Patients' Perspectives and Feasibility of Home Monitoring in Acute Care: The AcuteCare@Home Flash Mob Study.

Objective: To determine patients' perspectives on home monitoring at emergency department (ED) presentation and shortly after admission and compare these with their physicians' perspectives. Methods: Forty Dutch hospitals participated in this prospective flash mob study. Adult patients with acute medical conditions, treated by internal medicine specialties, presenting at the ED or admitted at the admission ward within the previous 24 h were included. The primary outcome was the proportion of patients who were able and willing to undergo home monitoring. Secondary outcomes included identifying barriers to home monitoring, patient's prerequisites, and assessing the agreement between the perspectives of patients and treating physicians. Results: On February 2, 2023, in total 665 patients [median age 69 (interquartile range: 55-78) years; 95.5% community dwelling; 29.3% Modified Early Warning Score ≥3; 29.5% clinical frailty score ≥5] were included. In total, 19.6% of ED patients were admitted and 26% of ward patients preferred home monitoring as continuation of care. Guaranteed readmission (87.8%), ability to contact the hospital 24/7 (77.3%), and a family caregiver at home (55.7%) were the most often reported prerequisites. Barriers for home monitoring were feeling too severely ill (78.8%) and inability to receive the required treatment at home (64.4%). The agreement between patients and physicians was fair (Cohens kappa coefficient 0.26). Conclusions: A substantial proportion of acutely ill patients stated that they were willing and able to be monitored at home. Guaranteed readmission, availability of a treatment team (24/7), and a home support system are needed for successful implementation of home monitoring in acute care.

Designing a Virtual Hospital-at-Home Intervention for Patients with Infectious Diseases: A Data-Driven Approach.

BACKGROUND: Virtual hospital-at-home care might be an alternative to standard hospital care for patients with infectious diseases. In this study, we explore the potential for virtual hospital-at-home care and a potential design for this population. METHODS: This was a retrospective cohort study of internal medicine patients suspected of infectious diseases, admitted between 1 January and 31 December 2019. We collected information on delivered care during emergency department visits, the first 24 h, between 24 and 72 h, and after 72 h of admission. Care components that could be delivered at home were combined into care packages, and the potential number of eligible patients per package was described. The most feasible package was described in detail. RESULTS: 763 patients were included, mostly referred for general internal medicine (35%), and the most common diagnosis was lower respiratory tract infection (27%). The most frequently administered care components were laboratory tests, non-oral medication, and intercollegiate consultation. With a combination of telemonitoring, video consultation, non-oral medication administration, laboratory tests, oxygen therapy, and radiological diagnostics, 48% of patients were eligible for hospital-at-home care, with 35% already eligible directly after emergency department visits. CONCLUSION: While the potential for virtual hospital-at-home care is high, it depends greatly on which care can be arranged.

Point-of-care neutrophil and monocyte surface markers differentiate bacterial from viral infections at the emergency department within 30†min.

Rapid discrimination between viral and bacterial infections in a point-of-care setting will improve clinical outcome. Expression of CD64 on neutrophils (neuCD64) increases during bacterial infections, whereas expression of CD169 on classical monocytes (cmCD169) increases during viral infections. The diagnostic value of automated point-of-care neuCD64 and cmCD169 analysis was assessed for detecting bacterial and viral infections at the emergency department. Additionally, their value as input for machine learning models was studied. A prospective observational cohort study in patients suspected of infection was performed at an emergency department. A fully automated point-of-care flow cytometer measured neuCD64, cmCD169, and additional leukocyte surface markers. Flow cytometry data were gated using the FlowSOM algorithm. Bacterial and viral infections were assessed in standardized clinical care. The sole and combined diagnostic value of the markers was investigated. Clustering based on unsupervised machine learning identified unique patient clusters. Eighty-six patients were included. Thirty-five had a bacterial infection, 30 had a viral infection, and 21 had no infection. neuCD64 was increased in bacterial infections (P < 0.001), with an area under the receiver operating characteristic curve (AUROC) of 0.73. cmCD169 was higher in virally infected patients (P < 0.001; AUROC 0.79). Multivariate analyses incorporating additional markers increased the AUROC for bacterial and viral infections to 0.86 and 0.93, respectively. The additional clustering identified 4 distinctive patient clusters based on infection type and outcome. Automated neuCD64 and cmCD169 determination can discriminate between bacterial and viral infections. These markers can be determined within 30 min, allowing fast infection diagnostics in the acute clinical setting.

Home-based management of hypoxaemic COVID-19 patients: design of the Therapy@Home pilot study.

INTRODUCTION: During the COVID-19 pandemic, hospital capacity was strained. Home-based care could relieve the hospital care system and improve patient well-being if safely organised.We designed an intervention embedded in a regional collaborative healthcare network for the home-based management of acutely ill COVID-19 patients requiring oxygen treatment. Here, we describe the design and pilot protocol for the evaluation of the feasibility of this complex intervention. METHODS AND ANALYSIS: Following a participatory action research approach, the intervention was designed in four consecutive steps: (1) literature review and establishment of an expert panel; (2) concept design of essential intervention building blocks (acute medical care, acute nursing care, remote monitoring, equipment and technology, organisation and logistics); (3) safety assessments (prospective risk analysis and a simulation patient evaluation) and (4) description of the design of the pilot (feasibility) study aimed at including approximately 15-30 patients, sufficient for fine-tuning for a large-scale randomised intervention. ETHICS AND DISSEMINATION: All patients will provide written, informed consent. The study was approved by the Medical Ethics Review Committee of the University Medical Center Utrecht, the Netherlands (protocol NL77421.041.21). The preparatory steps (1-4) needed to perform the pilot are executed and described in this paper. The findings of the pilot will be published in academic journals. If we consider the complex intervention feasible, we aim to continue with a large-scale randomised controlled study evaluating the clinical effectiveness, safety and implementation of the complex intervention.

Performance of the 4-Level Pulmonary Embolism Clinical Probability Score (4PEPS) in the diagnostic management of pulmonary embolism: An external validation study.

BACKGROUND: The recently published 4-level Pulmonary Embolism Clinical Probability Score (4PEPS) integrates different aspects from currently available diagnostic strategies to further reduce imaging testing in patients with clinically suspected pulmonary embolism (PE). AIM: To externally validate the performance of 4PEPS in an independent cohort. METHODS: In this post-hoc analysis of the prospective diagnostic management YEARS study, the primary outcome measures were discrimination, calibration, efficiency (proportion of imaging tests potentially avoided), and failure rate (venous thromboembolism (VTE) diagnosis at baseline or follow-up in patients with a negative 4PEPS algorithm). Multiple imputation was used for missing 4PEPS items. Based on 4PEPS, PE was considered ruled out in patients with a very low clinical pre-test probability (CPTP) without D-dimer testing, in patients with a low CPTP and D-dimer <1000 µg/L, and in patients with a moderate CPP and D-dimer below the age-adjusted threshold. RESULTS: Of the 3465 patients, 474 (14 %) were diagnosed with VTE at baseline or during 3-month follow-up. Discriminatory performance of the 4PEPS items was good (area under ROC-curve, 0.82; 95%CI, 0.80-0.84) as was calibration. Based on 4PEPS, PE could be considered ruled out without imaging in 58 % (95%CI 57-60) of patients (efficiency), for an overall failure rate of 1.3 % (95%CI 0.86-1.9). CONCLUSION: In this retrospective external validation, 4PEPS appeared to safely rule out PE with a high efficiency. Nevertheless, although not exceeding the failure rate margin by ISTH standards, the observed failure rate in our analysis appeared to be higher than in the original 4PEPS derivation and validation study. This highlights the importance of a prospective outcome study.

Design, validation and implementation of an automated e-alert for acute kidney injury: 6-month pilot study shows increased awareness.

BACKGROUND: Acute kidney injury (AKI) is defined as a sudden episode of kidney failure but is known to be under-recognized by healthcare professionals. The Kidney Disease Improving Global Outcome (KDIGO) guidelines have formulated criteria to facilitate AKI diagnosis by comparing changes in plasma creatinine measurements (PCr). To improve AKI awareness, we implemented these criteria as an electronic alert (e-alert), in our electronic health record (EHR) system. METHODS: For every new PCr measurement measured in the University Medical Center Utrecht that triggered the e-alert, we provided the physician with actionable insights in the form of a memo, to improve or stabilize kidney function. Since e-alerts qualify for software as a medical device (SaMD), we designed, implemented and validated the e-alert according to the European Union In Vitro Diagnostic Regulation (IVDR). RESULTS: We evaluated the impact of the e-alert using pilot data six months before and after implementation. 2,053 e-alerts of 866 patients were triggered in the before implementation, and 1,970 e-alerts of 853 patients were triggered after implementation. We found improvements in AKI awareness as measured by (1) 2 days PCr follow up (56.6-65.8%, p-value: 0.003), and (2) stop of nephrotoxic medication within 7 days of the e-alert (59.2-63.2%, p-value: 0.002). CONCLUSION: Here, we describe the design and implementation of the e-alert in line with the IVDR, leveraging a multi-disciplinary team consisting of physicians, clinical chemists, data managers and data scientists, and share our firsts results that indicate an improved awareness among treating physicians.

Interpretation of continuously measured vital signs data of COVID-19 patients by nurses and physicians at the general ward: A mixed methods study.

BACKGROUND: Continuous monitoring of vital signs is introduced at general hospital wards to detect patient deterioration. Interpretation and response currently rely on experience and expert opinion. This study aims to determine whether consensus exist among hospital professionals regarding the interpretation of vital signs of COVID-19 patients. In addition, we assessed the ability to recognise respiratory insufficiency and evaluated the interpretation process. METHODS: We performed a mixed methods study including 24 hospital professionals (6 nurses, 6 junior physicians, 6 internal medicine specialists, 6 ICU nurses). Each participant was presented with 20 cases of COVID-19 patients, including 4 or 8 hours of continuously measured vital signs data. Participants estimated the patient's situation ('improving', 'stable', or 'deteriorating') and the possibility of developing respiratory insufficiency. Subsequently, a semi-structured interview was held focussing on the interpretation process. Consensus was assessed using Krippendorff's alpha. For the estimation of respiratory insufficiency, we calculated the mean positive/negative predictive value. Interviews were analysed using inductive thematic analysis. RESULTS: We found no consensus regarding the patient's situation (α 0.41, 95%CI 0.29-0.52). The mean positive predictive value for respiratory insufficiency was high (0.91, 95%CI 0.86-0.97), but the negative predictive value was 0.66 (95%CI 0.44-0.88). In the interviews, two themes regarding the interpretation process emerged. "Interpretation of deviations" included the strategies participants use to determine stability, focused on finding deviations in data. "Inability to see the patient" entailed the need of hospital professionals to perform a patient evaluation when estimating a patient's situation. CONCLUSION: The interpretation of continuously measured vital signs by hospital professionals, and recognition of respiratory insufficiency using these data, is variable, which might be the result of different interpretation strategies, uncertainty regarding deviations, and not being able to see the patient. Protocols and training could help to uniform interpretation, but decision support systems might be necessary to find signs of deterioration that might otherwise go unnoticed.

Migration background and COVID-19 related intensive care unit admission and mortality in the Netherlands: A cohort study.

BACKGROUND: Since the beginning of the SARS-CoV-2 pandemic, studies have been reporting inconsistently on migration background as a risk factor for COVID-19 outcomes. The aim of this study was to evaluate the association between migration background and clinical outcomes with COVID-19 in the Netherlands. METHODS: This cohort study included 2,229 adult COVID-19 patients admitted in two Dutch hospitals between February 27, 2020 and March 31, 2021. Odds ratios (ORs) for hospital admission, intensive care unit (ICU) admission and mortality with 95% confidence intervals (CIs) were calculated for non-Western (Moroccan, Turkish, Surinamese or other) persons as compared with Western persons in the general population of the province of Utrecht (the Netherlands) as source population. Furthermore, among hospitalized patients, Hazard ratios (HRs) with 95% CIs for in-hospital mortality and intensive care unit (ICU) admission were calculated using Cox proportional hazard analyses. Hazard ratios were adjusted for age, sex, body mass index, hypertension, Charlson Comorbidity Index, chronic corticosteroid use before admission, income, education and population density to investigate explanatory variables. RESULTS: Of the 2,229 subjects, 1,707 were of Western origin and 522 were of non-Western origin. There were 313 in-hospital deaths and 503 ICU admissions. As compared with persons with a Western origin in the general population of the province of Utrecht, the ORs for non-Western persons was 1.8 (95% CI 1.7-2.0) for hospitalization, 2.1 (95% CI 1.7-2.5) for ICU admission and 1.3 (95% CI 1.0-1.7) for mortality. Among hospitalized patients, HR for ICU admission was 1.1 (95% CI 0.9-1.4) and 0.9 (95% CI 0.7-1.3) for mortality for non-Western hospitalized persons as compared with hospitalized patients of Western origin after adjustment. CONCLUSION: Non-Western persons, including Moroccan, Turkish and Surinamese subjects, had increased risks of hospital admission, ICU admission and COVID-19 related death on a population level. Among hospitalized COVID-19 patients, no association was found between migration background and ICU admission or mortality.

Home monitoring by pulse oximetry of primary care patients with COVID-19: a pilot randomised controlled trial.

BACKGROUND: Pulse oximetry as a home or remote monitoring tool accelerated during the pandemic for patients with COVID-19, but evidence on its use is lacking. AIM: To assess the feasibility of home monitoring by pulse oximetry of patients aged ≥40 years with cardiovascular comorbidity and moderate-to-severe COVID-19. DESIGN AND SETTING: A primary care-based, open, pilot randomised controlled trial, with nested process evaluation, was undertaken in the Netherlands. METHOD: From November 2020 to June 2021, eligible patients presenting to one of 14 participating Dutch general practices were randomly allocated to regular measurement of peripheral oxygen saturation (at least three SpO2 measurements per day for 14 days) with a validated pulse oximeter or usual care. RESULTS: All 41 participants (21 intervention, 20 usual care) completed the 45-day follow-up period. Overall, the intervention group performed 97.6% of protocolised measurements; the median daily measurement per participant was 2.7 (interquartile range 1-4). Hypoxemia (SpO2 <94%) was reported in 10 participants (in 52 measurements); of those, six consulted the GP as instructed. Participants reported a high feeling of safety (0-100 visual analogue scale): 71.8 for the intervention group versus 59.8 for the control (P = 0.09). Primary care consultations were similar across groups: 50 for the intervention versus 51 for the control. Eleven visits by 10 participants were made to the emergency department (eight from the intervention group versus three from usual care), of which six participants were hospitalised (five intervention versus one usual care). No participants were admitted to the intensive care unit or died during follow-up. CONCLUSION: Home monitoring of patients with moderate-to-severe COVID-19 by pulse oximetry appeared feasible; adherence was high, patients reported a high feeling of safety, while the number of primary care consultations remained similar to usual care.

Recurrent venous thromboembolism and bleeding with extended anticoagulation: the VTE-PREDICT risk score.

AIMS: Deciding to stop or continue anticoagulation for venous thromboembolism (VTE) after initial treatment is challenging, as individual risks of recurrence and bleeding are heterogeneous. The present study aimed to develop and externally validate models for predicting 5-year risks of recurrence and bleeding in patients with VTE without cancer who completed at least 3 months of initial treatment, which can be used to estimate individual absolute benefits and harms of extended anticoagulation. METHODS AND RESULTS: Competing risk-adjusted models were derived to predict recurrent VTE and clinically relevant bleeding (non-major and major) using 14 readily available patient characteristics. The models were derived from combined individual patient data from the Bleeding Risk Study, Hokusai-VTE, PREFER-VTE, RE-MEDY, and RE-SONATE (n = 15,141, 220 recurrences, 189 bleeding events). External validity was assessed in the Danish VTE cohort, EINSTEIN-CHOICE, GARFIELD-VTE, MEGA, and Tromsø studies (n = 59 257, 2283 recurrences, 3335 bleeding events). Absolute treatment effects were estimated by combining the models with hazard ratios from trials and meta-analyses. External validation in different settings showed agreement between predicted and observed risks up to 5 years, with C-statistics ranging from 0.48-0.71 (recurrence) and 0.61-0.68 (bleeding). In the Danish VTE cohort, 5-year risks ranged from 4% to 19% for recurrent VTE and 1% -19% for bleeding. CONCLUSION: The VTE-PREDICT risk score can be applied to estimate the effect of extended anticoagulant treatment for individual patients with VTE and to support shared decision-making.

Redefining clinical venous thromboembolism phenotypes: a novel approach using latent class analysis.

BACKGROUND: Patients with venous thromboembolism (VTE) are commonly classified by the presence or absence of provoking factors at the time of VTE to guide treatment decisions. This approach may not capture the heterogeneity of the disease and its prognosis. OBJECTIVES: To evaluate clinically important novel phenotypic clusters among patients with VTE without cancer and to explore their association with anticoagulant treatment and clinical outcomes. METHODS: Latent class analysis was performed with 18 baseline clinical variables in 3062 adult patients with VTE without active cancer participating in PREFER in VTE, a noninterventional disease registry. The derived latent classes were externally validated in a post hoc analysis of Hokusai-VTE (n = 6593), a randomized trial comparing edoxaban with warfarin. The associations between cluster membership and anticoagulant treatment, recurrent VTE, bleeding, and mortality after initial treatment were studied. RESULTS: The following 5 clusters were identified: young men cluster (n = 1126, 37%), young women cluster (n = 215, 7%), older people cluster (n = 1106, 36%), comorbidity cluster (n = 447, 15%), and history of venous thromboembolism cluster (n = 168, 5%). Patient characteristics varied by age, sex, medical history, and treatment patterns. Consistent clusters were evident on external validation. In Cox proportional hazard models, recurrence risk was lower in the young women cluster (hazard ratio [HR], 0.27; 95% CI, 0.12-0.61) compared with the comorbidity cluster, after adjusting for extended anticoagulation. The risk of bleeding was lower in young men, young women, and older people clusters (HR, 0.50; 95% CI, 0.38-0.66; HR, 0.23; 95% CI, 0.11-0.46; and HR, 0.55; 95% CI 0.41-0.73, respectively). CONCLUSION: The heterogeneity of VTE cases extends beyond the distinction between provoked and unprovoked VTE.

A machine learning approach using endpoint adjudication committee labels for the identification of sepsis predictors at the emergency department.

Accurate sepsis diagnosis is paramount for treatment decisions, especially at the emergency department (ED). To improve diagnosis, clinical decision support (CDS) tools are being developed with machine learning (ML) algorithms, using a wide range of variable groups. ML models can find patterns in Electronic Health Record (EHR) data that are unseen by the human eye. A prerequisite for a good model is the use of high-quality labels. Sepsis gold-standard labels are hard to define due to a lack of reliable diagnostic tools for sepsis at the ED. Therefore, standard clinical tools, such as clinical prediction scores (e.g. modified early warning score and quick sequential organ failure assessment), and claims-based methods (e.g. ICD-10) are used to generate suboptimal labels. As a consequence, models trained with these "silver" labels result in ill-trained models. In this study, we trained ML models for sepsis diagnosis at the ED with labels of 375 ED visits assigned by an endpoint adjudication committee (EAC) that consisted of 18 independent experts. Our objective was to evaluate which routinely measured variables show diagnostic value for sepsis. We performed univariate testing and trained multiple ML models with 95 routinely measured variables of three variable groups; demographic and vital, laboratory and advanced haematological variables. Apart from known diagnostic variables, we identified added diagnostic value for less conventional variables such as eosinophil count and platelet distribution width. In this explorative study, we show that the use of an EAC together with ML can identify new targets for future sepsis diagnosis research.

The effect of physician training and patient education on the discussion of care decisions at the internal medicine outpatient clinic.

BACKGROUND: Care decision discussions are intended to align treatment with the patient's wishes, goals and values. To overcome the numerous barriers to such discussions, physicians as well as patients need tailored support. We evaluate the effect of a physicians' training and a conversation aid for patients about care decisions on patient and physician outcomes. METHODS: At the internal medicine outpatient clinic of the University Medical Centre Utrecht, a 1:1 randomized, parallel-group study (patient conversation aid) was combined with a pre-post intervention (physicians' training) design. Primary outcome was patient satisfaction, secondary outcomes were patient-doctor relationship, shared-decision-making, doctor preparedness and patient appreciation of the conversation aid. RESULTS: Between October 2018 and February 2020 11 physicians (36% residents, 73% female) and 185 patients (median age 58 years (interquartile range (IQR) 50-68), 60% male) participated. Only 28% of the patients reported a care decision discussion during the consultation. We found no effect of the interventions on patient satisfaction (effect sizes -0.14 (95% confidence interval (CI) -0.56-0.27) for conversation aid; 0.04 (95% CI -0.40-0.48) for physician's training), nor on the patient-doctor relationship or shared-decision-making. However, physicians felt more prepared to discuss care decisions after training (median 3 (IQR 1-4) vs 1 (IQR 0-3), p = 0.015). Patients assessed the conversation aid informative and gave an overall mark of median 7 (IQR 7-8). CONCLUSIONS: First steps towards fruitful discussions about care decisions were made: patients considered the conversation aid informative and physicians felt better prepared to discuss care decisions after training. The low number of care decision conversations patients reported shows exactly how important it is to focus on interventions that facilitate these discussions, for both the patient and physician. Further work needs to be done to establish the best way to empower patients and physicians. TRIAL REGISTRATION: Dutch trial register, trial 6998 (NTR 7188), registered 04/05/2018, https://www.trialregister.nl/trial/6998 .

Association of Continuously Measured Vital Signs With Respiratory Insufficiency in Hospitalized COVID-19 Patients: Retrospective Cohort Study.

BACKGROUND: Continuous monitoring of vital signs has the potential to assist in the recognition of deterioration of patients admitted to the general ward. However, methods to efficiently process and use continuously measured vital sign data remain unclear. OBJECTIVE: The aim of this study was to explore methods to summarize continuously measured vital sign data and evaluate their association with respiratory insufficiency in COVID-19 patients at the general ward. METHODS: In this retrospective cohort study, we included patients admitted to a designated COVID-19 cohort ward equipped with continuous vital sign monitoring. We collected continuously measured data of respiratory rate, heart rate, and oxygen saturation. For each patient, 7 metrics to summarize vital sign data were calculated: mean, slope, variance, occurrence of a threshold breach, number of episodes, total duration, and area above/under a threshold. These summary measures were calculated over timeframes of either 4 or 8 hours, with a pause between the last data point and the endpoint (the "lead") of 4, 2, 1, or 0 hours, and with 3 predefined thresholds per vital sign. The association between each of the summary measures and the occurrence of respiratory insufficiency was calculated using logistic regression analysis. RESULTS: Of the 429 patients that were monitored, 334 were included for analysis. Of these, 66 (19.8%) patients developed respiratory insufficiency. Summarized continuously measured vital sign data in timeframes close to the endpoint showed stronger associations than data measured further in the past (ie, lead 0 vs 1, 2, or 4 hours), and summarized estimates over 4 hours of data had stronger associations than estimates taken over 8 hours of data. The mean was consistently strongly associated with respiratory insufficiency for the three vital signs: in a 4-hour timeframe without a lead, the standardized odds ratio for heart rate, respiratory rate, and oxygen saturation was 2.59 (99% CI 1.74-4.04), 5.05 (99% CI 2.87-10.03), and 3.16 (99% CI 1.78-6.26), respectively. The strength of associations of summary measures varied per vital sign, timeframe, and lead. CONCLUSIONS: The mean of a vital sign showed a relatively strong association with respiratory insufficiency for the majority of vital signs and timeframes. The type of vital sign, length of the timeframe, and length of the lead influenced the strength of associations. Highly associated summary measures and their combinations could be used in a clinical prediction score or algorithm for an automatic alarm system.

Circadian patterns of heart rate, respiratory rate and skin temperature in hospitalized COVID-19 patients.

RATIONALE: Vital signs follow circadian patterns in both healthy volunteers and critically ill patients, which seem to be influenced by disease severity in the latter. In this study we explored the existence of circadian patterns in heart rate, respiratory rate and skin temperature of hospitalized COVID-19 patients, and aimed to explore differences in circadian rhythm amplitude during patient deterioration. METHODS: We performed a retrospective study of COVID-19 patients admitted to the general ward of a tertiary hospital between April 2020 and March 2021. Patients were continuously monitored using a wireless sensor and fingertip pulse oximeter. Data was divided into three cohorts: patients who recovered, patients who developed respiratory insufficiency and patients who died. For each cohort, a population mean cosinor model was fitted to detect rhythmicity. To assess changes in amplitude, a mixed-effect cosinor model was fitted. RESULTS: A total of 429 patients were monitored. Rhythmicity was observed in heartrate for the recovery cohort (p<0.001), respiratory insufficiency cohort (p<0.001 and mortality cohort (p = 0.002). Respiratory rate showed rhythmicity in the recovery cohort (p<0.001), but not in the other cohorts (p = 0.18 and p = 0.51). Skin temperature also showed rhythmicity in the recovery cohort (p<0.001), but not in the other cohorts (p = 0.22 and p = 0.12). For respiratory insufficiency, only the amplitude of heart rate circadian pattern increased slightly the day before (1.2 (99%CI 0.16-2.2, p = 0.002)). In the mortality cohort, the amplitude of heart rate decreased (-1.5 (99%CI -2.6- -0.42, p<0.001)) and respiratory rate amplitude increased (0.72 (99%CI 0.27-1.3, p = 0.002) the days before death. CONCLUSION: A circadian rhythm is present in heart rate of COVID-19 patients admitted to the general ward. For respiratory rate and skin temperature, rhythmicity was only found in patients who recover, but not in patients developing respiratory insufficiency or death. We found no consistent changes in circadian rhythm amplitude accompanying patient deterioration.

Axial light loss of monocytes as a readily available prognostic biomarker in patients with suspected infection at the emergency department.

OBJECTIVES: To evaluate the prognostic value of the coefficient of variance of axial light loss of monocytes (cv-ALL of monocytes) for adverse clinical outcomes in patients suspected of infection in the emergency department (ED). METHODS: We performed an observational, retrospective monocenter study including all medical patients ≥18 years admitted to the ED between September 2016 and June 2019 with suspected infection. Adverse clinical outcomes included 30-day mortality and ICU/MCU admission <3 days after presentation. We determined the additional value of monocyte cv-ALL and compared to frequently used clinical prediction scores (SIRS, qSOFA, MEWS). Next, we developed a clinical model with routinely available parameters at the ED, including cv-ALL of monocytes. RESULTS: A total of 3526 of patients were included. The OR for cv-ALL of monocytes alone was 2.21 (1.98-2.47) for 30-day mortality and 2.07 (1.86-2.29) for ICU/MCU admission <3 days after ED presentation. When cv-ALL of monocytes was combined with a clinical score, the prognostic accuracy increased significantly for all tested scores (SIRS, qSOFA, MEWS). The maximum AUC for a model with routinely available parameters at the ED was 0.81 to predict 30-day mortality and 0.81 for ICU/MCU admission. CONCLUSIONS: Cv-ALL of monocytes is a readily available biomarker that is useful as prognostic marker to predict 30-day mortality. Furthermore, it can be used to improve routine prediction of adverse clinical outcomes at the ED. CLINICAL TRIAL REGISTRATION: Registered in the Dutch Trial Register (NTR) und number 6916.

Pancreatic Stone Protein as a Biomarker for Sepsis at the Emergency Department of a Large Tertiary Hospital.

Early recognition of sepsis is essential for improving outcomes and preventing complications such as organ failure, depression, and neurocognitive impairment. The emergency department (ED) plays a key role in the early identification of sepsis, but clinicians lack diagnostic tools. Potentially, biomarkers could be helpful in assisting clinicians in the ED, but no marker has yet been successfully implemented in daily practice with good clinical performance. Pancreatic stone protein (PSP) is a promising biomarker in the context of sepsis, but little is known about the diagnostic performance of PSP in the ED. We prospectively investigated the diagnostic value of PSP in such a population for patients suspected of infection. PSP was compared with currently used biomarkers, including white blood cell count (WBC) and C-reactive protein (CRP). Of the 156 patients included in this study, 74 (47.4%) were diagnosed with uncomplicated infection and 26 (16.7%) patients with sepsis, while 56 (35.9%) eventually had no infection. PSP was significantly higher for sepsis patients compared to patients with no sepsis. In multivariate regression, PSP was a significant predictor for sepsis, with an area under the curve (AUC) of 0.69. Positive and negative predictive values for this model were 100% and 84.4%, respectively. Altogether, these findings show that PSP, measured at the ED of a tertiary hospital, is associated with sepsis but lacks the diagnostic performance to be used as single marker.

Hematological Ratios Are Associated with Acute Kidney Injury and Mortality in Patients That Present with Suspected Infection at the Emergency Department.

The early recognition of acute kidney injury (AKI) is essential to improve outcomes and prevent complications such as chronic kidney disease, the need for renal-replacement therapy, and an increased length of hospital stay. Increasing evidence shows that inflammation plays an important role in the pathophysiology of AKI and mortality. Several inflammatory hematological ratios can be used to measure systemic inflammation. Therefore, the association between these ratios and outcomes (AKI and mortality) in patients suspected of having an infection at the emergency department was investigated. Data from the SPACE cohort were used. Cox regression was performed to investigate the association between seven hematological ratios and outcomes. A total of 1889 patients were included, of which 160 (8.5%) patients developed AKI and 102 (5.4%) died in <30 days. The Cox proportional-hazards model revealed that the neutrophil-to-lymphocyte ratio (NLR), segmented-neutrophil-to-monocyte ratio (SMR), and neutrophil-lymphocyte-platelet ratio (NLPR) are independently associated with AKI <30 days after emergency-department presentation. Additionally, the NLR, SMR and NLPR were associated with 30-day all-cause mortality. These findings are an important step forward for the early recognition of AKI. The use of these markers might enable emergency-department physicians to recognize and treat AKI in an early phase to potentially prevent complications.