Automated Comprehensive Analysis of Preoperative Biometric Parameters in Cataract Patients: A Retrospective Study of over 6 000 Eyes

Abstract

Cataract surgery is one of the most successful surgical procedures, improving vision and quality of life for millions globally. An accurate preoperative measurement is crucial for predicting outcomes, particularly in minimizing postoperative refractive errors through precise intraocular lens (IOL) selection. This study aimed to analyze preoperative biometric data in cataract patients to identify key parameters relevant for clinical decision-making. The study also sought to understand patient demographics and biometrics in a representative population. An automated retrospective analysis was conducted on the preoperative biometric data of 6 163 eyes from 3 118 patients who underwent cataract or clear lens extraction (CLE) surgery in a German clinic over the past 2 years. All measurements were taken using the IOL Master 700 (Carl Zeiss Meditec, Jena, Germany), and data were automatically transferred for analysis using a dedicated software tool. Biometric parameters assessed included axial length (AL), keratometry values (K, TK), anterior chamber depth (ACD), lens thickness (LT), and vitreous length (VL). The age and gender distribution of the cohort was also considered. The biometric data from this large patient cohort largely aligns with published norms for cataract patients. The majority of eyes exhibited ALs and corneal curvatures within expected ranges, supporting accurate IOL power calculations. The study also confirmed a high prevalence of mild astigmatism, suggesting that toric IOLs could address residual astigmatism for better visual outcomes. This studyʼs large sample size adds valuable insights into preoperative cataract patient data and shows the value of an automated analysis.

Zusammenfassung

Die Kataraktoperation ist einer der erfolgreichsten chirurgischen Eingriffe, der das Sehvermögen und die Lebensqualität von Millionen Menschen auf der ganzen Welt verbessert. Eine genaue präoperative Messung ist entscheidend für die Vorhersage der Ergebnisse, insbesondere für die Minimierung postoperativer Brechungsfehler durch eine präzise Auswahl der Intraokularlinse (IOL). Ziel dieser Studie ist es, präoperative biometrische Daten von Kataraktpatienten zu analysieren, um Schlüsselparameter für die klinische Entscheidungsfindung zu ermitteln. Außerdem soll die Studie ein Verständnis der demografischen und biometrischen Daten der Patienten in einer repräsentativen Population ermöglichen. Es wurde eine automatisierte retrospektive Analyse der präoperativen biometrischen Daten von 6163 Augen von 3118 Patienten durchgeführt, die sich in den letzten 2 Jahren in einer deutschen Klinik einer Katarakt- oder Clear-Lens-Extraction-Operation (CLE) unterzogen. Alle Messungen wurden mit dem IOL Master 700 (Carl Zeiss Meditec) durchgeführt, und die Daten wurden automatisch zur Analyse mit einem speziellen Softwaretool übertragen. Zu den untersuchten biometrischen Parametern gehörten Achsenlänge (AL), Keratometriewerte (K, TK), Vorderkammertiefe (ACD), Linsendicke (LT) und Glaskörperlänge (VL). Auch die Alters- und Geschlechtsverteilung der Kohorte wurde berücksichtigt. Die biometrischen Daten dieser großen Patientenkohorte stimmen weitgehend mit den veröffentlichten Daten für Kataraktpatienten überein. Die Mehrheit der Augen wies Achsenlängen und Keratometriewerte innerhalb der erwarteten Bereiche auf. Die Studie bestätigte auch eine hohe Prävalenz eines leichten Astigmatismus, was durch torische IOLs ausgeglichen werden sollte, um bessere Sehergebnisse zu erzielen. Die Größe dieser Studie gibt wertvolle Einblicke in die präoperativen Daten von Kataraktpatienten und zeigt, wie nützlich eine automatische Analyse von Patientendaten sein kann.

Conclusion Box

Already known:

• The measurements observed in this study align with previously recorded data, further validating established methodologies and findings.

• Previous research has demonstrated the potential for digital tools to support data collection and analysis in clinical settings.

• The potential of fully automated data extraction from clinic software to streamline the analysis of large datasets has not been fully explored until now.

Newly described:

• This study highlights how automated extraction from clinic software can significantly aid in the efficient handling and analysis of big data.

• The approach presented here simplifies the process of data aggregation, reducing manual effort while improving accuracy.

• Despite these advancements, the rate of toric IOL implantation remains far too low compared to the high prevalence of astigmatism, underscoring an ongoing gap in surgical decision-making and patient care.

Keywords

cataract surgery - biometric analysis - patient cohort data

Schlüsselwörter

Kataraktchirurgie - Biometrie - Patientenkohorte

Publication History

Received: 15 October 2024

Accepted: 13 February 2025

Article published online:
27 March 2025

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