Kyala Norman Jonas, Mboya Innocent, Shao Elichilia, Sakita Francis, Kilonzo Kajiru Gadiel, Shirima Laura, Sadiq Abid, Mkwizu Elifuraha, Chamba Nyasatu, Marandu Annette, Muhali Sophia, Raza Faryal, Ndale Eliasa, Bayo Damas, Mujuni Daniel, Lyamuya Furaha
Faculty of Medicine, Kilimanjaro Christian Medical University College, Moshi, Tanzania.
Department of Internal Medicine, Kilimanjaro Christian Medical Centre, Moshi, Tanzania.
PLoS One. 2025 Jan 31;20(1):e0300231. doi: 10.1371/journal.pone.0300231. eCollection 2025.
COVID-19 caused a profound global impact, resulting in significant cases and deaths. The progression of COVID-19 clinical manifestations is influenced by a dysregulated inflammatory response. Early identification of the subclinical progression is crucial for timely intervention and improved patient outcomes. While there are various biomarkers to predict disease severity and outcomes, their accessibility and affordability pose challenges in resource-limited settings. We explored the potentiality of the neutrophil-to-lymphocyte ratio (NLR) as a cost-effective inflammatory marker to predict disease severity, clinical deterioration, and mortality in affected patients.
A hospital-based retrospective cohort study was conducted at KCMC Hospital among COVID-19 patients followed from admission to discharge between 1st March 2020 and 31st March 2022. NLR was calculated as the absolute neutrophil count in μL divided by the absolute lymphocyte count in μL. The NLR cut-off value was determined using Receiver Operating Characteristic (ROC) analysis and assessed its predictive ability at admission for in-hospital mortality. The Chi-square test compared the proportion of NLR by patient characteristics. The association of NLR with disease severity and mortality was analyzed using the modified Poisson and Cox regression models, respectively.
The study included 504 patients, with a median age of 64 years, 57.1% were males, and 68.3% had severe COVID-19. The in-hospital COVID-19 mortality rate was 37.7%. An NLR cutoff value of 6.1 or higher had a sensitivity of 92.1% (95% CI 89.2%-94.0%) and a specificity of 92.0% (95% CI 89.7%-94.4%). Additionally, 39.5% of patients with an NLR value of 6.1 or higher had increased risk of severe disease, subsequent clinical deterioration, and mortality.
An NLR value of 6.1 or higher at the time of hospital admission associated with severe disease, clinical deterioration, and mortality in patients with COVID-19. Integration of NLR as a prognostic parameter in COVID-19 prognosis scales could improve risk assessment and guide appropriate management strategies for COVID-19 patients, as well as for potential future viral-related pneumonias. Further prospective studies are necessary to validate these findings and evaluate the clinical utility of NLR in larger cohorts of patients.
新型冠状病毒肺炎(COVID-19)对全球产生了深远影响,导致大量病例和死亡。COVID-19临床表现的进展受炎症反应失调影响。早期识别亚临床进展对于及时干预和改善患者预后至关重要。虽然有多种生物标志物可用于预测疾病严重程度和预后,但在资源有限的环境中,其可及性和可负担性带来了挑战。我们探讨了中性粒细胞与淋巴细胞比值(NLR)作为一种经济有效的炎症标志物,用于预测受影响患者的疾病严重程度、临床恶化和死亡率的潜力。
在基苏木县中央医院(KCMC Hospital)进行了一项基于医院的回顾性队列研究,研究对象为2020年3月1日至2022年3月31日期间收治的COVID-19患者,从入院到出院进行随访。NLR计算方法为每微升绝对中性粒细胞计数除以每微升绝对淋巴细胞计数。使用受试者工作特征(ROC)分析确定NLR临界值,并评估其在入院时对院内死亡率的预测能力。卡方检验比较了不同患者特征的NLR比例。分别使用修正泊松回归模型和Cox回归模型分析NLR与疾病严重程度和死亡率的关联。
该研究纳入了�04例患者,中位年龄为64岁,57.1%为男性,68.3%患有重症COVID-19。院内COVID-19死亡率为37.7%。NLR临界值为6.1或更高时,敏感性为92.1%(95%置信区间89-2%-94.0%),特异性为92.0%(95%置信区间89.7%-94.4%)。此外,NLR值为6.1或更高的患者中,39.5%发生重症疾病、随后临床恶化和死亡的风险增加。
入院时NLR值为6.1或更高与COVID-19患者的重症疾病、临床恶化和死亡率相关。将NLR作为预后参数纳入COVID-19预后量表中,可改善风险评估,并指导针对COVID-19患者以及未来可能出现的病毒性肺炎患者的适当管理策略。需要进一步的前瞻性研究来验证这些发现,并评估NLR在更大患者队列中的临床实用性。