How is test laboratory data used and characterised by machine learning models? A systematic review of diagnostic and prognostic models developed for COVID-19 patients using only laboratory data

Abstract

The current gold standard for COVID-19 diagnosis, the rRT-PCR test, is hampered by long turnaround times, probable reagent shortages, high false-negative rates and high prices. As a result, machine learning (ML) methods have recently piqued interest, particularly when applied to digital imagery (X-rays and CT scans). In this review, the literature on ML-based diagnostic and prognostic studies grounded on hematochemical parameters has been considered. By doing so, a gap in the current literature was addressed concerning the application of machine learning to laboratory medicine. Sixty-eight articles have been included that were extracted from the Scopus and PubMed indexes. These studies were marked by a great deal of heterogeneity in terms of the examined laboratory test and clinical parameters, sample size, reference populations, ML algorithms, and validation approaches. The majority of research was found to be hampered by reporting and replicability issues: only four of the surveyed studies provided complete information on analytic procedures (units of measure, analyzing equipment), while 29 provided no information at all. Only 16 studies included independent external validation. In light of these findings, we discuss the importance of closer collaboration between data scientists and medical laboratory professionals in order to correctly characterise the relevant population, select the most appropriate statistical and analytical methods, ensure reproducibility, enable the proper interpretation of the results, and gain actual utility by using machine learning methods in clinical practice.

Longwise Cluster Analysis for the Prediction of COVID-19 Severity within 72 h of Admission: COVID-DATA-SAVE-LIFES Cohort

“…Indeed, the liver health and coagulation axis appears as a relevant surrogate for elucidating some COVID-19 outcomes linked to systemic inflammation [ 43 ], as well as thrombotic and fibrinolytic disturbances [ 44 ], which were deciphered in the currently emerged three clusters, including some markers of global health such as lactate dehydrogenase or creatinine/urea measurements [ 45 ], as particularly discriminated in Cluster C. Interestingly, hemoglobin and prothrombin values evidenced divergent patterns after the following 72-h period, which represent a worth for a cluster monitor. Indeed, our results provide a tool in the early management of COVID-19 patients, in contrast to other related papers in COVID where it has been taken into account with cardiac biomarkers [ 46 ] or other more complex techniques, such as imaging-based prognosis or gene/protein expression [ 47 , 48 ].…”

SARS-CoV-2 Affects Both Humans and Animals: What Is the Potential Transmission Risk? A Literature Review

“…However, although laboratory tests are simple, accessible, and low-cost, methods to evaluate SARS-CoV-2 infection, their accuracy, and specificity remain controversial [ 117 ].…”

How to diagnose COVID-19 in family practice? Usability of complete blood count as a COVID-19 diagnostic tool: a cross-sectional study in Turkey

“…8 There are also some studies developed for the usability of machine learning models in detecting COVID-19, confirming that CBC can be used diagnostically. [9][10][11] These studies express the potential of CBC as a diagnostic tool, and therefore, a comprehensive study is needed for the use of CBC parameters in the diagnosis of COVID-19 for use in family medicine.…”

“…In addition, among these studies, a study reporting that the NLR is higher in COVID-19-positive patients at the time of first admission to the hospital is noteworthy in order to demonstrate its diagnostic usability 8. There are also some studies developed for the usability of machine learning models in detecting COVID-19, confirming that CBC can be used diagnostically 9–11. These studies express the potential of CBC as a diagnostic tool, and therefore, a comprehensive study is needed for the use of CBC parameters in the diagnosis of COVID-19 for use in family medicine.…”