目的 分析长沙市输入性疟疾的特征，结合实验室指标探讨重症疟疾患者的影响因素和早期预警指标。 方法 回顾性分析2012—2023年在长沙市第一医院住院治疗的疟疾患者的病例资料，比较非重症与重症疟疾患者差异，采用双变量相关性-spearman相关系数、logistic回归分析观察指标与重症疟疾的相关性及影响程度，筛选出与预后相关较强的指标，找到疟疾患者进展为重症的独立影响因子，受试者工作特征（ROC）曲线分析各指标及联合检测早期预判重症疟疾的效能，计算曲线下面积（AUC）。 结果 共收集127例疟疾患者的病例资料，其中38例重症疟疾患者、89例非重症患者。与非重症疟疾患者相比，重症疟疾患者发病到住院时间间隔[4.00（2.75，6.00） d]和住院时间[7.00（4.75，12.00） d]更长（Z = -2.20、-3.05，P < 0.05、P < 0.01），出现尿隐血的比例[78.9%（30/38）]更高（χ² = 18.67，P < 0.01），红细胞数量[4.11（3.46，4.65） × 10¹²/L]、血小板数量[（53.50 ± 53.73） × 10⁹/L]、白蛋白水平[（34.99 ± 5.36） g/L]更低（Z = -2.37、t = 6.72、t = 4.10，P < 0.05、P < 0.01、P < 0.01），丙氨酸转氨酶（ALT）[53.50（38.63，73.75） U/L]、天冬氨酸转氨酶（AST）[50.85（34.00，97.05） U/L]、乳酸脱氢酶（LDH）[449.50（321.50，625.75） U/L]、总胆红素[（74.18 ± 78.09） μmol/L]、降钙素原（PCT）[2.95（0.91，19.47） ng/ml]水平更高（Z = -3.51、Z = -3.48、Z = -3.58、t = -3.91、Z = -4.63，均P < 0.01）。发病到住院时间间隔、住院时间、尿隐血情况及ALT、AST、总胆红素、LDH、PCT水平等指标与重症疟疾呈正相关（r > 0，均P < 0.05），红细胞数量、血小板数量、白蛋白水平等与重症疟疾呈负相关（r < 0，均P < 0.05），其中血小板数量能较好地反映疾病严重程度（|r| ≥ 0.5，P < 0.01）。尿隐血、AST、总胆红素、LDH、血清肌酐、尿素氮、PCT是重症疟疾的危险因素（OR > 1，P < 0.05），红细胞、血小板、血红蛋白、白蛋白是重症疟疾的保护因素（OR < 1，P < 0.05）。血小板数量、总胆红素是疟疾患者进展为重症的独立影响因子（P < 0.05），AUC分别为0.867、0.769，二者联合检测的AUC为0.900，高于单个指标检测（P < 0.01）。 结论 血小板、总胆红素可作为早期预警重症疟疾的独立影响因子，联合检测较单一检测更有助于重症疟疾的早期预警。

Objective To analyze the characteristics of imported malaria in Changsha and explore the influencing factors and early warning indicators of severe malaria patients in combination with laboratory indicators. Methods A retrospective analysis was conducted on the case data of malaria patients hospitalized in the First Hospital of Changsha from 2012 to 2023. Differences between non-severe and severe malaria patients were compared. Bivariate correlation-Spearman correlation coefficient and logistic regression analysis were used to observe the correlation and influence degree between indicators and severe malaria. Indicators strongly related to prognosis were screened to identify independent impact factors for the progression of malaria patients to severe cases. Receiver operating characteristic (ROC) curve analysis was performed to assess the efficacy of individual and combined indicators in early prediction of severe malaria, and the area under the curve (AUC) was calculated. Results Case data from 127 malaria patients were collected, which including 38 severe malaria patients and 89 non-severe patients. Compared with non-severe malaria patients, severe malaria patients had longer durations from onset to hospitalization [4.00 (2.75, 6.00) d] and longer hospitalization time [7.00 (4.75, 12.00) d] (Z = -2.20, -3.05, P < 0.05, P < 0.01). More severe malaria patients [78.9% (30/38)] were presenting with occult blood in urine (χ² = 18.67, P < 0.01). They had lower red blood cell count [4.11 (3.46, 4.65) × 10¹²/L], platelet count [(53.50 ± 53.73) × 10⁹/L] and albumin level [(34.99 ± 5.36) g/L] (Z = -2.37, t = 6.72, t = 4.10; P < 0.05, P < 0.01, P < 0.01), but higher levels of alanine aminotransferase (ALT) [53.50 (38.63, 73.75) U/L], aspartate aminotransferase (AST) [50.85 (34.00, 97.05) U/L], lactate dehydrogenase (LDH) [449.50 (321.50, 625.75) U/L], total bilirubin [(74.18 ± 78.09) μmol/L] and procalcitonin (PCT) [2.95 (0.91, 19.47) ng/ml] (Z = -3.51, Z = -3.48, Z = -3.58, t = -3.91, Z = -4.63; all P < 0.01) than non-severe patients. Durations from onset to hospitalization, hospitalization time, urinary occult blood and levels of ALT, AST, total bilirubin, LDH, and PCT were positively correlated with severe malaria (r > 0, all P < 0.05), while red blood cell count, platelet count and albumin level were negatively correlated with severe malaria (r < 0, all P < 0.05). Among them, platelet count was a good indicator of malaria severity (|r| ≥ 0.5, P < 0.01). Urinary occult blood, AST, total bilirubin, LDH, serum creatinine, urea nitrogen and PCT were risk factors for severe malaria (OR > 1, P < 0.05), while red blood cell count, platelet count, hemoglobin and albumin level were protective factors against severe malaria (OR < 1, P < 0.05). Platelet count and total bilirubin level were independent impact factors for the progression of malaria patients to severe cases (P < 0.05), with AUCs of 0.867 and 0.769, respectively. The AUC for the combined detection of the both was 0.900, which was higher than that for single indicator detection (P < 0.01). Conclusion Platelet count and total bilirubin level can serve as independent impact factors for early warning of severe malaria. Combined detection is more helpful than single detection for early warning of severe malaria.