Continuous-variable quantum key distribution (CV-QKD) has emerged as a prominent research focus in quantum communication, owing to its cost-effectiveness and compatibility with existing optical infrastructure. Nevertheless, achieving efficient data reconciliation under low signal-to-noise ratio (SNR) conditions remains a critical challenge impeding its widespread deployment. Low-density parity-check (LDPC) codes, recognized as a state-of-the-art error correction technique, have demonstrated significant potential for enhancing post-processing efficiency in CV-QKD systems. Leveraging their sparse parity-check matrix structure and iterative belief propagation decoding, LDPC codes enable robust error correction during quantum signal transmission, thereby optimizing the reconciliation process. This comprehensive review systematically examines recent advancements in LDPC code applications for both fiber-optic and free-space CV-QKD systems. The review analyzes key developments in code design, decoding algorithms, and implementation strategies that have contributed to improved reconciliation performance. Furthermore, The study identify promising research directions that could address current limitations and facilitate the transition of CV-QKD technology from experimental demonstrations to practical commercial applications. The evolution of LDPC codes in CV-QKD reconciliation can be categorized into three transformative phases. Initially, traditional LDPC codes demonstrated promising results, achieving reconciliation efficiencies of up to 88.7% at an SNR of 1.76 dB. However, their performance degraded significantly in ultra-low SNR regimes (<0.1 dB), limiting their applicability for long-distance quantum communication. The second phase marked a breakthrough with the introduction of multi-edge-type (MET) LDPC codes, which exhibited superior performance in low-SNR conditions. These codes achieved remarkable reconciliation efficiencies of 96.9% at an SNR of 0.029 dB, enabling secure key distribution over distances extending to 140 km. Further enhancements were realized through GPU-accelerated quasi-cyclic MET-LDPC (QC-MET-LDPC) variants, which pushed reconciliation efficiencies close to 99% while maintaining high processing speeds. For free-space CV-QKD systems, the dynamic and unpredictable nature of atmospheric turbulence poses additional challenges. Adaptive-rate LDPC codes have been developed to mitigate these effects, dynamically adjusting code rates in response to fluctuating channel conditions. These adaptive schemes have demonstrated significant improvements, boosting key rates by 87.5 kbit/s in experimental settings. Moreover, the integration of type-based-protograph (TBP) LDPC codes with high-dimensional reconciliation techniques has further enhanced performance, increasing secure key rates by up to 165% compared to traditional methods. LDPC codes have firmly established themselves as the foundational technology for achieving high-efficiency reconciliation in CV-QKD systems. The development of MET-LDPC codes and structured variants such as QC-MET and TBP LDPC codes has demonstrated transformative capabilities, delivering near-optimal reconciliation efficiencies (>96%) even in challenging low-SNR conditions (<0.03 dB). These advancements have been instrumental in extending secure transmission distances beyond 140 km in fiber-based systems while maintaining robust performance in turbulent free-space channels. Moving forward, five key research directions is critical for future development: 1) Innovative LDPC architectures, such as hybrid Quasi-Cyclic Accumulate-Repeat-Accumulate (QC-ARA) designs, to bridge the efficiency gap in ultra-low-SNR regimes (<0.01 dB); 2) Dynamic adaptation mechanisms leveraging machine learning for real-time optimization under channel fluctuations; 3) Hardware-algorithm co-design, aiming for high-throughput (>1 Gbps) FPGA/ASIC implementations with improved energy efficiency; 4) Cross-layer integration strategies that unify LDPC optimization with discrete modulation and post-processing to maximize end-to-end key rates; and 5) Synergy between quantum-classical network architectures, including quantum repeaters and measurement-device-independent protocols, to enhance scalability and practicality. To overcome these challenges, researchers must focus on optimizing LDPC code performance, developing adaptive reconciliation protocols, and improving hardware implementations. These advancements will enable the transition from experimental CV-QKD systems to practical, high-speed quantum networks, establishing LDPC codes as essential components of future-proof cryptographic infrastructure.