Diagnostic Bias in the COVID-19 Pandemic: A Series of Short Cases

During the COVID-19 pandemic, healthcare systems have faced unprecedented pressures. One challenge has been to promptly recognise non-COVID-19 conditions. Cognitive bias due to the availability heuristic may cause difficulties in reaching the correct diagnosis. Confirmation bias may also affect imaging interpretation. We report three cases with an alternative final diagnosis in whom COVID-19 was initially suspected: (a) Pneumocystis jirovecii pneumonia with unrecognised HIV infection; (b) pulmonary lymphangitis carcinomatosis; and (c) ST elevation myocardial infarction causing acute pulmonary oedema. To help mitigate bias, there is no substitute for thoughtful clinical assessment and critical appraisal when evaluating new information and formulating the differential diagnosis

Diagnostic bias during the COVID-19 era: COVID-19 or renal abscess?

Introduction: The Coronavirus disease-2019 (COVID-19) has been declared as a pandemic in March 2020 by the World Health Organization (WHO). Since then, this pandemic has dramatically affected the entire world, even radically influencing the way patients are framed at triage. Symptoms and tests in most cases lead to a correct diagnosis; however, error may be around the corner. Case report: A 60 years old patient was referred with weight loss, fatigue and mild fever for 3 weeks as he was working in a COVID-19 ward. After a positive swab and chest CT scan, he was admitted in the hospital and treated as mild COVID-19 patient. A CT scan performed after the patient was discharged revealed a renal lesion misidentified as a tumor then clarified to be an abscess which retrospectively appears to be the main cause of his symptoms. Conclusion: Clinicians should consider other life-threatening disease in the differential diagnosis of patients presenting with similar symptoms to minimize mistakes and avoid further unnecessary investigations.

Relationship between aortic valve stenosis and the hemodynamic pattern in the renal circulation, and restoration of the flow wave profile after correction of the valvular defect

Objective The index of maximal systolic acceleration ([AImax]: maximal systolic acceleration of the Doppler waveform divided by peak systolic velocity) shows diagnostic accuracy in screening of renal artery stenosis. This study aimed to determine whether an upstream factor of resistance, such as aortic valve stenosis (AVS), can affect Doppler parameters detected in the peripheral arteries. Methods In this prospective study, we measured the AImax in non-stenotic renal interlobar arteries of 62 patients with AVS. Patients were divided into three groups on the basis of severity of valvulopathy as follows: mild-to-moderate AVS (M-AVS; n = 24), intermediate AVS (I-AVS; n = 15), and severe AVS (S-AVS; n = 23) based on Nishimura’s criteria. Results The AImax in the renal parenchymal arteries was significantly lower in the S-AVS group (8.9 ± 3.6 s−1) than in the M-AVS (15.3 ± 3.8 s−1) and I-AVS groups (16.7 ± 5.2 s−1). The AImax was positively correlated with the aortic valve area and inversely correlated with the tranvalvular aortic pressure gradient. After aortic valve replacement, the AImax significantly increased from 10.7 ± 4.0 s−1 at baseline to 19.3 ± 4.4 s−1. Conclusions Proximal resistance can lead to diagnostic bias of Doppler parameters that are applied in the diagnosis of peripheral vasculopathies, particularly in renal artery stenosis.

Testicular vasculitis: a diagnostic conundrum

Vasculitis is rare in the context of testicular lesions but, when found, can be classified as a single organ vasculitis or part of a multi-organ inflammatory process. In the context of a patient with a pre-existing autoimmune disorder, this finding might cause diagnostic confusion and preferentially bias a physician towards attributing the condition to the known diagnosis or its treatment. This diagnostic bias can interfere with patient care and lead to over caution, resulting in a worse outcome for the patient involved. We describe such a patient with rheumatoid arthritis on biologic therapy.

Risk of non-affective psychotic disorder or bipolar disorder in autism spectrum disorder: a longitudinal register-based study in the Netherlands

BackgroundIndividuals with autism spectrum disorder (ASD) appear to be at increased risk of non-affective psychotic disorder (NAPD) and bipolar disorder (BD). However, most previous studies examined the co-occurrence of ASD and NAPD or BD, ignoring possible diagnostic bias and selection bias. We used longitudinal data from Dutch psychiatric case registers to assess the risk of NAPD or BD among individuals with ASD, and compared the results to those obtained for the Dutch population in earlier studies.MethodsIndividuals with ASD (n = 17 234) were followed up between 16 and 35 years of age. Kaplan–Meier estimates were used to calculate the risk of NAPD or BD. We conducted separate analyses to reduce possible bias, including an analysis among individuals diagnosed with ASD before age 16 years (n = 8337).ResultsOf the individuals with ASD, 23.50% (95% confidence interval 21.87–25.22) were diagnosed with NAPD and 3.79% (3.06–4.69) with BD before age 35 years. The corresponding figures for the general population were 0.91% (0.63–1.28) and 0.13% (0.08–0.20). Risk estimates were substantially lower, but still higher than general population estimates, when we restricted our analyses to individuals diagnosed with ASD before age 16, with 1.87% (1.33–2.61) being diagnosed with NAPD and 0.57% (0.21–1.53) with BD before age 25 years. The corresponding figures for the general population were 0.63% (0.44–0.86) and 0.08% (0.05–0.12).ConclusionsIndividuals with ASD are at increased risk of NAPD or BD. This is likely not the result of diagnostic or selection bias.