Predictors of clinical deterioration in patients with suspected COVID-19 managed in a 'virtual hospital' setting: a cohort study

Remote patient monitoring in patients with COVID-19 at home: literature review

BACKGROUND

During the pandemic healthcare providers implemented remote patient monitoring (RPM) for patients suffering from COVID-19. RPM is an interaction between healthcare professionals and patients who are in different locations, in which a certain number of patient's functioning parameters is assessed and followed up for a certain duration of time. By implementing RPM for these patients they obtained to reduce the strain on hospitals and primary care.

OBJECTIVE

With this literature review we aim at describing the characteristics of the RPM interventions, reporting on the patients with COVID-19 included in RPM, and providing an overview of outcome variables such as length of stay (LOS), hospital (re)admissions, and mortality.

METHODS

A combination of different searches in several database types (traditional databases, trial registers, daily (google) searches and daily Pubmed alerts) were run daily from March 2020 till December 2021. A search update for randomized clinical trials (RCT's) was done in April 2022.

RESULTS

The initial search yielded more than 4448 articles (not including daily searches). After deduplication and assessment for eligibility, 241 articles were retained describing 164 telemonitoring studies from 160 centres. None of the 164 studies covering 248,431 included patients reported on the presence of a randomized control group. Studies described a 'prehosp' group (96 studies) with patients who had a suspected or confirmed COVID-19 diagnosis and for whom it was decided not to hospitalize them yet, but closely monitor them at home, or a 'posthosp' group (32 studies) with patients who were monitored at home after hospitalization for COVID-19; 34 studies described both groups, in 2 studies it was unclear. There is a large variety in number of emergency department (ED) visits (0-36% and 0-16%) and no convincing evidence that RPM leads to less or more ED-visits as well as hospital (re)admissions (0-30% and 0-22%) in prehosp and posthosp, respectively. Mortality was generally low, and there is weak to no evidence that RPM is associated with lower mortality. There is neither evidence that RPM shortens previous LOS. A literature update detected three small scale RCT's which could not demonstrate statistically significant differences in these outcomes. Most papers claim savings, however the scientific base for these claims is doubtful. The overall patient experiences with RPM were positive, as patients felt more reassured, although many patients declined RPM for several reasons (eg, technological embarrassment, digital literacy, etc.).

CONCLUSIONS

Based on these results, there is no convincing evidence that RPM in COVID-19 patients could avoid ED-visits or hospital (re)admissions, could shorten LOS or reduce mortality, but neither is there evidence that RPM has adverse outcomes. Further research should focus on developing, implementing, and evaluating an RPM framework.

CLINICALTRIAL

COVID-19 risk, course and outcome in people with mental disorders: a systematic review and meta-analyses

AIMS

It has been suggested that people with mental disorders have an elevated risk to acquire severe acute respiratory syndrome coronavirus 2 and to be disproportionally affected by coronavirus disease 19 (COVID-19) once infected. We aimed to analyse the COVID-19 infection rate, course and outcome, including mortality and long COVID, in people with anxiety, depressive, neurodevelopmental, schizophrenia spectrum and substance use disorders relative to control subjects without these disorders.

METHODS

This study constitutes a preregistered systematic review and random-effects frequentist and Bayesian meta-analyses. Major databases were searched up until 27 June 2023.

RESULTS

Eighty-one original articles were included reporting 304 cross-sectional and prospective effect size estimates (median n per effect-size = 114837) regarding associations of interest. Infection risk was not significantly increased for any mental disorder that we investigated relative to samples of people without these disorders. The course of COVID-19, however, is relatively severe, and long COVID and COVID-19-related hospitalization are more likely in all patient samples that we investigated. The odds of dying from COVID-19 were high in people with most types of mental disorders, except for those with anxiety and neurodevelopmental disorders relative to non-patient samples (pooled ORs range, 1.26-2.57). Bayesian analyses confirmed the findings from the frequentist approach and complemented them with estimates of the strength of evidence.

CONCLUSIONS

Once infected, people with pre-existing mental disorders are at an elevated risk for a severe COVID-19 course and outcome, including long COVID and mortality, relative to people without pre-existing mental disorders, despite an infection risk not significantly increased.

Correlation of plasma N-terminal pro-brain natriuretic peptide (NT-proBNP) with radiographic features of congestion in chest CT scan of patients with COVID-19

BACKGROUND

Given the importance of chest computed tomography (CT) to differentiate congestion from COVID-19 pneumonia, and considering the association of chest CT findings with cardiac biomarkers in patients with concomitant COVID-19 and heart failure, this study was conducted to identify the correlation between plasma NT-proBNP level and radiographic features of congestion in patients with COVID-19. This retrospective cohort research was carried out on adult hospitalized patients with COVID-19 and the plasma concentration of NT-proBNP was measured. The most important findings in chest CT have been considered to differentiate COVID-19 pneumonia from congestion. The study population was divided into two groups based on the presence of these imaging characteristics.

RESULTS

Totally, 180 patients with a mean age of 59.6 ± 14.6 years were included in the research. The radiographic findings related to congestion have been found in chest CT of 107 (59.4%) patients. Mean plasma concentration of NT-proBNP in patients with and without radiographic features of congestion was 9886.5 ± 12,676 and 2079.9 ± 4209.3 pg/mL, respectively (p < 0.001). The area under the curve of plasma levels of NT-proBNP for identification of patients with COVID-19 who had pulmonary vein enlargement in chest CT was 0.765 (95% CI 0.688-0.842) and 0.731 (95% CI 0.648-0.813) for the individuals who had interlobar fissure thickening (p < 0.001).

CONCLUSIONS

The diagnostic accuracy of plasma NT-proBNP and its positive correlation with radiographic features of congestion in chest CT scan of patients with COVID-19 can be helpful for administering appropriate medications to prevent blood volume overload.

A rapid mixed-methods evaluation of remote home monitoring models during the COVID-19 pandemic in England

Background

Remote home monitoring services were developed and implemented for patients with COVID-19 during the pandemic. Patients monitored blood oxygen saturation and other readings (e.g. temperature) at home and were escalated as necessary.

Objective

To evaluate effectiveness, costs, implementation, and staff and patient experiences (including disparities and mode) of COVID-19 remote home monitoring services in England during the COVID-19 pandemic (waves 1 and 2).

Methods

A rapid mixed-methods evaluation, conducted in two phases. Phase 1 (July-August 2020) comprised a rapid systematic review, implementation and economic analysis study (in eight sites). Phase 2 (January-June 2021) comprised a large-scale, multisite, mixed-methods study of effectiveness, costs, implementation and patient/staff experience, using national data sets, surveys (28 sites) and interviews (17 sites).

Results

Phase 1 Findings from the review and empirical study indicated that these services have been implemented worldwide and vary substantially. Empirical findings highlighted that communication, appropriate information and multiple modes of monitoring facilitated implementation; barriers included unclear referral processes, workforce availability and lack of administrative support. Phase 2 We received surveys from 292 staff (39% response rate) and 1069 patients/carers (18% response rate). We conducted interviews with 58 staff, 62 patients/carers and 5 national leads. Despite national roll-out, enrolment to services was lower than expected (average enrolment across 37 clinical commissioning groups judged to have completed data was 8.7%). There was large variability in implementation of services, influenced by patient (e.g. local population needs), workforce (e.g. workload), organisational (e.g. collaboration) and resource (e.g. software) factors. We found that for every 10% increase in enrolment to the programme, mortality was reduced by 2% (95% confidence interval: 4% reduction to 1% increase), admissions increased by 3% (-1% to 7%), in-hospital mortality fell by 3% (-8% to 3%) and lengths of stay increased by 1.8% (-1.2% to 4.9%). None of these results are statistically significant. We found slightly longer hospital lengths of stay associated with virtual ward services (adjusted incidence rate ratio 1.05, 95% confidence interval 1.01 to 1.09), and no statistically significant impact on subsequent COVID-19 readmissions (adjusted odds ratio 0.95, 95% confidence interval 0.89 to 1.02). Low patient enrolment rates and incomplete data may have affected chances of detecting possible impact. The mean running cost per patient varied for different types of service and mode; and was driven by the number and grade of staff. Staff, patients and carers generally reported positive experiences of services. Services were easy to deliver but staff needed additional training. Staff knowledge/confidence, NHS resources/workload, dynamics between multidisciplinary team members and patients' engagement with the service (e.g. using the oximeter to record and submit readings) influenced delivery. Patients and carers felt services and human contact received reassured them and were easy to engage with. Engagement was conditional on patient, support, resource and service factors. Many sites designed services to suit the needs of their local population. Despite adaptations, disparities were reported across some patient groups. For example, older adults and patients from ethnic minorities reported more difficulties engaging with the service. Tech-enabled models helped to manage large patient groups but did not completely replace phone calls.

Limitations

Limitations included data completeness, inability to link data on service use to outcomes at a patient level, low survey response rates and under-representation of some patient groups.

Future work

Further research should consider the long-term impact and cost-effectiveness of these services and the appropriateness of different models for different groups of patients.

Conclusions

We were not able to find quantitative evidence that COVID-19 remote home monitoring services have been effective. However, low enrolment rates, incomplete data and varied implementation reduced our chances of detecting any impact that may have existed. While services were viewed positively by staff and patients, barriers to implementation, delivery and engagement should be considered.

Study registration

This study is registered with the ISRCTN (14962466).

Funding

This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (RSET: 16/138/17; BRACE: 16/138/31) and NHSEI and will be published in full in Health and Social Care Delivery Research; Vol. 11, No. 13. See the NIHR Journals Library website for further project information. The views expressed in this publication are those of the authors and not necessarily those of the National Institute for Health and Care Research or the Department of Health and Social Care.

Relevance of prediction scores derived from the SARS-CoV-2 first wave, in the evolving UK COVID-19 second wave, for safe early discharge and mortality: a PREDICT COVID-19 UK prospective observational cohort study

OBJECTIVE

Prospectively validate prognostication scores, SOARS and 4C Mortality Score, derived from the COVID-19 first wave, for mortality and safe early discharge in the evolving pandemic with SARS-CoV-2 variants (B.1.1.7 replacing D614) and healthcare responses altering patient demographic and mortality.

DESIGN

Protocol-based prospective observational cohort study.

SETTING

Single site PREDICT and multisite ISARIC (International Severe Acute Respiratory and Emerging Infections Consortium) cohorts in UK COVID-19 second wave, October 2020 to January 2021.

PARTICIPANTS

1383 PREDICT and 20 595 ISARIC SARS-CoV-2 patients.

PRIMARY OUTCOME MEASURES

Relevance of SOARS and 4C Mortality Score determining in-hospital mortality and safe early discharge in the evolving UK COVID-19 second wave.

RESULTS

1383 (median age 67 years, IQR 52-82; mortality 24.7%) PREDICT and 20 595 (mortality 19.4%) ISARIC patient cohorts showed SOARS had area under the curve (AUC) of 0.8 and 0.74, while 4C Mortality Score had AUC of 0.83 and 0.91 for hospital mortality, in the PREDICT and ISARIC cohorts respectively, therefore, effective in evaluating safe discharge and in-hospital mortality. 19.3% (231/1195, PREDICT cohort) and 16.7% (2550/14992, ISARIC cohort) with SOARS of 0-1 were candidates for safe discharge to a virtual hospital (VH) model. SOARS implementation in the VH pathway resulted in low readmission, 11.8% (27/229) and low mortality, 0.9% (2/229). Use to prevent admission is still suboptimal, as 8.1% in the PREDICT cohort and 9.5% in the ISARIC cohort were admitted despite SOARS score of 0-1.

CONCLUSIONS

SOARS and 4C Mortality Score remains valid, transforming complex clinical presentations into tangible numbers, aiding objective decision making, despite SARS-CoV-2 variants and healthcare responses altering patient demographic and mortality. Both scores, easily implemented within urgent care pathways for safe early discharge, allocate hospital resources appropriately to the pandemic's needs while enabling normal healthcare services resumption.

Impact of influenza vaccination on GP-diagnosed COVID-19 and all-cause mortality: a Dutch cohort study

OBJECTIVES

As clinical presentation and complications of both viruses overlap, it was hypothesised that influenza vaccination was associated with lower general practitioner (GP)-diagnosed COVID-19 rates and lower all-cause mortality rates.

STUDY DESIGN

From a primary care population-based cohort in the Netherlands, GP-diagnosed COVID-19 (between 10 March and 22 November 2020) and all-cause mortality events (between 30 December 2019 and 22 November 2020) were recorded. 223 580 persons were included, representing the influenza vaccination 2019 target group (all aged ≥60 years, and those <60 years with a medical indication). Proportional hazards regression analyses evaluated associations between influenza vaccination in 2019 and two outcomes: GP-diagnosed COVID-19 and all-cause mortality. Covariables were sex, age, comorbidities and number of acute respiratory infection primary care consultations in 2019.

RESULTS

A slightly positive association (HR 1.15; 95% CI 1.08 to 1.22) was found between influenza vaccination in 2019 and GP-diagnosed COVID-19, after adjusting for covariables. A slightly protective effect for all-cause mortality rates (HR 0.90; 95% CI 0.83 to 0.97) was found for influenza vaccination, after adjusting for covariables. A subgroup analysis among GP-diagnosed COVID-19 cases showed no significant association between influenza vaccination in 2019 and all-cause mortality.

CONCLUSIONS

Our hypothesis of a possibly negative association between influenza vaccination in 2019 and GP-diagnosed COVID-19 was not confirmed as we found a slightly positive association. A slightly protective effect on all-cause mortality was found after influenza vaccination, possibly by a wider, overall protective effect on health. Future research designs should include test-confirmed COVID-19 cases and controls, adjustments for behavioural, socioeconomic and ethnic factors and validated cause-specific mortality cases.

The impact of post-hospital remote monitoring of COVID-19 patients using pulse oximetry: A national observational study using hospital activity data

BACKGROUND

There was a national roll out of 'COVID Virtual Wards' (CVW) during England's second COVID-19 wave (Autumn 2020 - Spring 2021). These services used remote pulse oximetry monitoring for COVID-19 patients following discharge from hospital. A key aim was to enable rapid detection of patient deterioration. It was anticipated that the services would support early discharge, reducing pressure on beds. This study is an evaluation of the impact of the CVW services on hospital activity.

METHODS

Using retrospective patient-level hospital admissions data, we built multivariate models to analyze the relationship between the implementation of CVW services and hospital activity outcomes: length of COVID-19 related stays and subsequent COVID-19 readmissions within 28 days. We used data from more than 98% of recorded COVID-19 hospital stays in England, where the patient was discharged alive between mid-August 2020 and late February 2021.

FINDINGS

We found a longer length of stay for COVID-19 patients discharged from hospitals where a CVW was available, when compared to patients discharged from hospitals where there was no CVW (adjusted IRR 1·05, 95% CI 1·01 to 1·09). We found no evidence of a relationship between the availability of CVW and subsequent rates of readmission for COVID-19 (adjusted OR 0.97, 95% CI 0.91 to 1·03).

INTERPRETATION

We found no evidence of early discharges or changes in readmissions associated with the roll out of COVID Virtual Wards across England. Our analysis made pragmatic use of national-scale hospital data, but it is possible that a lack of specific data (for example, on which patients were enrolled and on potentially important confounders) may have meant that true impacts, especially at a local level, were not ultimately discernible. It is important that future research is able to make use of better quality - preferably linked - data, from multiple sites.

FUNDING

This is independent research funded by the National Institute for Health Research, Health Services & Delivery Research program (RSET Project no. 16/138/17; BRACE Project no. 16/138/31) and NHSE&I. NJF is an NIHR Senior Investigator.

Incubation period, clinical and lung CT features for early prediction of COVID-19 deterioration: development and internal verification of a risk model

Background

Most severe, critical, or mortal COVID-19 cases often had a relatively stable period before their status worsened. We developed a deterioration risk model of COVID-19 (DRM-COVID-19) to predict exacerbation risk and optimize disease management on admission.

Method

We conducted a multicenter retrospective cohort study with 239 confirmed symptomatic COVID-19 patients. A combination of the least absolute shrinkage and selection operator (LASSO), change-in-estimate (CIE) screened out independent risk factors for the multivariate logistic regression model (DRM-COVID-19) from 44 variables, including epidemiological, demographic, clinical, and lung CT features. The compound study endpoint was progression to severe, critical, or mortal status. Additionally, the model's performance was evaluated for discrimination, accuracy, calibration, and clinical utility, through internal validation using bootstrap resampling (1000 times). We used a nomogram and a network platform for model visualization.

Results

In the cohort study, 62 cases reached the compound endpoint, including 42 severe, 18 critical, and two mortal cases. DRM-COVID-19 included six factors: dyspnea [odds ratio (OR) 4.89;confidence interval (95% CI) 1.53–15.80], incubation period (OR 0.83; 95% CI 0.68–0.99), number of comorbidities (OR 1.76; 95% CI 1.03–3.05), D-dimer (OR 7.05; 95% CI, 1.35–45.7), C-reactive protein (OR 1.06; 95% CI 1.02–1.1), and semi-quantitative CT score (OR 1.50; 95% CI 1.27–1.82). The model showed good fitting (Hosmer–Lemeshow goodness, X²(8) = 7.0194, P = 0.53), high discrimination (the area under the receiver operating characteristic curve, AUROC, 0.971; 95% CI, 0.949–0.992), precision (Brier score = 0.051) as well as excellent calibration and clinical benefits. The precision-recall (PR) curve showed excellent classification performance of the model (AUC_PR = 0.934). We prepared a nomogram and a freely available online prediction platform (https://deterioration-risk-model-of-covid-19.shinyapps.io/DRMapp/).

Conclusion

We developed a predictive model, which includes the including incubation period along with clinical and lung CT features. The model presented satisfactory prediction and discrimination performance for COVID-19 patients who might progress from mild or moderate to severe or critical on admission, improving the clinical prognosis and optimizing the medical resources.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-01986-0.

Implementation and Evaluation of COVIDCare@Home, a Family Medicine Led Remote Monitoring Program for COVID-19 Patients: a multi-method cross-sectional study

Background

COVIDCare@Home (CC@H) is a multifaceted, interprofessional team-based remote monitoring program led by family medicine for patients diagnosed with COVID-19, based at Women’s College Hospital (WCH), an ambulatory academic center in Toronto, Canada. CC@H offers virtual visits (phone and video) to address the clinical needs and broader social determinants of the health of patients during the acute phase of COVID-19 infection, including finding a primary care provider (PCP) and support for food insecurity.

Objective

The objective of this evaluation is to understand the implementation and quality outcomes of CC@H within the Quadruple Aim framework of patient experience, provider experience, cost, and population health.

Methods

This multimethod cross-sectional evaluation follows the Quadruple Aim framework to focus on implementation and service quality outcomes, including feasibility, adoption, safety, effectiveness, equity, and patient centeredness. These measures were explored using clinical and service utilization data, patient experience data (an online survey and a postdischarge questionnaire), provider experience data (surveys, interviews, and focus groups), and stakeholder interviews. Descriptive analysis was conducted for surveys and utilization data. Deductive analysis was conducted for interviews and focus groups, mapping to implementation and quality domains. The Ontario Marginalization Index (ON-Marg) measured the proportion of underserved patients accessing CC@H.

Results

In total, 3412 visits were conducted in the first 8 months of the program (April 8-December 8, 2020) for 616 discrete patients, including 2114 (62.0%) visits with family physician staff/residents and 149 (4.4%) visits with social workers/mental health professionals. There was a median of 5 (IQR 4) visits per patient, with a median follow-up of 7 days (IQR 27). The net promoter score was 77. In addition, 144 (23.3%) of the patients were in the most marginalized populations based on the residential postal code (as per ON-Marg). Interviews with providers and stakeholders indicated that the program continued to adapt to meet the needs of patients and the health care system.

Conclusions

Future remote monitoring should integrate support for addressing the social determinants of health and ensure patient-centered care through comprehensive care teams.

The impact of remote home monitoring of people with COVID-19 using pulse oximetry: A national population and observational study

BACKGROUND

Remote home monitoring of people testing positive for COVID-19 using pulse oximetry was implemented across England during the Winter of 2020/21 to identify falling blood oxygen saturation levels at an early stage. This was hypothesised to enable earlier hospital admission, reduce the need for intensive care and improve survival. This study is an evaluation of the clinical effectiveness of the pre-hospital monitoring programme, COVID oximetry @home (CO@h).

METHODS

The setting was all Clinical Commissioning Group (CCG) areas in England where there were complete data on the number of people enrolled onto the programme between 2nd November 2020 and 21st February 2021. We analysed relationships at a geographical area level between the extent to which people aged 65 or over were enrolled onto the programme and outcomes over the period between November 2020 to February 2021.

FINDINGS

For every 10% increase in coverage of the programme, mortality was reduced by 2% (95% confidence interval:4% reduction to 1% increase), admissions increased by 3% (-1% to 7%), in-hospital mortality fell by 3% (-8% to 3%) and lengths of stay increased by 1·8% (-1·2% to 4·9%). None of these results are statistically significant, although the confidence interval indicates that any adverse effect on mortality would be small, but a mortality reduction of up to 4% may have resulted from the programme.

INTERPRETATION

There are several possible explanations for our findings. One is that CO@h did not have the hypothesised impact. Another is that the low rates of enrolment and incomplete data in many areas reduced the chances of detecting any impact that may have existed. Also, CO@h has been implemented in many different ways across the country and these may have had varying levels of effect.

FUNDING

This is independent research funded by the National Institute for Health Research, Health Services & Delivery Research programme (RSET Project no. 16/138/17; BRACE Project no. 16/138/31) and NHSEI. NJF is an NIHR Senior Investigator.

Virtual Behavioral Medicine Program: A Novel Model of Care for Neuropsychiatric Symptoms in Dementia

BACKGROUND

Patients with severe neuropsychiatric symptoms (NPS) due to dementia are often uprooted from their familiar environments in long-term care or the community and transferred to emergency departments, acute care hospitals, or specialized behavioral units which can exacerbate NPS. To address this issue, we developed the Virtual Behavioral Medicine Program (VBM), an innovative model of virtual care designed to support management of patients with NPS in their own environment.

OBJECTIVE

To determine efficacy of VBM in reducing admission to a specialized inpatient neurobehavioral unit for management of NPS.

METHODS

We reviewed outcomes in the first consecutive 95 patients referred to VBM. Referrals were classified into two groups. In one group, patients were referred to VBM with a simultaneous application to an inpatient Behavioral Neurology Unit (BNU). The other group was referred only to VBM. The primary outcome was reduction in proportion of patients requiring admission to the BNU regardless of whether they were referred to the BNU or to VBM alone.

RESULTS

For patients referred to VBM plus the BNU, the proportion needing admission to the BNU was reduced by 60.42%. For patients referred to VBM alone, it was 68.75%.

CONCLUSION

VBM is a novel virtual neurobehavioral unit for treatment of NPS. Although the sample size was relatively small, especially for the VBM group, the data suggest that this program is a game changer that can reduce preventable emergency department visits and acute care hospital admissions. VBM is a scalable model of virtual care that can be adopted worldwide.

Too early for admission? A Telemedicine follow up comparison of mild COVID-19 patients from the Emergency Department and Clinics

OBJECTIVE

Mildly symptomatic COVID-19 patients may seek medical attention either in the Emergency Department (ED) or Ambulatory Clinics (AC). However, it is unclear if ED patients have different characteristics and outcomes than AC patients when discharged under telemedicine surveillance, which we explored in this study.

METHODS

Patients with mild or asymptomatic COVID-19 disease referred to a multidisciplinary Telemedicine clinical service (TM-CS) program in an urban tertiary-care hospital, between June 2020 and February 2021, were evaluated. Those referred from ED were labeled "ED Group" and ones from AC as "AC Group." Their characteristics, clinical features and outcomes including telemedicine parameters, subsequent ED visits, hospital admission, oxygen requirements, intensive care unit (ICU) admission, and mortality were compared.

RESULTS

Out of 1132 confirmed non-admitted COVID-19 patients, 526 with mild (89%) or asymptomatic (11%) disease were enrolled in TM-CS. Majority of these were referred from ED (n = 370; 70%) and rest (n = 156, 30%) from the AC. Patients in the ED group compared to AC group, had higher BMI (28.9 vs. 27.5), higher Charlson Comorbidity Index (1.4 vs. 0.9), and higher incidence of comorbidities (50% vs. 22%), P ≤ 0.01. However, there were no differences in the ED and AC groups in subsequent ED visits (26% vs. 24%), hospital admission (18% vs. 15%), oxygen requirements (5% vs. 4%), ICU admission (1% vs. 2%), and mortality (0.3% vs. 0.6%), respectively (P > 0.40).

CONCLUSION

Significant number of mild COVID-19 patients head to the ED for initial assistance but have similar outcomes to AC patients. TM-CS could be a safe alternative for follow-up monitoring of these patients.

Mental and neurological disorders and risk of COVID-19 susceptibility, illness severity and mortality: A systematic review, meta-analysis and call for action

BACKGROUND

Coronavirus disease 2019 (COVID-19) has evolved into a worldwide pandemic, and has been found to be closely associated with mental and neurological disorders. We aimed to comprehensively quantify the association between mental and neurological disorders, both pre-existing and subsequent, and the risk of susceptibility, severity and mortality of COVID-19.

METHODS

In this systematic review and meta-analysis, we searched PubMed, Web of Science, Embase, PsycINFO, and Cochrane library databases for studies published from the inception up to January 16, 2021 and updated at July 7, 2021. Observational studies including cohort and case-control, cross-sectional studies and case series that reported risk estimates of the association between mental or neurological disorders and COVID-19 susceptibility, illness severity and mortality were included. Two researchers independently extracted data and conducted the quality assessment. Based on I2 heterogeneity, we used a random effects model to calculate pooled odds ratios (OR) and 95% confidence intervals (95% CI). Subgroup analyses and meta-regression analysis were also performed. This study was registered on PROSPERO (registration number: CRD 42021230832).

FINDING

A total of 149 studies (227,351,954 participants, 89,235,737 COVID-19 patients) were included in this analysis, in which 27 reported morbidity (132,727,798), 56 reported illness severity (83,097,968) and 115 reported mortality (88,878,662). Overall, mental and neurological disorders were associated with a significant high risk of infection (pre-existing mental: OR 1·67, 95% CI 1·12-2·49; and pre-existing neurological: 2·05, 1·58-2·67), illness severity (mental: pre-existing, 1·40, 1·25-1·57; sequelae, 4·85, 2·53-9·32; neurological: pre-existing, 1·43, 1·09-1·88; sequelae, 2·17, 1·45-3·24), and mortality (mental: pre-existing, 1·47, 1·26-1·72; neurological: pre-existing, 2·08, 1·61-2·69; sequelae, 2·03, 1·66-2·49) from COVID-19. Subgroup analysis revealed that association with illness severity was stronger among younger COVID-19 patients, and those with subsequent mental disorders, living in low- and middle-income regions. Younger patients with mental and neurological disorders were associated with higher mortality than elders. For type-specific mental disorders, susceptibility to contracting COVID-19 was associated with pre-existing mood disorders, anxiety, and attention-deficit hyperactivity disorder (ADHD); illness severity was associated with both pre-existing and subsequent mood disorders as well as sleep disturbance; and mortality was associated with pre-existing schizophrenia. For neurological disorders, susceptibility was associated with pre-existing dementia; both severity and mortality were associated with subsequent delirium and altered mental status; besides, mortality was associated with pre-existing and subsequent dementia and multiple specific neurological diseases. Heterogeneities were substantial across studies in most analysis.

INTERPRETATION

The findings show an important role of mental and neurological disorders in the context of COVID-19 and provide clues and directions for identifying and protecting vulnerable populations in the pandemic. Early detection and intervention for neurological and mental disorders are urgently needed to control morbidity and mortality induced by the COVID-19 pandemic. However, there was substantial heterogeneity among the included studies, and the results should be interpreted with caution. More studies are needed to explore long-term mental and neurological sequela, as well as the underlying brain mechanisms for the sake of elucidating the causal pathways for these associations.

FUNDING

This study is supported by grants from the National Key Research and Development Program of China, the National Natural Science Foundation of China, Special Research Fund of PKUHSC for Prevention and Control of COVID-19, and the Fundamental Research Funds for the Central Universities.

Remote home monitoring (virtual wards) for confirmed or suspected COVID-19 patients: a rapid systematic review

BACKGROUND

the aim of this review was to analyze the implementation and impact of remote home monitoring models (virtual wards) for confirmed or suspected COVID-19 patients, identifying their main components, processes of implementation, target patient populations, impact on outcomes, costs and lessons learnt.

METHODS

we carried out a rapid systematic review on models led by primary and secondary care across seven countries (US, Australia, Canada, The Netherlands, Ireland, China, UK). The main outcomes included in the review were: impact of remote home monitoring on virtual length of stay, escalation, emergency department attendance/reattendance, admission/readmission and mortality. The search was updated on February 2021. We used the PRISMA statement and the review was registered on PROSPERO (CRD: 42020202888).

FINDINGS

the review included 27 articles. The aim of the models was to maintain patients safe in the appropriate setting. Most models were led by secondary care and confirmation of COVID-19 was not required (in most cases). Monitoring was carried via online platforms, paper-based systems with telephone calls or (less frequently) through wearable sensors. Models based on phone calls were considered more inclusive. Patient/career training was identified as a determining factor of success. We could not reach substantive conclusions regarding patient safety and the identification of early deterioration due to lack of standardized reporting and missing data. Economic analysis was not reported for most of the models and did not go beyond reporting resources used and the amount spent per patient monitored.

INTERPRETATION

future research should focus on staff and patient experiences of care and inequalities in patients' access to care. Attention needs to be paid to the cost-effectiveness of the models and their sustainability, evaluation of their impact on patient outcomes by using comparators, and the use of risk-stratification tools.