Lipoprotein(a), venous thromboembolism and COVID-19: A pilot study

Background and aims

Thrombosis is a major driver of adverse outcome and mortality in patients with Coronavirus disease 2019 (COVID-19). Hypercoagulability may be related to the cytokine storm associated with COVID-19, which is mainly driven by interleukin (IL)-6. Plasma lipoprotein(a) [Lp(a)] levels increase following IL-6 upregulation and Lp(a) has anti-fibrinolytic properties. This study investigated whether Lp(a) elevation may contribute to the pro-thrombotic state hallmarking COVID-19 patients.

Methods

Lp(a), IL-6 and C-reactive protein (CRP) levels were measured in 219 hospitalized patients with COVID-19 and analyzed with linear mixed effects model. The baseline biomarkers and increases during admission were related to venous thromboembolism (VTE) incidence and clinical outcomes in a Kaplan-Meier and logistic regression analysis.

Results

Lp(a) levels increased significantly by a mean of 16.9 mg/dl in patients with COVID-19 during the first 21 days after admission. Serial Lp(a) measurements were available in 146 patients. In the top tertile of Lp(a) increase, 56.2% of COVID-19 patients experienced a VTE event compared to 18.4% in the lowest tertile (RR 3.06, 95% CI 1.61–5.81; p < 0.001). This association remained significant after adjusting for age, sex, IL-6 and CRP increase and number of measurements. Increases in IL-6 and CRP were not associated with VTE. Increase in Lp(a) was strongly correlated with increase in IL-6 (r = 0.44, 95% CI 0.30–0.56, p < 0.001).

Conclusions

Increases in Lp(a) levels during the acute phase of COVID-19 were strongly associated with VTE incidence. The acute increase in anti-fibrinolytic Lp(a) may tilt the balance to VTE in patients hospitalized for COVID-19.

Indoleamine 2,3-dioxygenase (IDO)-1 and IDO-2 activity and severe course of COVID-19

COVID-19 is a pandemic with high morbidity and mortality. In an autopsy cohort of COVID-19 patients, we found extensive accumulation of the tryptophan degradation products 3-hydroxy anthranilic acid and quinolinic acid in lungs, heart, and brain. This was not related to the expression of the tryptophan-catabolizing indoleamine 2,3-dioxygenase (IDO)-1, but rather to that of its isoform IDO-2, which otherwise is expressed rarely. Bioavailability of tryptophan is an absolute requirement for proper cell functioning and synthesis of hormones, whereas its degradation products can cause cell death. Markers of apoptosis and severe cellular stress were associated with IDO-2 expression in large areas of lung and heart tissue, whereas affected areas in brain were more restricted. Analyses of tissue, cerebrospinal fluid, and sequential plasma samples indicate early initiation of the kynurenine/aryl-hydrocarbon receptor/IDO-2 axis as a positive feedback loop, potentially leading to severe COVID-19 pathology. This article is protected by copyright. All rights reserved.

Early warning scores to assess the probability of critical illness in patients with COVID-19

OBJECTIVE

Validated clinical risk scores are needed to identify patients with COVID-19 at risk of severe disease and to guide triage decision-making during the COVID-19 pandemic. The objective of the current study was to evaluate the performance of early warning scores (EWS) in the ED when identifying patients with COVID-19 who will require intensive care unit (ICU) admission for high-flow-oxygen usage or mechanical ventilation.

METHODS

Patients with a proven SARS-CoV-2 infection with complete resuscitate orders treated in nine hospitals between 27 February and 30 July 2020 needing hospital admission were included. Primary outcome was the performance of EWS in identifying patients needing ICU admission within 24 hours after ED presentation.

RESULTS

In total, 1501 patients were included. Median age was 71 (range 19-99) years and 60.3% were male. Of all patients, 86.9% were admitted to the general ward and 13.1% to the ICU within 24 hours after ED admission. ICU patients had lower peripheral oxygen saturation (86.7% vs 93.7, p≤0.001) and had a higher body mass index (29.2 vs 27.9 p=0.043) compared with non-ICU patients. National Early Warning Score 2 (NEWS2) ≥ 6 and q-COVID Score were superior to all other studied clinical risk scores in predicting ICU admission with a fair area under the receiver operating characteristics curve of 0.740 (95% CI 0.696 to 0.783) and 0.760 (95% CI 0.712 to 0.800), respectively. NEWS2 ≥6 and q-COVID Score ≥3 discriminated patients admitted to the ICU with a sensitivity of 78.1% and 75.9%, and specificity of 56.3% and 61.8%, respectively.

CONCLUSION

In this multicentre study, the best performing models to predict ICU admittance were the NEWS2 and the Quick COVID-19 Severity Index Score, with fair diagnostic performance. However, due to the moderate performance, these models cannot be clinically used to adequately predict the need for ICU admission within 24 hours in patients with SARS-CoV-2 infection presenting at the ED.

Multicenter Validation of Individual Preoperative Motor Outcome Prediction for Deep Brain Stimulation in Parkinson's Disease

BACKGROUND

Subthalamic nucleus deep brain stimulation (STN DBS) is an established therapy for Parkinson's disease (PD) patients suffering from motor response fluctuations despite optimal medical treatment, or severe dopaminergic side effects. Despite careful clinical selection and surgical procedures, some patients do not benefit from STN DBS. Preoperative prediction models are suggested to better predict individual motor response after STN DBS. We validate a preregistered model, DBS-PREDICT, in an external multicenter validation cohort.

METHODS

DBS-PREDICT considered eleven, solely preoperative, clinical characteristics and applied a logistic regression to differentiate between weak and strong motor responders. Weak motor response was defined as no clinically relevant improvement on the Unified Parkinson's Disease Rating Scale (UPDRS) II, III, or IV, 1 year after surgery, defined as, respectively, 3, 5, and 3 points or more. Lower UPDRS III and IV scores and higher age at disease onset contributed most to weak response predictions. Individual predictions were compared with actual clinical outcomes.

RESULTS

322 PD patients treated with STN DBS from 6 different centers were included. DBS-PREDICT differentiated between weak and strong motor responders with an area under the receiver operator curve of 0.76 and an accuracy up to 77%.

CONCLUSION

Proving generalizability and feasibility of preoperative STN DBS outcome prediction in an external multicenter cohort is an important step in creating clinical impact in DBS with data-driven tools. Future prospective studies are required to overcome several inherent practical and statistical limitations of including clinical decision support systems in DBS care.

Isolated proximal weakness of the legs due to neuroborreliosis

Proximal muscle weakness of the legs is a symptom with a broad differential diagnosis. It is mainly caused by neuromuscular disorders and is often a diagnostic challenge. Here, we present a 73-year-old man with isolated proximal weakness of the legs due to lumbar root involvement on the basis of neuroborreliosis. After treatment with intravenous antibiotics he recovered completely. This is the first described case with isolated proximal muscle weakness of the legs due to neuroborreliosis. Despite the fact neuroborreliosis is a rare cause of proximal muscle weakness of the legs, clinicians should include it in their differential diagnosis, especially since it is a treatable condition.

Evaluating and Optimizing Dentato-Rubro-Thalamic-Tract Deterministic Tractography in Deep Brain Stimulation for Essential Tremor

BACKGROUND

Dentato-rubro-thalamic tract (DRT) deep brain stimulation (DBS) suppresses tremor in essential tremor (ET) patients. However, DRT depiction through tractography can vary depending on the included brain regions. Moreover, it is unclear which section of the DRT is optimal for DBS.

OBJECTIVE

To evaluate deterministic DRT tractography and tremor control in DBS for ET.

METHODS

After DBS surgery, DRT tractography was conducted in 37 trajectories (20 ET patients). Per trajectory, 5 different DRT depictions with various regions of interest (ROI) were constructed. Comparison resulted in a DRT depiction with highest correspondence to intraoperative tremor control. This DRT depiction was subsequently used for evaluation of short-term postoperative adverse and beneficial effects.

RESULTS

Postoperative optimized DRT tractography employing the ROI motor cortex, posterior subthalamic area (PSA), and ipsilateral superior cerebellar peduncle and dentate nucleus best corresponded with intraoperative trajectories (92%) and active DBS contacts (93%) showing optimal tremor control. DRT tractography employing a red nucleus or ventral intermediate nucleus of the thalamus (VIM) ROI often resulted in a more medial course. Optimal stimulation was located in the section between VIM and PSA.

CONCLUSION

This optimized deterministic DRT tractography strongly correlates with optimal tremor control. This technique is readily implementable for prospective evaluation in DBS target planning for ET.

General Anesthesia vs Local Anesthesia in Microelectrode Recording-Guided Deep-Brain Stimulation for Parkinson Disease: The GALAXY Randomized Clinical Trial

Importance

It is unknown if there is a difference in outcome in asleep vs awake deep brain stimulation (DBS) of the subthalamic nucleus for advanced Parkinson disease.

Objective

To determine the difference in adverse effects concerning cognition, mood, and behavior between awake and asleep DBS favoring the asleep arm of the study.

Design, Setting, and Participants

This study was a single-center prospective randomized open-label blinded end point clinical trial. A total of 187 persons with Parkinson disease were referred for DBS between May 2015 to March 2019. Analysis took place from January 2016 to January 2020. The primary outcome follow-up visit was conducted 6 months after DBS.

Interventions

Bilateral subthalamic nucleus DBS was performed while the patient was asleep (under general anesthesia) in 1 study arm and awake in the other study arm. Both arms of the study used a frame-based intraoperative microelectrode recording technique to refine final target placement of the DBS lead.

Main Outcomes and Measures

The primary outcome variable was the between-group difference in cognitive, mood, and behavioral adverse effects as measured by a composite score. The secondary outcomes included the Movement Disorders Society Unified Parkinson's Disease Rating Scale, the patient assessment of surgical burden and operative time.

Results

A total of 110 patients were randomized to awake (local anesthesia; n = 56; mean [SD] age, 60.0 (7.4) years; 40 [71%] male) or to asleep (general anesthesia; n = 54; mean [SD] age, 61.3 [7.9] years; 38 [70%] male) DBS surgery. The 6-month follow-up visit was completed by 103 participants. The proportion of patients with adverse cognitive, mood, and behavioral effects on the composite score was 15 of 52 (29%) after awake and 11 of 51 (22%) after asleep DBS (odds ratio, 0.7 [95% CI, 0.3-1.7]). There was no difference in improvement in the off-medication Movement Disorders Society Unified Parkinson's Disease Rating Scale Motor Examination scores between groups (awake group: mean [SD], -27.3 [17.5] points; asleep group: mean [SD], -25.3 [14.3] points; mean difference, -2.0 [95% CI, -8.1 to 4.2]). Asleep surgery was experienced as less burdensome by patients and was 26 minutes shorter than awake surgery.

Conclusions and Relevance

There was no difference in the primary outcome of asleep vs awake DBS. Future large randomized clinical trials should examine some of the newer asleep based DBS technologies because this study was limited to frame-based microelectrode-guided procedures.

Trial Registration

trialregister.nl Identifier: NTR5809.

The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients

BACKGROUND

The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients.

METHODS

A nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract-transform-load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers.

RESULTS

Out of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive.

CONCLUSIONS

In this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine.

Embedded adaptive deep brain stimulation for cervical dystonia controlled by motor cortex theta oscillations

Dystonia is a disabling movement disorder characterized by excessive muscle contraction for which the underlying pathophysiology is incompletely understood and treatment interventions limited in efficacy. Here we utilize a novel, sensing-enabled, deep brain stimulator device, implanted in a patient with cervical dystonia, to record local field potentials from chronically implanted electrodes in the sensorimotor cortex and subthalamic nuclei bilaterally. This rechargeable device was able to record large volumes of neural data at home, in the naturalistic environment, during unconstrained activity. We confirmed the presence of theta (3-7 Hz) oscillatory activity, which was coherent throughout the cortico-subthalamic circuit and specifically suppressed by high-frequency stimulation. Stimulation also reduced the duration, rate and height of theta bursts. These findings motivated a proof-of-principle trial of a new form of adaptive deep brain stimulation - triggered by theta-burst activity recorded from the motor cortex. This facilitated increased peak stimulation amplitudes without induction of dyskinesias and demonstrated improved blinded clinical ratings compared to continuous DBS, despite reduced total electrical energy delivered. These results further strengthen the pathophysiological role of low frequency (theta) oscillations in dystonia and demonstrate the potential for novel adaptive stimulation strategies linked to cortico-basal theta bursts.

Predicting mortality of individual patients with COVID-19: a multicentre Dutch cohort

OBJECTIVE

Develop and validate models that predict mortality of patients diagnosed with COVID-19 admitted to the hospital.

DESIGN

Retrospective cohort study.

SETTING

A multicentre cohort across 10 Dutch hospitals including patients from 27 February to 8 June 2020.

PARTICIPANTS

SARS-CoV-2 positive patients (age ≥18) admitted to the hospital.

MAIN OUTCOME MEASURES

21-day all-cause mortality evaluated by the area under the receiver operator curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value. The predictive value of age was explored by comparison with age-based rules used in practice and by excluding age from the analysis.

RESULTS

2273 patients were included, of whom 516 had died or discharged to palliative care within 21 days after admission. Five feature sets, including premorbid, clinical presentation and laboratory and radiology values, were derived from 80 features. Additionally, an Analysis of Variance (ANOVA)-based data-driven feature selection selected the 10 features with the highest F values: age, number of home medications, urea nitrogen, lactate dehydrogenase, albumin, oxygen saturation (%), oxygen saturation is measured on room air, oxygen saturation is measured on oxygen therapy, blood gas pH and history of chronic cardiac disease. A linear logistic regression and non-linear tree-based gradient boosting algorithm fitted the data with an AUC of 0.81 (95% CI 0.77 to 0.85) and 0.82 (0.79 to 0.85), respectively, using the 10 selected features. Both models outperformed age-based decision rules used in practice (AUC of 0.69, 0.65 to 0.74 for age >70). Furthermore, performance remained stable when excluding age as predictor (AUC of 0.78, 0.75 to 0.81).

CONCLUSION

Both models showed good performance and had better test characteristics than age-based decision rules, using 10 admission features readily available in Dutch hospitals. The models hold promise to aid decision-making during a hospital bed shortage.

Acute pancreatitis in COVID-19 patients: true risk?

BACKGROUND

A relation between coronavirus disease 2019 (COVID-19) and acute pancreatitis has been suggested. However, the incidence and clinical relevance of this relation remain unclear.

OBJECTIVE

We aimed to investigate the incidence, severity and clinical impact of acute pancreatitis in patients with COVID-19.

METHODS

This is a cross-sectional study of a prospective, observational cohort concerning all COVID-19 patients admitted to two Dutch university hospitals between 4 March 2020 and 26 May 2020. Primary outcome was acute pancreatitis potentially related to COVD-19 infection. Acute pancreatitis was defined according to the revised Atlanta Classification. Potential relation with COVID-19 was defined as the absence of a clear aetiology of acute pancreatitis.

RESULTS

Among 433 patients with COVID-19, five (1.2%) had potentially related acute pancreatitis according to the revised Atlanta Classification. These five patients suffered from severe COVID-19 infection; all had (multiple) organ failure and 60% died. None of the patients developed necrotizing pancreatitis. Moreover, development of acute pancreatitis did not lead to major treatment consequences.

CONCLUSIONS

In contrast with previous research, our study demonstrated that COVID-19 related acute pancreatitis is rare and of little clinical impact. It is therefore debatable if acute pancreatitis in COVID-19 patients requires specific screening. We hypothesize that acute pancreatitis occurs in patients with severe illness due to COVID-19 infection as a result of transient hypoperfusion and pancreatic ischemia, not as a direct result of the virus.

Can predicting COVID-19 mortality in a European cohort using only demographic and comorbidity data surpass age-based prediction: An externally validated study

OBJECTIVE

To establish whether one can build a mortality prediction model for COVID-19 patients based solely on demographics and comorbidity data that outperforms age alone. Such a model could be a precursor to implementing smart lockdowns and vaccine distribution strategies.

METHODS

The training cohort comprised 2337 COVID-19 inpatients from nine hospitals in The Netherlands. The clinical outcome was death within 21 days of being discharged. The features were derived from electronic health records collected during admission. Three feature selection methods were used: LASSO, univariate using a novel metric, and pairwise (age being half of each pair). 478 patients from Belgium were used to test the model. All modeling attempts were compared against an age-only model.

RESULTS

In the training cohort, the mortality group's median age was 77 years (interquartile range = 70-83), higher than the non-mortality group (median = 65, IQR = 55-75). The incidence of former/active smokers, male gender, hypertension, diabetes, dementia, cancer, chronic obstructive pulmonary disease, chronic cardiac disease, chronic neurological disease, and chronic kidney disease was higher in the mortality group. All stated differences were statistically significant after Bonferroni correction. LASSO selected eight features, novel univariate chose five, and pairwise chose none. No model was able to surpass an age-only model in the external validation set, where age had an AUC of 0.85 and a balanced accuracy of 0.77.

CONCLUSION

When applied to an external validation set, we found that an age-only mortality model outperformed all modeling attempts (curated on www.covid19risk.ai) using three feature selection methods on 22 demographic and comorbid features.

Cardiovascular risk factors and COVID-19 outcomes in hospitalised patients: a prospective cohort study

OBJECTIVES

Recent reports suggest a high prevalence of hypertension and diabetes in COVID-19 patients, but the role of cardiovascular disease (CVD) risk factors in the clinical course of COVID-19 is unknown. We evaluated the time-to-event relationship between hypertension, dyslipidaemia, diabetes and COVID-19 outcomes.

DESIGN

We analysed data from the prospective Dutch CovidPredict cohort, an ongoing prospective study of patients admitted for COVID-19 infection.

SETTING

Patients from eight participating hospitals, including two university hospitals from the CovidPredict cohort were included.

PARTICIPANTS

Admitted, adult patients with a positive COVID-19 PCR or high suspicion based on CT-imaging of the thorax. Patients were followed for major outcomes during the hospitalisation. CVD risk factors were established via home medication lists and divided in antihypertensives, lipid-lowering therapy and antidiabetics.

PRIMARY AND SECONDARY OUTCOMES MEASURES

The primary outcome was mortality during the first 21 days following admission, secondary outcomes consisted of intensive care unit (ICU) admission and ICU mortality. Kaplan-Meier and Cox regression analyses were used to determine the association with CVD risk factors.

RESULTS

We included 1604 patients with a mean age of 66±15 of whom 60.5% were men. Antihypertensives, lipid-lowering therapy and antidiabetics were used by 45%, 34.7% and 22.1% of patients. After 21-days of follow-up; 19.2% of the patients had died or were discharged for palliative care. Cox regression analysis after adjustment for age and sex showed that the presence of ≥2 risk factors was associated with increased mortality risk (HR 1.52, 95% CI 1.15 to 2.02), but not with ICU admission. Moreover, the use of ≥2 antidiabetics and ≥2 antihypertensives was associated with mortality independent of age and sex with HRs of, respectively, 2.09 (95% CI 1.55 to 2.80) and 1.46 (95% CI 1.11 to 1.91).

CONCLUSIONS

The accumulation of hypertension, dyslipidaemia and diabetes leads to a stepwise increased risk for short-term mortality in hospitalised COVID-19 patients independent of age and sex. Further studies investigating how these risk factors disproportionately affect COVID-19 patients are warranted.

[Clinical course of COVID-19 in the Netherlands: an overview of 2607 patients in hospital during the first wave]

OBJECTIVE

To systematically collect clinical data from patients with a proven COVID-19 infection in the Netherlands.

DESIGN

Data from 2579 patients with COVID-19 admitted to 10 Dutch centers in the period February to July 2020 are described. The clinical data are based on the WHO COVID case record form (CRF) and supplemented with patient characteristics of which recently an association disease severity has been reported.

METHODS

Survival analyses were performed as primary statistical analysis. These Kaplan-Meier curves for time to (early) death (3 weeks) have been determined for pre-morbid patient characteristics and clinical, radiological and laboratory data at hospital admission.

RESULTS

Total in-hospital mortality after 3 weeks was 22.2% (95% CI: 20.7% - 23.9%), hospital mortality within 21 days was significantly higher for elderly patients (> 70 years; 35, 0% (95% CI: 32.4% - 37.8%) and patients who died during the 21 days and were admitted to the intensive care (36.5% (95% CI: 32.1% - 41.3%)). Apart from that, in this Dutch population we also see a risk of early death in patients with co-morbidities (such as chronic neurological, nephrological and cardiac disorders and hypertension), and in patients with more home medication and / or with increased urea and creatinine levels.

CONCLUSION

Early death due to a COVID-19 infection in the Netherlands appears to be associated with demographic variables (e.g. age), comorbidity (e.g. cardiovascular disease) but also disease char-acteristics at admission.

Overweight and Obesity Are Associated With Acute Kidney Injury and Acute Respiratory Distress Syndrome, but Not With Increased Mortality in Hospitalized COVID-19 Patients: A Retrospective Cohort Study

OBJECTIVE

To evaluate the association between overweight and obesity on the clinical course and outcomes in patients hospitalized with COVID-19.

DESIGN

Retrospective, observational cohort study.

METHODS

We performed a multicenter, retrospective, observational cohort study of hospitalized COVID-19 patients to evaluate the associations between overweight and obesity on the clinical course and outcomes.

RESULTS

Out of 1634 hospitalized COVID-19 patients, 473 (28.9%) had normal weight, 669 (40.9%) were overweight, and 492 (30.1%) were obese. Patients who were overweight or had obesity were younger, and there were more women in the obese group. Normal-weight patients more often had pre-existing conditions such as malignancy, or were organ recipients. During admission, patients who were overweight or had obesity had an increased probability of acute respiratory distress syndrome [OR 1.70 (1.26-2.30) and 1.40 (1.01-1.96)], respectively and acute kidney failure [OR 2.29 (1.28-3.76) and 1.92 (1.06-3.48)], respectively. Length of hospital stay was similar between groups. The overall in-hospital mortality rate was 27.7%, and multivariate logistic regression analyses showed that overweight and obesity were not associated with increased mortality compared to normal-weight patients.

CONCLUSION

In this study, overweight and obesity were associated with acute respiratory distress syndrome and acute kidney injury, but not with in-hospital mortality nor length of hospital stay.

Outcomes of persons with coronavirus disease 2019 in hospitals with and without standard treatment with (hydroxy)chloroquine

Objective

To compare survival of individuals with coronavirus disease 2019 (COVID-19) treated in hospitals that either did or did not routinely treat patients with hydroxychloroquine or chloroquine.

Methods

We analysed data of COVID-19 patients treated in nine hospitals in the Netherlands. Inclusion dates ranged from 27 February to 15 May 2020, when the Dutch national guidelines no longer supported the use of (hydroxy)chloroquine. Seven hospitals routinely treated patients with (hydroxy)chloroquine, two hospitals did not. Primary outcome was 21-day all-cause mortality. We performed a survival analysis using log-rank test and Cox regression with adjustment for age, sex and covariates based on premorbid health, disease severity and the use of steroids for adult respiratory distress syndrome, including dexamethasone.

Results

Among 1949 individuals, 21-day mortality was 21.5% in 1596 patients treated in hospitals that routinely prescribed (hydroxy)chloroquine, and 15.0% in 353 patients treated in hospitals that did not. In the adjusted Cox regression models this difference disappeared, with an adjusted hazard ratio of 1.09 (95% CI 0.81–1.47). When stratified by treatment actually received in individual patients, the use of (hydroxy)chloroquine was associated with an increased 21-day mortality (HR 1.58; 95% CI 1.24–2.02) in the full model.

Conclusions

After adjustment for confounders, mortality was not significantly different in hospitals that routinely treated patients with (hydroxy)chloroquine compared with hospitals that did not. We compared outcomes of hospital strategies rather than outcomes of individual patients to reduce the chance of indication bias. This study adds evidence against the use of (hydroxy)chloroquine in hospitalised patients with COVID-19.

Optimal Parameters of Deep Brain Stimulation in Essential Tremor: A Meta-Analysis and Novel Programming Strategy

The programming of deep brain stimulation (DBS) parameters for tremor is laborious and empirical. Despite extensive efforts, the end-result is often suboptimal. One reason for this is the poorly understood relationship between the stimulation parameters’ voltage, pulse width, and frequency. In this study, we aim to improve DBS programming for essential tremor (ET) by exploring a new strategy. At first, the role of the individual DBS parameters in tremor control was characterized using a meta-analysis documenting all the available parameters and tremor outcomes. In our novel programming strategy, we applied 10 random combinations of stimulation parameters in eight ET-DBS patients with suboptimal tremor control. Tremor severity was assessed using accelerometers and immediate and sustained patient-reported outcomes (PRO’s), including the occurrence of side-effects. The meta-analysis showed no substantial relationship between individual DBS parameters and tremor suppression. Nevertheless, with our novel programming strategy, a significantly improved (accelerometer p = 0.02, PRO p = 0.02) and sustained (p = 0.01) tremor suppression compared to baseline was achieved. Less side-effects were encountered compared to baseline. Our pilot data show that with this novel approach, tremor control can be improved in ET patients with suboptimal tremor control on DBS. In addition, this approach proved to have a beneficial effect on stimulation-related complications.

A Clinical Applicable Smartwatch Application for Measuring Hyperkinetic Movement Disorder Severity

Measuring the severity of hyperkinetic movement disorders like tremor and myoclonus is challenging. Although many accelerometers are available to quantify movements, the vast majority lacks real-time analysis and an interface that makes it possible to real-time adjust therapy like deep brain stimulation (DBS). Here, we developed a smartwatch/smartphone application that is capable of real-time analysing movement disorder severity. Movement analysis was realised by integrating acceleration values, to velocity and subsequently to distance. Measured distances were compared with a validated accelerometer already applied for quantifying movement disorders. Further validation was done by quantitative assessment of simulated movement disorders in 10 healthy volunteers. Finally, the approach was tested in two patients treated with DBS to quantify the effect of different DBS settings on myoclonus and tremor severity, respectively. The distance measured with the application had a 96% accuracy. This was non-inferior (p = 0.76) compared to accelerometers already clinically applied. Furthermore, (simulated) movement disorder severity could be classified correctly in 93% of the cases. Finally, the method was capable of distinguishing effective from non-effective DBS parameters in two patients. In summary, with our approach we realised an instantaneous and reliable estimation of the severity of movement disorders which can assist in real time titrating therapy like DBS.

Toward adaptive deep brain stimulation for dystonia

The presence of abnormal neural oscillations within the cortico-basal ganglia-thalamo-cortical (CBGTC) network has emerged as one of the current principal theories to explain the pathophysiology of movement disorders. In theory, these oscillations can be used as biomarkers and thereby serve as a feedback signal to control the delivery of deep brain stimulation (DBS). This new form of DBS, dependent on different characteristics of pathological oscillations, is called adaptive DBS (aDBS), and it has already been applied in patients with Parkinson's disease. In this review, the authors summarize the scientific research to date on pathological oscillations in dystonia and address potential biomarkers that might be used as a feedback signal for controlling aDBS in patients with dystonia.