Diagnostic algorithm allows for a scientifically robust and reliable retrospective diagnosis using textual evidence from mid-19th century Basel, Switzerland

Abstract

Objective

Diagnosing disease from the past using historic textual sources can be controversial as to its accuracy. To overcome these objections, an empirical approach to the historical clinical data was developed. The approach follows a standardised, objective, and systematic evaluation, satisfying the requirements of the philosophy of science.

Material

Physician-managed medical records of mid-19th century patients reported to have suffered from tuberculosis.

Method

A diagnostic algorithm, quantifying clinical data into a scoring system, was developed based on criteria recorded in the medical sources. The findings were compared to the autopsy results using the Receiver Operating Characteristics method.

Results

The generated scoring system correctly predicted the diagnosis of tuberculosis in 86% of patients in the study. 6% false negatives and 8% false positives were predicted.

Conclusions

It is possible to retrospectively diagnose in a reliable and scientifically robust manner under certain conditions. It is important to embed the clinical data into the historical context. A general rejection of retrospective diagnosis is unsubstantiated. Well-designed, disease-specific, and source adapted medical scoring systems are new approaches and overcome criticism raised against retrospective diagnosis.

Significance

This new approach utilises diverse historic sources and potentially leads to reliable retrospective diagnosis of most common diseases of the past.

Limitations

Selection bias of the records allocated. Quality of the historic sources utilized. Restricted statistical assessment potential of historic sources.

Suggestions for further research

Development of disease- and epoch-specific medical score systems.