Machine-learning based prediction and analysis of prognostic risk factors in patients with candidemia and bacteraemia: a 5-year analysis

Abstract

Bacteraemia has attracted great attention owing to its serious outcomes, including deterioration of the primary disease, infection, severe sepsis, overwhelming septic shock or even death. Candidemia, secondary to bacteraemia, is frequently seen in hospitalised patients, especially in those with weak immune systems, and may lead to lethal outcomes and a poor prognosis. Moreover, higher morbidity and mortality associated with candidemia. Owing to the complexity of patient conditions, the occurrence of candidemia is increasing. Candidemia-related studies are relatively challenging. Because candidemia is associated with increasing mortality related to invasive infection of organs, its pathogenesis warrants further investigation. We collected the relevant clinical data of 367 patients with concomitant candidemia and bacteraemia in the first hospital of China Medical University from January 2013 to January 2018. We analysed the available information and attempted to obtain the undisclosed information. Subsequently, we used machine learning to screen for regulators such as prognostic factors related to death. Of the 367 patients, 231 (62.9%) were men, and the median age of all patients was 61 years old (range, 52–71 years), with 133 (36.2%) patients aged >65 years. In addition, 249 patients had hypoproteinaemia, and 169 patients were admitted to the intensive care unit (ICU) during hospitalisation. The most common fungi and bacteria associated with tumour development and Candida infection were Candida parapsilosis and Acinetobacter baumannii, respectively. We used machine learning to screen for death-related prognostic factors in patients with candidemia and bacteraemia mainly based on integrated information. The results showed that serum creatinine level, endotoxic shock, length of stay in ICU, age, leukocyte count, total parenteral nutrition, total bilirubin level, length of stay in the hospital, PCT level and lymphocyte count were identified as the main prognostic factors. These findings will greatly help clinicians treat patients with candidemia and bacteraemia.

Factors Associated with Outcome in Patients Managed for Invasive Fungal Infections at the Infectious Diseases Department of a Tertiary Care Hospital

“…Overall mortality was observed in 73% of the patients. 18 31.1% of our patients had a poor outcome, and 6(6.7%) patients had HIV. HIV was also related to poor outcomes in our study participants.…”

Invasive Candidiasis in Patients with Solid Tumors: A Single-Center Retrospective Study

“…According to the anticandida susceptibility test, candida strains isolated from 243 patients were not resistant to amphotericin B, which was consistent with another study on anticandida susceptibility of candida. 17,18 Although fluconazole is the most commonly used anticandida drug, our results show that 7.4% (18/243) of candida are resistant to fluconazole, which is the drug with the strongest resistance. This is similar to the results of a recent study on candida resistance.…”

Development and Validation of a Prognostic Model for Multi-Drug-Resistant Non-Hospital-Acquired Bloodstream Infection

“…The presented model was developed using readily available data. Unlike previous studies and prognostic models [ 12 , 13 , 14 , 20 , 21 ], all parameters reflect patient demographics (i.e., age and gender) and recent medical history data. It shares some parameters with the healthcare-associated infection definition [ 15 ] by adding information about the need of central lines and any recent invasive procedures.…”

“…Other studies evaluated prognostic factors in more selected clusters of patients: a machine-learning-based study showed that the most important predictors of death in patients with concomitant candidemia and bacteriaemia are age, serum creatinine level, leukocyte and lymphocyte counts, total bilirubin level, procalcitonin level, endotoxic shock, length of stay in the intensive care unit (ICU), length of stay in the hospital and total parental nutrition [ 13 ]; another recent Chinese cohort study indicates that ICU admission, coronary heart disease, biliary infection and the use of tigecycline are independent prognostic factors of 90-day mortality in elderly people (≥65 years old) with both typical (e.g., transplant recipient, hematological malignancy) and atypical (e.g., diabetes mellitus, liver cirrhosis, burns, postoperative) immunosuppression status, and that a decrease in body mass index is a protective factor [ 14 ].…”