1. Introduction
Cataract surgery with intraocular lens (IOL) implantation is one of the most commonly performed surgical procedures worldwide to restore visual acuity in individuals with cataracts. Achieving precise refractive outcomes following cataract surgery is imperative to enhance patient satisfaction and minimize the need for postoperative visual aids like glasses or contact lenses. Accurate biometric measurements of the eye, encompassing axial length and corneal power, are pivotal for determining the appropriate IOL power to achieve the targeted postoperative refraction.
Two widely used biometry devices, the IOL Master 500 and the IOL Master 700, employ advanced optical technology to capture various biometric parameters, providing necessary information in order to accurately calculate IOL power. The IOL Master 500 utilizes partial coherence interferometry (PCI), while the IOL Master 700 uses swept-source optical coherence tomography (SS-OCT). SS-OCT offers several advantages over PCI, including superior depth resolution, faster acquisition speeds, and reduced susceptibility to signal attenuation in highly scattering tissues.
Previous studies have investigated the agreement between the IOL Master 500 and IOL Master 700 in terms of biometric measurements. Song et al. found high agreement between the devices, with no difference in predicting refractive outcomes after cataract surgery in a subgroup of 54 eyes [
1]. Jiang et al. also reported good reliability between the two instruments for various biometric parameters in a study of 518 eyes [
2]. However, these studies were limited by relatively small sample sizes due to a prospective approach and focused primarily on the alignment of biometric data rather than postoperative refractive outcomes.
While these studies provide valuable insights into the agreement between the IOL Master 500 and IOL Master 700, there is a lack of large-scale, real-world studies comparing the refractive outcomes of cataract surgery using these devices. Additionally, the influence of patient-related factors, such as age, gender, and insurance status, on refractive outcomes has not been extensively investigated in the context of these biometry devices.
Our hospital possesses both IOL Master 700 and IOL Master 500 devices, necessitating research to determine whether the measurements and refractive outcomes obtained from these devices are interchangeable. Establishing the interchangeability of these devices is crucial for ensuring consistent and reliable results, regardless of which device is used for a particular patient.
This study aims to address these gaps by comparing the refractive outcomes of cataract surgery patients when employing the IOL Master 500 and IOL Master 700 for biometry in a large, real-world cohort. Furthermore, we investigate the influence of patient-related factors, including age, gender, time elapsed between biometry and surgery, and insurance status, on refractive outcomes. By utilizing a retrospective approach with clinical standard data, we introduce an unconventional method for determining the alignment of different devices for IOL power calculation in a large patient cohort, which has not been performed in previous studies.
The insights gained from this study will provide valuable information for optimizing cataract surgery outcomes and possibly selecting the most suitable biometry device for individual patients. Additionally, understanding the impact of patient-related factors on refractive outcomes will help surgeons tailor their approach to achieve the best possible results for each patient. With the knowledge of the range of the most likely postoperative refraction, it might be a further step for better individual patient guidance in IOL choice.
Differences between the IOL Master 500/700
Before optical devices were established, ultrasound biometry was state-of-the-art for pre-surgery biometry. However, there are disadvantages regarding these measurements. In order to measure axial length, the ultrasound probe has to make contact with the cornea, which can affect the measurements and could potentially harm the corneal surface. Furthermore, the measurement is dependent on the skills of the performing healthcare provider. Also, depending on patient compliance, acquisition time is another factor to be considered. Although these factors have to be considered, ultrasound biometry is still a valid method for IOL calculation, as was found by Haigis et al. [
3]. Meanwhile, another investigation by Connors et al. suggests that there is an advantage in reproducibility and accuracy using partial coherence interferometry instead of ultrasound [
4]. Eleftheriadis was able to find similar results, suggesting an advantage for partial coherence tomography over ultrasound biometry in 100 cases [
5]. The superiority of IOL Master device measurements, especially considering the experience of the performing physician, was investigated by Findl et al. [
6].
The IOL Master 500 and 700 are advanced ophthalmic devices designed for precise biometry measurements essential in cataract surgery planning. Both instruments operate on the principle of optical biometry, utilizing low-coherence laser beams to scan intraocular structures and attain data on axial length, corneal curvature, and anterior chamber depth.
The key technical difference lies in their underlying technologies for optical coherence. The IOL Master 500 employs partial coherence interferometry (PCI), where interference patterns of reflected light waves are analyzed to extract biometric parameters. In contrast, the IOL Master 700 incorporates swept-source optical coherence tomography (SS-OCT), an advanced imaging technique that utilizes a rapidly turning laser source to acquire high-resolution cross-sectional images of ocular structures.
SS-OCT offers several advantages over PCI, including superior depth resolution, faster acquisition speeds, and reduced susceptibility to signal attenuation in highly scattering tissues. By providing detailed, three-dimensional visualization of ocular anatomy, SS-OCT is believed to enable more accurate and comprehensive biometric measurements, especially in challenging cases such as eyes with dense cataracts, high ametropia, or high irregular astigmatism. Beyond this, the IOL Master 700 is able to perform a total keratometry of the anterior and posterior corneal surfaces. This allows for a precise measurement of corneal curvature and thickness, providing data for accurate intraocular lens (IOL) power calculations and enabling the use of more refined IOL calculation formulas.
2. Materials and Methods
2.1. Data Collection
The study incorporates a dataset comprising records of 2994 eyes from 1907 patients who underwent cataract surgery. Biometry was performed in-house prior to cataract surgery. Measurements of postoperative refraction were performed by registered ophthalmologists of the ‘South Baden eye network’, which is a network of practices that work together over common IT infrastructure with the University Eye Clinic in Freiburg and provide data such as postoperative refraction and visual acuity. A vote of the ethics committee of the University of Freiburg was obtained before the study.
Key variables collected for each patient are as follows:
The main endpoint of our study was deviation from target refraction as the spherical equivalent. Deviation from target refraction was defined as the absolute difference between manifest and targeted refraction 79 days (mean = 79 days, median = 77 days, min = 1 day/max = 189 days + SD 23 days) after cataract surgery as the spherical equivalent. Spherical equivalent (SE) is a measure of the refractive power of the eye, calculated as the sum of the spherical power (SP) and half of the cylindrical power (CP), expressed mathematically as: SE = SP + (CP/2). When more than one biometric measurement was available, we decided between two cases. When the same target refraction was present, we chose the biometry that was the closest before surgery. If there were different target refractions in the documents, we chose the one that matched our surgery data.
The covariates in our analysis included the IOL Master version (IOL Master 700 or IOL Master 500), age at the time of measurement, time elapsed between biometry and surgery, gender (male or female), insurance status in terms of private or public health insurance, and the biometrical parameters: anterior chamber depth, axial length, and corneal radius. There were no explicit exclusion criteria regarding the patient cohort. Since we implant the Zeiss CT Asphina 409M IOL almost exclusively (in approximately 98% of cases) at our clinic, we did not include the lens type as a separate factor in our statistical analysis. The Haigis formula was used in nearly all cases, incorporating both axial length and anterior chamber depth. This formula is considered to be accurate over a wide range of ocular anatomies, but as with all formulas, it has limitations in some cases [
7,
8,
9]. The formula was applied with its standard implementation without any customized adjustments. Given the significant proportion of patients with complex ocular conditions at our clinic, tailoring the formula specifically to individual surgeons was not feasible.
2.2. Baseline Characteristics
Data from 2017 to 2023 were included due to the good availability of data enabled through a shared software solution. For further information on the characteristics of the patient cohort, a summary of the dataset is presented in
Table 1.
As a potential confounder, the waiting time until surgery was evaluated and can be seen in
Figure 1. The majority of patients were able to receive cataract surgery within 200 days after the indication for surgery was established.
2.3. Statistical Analysis
Multiple regression analysis was employed to assess the relationship between the dependent variable (deviation from target refraction) and the independent variables. The analysis aimed to determine which factors significantly influenced refractive outcomes following cataract surgery. Statistical analysis was performed using the Python programming language with open-source libraries including numpy, pandas, and duckdb. Graphs were created using the libraries matplotlib and seaborn.
3. Results
The overall mean deviation from target refraction was −0.3936 dpt, indicating a tendency for slightly myopic outcomes in the study population. The distribution of the deviation from target refraction is illustrated in
Figure 2.
The multiple linear regression analysis revealed that the constant term, age, and gender were statistically significant predictors of the deviation from target refraction. The constant term had a coefficient of −0.3936 (
p = 0.164). Age showed a statistically significant association, with a coefficient of −0.0036 (
p = 0.006), suggesting that increasing age was associated with a slightly more hyperopic outcome. Gender was also a significant predictor, with males having a significantly more hyperopic outcome compared to females, as indicated by a coefficient of −0.079 (
p = 0.001). The other independent variables, including time elapsed between biometry and surgery, IOL Master version, and insurance status, did not show statistically significant associations with the deviation from target refraction. We also examined the biometric influences on the deviation from target refraction with our multiple linear regression analysis to quantify any potential impacts of the main biometric parameters on deviations from target refraction. The results, detailed in
Figure 3 indicate no significant influence of these parameters on refractive outcomes. Specifically, the anterior chamber depth showed a small effect (coefficient: −0.005,
p-value: 0.623), but this was not statistically significant. Axial length (coefficient: 0.045,
p-value: 0.088) and corneal radius (coefficient: −0.045,
p-value: 0.019) did not show a significant effect. The detailed results can be found in
Table 2. The resulting forest plot can be found in
Figure 4.
The IOL Master 700 showed a marginal effect in comparison to the IOL Master 500, with patients measured using this equipment tending to have slightly more myopic outcomes, although this finding was not statistically significant (p = 0.086). This trend might be attributed to the automatic detection of the fovea by the IOL Master 700.
The time elapsed between biometry and surgery (p = 0.489) and insurance status (p = 0.172) did not show statistically significant associations with refractive outcomes.
In summary, the multiple regression analysis revealed that age and gender were significant predictors of post-cataract refractive outcomes, while the IOL Master version demonstrated a marginal effect but slightly missed statistical significance. The time between biometry and surgery as well as insurance status did not significantly influence the refractive outcomes in this study population.
4. Discussion
Our study aimed to compare the refractive outcomes of cataract surgery patients using the IOL Master 500 and IOL Master 700 for biometry, while also investigating the influence of patient-related factors in a large, real-world cohort. The results suggest that, although both devices are effective for biometry in cataract surgery, subtle differences in their ability to predict refractive outcomes may exist. The IOL Master 700 demonstrated a slight tendency in terms of deviation from target refraction, although this advantage did not reach statistical significance and cannot be considered clinically relevant.
Age and gender were identified as significant predictors of refractive outcomes. Older patients experienced slightly more hyperopic outcomes compared to younger patients, and males had slightly more hyperopic outcomes than females. These findings are consistent with the available literature, which has reported similar effects of age and gender on refractive outcomes following cataract surgery [
10]. However, it is important to note that the clinical significance of these differences may be limited, as the effects were observed within a relatively small range.
The consistent offset of 0.3936 observed across all patients, indicating a slight myopic outcome, is most likely to be attributed to the deliberate selection of intraocular lenses (IOLs) aimed at achieving a slightly myopic refractive target. This practice is commonplace in our clinic and is also observed in other eye care facilities. We interpret this consistent deviation as a positive indicator of the quality of the data in our study. The range of inaccuracy of the postoperative refractive outcome is consistent with the literature [
11,
12,
13]. The detection of such a subtle effect underscores the precision and reliability of our measurements.
Our study utilized real-world data, which have inherent limitations, such as the inability to control the method used for measuring postoperative refraction. While objective refraction is assumed to be commonly used due to its availability and efficiency, subjective refraction could also have been employed, potentially leading to differences in refractive outcomes. However, the large sample size of our study helps mitigate the impact of these uncontrolled factors, and the relatively small differences in deviation from target refraction demonstrate the suitability of our approach.
A key differentiating aspect of our work is the lack of exclusion criteria in our data, which we assume includes a wide range of ocular anatomy and cataract types encountered in real-world scenarios, from standard cataracts to more challenging situations. This is a great advantage compared to other studies, which often focus on specific subgroups of patients with different axial lengths and keratometry values.
Furthermore, the IOL Master 700 has been reported to have higher image acquisition rates, especially for patients with dense cataracts. Song et al. found failure rates of 9.7% for IOL Master 500 and 2.4% for IOL Master 700 [
1], while Jiang et al. reported even higher values of 17.6% for IOL Master 500 and 6.9% for IOL Master 700 [
2]. These findings suggest that the IOL Master 700 may be particularly advantageous for older patients, who are more likely to have dense cataracts.
One limitation of our study is the predominance of a single IOL (Zeiss Asphina 409M) and the low variability of IOL calculation formulas (we mostly used the Haigis formula). While this approach minimizes potential confounding factors and allows for a more robust analysis, it may also limit the generalizability of our findings. Further research is needed to explore these results across different IOL types and calculation formulas. Future studies should also consider including subgroups with extreme ocular biometry to gain a more comprehensive understanding. Given the numerous influential factors involved, we believe that AI-based approaches could be particularly well-suited, especially for handling these special cases.
In conclusion, our study provides valuable insights into the comparative performance of the IOL Master 500 and IOL Master 700 in predicting refractive outcomes following cataract surgery in a large, real-world cohort. Our data, along with evidence from other authors, support the standard procedure of using both devices equivalently as a safe practice for bilateral patients. Age and gender were identified as significant predictors of refractive outcomes, although their clinical significance may be limited. The insights from our investigation will help optimize biometry for cataract surgery for safe patient care.
Author Contributions
Data acquisition and preliminary preprocessing were conducted by S.A. and D.B., who also performed the statistical analyses. T.L. and T.R. oversaw the conception and design of the project, providing critical methodological insights and guidance throughout the research process. S.H.-M., as the senior author, provided overall supervision, contributed to the interpretation of results, and guided the drafting and critical revision of the manuscript. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The ethics committee has reviewed the research project in accordance with § 15 of the Professional Code of the State Medical Association of Baden-Württemberg. They have no ethical or legal concerns regarding the conduct of the research project. Approval number: 24-1146-S1-retro (11 June 2024)
Informed Consent Statement
Informed consent was not obtained as our study involved retrospective analysis utilizing routine clinical data, precluding direct patient contact. Given the large cohort size, individual consent was impractical. Ethical approval was granted by the committee without reservation regarding this procedural approach.
Data Availability Statement
Due to potential data privacy considerations, the dataset used in this study is not publicly accessible. However, upon request, we are prepared to furnish additional data as needed.
Acknowledgments
We acknowledge support by the Open Access Publication Fund of the University of Freiburg.
Conflicts of Interest
Although our clinic is a reference center for Carl Zeiss Meditec, there is no conflict of interest present. We received no funding for our analysis, no data was shared with Carl Zeiss Meditec, and there was no influence on us during the study.
References
- Song, J.S.; Yoon, D.Y.; Hyon, J.Y.; Jeon, H.S. Comparison of Ocular Biometry and Refractive Outcomes Using IOL Master 500, IOL Master 700, and Lenstar LS900. Korean J. Ophthalmol. 2020, 34, 126. [Google Scholar] [CrossRef] [PubMed]
- Jiang, J.; Pan, X.; Zhou, M.; Wang, X.; Zhu, H.; Li, D. A comparison of IOLMaster 500 and IOLMaster 700 in the measurement of ocular biometric parameters in cataract patients. Sci. Rep. 2022, 12, 12770. [Google Scholar] [CrossRef] [PubMed]
- Haigis, W.; Lege, B.; Miller, N.; Schneider, B. Comparison of immersion ultrasound biometry and partial coherence interferometry for intraocular lens calculation according to Haigis. Graefe’s Arch. Clin. Exp. Ophthalmol. 2000, 238, 765–773. [Google Scholar] [CrossRef] [PubMed]
- Connors, R.; Boseman, P.; Olson, R.J. Accuracy and reproducibility of biometry using partial coherence interferometry. J. Cataract. Refract. Surg. 2002, 28, 235–238. [Google Scholar] [CrossRef] [PubMed]
- Eleftheriadis, H. IOLMaster biometry: Refractive results of 100 consecutive cases. Br. J. Ophthalmol. 2003, 87, 960–963. [Google Scholar] [CrossRef] [PubMed]
- Findl, O.; Kriechbaum, K.; Sacu, S.; Kiss, B.; Polak, K.; Nepp, J.; Schild, G.; Rainer, G.; Maca, S.; Petternel, V.; et al. Influence of operator experience on the performance of ultrasound biometry compared to optical biometry before cataract surgery. J. Cataract. Refract. Surg. 2003, 29, 1950–1955. [Google Scholar] [CrossRef] [PubMed]
- Gökce, S.E.; De Oca, I.M.; Cooke, D.L.; Wang, L.; Koch, D.D.; Al-Mohtaseb, Z. Accuracy of 8 intraocular lens calculation formulas in relation to anterior chamber depth in patients with normal axial lengths. J. Cataract. Refract. Surg. 2018, 44, 362–368. [Google Scholar] [CrossRef] [PubMed]
- Stopyra, W.; Langenbucher, A.; Grzybowski, A. Intraocular Lens Power Calculation Formulas—A Systematic Review. Ophthalmol. Ther. 2023, 12, 2881–2902. [Google Scholar] [CrossRef] [PubMed]
- Hipólito-Fernandes, D.; Luís, M.E.; Serras-Pereira, R.; Gil, P.; Maduro, V.; Feijão, J.; Alves, N. Anterior chamber depth, lens thickness and intraocular lens calculation formula accuracy: Nine formulas comparison. Br. J. Ophthalmol. 2022, 106, 349–355. [Google Scholar] [CrossRef] [PubMed]
- Zhang, Y.; Li, T.; Reddy, A.; Nallasamy, N. Gender differences in refraction prediction error of five formulas for cataract surgery. BMC Ophthalmol. 2021, 21, 183. [Google Scholar] [CrossRef] [PubMed]
- Guzowski, M.; Rochtchina, E.; Wang, J.J.; Mitchell, P. Refractive changes following cataract surgery: The Blue Mountains Eye Study. Clin. Exper Ophthalmol. 2002, 30, 159–162. [Google Scholar] [CrossRef] [PubMed]
- Khoramnia, R.; Auffarth, G.; Łabuz, G.; Pettit, G.; Suryakumar, R. Refractive Outcomes after Cataract Surgery. Diagnostics 2022, 12, 243. [Google Scholar] [CrossRef] [PubMed]
- Lundström, M.; Dickman, M.; Henry, Y.; Manning, S.; Rosen, P.; Tassignon, M.-J.; Young, D.; Stenevi, U. Risk factors for refractive error after cataract surgery: Analysis of 282 811 cataract extractions reported to the European Registry of Quality Outcomes for cataract and refractive surgery. J. Cataract. Refract. Surg. 2018, 44, 447–452. [Google Scholar] [CrossRef]
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