Volkher Scharnhorst

Objectives: Clinical algorithms increasingly combine multiple laboratory measurands to support diagnosis, prognosis, and treatment decisions. Yet, measurement bias arising from differences in calibration, reagent lots, or analytical platforms can propagate through such algorithms in non-linear ways, shifting outputs and altering clinical classifications. Existing external quality assessment (EQA) programmes evaluate measurands individually and do not capture the cumulative effect of bias on algorithm behaviour. We present a framework that extends EQA to quantify and communicate the impact of laboratory-specific measurement bias on clinical algorithm outputs. Methods: Bias estimates derived from EQA results are injected into a representative patient cohort and propagated through the algorithm; when clinical outcomes are available, output shifts are translated into changes in clinically interpretable performance characteristics. Measurand-specific what-if analyses estimate the expected benefit of correcting individual bias. The framework is illustrated using the Fibrosis-4 (FIB-4) index and scalability is demonstrated on the ten-input CoLab COVID-19 severity score. Results: Participant-facing reports were developed that summarise deviation from a zero-bias reference, position each laboratory within the peer distribution, and identify which input measurands offer the greatest potential for performance recovery. Applied to FIB-4, the reports demonstrate how laboratories can locate themselves relative to clinically desired performance thresholds and receive actionable, measurand-specific guidance to prioritise corrective efforts. Conclusions: By translating bias-propagation analysis into interpretable laboratory reports, this framework bridges the gap between measurand-level analytical performance and clinical algorithm performance. It supports post-deployment monitoring, cross-laboratory comparability and verification, targeted quality improvement, and is applicable to any transparent formula-based clinical algorithm.

Single-molecule imaging and tracking have revealed fundamental biological mechanisms at the molecular scale, yet their application to clinical research remains limited by technical complexity and sample preparation incompatible with patient-derived specimens. As a result, we lack information with molecular-scale resolution of clinically relevant biomarkers. Here, we develop a workflow enabling Points Accumulation in Nanoscale Topography (PAINT) combined with single-particle tracking (SPT) on clinical liquid biopsies, allowing analysis of biomarker nanoscale organization at the single-molecule level in cancer patients. Our approach features a sample preparation tailored to liquid biopsies and requires no fixation, covalent labelling, or genetic modification, making single-molecule imaging compatible with hospital clinical workflows. We demonstrate the method’s diversity by imaging liquid biopsies from blood, bone marrow aspirates, and pleural effusions across different cancer types. PAINT-SPT captures both the expression and mobility of clinically relevant membrane receptor biomarkers, revealing pronounced inter- and intra-patient heterogeneity at the molecular and cellular levels. We discover that individual patients exhibit distinct molecular mobility fingerprints that reflect biomarker interaction states and correlate with clinical diagnostic readouts. Furthermore, these fingerprints distinguish healthy from cancer cells, enabling the development of a classifier that accurately identifies cancer cells based on their single-molecule behaviour. Together, our results establish a route to investigate patient-derived clinical samples at the single-molecule level and open new opportunities to understand cancer biology and biomarker function beyond ensemble-averaged measurements.

Introduction: Elevated vitamin B12 concentration can be caused by supplementation, liver disease, kidney disease, or myeloid malignancies. Persistent, unexplained elevations of vitamin B12 can raise concern among patients and may lead to invasive diagnostic procedures, including bone marrow biopsy. A potential benign cause of this elevation is macro‐B12, a complex of vitamin B12, transcobalamin, and immunoglobulins. Although not bioactive, this complex can cause elevated plasma vitamin B12 concentrations due to reduced clearance. Methods: Polyethylene glycol (PEG) precipitation is a laboratory technique that can be used to support the suspicion of macro‐B12. Here, a case is described in which a PEG precipitation could potentially have prevented an unnecessary bone marrow biopsy. In addition, the presence of macro‐B12 was studied in a group of patients with and without myeloid malignancies. Results: Macro‐B12 was identified in 24% of 72 individuals with vitamin B12 > 1476 pmol/L. In one of these patients, a functional vitamin B12 deficiency was confirmed by an elevated methylmalonic acid (MMA) concentration. Macro‐B12 was not detected in 8 patients with a myeloid malignancy. Conclusion: These findings suggest that, in patients with persistently elevated vitamin B12 concentrations and a low suspicion of a myeloid malignancy, PEG precipitation may help to explain the elevated vitamin B12 and prevent unnecessary diagnostic procedures including bone marrow punctures.

This study describes and compares the performance of several semi-parametric statistical modeling approaches to dynamically classify subjects into two groups, based on an irregularly and sparsely sampled curve. The motivating example of this study is the diagnosis of a complication following cardiac surgery, based on repeated measures of a single cardiac biomarker where early detection enables prompt intervention by clinicians. We first simulate data to compare the dynamic predictive performance over time for growth charts, conditional growth charts, a varying-coefficient model, a generalized functional linear model and longitudinal discriminant analysis. Our results demonstrate that functional regression approaches that implicitly incorporate historic information through random effects, provide superior discriminative ability compared to approaches that do not take historic information into account or explicitly model historic information through autoregressive terms. Semi-parametric modeling approaches show a benefit in terms of dynamic discriminative ability compared to the clinical practice of using a fixed threshold on the raw measured value. Under high degrees of sparsity the functional regression approaches are less advantageous compared to varying-coefficient models or quantile regression. The class imbalance of the outcome affects the historic and non-historic approaches in equal measure, with lower event rates reducing performance. Finally, the functional regression and varying-coefficient model were applied to a real-world clinical dataset to demonstrate their performance and application.

Background: Postoperative deterioration is often preceded by abnormal vital parameters. Therefore, vital parameters of postoperative patients are routinely measured by nursing staff. Wrist-worn sensors could potentially provide an alternative tool for the measurement of vital parameters in low-acuity settings. These devices would allow more frequent or even continuous measurements of vital parameters without relying on time-consuming manual measurements, provided their accuracy in this clinical population is established. Objective: This study aimed to assess the accuracy of heart rate (HR) and respiratory rate (RR) measures obtained via a wearable photoplethysmography (PPG) wristband in a cohort of postoperative patients. Methods: The accuracy of the wrist-worn PPG sensor was assessed in 62 post–abdominal surgery patients (mean age 55, SD 15 years; median BMI 34, IQR 25-40 kg/m2). The wearable obtained HR and RR measurements were compared to those of the reference monitor in the postanesthesia or intensive care unit. Bland-Altman and Clarke error grid analyses were performed to determine agreement and clinical accuracy. Results: Data were collected for a median of 1.2 hours per patient. With a coverage of 94% for HR and 34% for RR, the device was able to provide accurate measurements for the large majority of the measurements as 98% and 93% of the measurements were within 5 bpm or 3 rpm of the reference signal. Additionally, 100% of the HR and 98% of the RR measurements were clinically acceptable on Clarke error grid analysis. Conclusions: The wrist-worn PPG device is able to provide measurements of HR and RR that can be seen as sufficiently accurate for clinical applications. Considering the coverage, the device was able to continuously monitor HR and report RR when measurements of sufficient quality were obtained. Trial Registration: ClinicalTrials.gov NCT03923127; https://www.clinicaltrials.gov/ct2/show/NCT03923127

Jonna A. van der Stam, M.Sc., Sjoerd Bouwmeester, M.D., Saskia L. M. van Loon, Ph.D., Natal A. W. van Riel, Ph.D., Lukas R. Dekker, Ph.D., Arjen-Kars Boer, Ph.D., Patrick Houthuizen, Ph.D., and Volkher Scharnhorst, Ph.D.. Ann Lab Med 2023;43:253-62. https://doi.org/10.3343/alm.2023.43.3.253

BACKGROUND Postoperative deterioration is often preceded by abnormal vital parameters. Therefore, vital parameters of postoperative patients are routinely measured by nursing staff. Wrist-worn sensors could potentially provide an alternative tool for the measurement of vital parameters in low-acuity settings. These devices would allow more frequent or even continuous measurements of vital parameters without relying on time-consuming manual measurements, provided their accuracy in this clinical population is established. OBJECTIVE This study aimed to assess the accuracy of heart rate (HR) and respiratory rate (RR) measures obtained via a wearable photoplethysmography (PPG) wristband in a cohort of postoperative patients. METHODS The accuracy of the wrist-worn PPG sensor was assessed in 62 post–abdominal surgery patients (mean age 55, SD 15 years; median BMI 34, IQR 25-40 kg/m2). The wearable obtained HR and RR measurements were compared to those of the reference monitor in the postanesthesia or intensive care unit. Bland-Altman and Clarke error grid analyses were performed to determine agreement and clinical accuracy. RESULTS Data were collected for a median of 1.2 hours per patient. With a coverage of 94% for HR and 34% for RR, the device was able to provide accurate measurements for the large majority of the measurements as 98% and 93% of the measurements were within 5 bpm or 3 rpm of the reference signal. Additionally, 100% of the HR and 98% of the RR measurements were clinically acceptable on Clarke error grid analysis. CONCLUSIONS The wrist-worn PPG device is able to provide measurements of HR and RR that can be seen as sufficiently accurate for clinical applications. Considering the coverage, the device was able to continuously monitor HR and report RR when measurements of sufficient quality were obtained. CLINICALTRIAL ClinicalTrials.gov NCT03923127; https://www.clinicaltrials.gov/ct2/show/NCT03923127

Background: Measurement of heart rate (HR) through an unobtrusive, wrist-worn optical HR monitor (OHRM) could enable earlier recognition of patient deterioration in low acuity settings and enable timely intervention. Objective: The goal of this study was to assess the agreement between the HR extracted from the OHRM and the gold standard 5-lead electrocardiogram (ECG) connected to a patient monitor during surgery and in the recovery period. Methods: In patients undergoing surgery requiring anesthesia, the HR reported by the patient monitor’s ECG module was recorded and stored simultaneously with the photopletysmography (PPG) from the OHRM attached to the patient’s wrist. The agreement between the HR reported by the patient’s monitor and the HR extracted from the OHRM’s PPG signal was assessed using Bland-Altman analysis during the surgical and recovery phase. Results: A total of 271.8 hours of data in 99 patients was recorded simultaneously by the OHRM and patient monitor. The median coverage was 86% (IQR 65%-95%) and did not differ significantly between surgery and recovery (Wilcoxon paired difference test P=.17). Agreement analysis showed the limits of agreement (LoA) of the difference between the OHRM and the ECG HR were within the range of 5 beats per minute (bpm). The mean bias was –0.14 bpm (LoA between –3.08 bpm and 2.79 bpm) and –0.19% (LoA between –5 bpm to 5 bpm) for the PPG- measured HR compared to the ECG-measured HR during surgery; during recovery, it was –0.11 bpm (LoA between –2.79 bpm and 2.59 bpm) and –0.15% (LoA between –3.92% and 3.64%). Conclusions: This study shows that an OHRM equipped with a PPG sensor can measure HR within the ECG reference standard of –5 bpm to 5 bpm or –10% to 10% in the perioperative setting when the PPG signal is of sufficient quality. This implies that an OHRM can be considered clinically acceptable for HR monitoring in low acuity hospitalized patients.

BACKGROUND Measurement of heart rate (HR) through an unobtrusive, wrist-worn optical HR monitor (OHRM) could enable earlier recognition of patient deterioration in low acuity settings and enable timely intervention. OBJECTIVE The goal of this study was to assess the agreement between the HR extracted from the OHRM and the gold standard 5-lead electrocardiogram (ECG) connected to a patient monitor during surgery and in the recovery period. METHODS In patients undergoing surgery requiring anesthesia, the HR reported by the patient monitor’s ECG module was recorded and stored simultaneously with the photopletysmography (PPG) from the OHRM attached to the patient’s wrist. The agreement between the HR reported by the patient’s monitor and the HR extracted from the OHRM’s PPG signal was assessed using Bland-Altman analysis during the surgical and recovery phase. RESULTS A total of 271.8 hours of data in 99 patients was recorded simultaneously by the OHRM and patient monitor. The median coverage was 86% (IQR 65%-95%) and did not differ significantly between surgery and recovery (Wilcoxon paired difference test P=.17). Agreement analysis showed the limits of agreement (LoA) of the difference between the OHRM and the ECG HR were within the range of 5 beats per minute (bpm). The mean bias was –0.14 bpm (LoA between –3.08 bpm and 2.79 bpm) and –0.19% (LoA between –5 bpm to 5 bpm) for the PPG- measured HR compared to the ECG-measured HR during surgery; during recovery, it was –0.11 bpm (LoA between –2.79 bpm and 2.59 bpm) and –0.15% (LoA between –3.92% and 3.64%). CONCLUSIONS This study shows that an OHRM equipped with a PPG sensor can measure HR within the ECG reference standard of –5 bpm to 5 bpm or –10% to 10% in the perioperative setting when the PPG signal is of sufficient quality. This implies that an OHRM can be considered clinically acceptable for HR monitoring in low acuity hospitalized patients.