A Nomogram Prediction of Length of Hospital Stay in Patients with COVID-19 Pneumonia: A Retrospective Cohort Study

Abstract

Assessing the length of hospital stay (LOS) in patients with coronavirus disease 2019 (COVID-19) pneumonia is helpful in optimizing the use efficiency of hospital beds and medical resources and relieving medical resource shortages. This retrospective cohort study of 97 patients was conducted at Beijing You’An Hospital between January 21, 2020, and March 21, 2020. A multivariate Cox proportional hazards regression based on the smallest Akaike information criterion value was used to select demographic and clinical variables to construct a nomogram. Discrimination, area under the receiver operating characteristic curve (AUC), calibration, and Kaplan–Meier curves with the log-rank test were used to assess the nomogram model. The median LOS was 13 days (interquartile range [IQR]: 10–18). Age, alanine aminotransferase, pneumonia, platelet count, and PF ratio (PaO2/FiO2) were included in the final model. The C-index of the nomogram was 0.76 ( 95 % confidence interval CI = 0.69 – 0.83 ), and the AUC was 0.88 ( 95 % CI = 0.82 – 0.95 ). The adjusted C-index was 0.75 ( 95 % CI = 0.67 – 0.82 ) and adjusted AUC 0.86 ( 95 % CI = 0.73 – 0.95 ), both after 1000 bootstrap cross internal validations. A Brier score of 0.11 ( 95 % CI = 0.07 – 0.15 ) and adjusted Brier score of 0.130 ( 95 % CI = 0.07 – 0.20 ) for the calibration curve showed good agreement. The AUC values for the nomogram at LOS of 10, 20, and 30 days were 0.79 ( 95 % CI = 0.69 – 0.89 ), 0.89 ( 95 % CI = 0.83 – 0.96 ), and 0.96 ( 95 % CI = 0.92 – 1.00 ), respectively, and the high fit score of the nomogram model indicated a high probability of hospital stay. These results confirmed that the nomogram model accurately predicted the LOS of patients with COVID-19. We developed and validated a nomogram that incorporated five independent predictors of LOS. If validated in a future large cohort study, the model may help to optimize discharge strategies and, thus, shorten LOS in patients with COVID-19.

Factor Contributing Length of Stay of COVID-19 Patients in Hospitals: Scoping Review

“…Laboratory results obtained from the blood of COVID-19 patients can be identified as affecting on the patient's LOS. High levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) (>40 U/L) and high myoglobin on laboratory tests were also identified as being able to increase LOS in COVID-19 patients (Li et al, 2021). In addition, the Systemic Inflammation Index (SII) is a count of [neutrophils × platelets]/lymphocytes having a significant effect on the length of hospital stay.…”

“…Research shows that age > 50 can increase the risk of patient severity, so a long time is needed for in-hospital treatment (Li et al, 2021). Patients over 65 years of age have the highest severity and the lowest in children under 18 years of age (Stokes et al, 2020).…”

“…Clinical manifestations in children and infants are generally milder than in adults, especially in those without any background in certain diseases or obesity (Diaz et al, 2021). Older age has decreased immune functionand more sensitive cytokine response, and T cells that produce interleukins increase with age, so the induction of proinflammatory cytokines is not controlled (Li et al, 2021).…”

Development of a model by LASSO to predict hospital length of stay (LOS) in patients with the SARS-Cov-2 omicron variant

“…Two previous studies were used to predict LOS in SARS-CoV-2 patients. However, in one study, the variables of the model contained “Wuhan travelling history” [ 11 ], and in another the virus was not Omicron variant [ 12 ]. Therefore, it is an urgent need to develop a validated predictive model to predict LOS in Omicron patients, which can optimize the management of patients to alleviate the strain on medical resources.…”

Fever, Tachypnea, and Monocyte Distribution Width Predicts Length of Stay for Patients with COVID-19: A Pioneer Study

“…Studies have indicated that the mean LOS of patients hospitalized for COVID-19 ranges from 5 to 17 days [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 ]. A patient’s LOS is influenced by various clinical and personal factors, and some clinical tools have been developed to predict patients’ LOSs [ 19 , 20 ]. Patients with multiple comorbidities [ 11 , 17 , 18 , 21 , 22 ] and older age [ 18 , 23 , 24 ] are more vulnerable and associated with prolonged LOS for COVID-19.…”