Leukopenia and leukocytosis as strong predictors of COVID-19 severity: A cross-sectional study of the hematologic abnormalities and COVID-19 severity in hospitalized patients

Background and Aims

Predicting severe disease is important in provocative decision-making for the management of patients with the coronavirus disease 2019 (COVID-19); However, there are still some controversies about the COVID-19's severity predicting factors. This study aimed to investigate the relationships between clinical and laboratory findings regarding COVID-19's severity in patients admitted to a tertiary hospital in Mashhad, Iran.

Methods

A cross-sectional study was conducted on patients with documented COVID-19 infection based on the reverse transcription-polymerase chain reaction test. Clinical symptoms, vital signs, and medical history of the patients were recorded from their medical records. Laboratory findings and computed tomography (CT) study findings were documented. Disease severity was defined based on CT scan findings.

Results

A total of 564 patients (58.8 ± 16.8 years old) were evaluated. The frequency of severe disease was 70.4%. There was a significant difference in heart rate (p = 0.0001), fever (p = 0.002), dyspnea (p = 0.0001), chest pain (p = 0.0001), diarrhea (p = 0.021), arthralgia (p = 0.0001), and chills (p = 0.044) as well as lymphopenia (p = 0.014), white blood cell count (p = 0.001), neutrophil count (p < 0.0001), lymphocyte count (p < 0.0001), and prothrombin time (p = 0.001) between disease severity groups. Predictors of severe COVID-19 were pulse rate (crude odds ratio [cOR] = 1.014, 95% confidence interval [CI] for cOR: 1.001, 1.027) and leukopenia (cOR = 3.910, 95% CI for cOR: 1.294, 11.809). Predictors for critical COVID-19 were pulse rate (cOR = 1.075, 95% CI for cOR: 1.046, 1.104), fever (cOR = 2.516, 95%CI for cOR: 1.020, 6.203), dyspnea (cOR = 4.190, 95% CI for cOR: 1.227, 14.306), and leukocytosis (cOR = 3.866, 95% CI for cOR: 1.815, 8.236).

Conclusions

Leukopenia and leukocytosis have the strongest correlation with the COVID-19 severity. These findings could be a valuable guild for clinicians in COVID-19 patient management in the inpatient setting.

A validated nomogram integrating hematological indicators to predict response to neoadjuvant therapy in esophageal squamous cell carcinoma patients

BACKGROUND

The prognoses for advanced Esophageal squamous cell cancer (ESCC) was very poor. Neoadjuvant therapy was shown to improve overall survival of ESCC patients. However, there is still no effective indicator to predict the efficacy of neoadjuvant therapy. The present study intended to investigate the correlation between hematological parameters and the efficacy of neoadjuvant therapy so as to provide a reference for the prediction of cancer response to neoadjuvant therapy.

METHODS

This study included 197 ESCC patients in our center from January 2010 to December 2018. Response evaluation criteria in solid tumors (RECIST) criteria were used for the treatment evaluation. The results of univariate and multivariate logistic regression analysis were used to select independent factors for construction of the prediction model. The concordance index (C-index), receiver operating characteristic (ROC) curve, and calibration curve were used to evaluate the robustness of the model, while the bootstrap method was used for internal validation.

RESULTS

Among the 197 included ESCC patients, 94 patients achieved partial remission, 80 patients were in stable condition, and 23 patients had disease progression, 123 of whom underwent surgery. The comparisons of the dynamic hematological test results before and after treatment show that pre-PLT, pre-MONO%, post-Hb, △WBC, and the option of undergoing neoadjuvant chemoradiation were the potential predictors for the effectiveness of neoadjuvant therapy. The model in which the C-index was 0.803 (95% confidence interval: 0.742-0.864) showed good prediction performance, and still reach a C-index of 0.764 when internally validated.

CONCLUSIONS

For the neoadjuvant treatment of ESCC, hematological indexes are closely related to the efficacy of neoadjuvant therapy. The nomogram can be used to easily predict the efficacy of neoadjuvant therapy in patients.