PurposeSecondary hyperparathyroidism (SHPT) is one of the most common complications of chronic kidney disease and has a high rate of morbidity and mortality. Current studies on prognostic factors in SHPT are inadequate. We aimed to identify a single-center cohort of severe SHPT to elucidate relevant clinical and laboratory features and explore laboratory indicators that related to its prognosis.MethodsThe clinical data of 46 patients with SHPT, admitted to the intensive care unit (ICU) of the First Affiliated Hospital of Zhengzhou University in the time period ranging from January 2019 to March 2022 were analyzed retrospectively. Clinical data collected were screened univariately for influences that were associated with poor prognosis. A binary logistic regression model was constructed to analyze the independent risk factors for poor clinical prognosis, using correlated influences. The value of each indicator in predicting patient prognosis was analyzed using receiver operating characteristic curves (ROC) curves.ResultsThe causes of death among the 46 patients with severe SHPT were cardiogenic death (malignant arrhythmia, cardiac arrest) in 11 cases (47.8%), sepsis in 9 cases (39.2%), and neurogenic death (intracranial hemorrhage) in 3 cases (13.0%). Patients were divided into a good prognosis group and a poor prognosis group according to their status at the time of leaving the ICU. There was no statistically significant difference in sex, BUN, NT-pro BNP, ALP, Scr, Mg, Ca, Pi, K, CRP, Hb, and PLT between the poor prognosis group and the good prognosis groups. The age, PTH, PCT, WBC, APACHE II, and neutrophil ratio of the poor prognosis group were higher than those of the good prognosis group, and the ALB level was lower than that of the good prognosis group, with a statistically significant difference of P < 0.05. The 19 clinical indicators mentioned above were screened univariately. Among them, age, PTH, WBC, ALB, APACHE II and neutrophil ratio were significantly associated with prognosis, P < 0.05. Binary logistic regression analysis showed that age (OR = 1.076, 95% CI (1.011, 1.145)), PTH (OR = 1.004, 95% CI (1.000, 1.007)), WBC (OR = 1.295, 95% CI (1.026, 1.634)) were indicators for poor prognosis in patients with severe SHPT, and ALB (OR = 0.803, 95% CI (0.645, 0.998)) was a protective factor for poor prognosis. The ROC curve showed that the optimal cut-off point for patient age was 51 years, with a sensitivity of 86.9% and specificity of 52.2%; the optimal cut-off point for PTH was 346 pg/ml, with a sensitivity of 59.1% and specificity of 82.6%; the optimal cut-off point for WBC was 11.95 × 10^9/L, with a sensitivity of 56.52% and specificity of 91.3%; the optimal cut-off point for neutrophil ratio was 82.4%, sensitivity 82.6%, specificity 73.9%.ConclusionAge, PTH, and WBC are independent risk factors for poor prognosis of severe SHPT, and ALB is an independent protective factor for poor prognosis. Patients with severe SHPT should be assessed for risk of the poor prognosis based on age, admission PTH, WBC, ALB, and neutrophil ratio as early as possible to adjust the treatment strategy.
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