Predicting COVID-19 progression from diagnosis to recovery or death linking primary care and hospital records in Castilla y León (Spain)

Abstract

This paper analyses COVID-19 patients’ dynamics during the first wave in the region of Castilla y León (Spain) with around 2.4 million inhabitants using multi-state competing risk survival models. From the date registered as the start of the clinical process, it is assumed that a patient can progress through three intermediate states until reaching an absorbing state of recovery or death. Demographic characteristics, epidemiological factors such as the time of infection and previous vaccinations, clinical history, complications during the course of the disease and drug therapy for hospitalised patients are considered as candidate predictors. Regarding risk factors associated with mortality and severity, consistent results with many other studies have been found, such as older age, being male, and chronic diseases. Specifically, the hospitalisation (death) rate for those over 69 is 27.2% (19.8%) versus 5.3% (0.7%) for those under 70, and for males is 14.5%(7%) versus 8.3%(4.6%)for females. Among patients with chronic diseases the highest rates of hospitalisation are 26.1% for diabetes and 26.3% for kidney disease, while the highest death rate is 21.9% for cerebrovascular disease. Moreover, specific predictors for different transitions are given, and estimates of the probability of recovery and death for each patient are provided by the model. Some interesting results obtained are that for patients infected at the end of the period the hazard of transition from hospitalisation to ICU is significatively lower (p < 0.001) and the hazard of transition from hospitalisation to recovery is higher (p < 0.001). For patients previously vaccinated against pneumococcus the hazard of transition to recovery is higher (p < 0.001). Finally, internal validation and calibration of the model are also performed.

Factors Associated with Length of Hospital Stay among COVID-19 Patients in Saudi Arabia: A Retrospective Study during the First Pandemic Wave

“…Our results of prolonged LoHS among patients with either severe or critical symptoms were aligned with Wang et al’s findings. Álvarez-Esteban et al found that the hospitalisation rate for those over 69 is 27.2% and for those under 70 is 5.3%; furthermore, the hospitalisation rate for males is 14.5% and for females 8.3% [ 41 ]. They also reported that, among patients with chronic diseases, the highest rates of hospitalisation were 26.3% for kidney disease and 26.1% for diabetes [ 41 ].…”

“…Álvarez-Esteban et al found that the hospitalisation rate for those over 69 is 27.2% and for those under 70 is 5.3%; furthermore, the hospitalisation rate for males is 14.5% and for females 8.3% [ 41 ]. They also reported that, among patients with chronic diseases, the highest rates of hospitalisation were 26.3% for kidney disease and 26.1% for diabetes [ 41 ]. Furthermore, Guo et al concluded that fever, female sex, higher creatinine levels, and chronic liver or kidney disease before admission were associated with prolonged LoHS in COVID-19 patients [ 42 ].…”

Predicting COVID-19 progression in hospitalized patients in Belgium from a multi-state model

“…Like this, the multi-state model more accurately describes the evolution of hospitalised patients, by accounting for intermediate events of disease progression that likely influence disease outcomes over time, i.e., time and event-related dependencies of disease progression. Similar to a smaller sample size study covering only one region of Spain ( 51 ), the present study devised the multi-state framework for building a risk prediction model for COVID-19 critical state (ICU transfer) and death versus recovery, and consistently co-morbidities were more frequently observed to be the more prevalent among those experiencing worst COVID-19 outcomes, like hospitalisation, and subsequently in-hospital death. In addition, we thereby identified male sex, high levels of CRP and LDH as well as reporting lower respiratory complaints as common important predictive factors for transitioning to ICU or in-hospital death after hospitalisation due to SARS-CoV-2 infection, with additionally middle-age, obesity, reporting loss of appetite and staying in a university hospital for a transfer to ICU, while advanced age and a higher number of comorbidities for in-hospital death.…”

Health trajectories in older patients hospitalized for COVID-19: Results from the GeroCovid multicenter study

“…Hospitalized COVID-19 patients show varying disease dynamics [ 6 ]. While most persons show rapid clinical improvements and require brief stays, others progress towards more severe disease and need admission to intensive care unit (ICU) with or without invasive mechanical ventilation [ 6 , 7 ].…”

“…The risk factors associated with stable/unstable disease courses, as well as worsening or improving transitions, have not been clearly established, because, to date, most of the studies on COVID-19 hospitalization are cross-sectional and focused on critically ill patients, mainly from single clinical centers [ [8] , [9] , [10] ]. Indeed, data on transitions between clinical states in COVID-19 hospitalized patients from multiple clinical centers over time are limited [ 6 , 7 ].…”