, focusing on the effects of individual parameters and reaching controversial conclusions. The WHO 6th edition manual highlights a new semen assay, the sperm DNA fragmentation index, for use after routine semen examination. However, the combined effect of the sperm DNA fragmentation index (DFI) and routine semen parameters remains largely unknown.

METHODS

We assessed the combined effect of the sperm DFI and conventional semen parameters on single fresh conventional IVF outcomes for infertile couples from January 1, 2017, to December 31, 2020. IVF outcomes were obtained from the cohort database follow-up records of the Clinical Reproductive Medicine Management System of the Third Affiliated Hospital of Guangzhou Medical University. An unsupervised K-means clustering method was applied to classify participants into several coexposure pattern groups. A multivariate logistic regression model was used for statistical analysis.

RESULTS

A total of 549 live births among 1258 couples occurred during the follow-up period. A linear exposure-response relationship was observed among the sperm DFI, sperm motility, and IVF outcomes. In multivariable adjustment, increased sperm DFI values and decreased sperm motility and semen concentration levels were associated with reduced odds of favourable IVF outcomes. Four coexposure patterns were generated based on the sperm DFI and the studied semen parameters, as follows: Cluster 1 (low sperm DFI values and high sperm motility and semen concentration levels), Cluster 2 (low sperm DFI values and moderate sperm motility and semen concentration levels), Cluster 3 (low sperm DFI values and low sperm motility and semen concentration levels) and Cluster 4 (high sperm DFI values and low sperm motility and semen concentration levels). Compared with those in Cluster 1, participants in Cluster 3 and Cluster 4 had lower odds of a live birth outcome, with odds ratios (95% confidence intervals [CIs]) of 0.733 (0.537, 0.998) and 0.620 (0.394, 0.967), respectively.

CONCLUSIONS

When combined with low sperm DFI values, there was no significant difference between high or moderate sperm concentration and motility levels, and both were associated with favourable IVF outcomes. Low sperm parameter levels, even when DFI values remain low, may still lead to poor IVF outcomes. Participants with high sperm DFI values and low sperm motility and semen concentration levels had the worst outcomes. Our findings offer a novel perspective for exploring the joint effects of sperm DFI and routine semen parameter values.

A Bayesian network model for prediction of low or failed fertilization in assisted reproductive technology based on a large clinical real-world data

STUDY QUESTION

To construct prediction models based on the Bayesian network (BN) learning method for the probability of fertilization failure (including low fertilization rate [LRF] and total fertilization failure [TFF]) in assisted reproductive technology (ART) treatment. A BN model was developed to predict TFF/LFR. The model showed relatively high calibration in external validation, which could facilitate the identification of risk factors for fertilization disorders and improve the efficiency of in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) treatment.

WHAT IS KNOWN ALREADY

The prediction of TFF/LFR is very complex. Although some studies attempted to construct prediction models for TFF/LRF, most of the reported models were based on limited variables and traditional regression-based models, which are unsuitable for analyzing real-world clinical data. Therefore, none of the reported models have been widely used in routine clinical practice. To date, BN modeling analysis is a prominent and increasingly popular machine learning method that is powerful in dealing with dynamic and complex real-world data.

STUDY DESIGN, SIZE, DURATION

A retrospective study was performed with 106,640 fresh embryo IVF/ICSI cycles from 2009 to 2019 in one of China's largest reproductive health centers.

PARTICIPANTS/MATERIALS, SETTING, METHODS

A total of 106, 640 cycles were included in this study, including 97,102 controls, 4,339 LFR cases, and 5,199 TFF cases. Twenty-four predictors were initially included, including 13 female-related variables, five male-related variables, and six variables related to IVF/ICSI treatment. BN modeling analysis with tenfold cross-validation was performed to construct the predictive model for TFF/LFR. The receiver operating characteristic (ROC) curves and the corresponding area under the curves (AUCs) were used to evaluate the performance of the BN model.

MAIN RESULTS AND THE ROLE OF CHANCE

All twenty-four predictors were first organized into seven hierarchical layers in a theoretical BN model, according to prior knowledge from previous literature and clinical practice. A machine-learning BN model was generated based on real-world clinical data, containing a total of eighteen predictors, of which the infertility type, ART method, and number of retrieved oocytes directly influence the probabilities of LFR/TFF. The prediction accuracy of the BN model was 91.7%. The AUC of the TFF versus control groups was 0.779 (95% CI: 0.766-0.791), with a sensitivity of 71.2% and specificity of 70.1%; the AUC of of TFF versus LFR groups was 0.807 (95% CI: 0.790-0.824), with a sensitivity of 49.0% and specificity of 99.0%.

LIMITATIONS, REASON FOR CAUTION

First, our study was based on clinical data from a single center, and the results of this study should be further verified by external data. In addition, some critical data (e.g., the detailed IVF laboratory parameters of the sperm and oocytes used for insemination) were not available in this study, which should be given full consideration when further improving the performance of the BN model.

WIDER IMPLICATIONS OF THE FINDINGS

Based on extensive clinical real-world data, we developed a BN model to predict the probabilities of fertilization failures in ART, which provides new clues for clinical decision-making support for clinicians in formulating personalized treatment plans and further improving ART treatment outcomes.

STUDY FUNDING/COMPETING INTEREST(S)

Dr. Y. Wang was supported by grants from the Beijing Municipal Science & Technology Commission (Z191100006619086). We declare that there are no conflicts of interest.

TRIAL REGISTRATION NUMBER

N/A.

Nomogram models to predict low fertilisation rate and total fertilisation failure in patients undergoing conventional IVF cycles

OBJECTIVES

To establish visualised prediction models of low fertilisation rate (LFR) and total fertilisation failure (TFF) for patients in conventional in vitro fertilisation (IVF) cycles.

DESIGN

A retrospective cohort study.

SETTING

Data from August 2017 to August 2021 were collected from the electronic records of a large obstetrics and gynaecology hospital in Sichuan, China.

PARTICIPANTS

A total of 11 598 eligible patients who underwent the first IVF cycles were included. All patients were randomly divided into the training group (n=8129) and the validation group (n=3469) in a 7:3 ratio.

PRIMARY OUTCOME MEASURE

The incidence of LFR and TFF.

RESULTS

Logistic regressions showed that ovarian stimulation protocol, primary infertility and initial progressive sperm motility were the independent predictors of LFR, while serum luteinising hormone and P levels before human chorionic gonadotropin injection and number of oocytes retrieved were the critical predictors of TFF. And these indicators were incorporated into the nomogram models. According to the area under the curve values, the predictive ability for LFR and TFF were 0.640 and 0.899 in the training set and 0.661 and 0.876 in the validation set, respectively. The calibration curves also showed good concordance between the actual and predicted probabilities both in the training and validation group.

CONCLUSION

The novel nomogram models provided effective methods for clinicians to predict LFR and TFF in traditional IVF cycles.

Prediction of Fertilization Disorders in the In Vitro Fertilization/Intracytoplasmic Sperm Injection: A Retrospective Study of 106,728 Treatment Cycles

Purpose

This study aimed to develop a risk prediction of fertilization disorders during the in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI).

Methods

A retrospective study was performed with 106,728 fresh embryo IVF/ICSI cycles from 2009 to 2019. Basic characteristics of patients, clinical treatment data, and laboratory parameters were involved. The associations between the selected variables and risks for low fertilization rate (LFR) and total fertilization failure (TFF) were investigated. Ordinal logistic regression and the receiver operating characteristic curves (ROCs) were used to construct and evaluate the prediction models.

Results

A total of 97,181 controls, 4,343 LFR and 5,204 TFF cases were involved in this study. The model based on clinical characteristics (the ages of the couples, women's BMI, types of infertility, ART failure history, the diminished ovarian reserve, sperm quality, insemination method, and the number of oocytes retrieved) had an AUC of 0.743 for TFF. The laboratory model showed that primary infertility, ART failure history, minimal-stimulation cycle/natural cycle, numbers of oocyte retrieved < 5, IVF, and Anti-Mullerian hormone (AMH) level < 1.1ng/ml are predictors of TFF, with an AUC of 0.742.

Conclusion

We established a clinical and a laboratory prediction model for LFR/TFF. Both of the models showed relatively high AUCs.

Male waist circumference in relation to semen quality and partner infertility treatment outcomes among couples undergoing infertility treatment with assisted reproductive technologies

BACKGROUND

Male obesity has been related to poor semen quality and may also have a negative effect on assisted reproductive technologies (ART) outcomes. Whether male waist circumference (WC), as a measure of central obesity, impacts a couple's fertility independently of BMI is unclear.

OBJECTIVES

To examine the associations of male WC with semen quality and couples' outcomes of infertility treatment with ART.

METHODS

Couples presenting to the Massachusetts General Hospital Fertility Center were invited to participate in the study. Between 2009 and 2019, 269 males provided 671 semen samples and 176 couples underwent 317 ART cycles. Height, weight, and WC were measured on site. We analyzed the association of male WC with semen quality and pregnancy outcomes using cluster-weighted regression models to account for repeated observations while adjusting for potential confounders. Models were also stratified by male BMI (<25 kg/m2 compared with ≥25 kg/m2).

RESULTS

The median male age, WC, and BMI were 36.1 years, 96.0 cm, and 26.8 kg/m2, respectively. A 5-cm increase in WC was associated with a 6.3% (95% CI, 2.1-10.5%) lower sperm concentration after adjustment for potential confounders, including BMI. Male WC was also inversely related to the probability of achieving a live birth. For each 5-cm increase in male WC, the odds of a live birth per initiated cycle decreased by 9.0% (95% CI, 1.1%-16.4%) after accounting for several anthropometric and demographic characteristics of both partners. These associations were stronger among males in the normal BMI category (<25 kg/m2) than among overweight or obese males.

CONCLUSIONS

A higher male WC may be an additional risk factor for poor outcomes of infertility treatment, even after accounting for male and female partner BMIs, particularly in couples where the male partner has a normal BMI.

Effect of early rescue ICSI and split IVF-ICSI in preventing low fertilization rate during the first ART cycle: A real-world retrospective cohort study

Purpose

To determine the utility of short gamete coincubation in in vitro fertilization (IVF‐S) combined with early rescue intracytoplasmic sperm injection (R‐ICSI) and split IVF‐ICSI in preventing low fertilization based on a retrospective cohort study.

Methods

Couples with a high risk of low IVF fertilization during the first ART cycle underwent IVF‐S with R‐ICSI or split IVF‐ICSI. Fertilization rate, embryo quality, and clinical outcomes were measured.

Results

After propensity score matching, we included 188 couples in the IVF‐S with R‐ICSI group as Group 1 and 720 in the split IVF‐ICSI group as Group 2. Normal fertilization rates were similar; however, Group 1 had a higher multiple pronuclei rate (10.42% vs. 4.50%, p < 0.001) but a higher embryo utilization rate (59.84% vs. 53.60%, p < 0.001). The groups were similar in the rates of high‐quality embryos, embryo implantation, clinical pregnancy, and live birth. Low IVF fertilization rate was 4.79% and 9.03% in Group 1 and Group 2, respectively, with similar fertilization rate and embryo development.

Conclusion

IVF‐S with early R‐ICSI and split IVF‐ICSI were effective strategies in preventing low fertilization rate. IVF‐S with early R‐ICSI could become the preferred approach because of its advantages—higher embryo utilization rate, fewer ICSI procedures, similar clinical pregnancy rate, and live birth rate.

Association between intake of soft drinks and testicular function in young men

STUDY QUESTION

Is intake of sugar-sweetened beverages (SSB) or artificially sweetened beverages (ASB) associated with testicular function in young men?

SUMMARY ANSWER

Among young men unaware of their semen quality and reproductive hormone levels, intake of SSBs was associated with lower sperm concentration, lower total sperm count, and a lower ratio of serum inhibin-B/FSH.

WHAT IS KNOWN ALREADY

SSBs may adversely impact testicular function, but results are not consistent across studies. Moreover, the associations of ASB, energy-drinks or fruit juices with testicular function are unclear.

STUDY DESIGN, SIZE, DURATION

Young healthy men and unselected for fertility status men enrolled in a cross-sectional study between 2008 and 2017.

PARTICIPANTS/MATERIALS, SETTING, METHODS

A total of 2935 young (median age: 19 years) men enrolled in the study. Intake of SSBs, ASBs, fruit juices, and energy-drinks was assessed with a validated food frequency questionnaire. Testicular function was assessed through conventional semen quality parameters (semen volume, sperm concentration, total count, motility and morphology), testicular volume assessed with ultrasound, and serum reproductive hormone concentrations (total testosterone, free testosterone, E2, inhibin-B, LH, FSH, sex hormone-binding globulin) were measured.

MAIN RESULTS AND THE ROLE OF CHANCE

In multivariable-adjusted analyses, men in the highest category of SSB intake (median: 1.1 servings (∼220 ml)/day) had a 13.2 million/ml lower median sperm concentration (95% CI: -21.0, -5.5) than non-consumers. A similar pattern was observed with total sperm count (-28 million (95% CI: -48, -9)), serum inhibin-B (-12 pg/ml (95% CI: -21, -4)), and inhibin-B/FSH ratio (-9 (95% CI: -18, 0)). The adjusted median difference in sperm concentration and inhibin-B associated with increasing SSB intake by 1 serving (∼200ml)/day at the expense of water was -3.4 million sperm/ml (95% CI: -5.8, -1.0) and -7 pg/ml (95% CI: -11, -3), respectively.

LIMITATIONS, REASONS FOR CAUTION

Inferring causality is limited owing to the cross-sectional design. We adjusted for a number of potential confounders but cannot exclude that unmeasured lifestyle and behavior associated with soft drink intake is associated with testicular function in these young men.

WIDER IMPLICATIONS OF THE FINDINGS

In the largest study to date, intake of SSBs was associated with lower sperm concentration, total sperm count, and serum inhibin-B/FSH ratio, consistent with a direct suppressive effect of SSB intake on testicular function among otherwise healthy men, potentially affecting fertility. However, the observed association between higher SSB intake and lower semen quality does not necessarily imply a decrease in fertility.

STUDY FUNDING/COMPETING INTEREST(S)

Supported by research from the Danish Council for Strategic Research (2101-08-0058), Independent Research Fund Denmark (8020-00218B), European Union (212844), the Kirsten and Freddy Johansen's Foundation (95-103-72087), the Research Fund of the Capital Region of Denmark (A6176), and the NIH (P30DK046200). The authors report no conflict of interest.

TRIAL REGISTRATION NUMBER

N/A.

Ultrasonic Cutting of Frozen Semen Straws to Optimize the Use of Spermatozoa for In Vitro Fertilization

The objective of the present study was to establish conditions for using technology that can potentially enhance the efficiency of bovine embryos derived from in vitro fertilization (IVF) with frozen semen. Frozen semen from selected bulls can be stored indefinitely in liquid nitrogen as genetic resources; however, these resources are considered consumable because they cannot be regenerated. Therefore, to optimize the utilization of frozen semen, as many oocytes as possible should be fertilized with one straw. However, a sufficient number of prepared oocytes might not be available for one experiment, which can limit the use of the total spermatozoa population. Thus, an economical method for producing embryos needs to be established by optimizing technology for transplantable embryos. In this study, the utilization of frozen semen was increased by dividing the straw with an ultrasonic cutter. The post-thaw survival rate of uncut straws from Korean Proven Bulls did not differ from that of half cuttings. When ultrasonic cutting was applied to frozen semen, spermatozoa could be prepared for IVF trials at least four times, and blastocysts were produced. Therefore, cutting frozen semen with an ultrasonic cutter represents a potentially useful tool to expand genetic resources from excellent breeding stocks. This approach could also be valuable in the field of IVF of endangered species or rare breeds for their preservation, as well as in ovum pick-up (OPU) techniques.

Relationship between male age, semen parameters and assisted reproductive technology outcomes

BACKGROUND

Low semen quality often obligates the use of assisted reproductive technology; however, the association between semen quality and assisted reproductive technology outcomes is uncertain.

OBJECTIVES

To further assess the impact of semen quality on assisted reproductive technology outcomes.

MATERIALS AND METHODS

A retrospective cohort study was carried out at a single academic reproductive medicine center (January 2012-December 2018). Patients undergoing at least one assisted reproductive technology cycle utilizing freshly ejaculated spermatozoa from the male partner were included. We assessed the association between semen quality (as stratified based on WHO 5th edition criteria), paternal age (< or ≥40), and reproductive/perinatal outcomes. To evaluate the differences in assisted reproductive technology outcomes by semen parameters and age, generalized estimating equations were applied for rates of fertilization, pregnancy, implantation, miscarriage, live birth, blast formation, gestational age, and normal embryo biopsy.

RESULTS

A total of 2063 couples were identified who underwent 4517 assisted reproductive technology cycles. Average ages of the male and female partners were 39.8 and 37.7, respectively. Lower pregnancy rates were observed in cycles with lower sperm motility (ie <40%; 39.9% vs 44.1%) and total motile count (ie <9 million; 38.3% vs 43.5%). When examining only cycles utilizing Intracytoplasmic Sperm Injection, only a lower motility count was associated with a decline in pregnancy rate (39.1% vs 44.9%). No association was identified between semen quality and gestational age or birth weight. Paternal age was not associated with ART outcomes. However, among assisted reproductive technology cycles in women <40, aneuploidy rate was higher for older men (P < .001). In cycles with women >40, no association between aneuploidy and male age was identified.

DISCUSSION

Sperm motility is associated with pregnancy rates, while other semen parameters are not. In cycles in women <40, paternal age is associated with embryo aneuploidy rate.

CONCLUSION

Paternal factors are associated with assisted reproductive technology outcomes, and future studies should explore mechanisms by which semen quality is associated with assisted reproductive technology outcomes.

Alterations in seminal plasma proteomic profile in men with primary and secondary infertility

Proteome of seminal plasma provides profound information related to the male reproductive health. This pilot study was conducted to characterize proteomic profile of seminal plasma from men with primary, or secondary infertility and compare it with proven fertile men. Study participants (n = 59) were recruited at the Cleveland Clinic and divided according to their fertility status: proven fertile (n = 39); primary infertility (n = 11) and secondary infertility (n = 9). Proteomic shotgun analysis revealed a total of 515 peptides common to primary infertility and control group; whereas 523 peptides were common to secondary infertility and control group. Bioinformatic analysis revealed dysregulation of biological processes such as cell secretion and vesicle mediated transport in primary infertility, whereas immune system response, regulation of proteolysis and iron homeostasis were dysregulated in secondary infertility. Western blot validation showed overexpression of ANXA2 and CDC42, and underexpression of SEMG2 proteins in primary infertility; and overexpression of ANXA2 and APP proteins in secondary infertility. This study elucidates the potential role of differentially expressed proteins in the seminal plasma as diagnostic biomarker for primary and secondary infertility. Furthermore, our results suggest maturation failure and immune reaction response as the main cause of infertility in men with primary and secondary infertility, respectively. Additional validation of the proteins involved in the above pathways is warranted.

Membrane Potential Determined by Flow Cytometry Predicts Fertilizing Ability of Human Sperm

Infertility affects 10 to 15% of couples worldwide, with a male factor contributing up to 50% of these cases. The primary tool for diagnosing male infertility is traditional semen analysis, which reveals sperm concentration, morphology, and motility. However, 25% of infertile men are diagnosed as normozoospermic, meaning that, in many cases, normal-appearing sperm fail to fertilize an egg. Thus, new information regarding the mechanisms by which sperm acquire fertilizing ability is needed to develop a clinically feasible test that can predict sperm function failure. An important feature of sperm fertilization capability in many species is plasma membrane hyperpolarization (membrane potential becoming more negative inside) in response to signals from the egg or female genital tract. In mice, this hyperpolarization is necessary for sperm to undergo the changes in motility (hyperactivation) and acrosomal exocytosis required to fertilize an egg. Human sperm also hyperpolarize during capacitation, but the physiological relevance of this event has not been determined. Here, we used flow cytometry combined with a voltage-sensitive fluorescent probe to measure absolute values of human sperm membrane potential. We found that hyperpolarization of human sperm plasma membrane correlated positively with fertilizing ability. Hyperpolarized human sperm had higher in vitro fertilization (IVF) ratios and higher percentages of acrosomal exocytosis and hyperactivated motility than depolarized sperm. We propose that measurements of human sperm membrane potential could be used to diagnose men with idiopathic infertility and predict IVF success in normozoospermic infertile patients. Patients with depolarized values could be guided toward intracytoplasmic sperm injection, preventing unnecessary cycles of intrauterine insemination or IVF. Conversely, patients with hyperpolarized values of sperm membrane potential could undergo only conventional IVF, avoiding the risks and costs associated with intracytoplasmic sperm injection.