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Mortality and Advanced Support Requirement for Patients With Cancer With COVID-19: A Mathematical Dynamic Model for Latin America.

癌症新型冠状病毒肺炎患者的死亡率和高级支持需求: 拉丁美洲的数学动态模型。

  • 影响因子:0
  • DOI:10.1200/GO.20.00156
  • 作者列表:"Ruiz-Patiño A","Arrieta O","Pino LE","Rolfo C","Ricaurte L","Recondo G","Zatarain-Barron ZL","Corrales L","Martín C","Barrón F","Vargas C","Carranza H","Otero J","Rodriguez J","Sotelo C","Viola L","Russo A","Rosell R","Cardona AF
  • 发表时间:2020-05-01
Abstract

PURPOSE:In the midst of a global pandemic, evidence suggests that similar to other severe respiratory viral infections, patients with cancer are at higher risk of becoming infected by COVID-19 and have a poorer prognosis. METHODS:We have modeled the mortality and the intensive care unit (ICU) requirement for the care of patients with cancer infected with COVID-19 in Latin America. A dynamic multistate Markov model was constructed. Transition probabilities were estimated on the basis of published reports for cumulative probability of complications. Basic reproductive number (R0) values were modeled with R using the EpiEstim package. Estimations of days of ICU requirement and absolute mortality were calculated by imputing number of cumulative cases in the Markov model. RESULTS:Estimated median time of ICU requirement was 12.7 days, median time to mortality was 16.3 days after infection, and median time to severe event was 8.1 days. Peak ICU occupancy for patients with cancer was calculated at 16 days after infection. Deterministic sensitivity analysis revealed an interval for mortality between 18.5% and 30.4%. With the actual incidence tendency, Latin America would be expected to lose approximately 111,725 patients with cancer to SARS-CoV-2 (range, 87,116-143,154 patients) by the 60th day since the start of the outbreak. Losses calculated vary between < 1% to 17.6% of all patients with cancer in the region. CONCLUSION:Cancer-related cases and deaths attributable to SARS-CoV-2 will put a great strain on health care systems in Latin America. Early implementation of interventions on the basis of data given by disease modeling could mitigate both infections and deaths among patients with cancer.

摘要

目的: 在全球大流行中,有证据表明,与其他严重呼吸道病毒感染一样,癌症患者感染新型冠状病毒肺炎的风险较高,预后较差。 方法: 我们模拟了拉丁美洲癌症患者感染新型冠状病毒肺炎的死亡率和重症监护病房 (ICU) 的护理需求。构建了一个动态多状态马尔可夫模型。根据已发表的并发症累积概率报告估计转移概率。使用EpiEstim包对基本生殖数 (基本传染数) 值进行R建模。通过在Markov模型中估算累积病例数,计算ICU需求天数和绝对死亡率的估计值。 结果: 估计ICU需求的中位时间为 12.7 天,感染后至死亡的中位时间为 16.3 天,至严重事件的中位时间为 8.1 天。计算癌症患者感染后 16 天的ICU入住峰值。确定性敏感性分析显示死亡率的区间在 18.5%-30.4% 之间。根据实际发病趋势,预计到疫情开始后 111,725 天,拉丁美洲将有大约 87,116 名癌症患者SARS-CoV-2 (范围为 143,154-名患者)。计算的损失在该地区所有癌症患者的 <1% 至 17.6% 之间变化。 结论: 癌症相关病例和SARS-CoV-2 导致的死亡将给拉丁美洲的卫生保健系统带来巨大压力。根据疾病建模提供的数据早期实施干预措施可以减轻癌症患者的感染和死亡。

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影响因子:2.48
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呼吸道感染方向

呼吸道感染分为上呼吸道感染与下呼吸道感染。上呼吸道感染是指自鼻腔至喉部之间的急性炎症的总称,是最常见的感染性疾病。下呼吸道感染是最常见的感染性疾患,治疗时必须明确引起感染的病原体以选择有效的抗生素。

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