Coronary　artery　disease　(CAD)　remains　a　major　global　health　concern,　significantly　contributing　to　morbidity　and　mortality.　This　study　aimed　to　investigate　the　co-occurrence　patterns　of　diagnoses　and　comorbidities　in　CAD　patients　using　a　network-based　approach.　A　retrospective　analysis　was　conducted　on　195　hospitalized　CAD　patients　from　a　single　hospital　in　Guangxi,　China,　with　data　collected　on　age,　sex,　and　comorbidities.　Network　analysis,　supported　by　sensitivity　analysis,　revealed　key　diagnostic　clusters　and　comorbidity　hubs,　with　hypertension　emerging　as　the　central　node　in　the　co-occurrence　network.　Unstable　angina　and　myocardial　infarction　were　identified　as　central　diagnoses,　frequently　co-occurring　with　metabolic　conditions　such　as　diabetes.　The　results　also　highlighted　significant　age-　and　sex-specific　differences　in　CAD　diagnoses　and　comorbidities.　Sensitivity　analysis　confirmed　the　robustness　of　the　network　structure　and　identified　clusters,　despite　the　limitations　of　sample　size　and　data　source.　Modularity　analysis　uncovered　distinct　clusters,　illustrating　the　complex　interplay　between　cardiovascular　and　metabolic　disorders.　These　findings　provide　valuable　insights　into　the　relationships　between　CAD　and　its　comorbidities,　emphasizing　the　importance　of　integrated,　personalized　management　strategies.　Future　studies　with　larger,　multi-center　datasets　and　longitudinal　designs　are　needed　to　validate　these　results　and　explore　the　temporal　dynamics　of　CAD　progression.