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1.
BMJ Open ; 12(5): e056817, 2022 05 03.
Article in English | MEDLINE | ID: covidwho-1822071

ABSTRACT

OBJECTIVES: To identify research priorities for primary care in Scotland following the COVID-19 pandemic. DESIGN: Modified James Lind Alliance methodology; respondents completed an online survey to make research suggestions and rank research themes in order of priority. SETTING: Scotland primary care. PARTICIPANTS: Healthcare professionals in primary care in Scotland and members of primary care patient and public involvement groups. 512 respondents provided research suggestions; 8% (n=40) did not work in health or social care; of those who did work, 68.8% worked in primary care, 16.3% community care, 11.7% secondary care, 4.5% third sector, 4.2% university (respondents could select multiple options). Of those respondents who identified as healthcare professionals, 33% were in nursing and midwifery professions, 25% were in allied health professions (of whom 45% were occupational therapists and 35% were physiotherapists), 20% were in the medical profession and 10% were in the pharmacy profession. MAIN OUTCOMES: Suggestions for research for primary care made by respondents were categorised into themes and subthemes by researchers and ranked in order of priority by respondents. RESULTS: There were 1274 research suggestions which were categorised under 12 themes and 30 subthemes. The following five themes received the most suggestions for research: disease and illness (n=461 suggestions), access (n=202), workforce (n=164), multidisciplinary team (MDT; n=143) and integration (n=108). One hundred and three (20%) respondents to the survey participated in ranking the list of 12 themes in order of research priority. The five most highly ranked research priorities were disease and illness, health inequalities, access, workforce and MDTs. The disease and illness theme had the greatest number of suggestions for research and was scored the most highly in the ranking exercise. The subtheme ranked as the most important research priority in the disease and illness theme was 'mental health'. CONCLUSIONS: The themes and subthemes identified in this study should inform research funders so that the direction of primary healthcare is informed by evidence.


Subject(s)
Biomedical Research , COVID-19 , COVID-19/epidemiology , Humans , Pandemics , Primary Health Care , Scotland , Surveys and Questionnaires
2.
Orphanet J Rare Dis ; 17(1): 166, 2022 04 12.
Article in English | MEDLINE | ID: covidwho-1789126

ABSTRACT

BACKGROUND: Several common conditions have been widely recognised as risk factors for COVID-19 related death, but risks borne by people with rare diseases are largely unknown. Therefore, we aim to estimate the difference of risk for people with rare diseases comparing to the unaffected. METHOD: To estimate the correlation between rare diseases and COVID-19 related death, we performed a retrospective cohort study in Genomics England 100k Genomes participants, who tested positive for Sars-Cov-2 during the first wave (16-03-2020 until 31-July-2020) of COVID-19 pandemic in the UK (n = 283). COVID-19 related mortality rates were calculated in two groups: rare disease patients (n = 158) and unaffected relatives (n = 125). Fisher's exact test and logistic regression was used for univariable and multivariable analysis, respectively. RESULTS: People with rare diseases had increased risk of COVID19-related deaths compared to the unaffected relatives (OR [95% CI] = 3.47 [1.21- 12.2]). Although, the effect was insignificant after adjusting for age and number of comorbidities (OR [95% CI] = 1.94 [0.65-5.80]). Neurology and neurodevelopmental diseases was significantly associated with COVID19-related death in both univariable (OR [95% CI] = 4.07 [1.61-10.38]) and multivariable analysis (OR [95% CI] = 4.22 [1.60-11.08]). CONCLUSIONS: Our results showed that rare disease patients, especially ones affected by neurology and neurodevelopmental disorders, in the Genomics England cohort had increased risk of COVID-19 related death during the first wave of the pandemic in UK. The high risk is likely associated with rare diseases themselves, while we cannot rule out possible mediators due to the small sample size. We would like to raise the awareness that rare disease patients may face increased risk for COVID-19 related death. Proper considerations for rare disease patients should be taken when relevant policies (e.g., returning to workplace) are made.


Subject(s)
COVID-19 , COVID-19/genetics , Cohort Studies , England , Genomics , Humans , Pandemics , Rare Diseases/epidemiology , Rare Diseases/genetics , Retrospective Studies , SARS-CoV-2
3.
Heart ; 2022 Mar 31.
Article in English | MEDLINE | ID: covidwho-1769936

ABSTRACT

OBJECTIVE: Treatment of acute myocardial infarction (MI) requires rapid transfer of people with chest pain to hospital, however, unscheduled care pathways vary in their directness (the minimal number of contacts to hospital admission). The aim was to examine unscheduled care pathways and the associations with mortality in people admitted with MI. METHODS: Retrospective population study of all people admitted to Scottish hospitals with a diagnosis of MI between 1 January 2015 and 31 December 2017. Linked data for all National Health Service Scotland unscheduled care services (NHS24 telephone triage service, primary care out of hours, ambulance, emergency department (ED)) was used to define continuous unscheduled care pathways (pathways), which were categorised by initial contact, and whether they were 'direct' (had minimum number of contacts between first contact and admission). Analysis estimated ORs and 95% CIs in adjusted models in which all covariates were included. RESULTS: 26 325 people admitted with MI (63.1% men, 61.6% aged 65+ years), of whom 5.6% died from coronary heart disease within 28 days. For 47.0%, the first unscheduled care contact was ambulance, 23.3% attended ED directly and 18.7% called telephone triage. 92.1% of pathways were direct. Pathways starting with telephone triage were more likely to be indirect compared with other initial contacts (adjusted OR (aOR) 1.97, 95% CI 1.61 to 2.40). Compared to direct pathways, indirect pathways starting with telephone triage were associated with higher mortality (aOR 1.97, 95% CI 1.61 to 2.40) as were indirect pathways starting with another service (aOR 1.55, 95% CI 1.19 to 2.01), but not direct pathways starting with telephone triage (aOR 0.87, 95% CI 0.74 to 1.02). CONCLUSION: Unscheduled care pathways leading to admission with MI in Scotland are usually direct, but those starting with telephone triage were more commonly indirect. Those indirect pathways were associated with higher mortality.

5.
Age Ageing ; 51(3)2022 03 01.
Article in English | MEDLINE | ID: covidwho-1692262

ABSTRACT

The COVID-19 pandemic resulted in catastrophic levels of morbidity and mortality for care home residents. Despite this, research platforms for COVID-19 in care homes arrived late in the pandemic compared with other care settings. The Prophylactic Therapy in Care Homes Trial (PROTECT-CH) was established to provide a platform to deliver multi-centre cluster-randomized clinical trials of investigational medicinal products for COVID-19 prophylaxis in UK care homes. Commencing set-up in January 2021, this involved the design and development of novel infrastructure for contracting and recruitment, remote consent, staff training, research insurance, eligibility screening, prescribing, dispensing and adverse event reporting; such infrastructure being previously absent. By the time this infrastructure was in place, the widespread uptake of vaccination in care homes had changed the epidemiology of COVID-19 rendering the trial unfeasible. While some of the resources developed through PROTECT-CH will enable the future establishment of care home platform research, the near absence of care home trial infrastructure and nationally linked databases involving the care home sector will continue to significantly hamper progress. These issues are replicated in most other countries. Beyond COVID-19, there are many other research questions that require addressing to provide better care to people living in care homes. PROTECT-CH has exposed a clear need for research funders to invest in, and legislate for, an effective care home research infrastructure as part of national pandemic preparedness planning. Doing so would also invigorate care home research in the interim, leading to improved healthcare delivery specific to those living in this sector.


Subject(s)
COVID-19 , COVID-19/epidemiology , Delivery of Health Care , Humans , Pandemics/prevention & control
6.
PLoS Med ; 18(11): e1003828, 2021 11.
Article in English | MEDLINE | ID: covidwho-1596033

ABSTRACT

BACKGROUND: Clinical pathways are changing to incorporate support and appropriate follow-up for people to achieve remission of type 2 diabetes, but there is limited understanding of the prevalence of remission in current practice or patient characteristics associated with remission. METHODS AND FINDINGS: We carried out a cross-sectional study estimating the prevalence of remission of type 2 diabetes in all adults in Scotland aged ≥30 years diagnosed with type 2 diabetes and alive on December 31, 2019. Remission of type 2 diabetes was assessed between January 1, 2019 and December 31, 2019. We defined remission as all HbA1c values <48 mmol/mol in the absence of glucose-lowering therapy (GLT) for a continuous duration of ≥365 days before the date of the last recorded HbA1c in 2019. Multivariable logistic regression in complete and multiply imputed datasets was used to examine characteristics associated with remission. Our cohort consisted of 162,316 individuals, all of whom had at least 1 HbA1c ≥48 mmol/mol (6.5%) at or after diagnosis of diabetes and at least 1 HbA1c recorded in 2019 (78.5% of the eligible population). Over half (56%) of our cohort was aged 65 years or over in 2019, and 64% had had type 2 diabetes for at least 6 years. Our cohort was predominantly of white ethnicity (74%), and ethnicity data were missing for 19% of the cohort. Median body mass index (BMI) at diagnosis was 32.3 kg/m2. A total of 7,710 people (4.8% [95% confidence interval [CI] 4.7 to 4.9]) were in remission of type 2 diabetes. Factors associated with remission were older age (odds ratio [OR] 1.48 [95% CI 1.34 to 1.62] P < 0.001) for people aged ≥75 years compared to 45 to 54 year group), HbA1c <48 mmol/mol at diagnosis (OR 1.31 [95% CI 1.24 to 1.39] P < 0.001) compared to 48 to 52 mmol/mol), no previous history of GLT (OR 14.6 [95% CI 13.7 to 15.5] P < 0.001), weight loss from diagnosis to 2019 (OR 4.45 [95% CI 3.89 to 5.10] P < 0.001) for ≥15 kg of weight loss compared to 0 to 4.9 kg weight gain), and previous bariatric surgery (OR 11.9 [95% CI 9.41 to 15.1] P < 0.001). Limitations of the study include the use of a limited subset of possible definitions of remission of type 2 diabetes, missing data, and inability to identify self-funded bariatric surgery. CONCLUSIONS: In this study, we found that 4.8% of people with type 2 diabetes who had at least 1 HbA1c ≥48 mmol/mol (6.5%) after diagnosis of diabetes and had at least 1 HbA1c recorded in 2019 had evidence of type 2 diabetes remission. Guidelines are required for management and follow-up of this group and may differ depending on whether weight loss and remission of diabetes were intentional or unintentional. Our findings can be used to evaluate the impact of future initiatives on the prevalence of type 2 diabetes remission.


Subject(s)
Diabetes Mellitus, Type 2/epidemiology , Diabetes Mellitus, Type 2/therapy , Adult , Aged , Aged, 80 and over , Cross-Sectional Studies , Diabetes Mellitus, Type 2/blood , Diabetes Mellitus, Type 2/diagnosis , Female , Glycated Hemoglobin A/metabolism , Humans , Logistic Models , Male , Middle Aged , Multivariate Analysis , Odds Ratio , Prevalence , Remission Induction , Scotland/epidemiology
7.
8.
JMIR Form Res ; 5(9): e20131, 2021 Sep 27.
Article in English | MEDLINE | ID: covidwho-1376651

ABSTRACT

BACKGROUND: Most people with COVID-19 self-manage at home. However, the condition can deteriorate quickly, and some people may develop serious hypoxia with relatively few symptoms. Early identification of deterioration allows effective management with oxygen and steroids. Telemonitoring of symptoms and physiological signs may facilitate this. OBJECTIVE: The aim of this study was to design, implement, and evaluate a telemonitoring system for people with COVID-19 who are self-managing at home and are considered at significant risk of deterioration. METHODS: A multidisciplinary team developed a telemonitoring protocol using a commercial platform to record symptoms, pulse oximetry, and temperature. If symptoms or physiological measures breached targets, patients were alerted and asked to phone for an ambulance (red alert) or for advice (amber alert). Patients attending COVID-19 assessment centers, who were considered fit for discharge but at risk of deterioration, were shown how to use a pulse oximeter and the monitoring system, which they were to use twice daily for 2 weeks. Patients could interact with the system via app, SMS, or touch-tone phone. Written guidance on alerts was also provided. Following consent, patient data on telemonitoring usage and alerts were linked to data on the use of service resources. Subsequently, patients who had either used or not used the telemonitoring service, including those who had not followed advice to seek help, agreed to brief telephone interviews to explore their views on, and how they had interacted with, the telemonitoring system. Interviews were recorded and analyzed thematically. Professionals involved in the implementation were sent an online questionnaire asking them about their perceptions of the service. RESULTS: We investigated the first 116 patients who used the service. Of these patients, 71 (61.2%) submitted data and the remainder (n=45, 38.8%) chose to self-monitor without electronic support. Of the 71 patients who submitted data, 35 (49%) received 152 alerts during their 2-week observation. A total of 67 red alerts were for oxygen saturation (SpO2) levels of ≤93%, and 15 red alerts were because patients recorded severe breathlessness. Out of 71 patients, 14 (20%) were admitted to hospital for an average stay of 3.6 (SD 4.5) days. Of the 45 who used written guidance alone, 7 (16%) were admitted to hospital for an average stay of 4.0 (SD 4.2) days and 1 (2%) died. Some patients who were advised to seek help did not do so, some because parameters improved on retesting and others because they felt no worse than before. All patients found self-monitoring to be reassuring. Of the 11 professionals who used the system, most found it to be useful and easy to use. Of these 11 professionals, 5 (45%) considered the system "very safe," 3 (27%) thought it "could be safer," and 3 (27%) wished to have more experience with it before deciding. In total, 2 (18%) felt that SpO2 trigger thresholds were too high. CONCLUSIONS: Supported self-monitoring of patients with COVID-19 at home is reassuring to patients, is acceptable to clinicians, and can detect important signs of deterioration. Worryingly, some patients, because they felt well, occasionally ignored important signs of deterioration. It is important, therefore, to emphasize the importance of the early investigation and treatment of asymptomatic hypoxia at the time when patients are initiated and in the warning messages that are sent to patients.

9.
Lancet Healthy Longev ; 1(1): e21-e31, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-1281658

ABSTRACT

BACKGROUND: COVID-19 has affected care home residents internationally, but detailed information on outbreaks is scarce. We aimed to describe the evolution of outbreaks of COVID-19 in all care homes in one large health region in Scotland. METHODS: We did a population analysis of testing, cases, and deaths in care homes in the National Health Service (NHS) Lothian health region of the UK. We obtained data for COVID-19 testing (PCR testing of nasopharyngeal swabs for severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) and deaths (COVID-19-related and non-COVID-19-related), and we analysed data by several variables including type of care home, number of beds, and locality. Outcome measures were timing of outbreaks, number of confirmed cases of COVID-19 in care home residents, care home characteristics associated with the presence of an outbreak, and deaths of residents in both care homes and hospitals. We calculated excess deaths (both COVID-19-related and non-COVID-19-related), which we defined as the sum of deaths over and above the historical average in the same period over the past 5 years. FINDINGS: Between March 10 and Aug 2, 2020, residents at 189 care homes (5843 beds) were tested for COVID-19 when symptomatic. A COVID-19 outbreak was confirmed at 69 (37%) care homes, of which 66 (96%) were care homes for older people. The size of care homes for older people was strongly associated with a COVID-19 outbreak (odds ratio per 20-bed increase 3·35, 95% CI 1·99-5·63). 907 confirmed cases of SARS-CoV-2 infection were recorded during the study period, and 432 COVID-19-related deaths. 229 (25%) COVID-19-related cases and 99 (24%) COVID-related deaths occurred in five (3%) of 189 care homes, and 441 (49%) cases and 207 (50%) deaths were in 13 (7%) care homes. 411 (95%) COVID-19-related deaths occurred in the 69 care homes with a confirmed COVID-19 outbreak, 19 (4%) deaths were in hospital, and two (<1%) were in one of the 120 care homes without a confirmed COVID-19 outbreak. At the 69 care homes with a confirmed COVID-19 outbreak, 74 excess non-COVID-19-related deaths were reported, whereas ten non-COVID-19-related excess deaths were observed in the 120 care homes without a confirmed COVID-19 outbreak. 32 fewer non-COVID-19-related deaths than expected were reported among care home residents in hospital. INTERPRETATION: The effect of COVID-19 on care homes has been substantial but concentrated in care homes with known outbreaks. A key implication from our findings is that, if community incidence of COVID-19 increases again, many care home residents will be susceptible. Shielding care home residents from potential sources of SARS-CoV-2 infection, and ensuring rapid action to minimise outbreak size if infection is introduced, will be important for any second wave. FUNDING: None.

10.
Age Ageing ; 50(5): 1482-1492, 2021 09 11.
Article in English | MEDLINE | ID: covidwho-1219031

ABSTRACT

BACKGROUND: understanding care-home outbreaks of COVID-19 is a key public health priority in the ongoing pandemic to help protect vulnerable residents. OBJECTIVE: to describe all outbreaks of COVID-19 infection in Scottish care-homes for older people between 01/03/2020 and 31/03/2020, with follow-up to 30/06/2020. DESIGN AND SETTING: National linked data cohort analysis of Scottish care-homes for older people. METHODS: data linkage was used to identify outbreaks of COVID-19 in care-homes. Care-home characteristics associated with the presence of an outbreak were examined using logistic regression. Size of outbreaks was modelled using negative binomial regression. RESULTS: 334 (41%) Scottish care-homes for older people experienced an outbreak, with heterogeneity in outbreak size (1-63 cases; median = 6) and duration (1-94 days, median = 31.5 days). Four distinct patterns of outbreak were identified: 'typical' (38% of outbreaks, mean 11.2 cases and 48 days duration), severe (11%, mean 29.7 cases and 60 days), contained (37%, mean 3.5 cases and 13 days) and late-onset (14%, mean 5.4 cases and 17 days). Risk of a COVID-19 outbreak increased with increasing care-home size (for ≥90 beds vs <20, adjusted OR = 55.4, 95% CI 15.0-251.7) and rising community prevalence (OR = 1.2 [1.0-1.4] per 100 cases/100,000 population increase). No routinely available care-home characteristic was associated with outbreak size. CONCLUSIONS: reducing community prevalence of COVID-19 infection is essential to protect those living in care-homes. More systematic national data collection to understand care-home residents and the homes in which they live is a priority in ensuring we can respond more effectively in future.


Subject(s)
COVID-19 , Aged , Cohort Studies , Disease Outbreaks , Humans , Nursing Homes , SARS-CoV-2 , Scotland/epidemiology , Semantic Web
11.
Age Ageing ; 50(4): 1029-1037, 2021 06 28.
Article in English | MEDLINE | ID: covidwho-1207248

ABSTRACT

BACKGROUND: COVID-19 deaths are commoner among care-home residents, but the mortality burden has not been quantified. METHODS: Care-home residency was identified via a national primary care registration database linked to mortality data. Life expectancy was estimated using Makeham-Gompertz models to (i) describe yearly life expectancy from November 2015 to October 2020 (ii) compare life expectancy (during 2016-18) between care-home residents and the wider population and (iii) apply care-home life expectancy estimates to COVID-19 death counts to estimate years of life lost (YLL). RESULTS: Among care-home residents, life expectancy in 2015/16 to 2019/20 ranged from 2.7 to 2.3 years for women and 2.3 to 1.8 years for men. Age-sex-specific life expectancy in 2016-18 in care-home residents was lower than in the Scottish population (10 and 2.5 years in those aged 70 and 90, respectively). Applying care home-specific life expectancies to COVID-19 deaths yield mean YLLs for care-home residents of 2.6 and 2.2 for women and men, respectively. In total YLL care-home residents have lost 3,560 years in women and 2,046 years in men. Approximately half of deaths and a quarter of YLL attributed to COVID-19 were accounted for by the 5% of over-70s who were care-home residents. CONCLUSION: COVID-19 infection has led to the loss of substantial years of life in care-home residents aged 70 years and over in Scotland. Prioritising the 5% of older adults who are care-home residents for vaccination is justified not only in terms of total deaths, but also in terms of YLL.


Subject(s)
COVID-19 , Life Expectancy , Aged , Cause of Death , Female , Humans , Male , Mortality , SARS-CoV-2 , Scotland/epidemiology
12.
J Am Med Inform Assoc ; 28(4): 791-800, 2021 03 18.
Article in English | MEDLINE | ID: covidwho-1142659

ABSTRACT

OBJECTIVE: Risk prediction models are widely used to inform evidence-based clinical decision making. However, few models developed from single cohorts can perform consistently well at population level where diverse prognoses exist (such as the SARS-CoV-2 [severe acute respiratory syndrome coronavirus 2] pandemic). This study aims at tackling this challenge by synergizing prediction models from the literature using ensemble learning. MATERIALS AND METHODS: In this study, we selected and reimplemented 7 prediction models for COVID-19 (coronavirus disease 2019) that were derived from diverse cohorts and used different implementation techniques. A novel ensemble learning framework was proposed to synergize them for realizing personalized predictions for individual patients. Four diverse international cohorts (2 from the United Kingdom and 2 from China; N = 5394) were used to validate all 8 models on discrimination, calibration, and clinical usefulness. RESULTS: Results showed that individual prediction models could perform well on some cohorts while poorly on others. Conversely, the ensemble model achieved the best performances consistently on all metrics quantifying discrimination, calibration, and clinical usefulness. Performance disparities were observed in cohorts from the 2 countries: all models achieved better performances on the China cohorts. DISCUSSION: When individual models were learned from complementary cohorts, the synergized model had the potential to achieve better performances than any individual model. Results indicate that blood parameters and physiological measurements might have better predictive powers when collected early, which remains to be confirmed by further studies. CONCLUSIONS: Combining a diverse set of individual prediction models, the ensemble method can synergize a robust and well-performing model by choosing the most competent ones for individual patients.


Subject(s)
COVID-19/mortality , Models, Statistical , Prognosis , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19/prevention & control , China/epidemiology , Female , Humans , Male , Middle Aged , Risk Assessment/methods , SARS-CoV-2 , United Kingdom/epidemiology
13.
BMC Med ; 19(1): 51, 2021 02 22.
Article in English | MEDLINE | ID: covidwho-1094033

ABSTRACT

BACKGROUND: The objective of this study was to investigate the relation of severe COVID-19 to prior drug prescribing. METHODS: Severe cases were defined by entry to critical care or fatal outcome. For this matched case-control study (REACT-SCOT), all 4251 cases of severe COVID-19 in Scotland since the start of the epidemic were matched for age, sex and primary care practice to 36,738 controls from the population register. Records were linked to hospital discharges since June 2015 and dispensed prescriptions issued in primary care during the last 240 days. RESULTS: Severe COVID-19 was strongly associated with the number of non-cardiovascular drug classes dispensed. This association was strongest in those not resident in a care home, in whom the rate ratio (95% CI) associated with dispensing of 12 or more drug classes versus none was 10.8 (8.8, 13.3), and in those without any of the conditions designated as conferring increased risk of COVID-19. Of 17 drug classes postulated at the start of the epidemic to be "medications compromising COVID", all were associated with increased risk of severe COVID-19 and these associations were present in those without any of the designated risk conditions. The fraction of cases in the population attributable to exposure to these drug classes was 38%. The largest effect was for antipsychotic agents: rate ratio 4.18 (3.42, 5.11). Other drug classes with large effects included proton pump inhibitors (rate ratio 2.20 (1.72, 2.83) for = 2 defined daily doses/day), opioids (3.66 (2.68, 5.01) for = 50 mg morphine equivalent/day) and gabapentinoids. These associations persisted after adjusting for covariates and were stronger with recent than with non-recent exposure. CONCLUSIONS: Severe COVID-19 is associated with polypharmacy and with drugs that cause sedation, respiratory depression, or dyskinesia; have anticholinergic effects; or affect the gastrointestinal system. These associations are not easily explained by co-morbidity. Measures to reduce the burden of mortality and morbidity from COVID-19 should include reinforcing existing guidance on reducing overprescribing of these drug classes and limiting inappropriate polypharmacy. REGISTRATION: ENCEPP number EUPAS35558.


Subject(s)
COVID-19/diagnosis , COVID-19/epidemiology , Critical Care/trends , Polypharmacy , Psychotropic Drugs/adverse effects , Severity of Illness Index , Aged , Aged, 80 and over , COVID-19/chemically induced , Case-Control Studies , Comorbidity , Dose-Response Relationship, Drug , Drug Prescriptions , Female , Humans , Male , Middle Aged , Psychotropic Drugs/therapeutic use , Scotland/epidemiology
14.
BMC Med ; 19(1): 23, 2021 01 21.
Article in English | MEDLINE | ID: covidwho-1067228

ABSTRACT

BACKGROUND: The National Early Warning Score (NEWS2) is currently recommended in the UK for the risk stratification of COVID-19 patients, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for the prediction of severe COVID-19 outcome and identify and validate a set of blood and physiological parameters routinely collected at hospital admission to improve upon the use of NEWS2 alone for medium-term risk stratification. METHODS: Training cohorts comprised 1276 patients admitted to King's College Hospital National Health Service (NHS) Foundation Trust with COVID-19 disease from 1 March to 30 April 2020. External validation cohorts included 6237 patients from five UK NHS Trusts (Guy's and St Thomas' Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals, University Hospitals Birmingham), one hospital in Norway (Oslo University Hospital), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID-19 disease (transfer to intensive care unit (ICU) or death) at 14 days after hospital admission. Age, physiological measures, blood biomarkers, sex, ethnicity, and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) measured at hospital admission were considered in the models. RESULTS: A baseline model of 'NEWS2 + age' had poor-to-moderate discrimination for severe COVID-19 infection at 14 days (area under receiver operating characteristic curve (AUC) in training cohort = 0.700, 95% confidence interval (CI) 0.680, 0.722; Brier score = 0.192, 95% CI 0.186, 0.197). A supplemented model adding eight routinely collected blood and physiological parameters (supplemental oxygen flow rate, urea, age, oxygen saturation, C-reactive protein, estimated glomerular filtration rate, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI 0.715, 0.757), and these improvements were replicated across seven UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites. CONCLUSIONS: NEWS2 score had poor-to-moderate discrimination for medium-term COVID-19 outcome which raises questions about its use as a screening tool at hospital admission. Risk stratification was improved by including readily available blood and physiological parameters measured at hospital admission, but there was evidence of miscalibration in external sites. This highlights the need for a better understanding of the use of early warning scores for COVID.


Subject(s)
COVID-19/diagnosis , Early Warning Score , Aged , COVID-19/epidemiology , COVID-19/virology , Cohort Studies , Electronic Health Records , Female , Humans , Male , Middle Aged , Pandemics , Prognosis , SARS-CoV-2/isolation & purification , State Medicine , United Kingdom/epidemiology
15.
Arch Dis Child ; 106(9): 911-917, 2021 09.
Article in English | MEDLINE | ID: covidwho-1033181

ABSTRACT

OBJECTIVES: To determine the indirect consequences of the COVID-19 pandemic on paediatric healthcare utilisation and severe disease at a national level following lockdown on 23 March 2020. DESIGN: National retrospective cohort study. SETTING: Emergency childhood primary and secondary care providers across Scotland; two national paediatric intensive care units (PICUs); statutory death records. PARTICIPANTS: 273 455 unscheduled primary care attendances; 462 437 emergency department attendances; 54 076 emergency hospital admissions; 413 PICU unplanned emergency admissions requiring invasive mechanical ventilation; and 415 deaths during the lockdown study period and equivalent dates in previous years. MAIN OUTCOME MEASURES: Rates of emergency care consultations, attendances and admissions; clinical severity scores on presentation to PICU; rates and causes of childhood death. For all data sets, rates during the lockdown period were compared with mean or aggregated rates for the equivalent dates in 2016-2019. RESULTS: The rates of emergency presentations to primary and secondary care fell during lockdown in comparison to previous years. Emergency PICU admissions for children requiring invasive mechanical ventilation also fell as a proportion of cases for the entire population, with an OR of 0.52 for likelihood of admission during lockdown (95% CI 0.37 to 0.73), compared with the equivalent period in previous years. Clinical severity scores did not suggest children were presenting with more advanced disease. The greatest reduction in PICU admissions was for diseases of the respiratory system; those for injury, poisoning or other external causes were equivalent to previous years. Mortality during lockdown did not change significantly compared with 2016-2019. CONCLUSIONS: National lockdown led to a reduction in paediatric emergency care utilisation, without associated evidence of severe harm.


Subject(s)
COVID-19/epidemiology , Delivery of Health Care/methods , Hospitalization/trends , Intensive Care Units, Pediatric/statistics & numerical data , Pandemics , Population Surveillance , Adolescent , COVID-19/therapy , Child , Child, Preschool , Female , Humans , Infant , Infant, Newborn , Male , Retrospective Studies , SARS-CoV-2 , United Kingdom/epidemiology
16.
J Am Med Inform Assoc ; 28(4): 791-800, 2021 03 18.
Article in English | MEDLINE | ID: covidwho-970031

ABSTRACT

OBJECTIVE: Risk prediction models are widely used to inform evidence-based clinical decision making. However, few models developed from single cohorts can perform consistently well at population level where diverse prognoses exist (such as the SARS-CoV-2 [severe acute respiratory syndrome coronavirus 2] pandemic). This study aims at tackling this challenge by synergizing prediction models from the literature using ensemble learning. MATERIALS AND METHODS: In this study, we selected and reimplemented 7 prediction models for COVID-19 (coronavirus disease 2019) that were derived from diverse cohorts and used different implementation techniques. A novel ensemble learning framework was proposed to synergize them for realizing personalized predictions for individual patients. Four diverse international cohorts (2 from the United Kingdom and 2 from China; N = 5394) were used to validate all 8 models on discrimination, calibration, and clinical usefulness. RESULTS: Results showed that individual prediction models could perform well on some cohorts while poorly on others. Conversely, the ensemble model achieved the best performances consistently on all metrics quantifying discrimination, calibration, and clinical usefulness. Performance disparities were observed in cohorts from the 2 countries: all models achieved better performances on the China cohorts. DISCUSSION: When individual models were learned from complementary cohorts, the synergized model had the potential to achieve better performances than any individual model. Results indicate that blood parameters and physiological measurements might have better predictive powers when collected early, which remains to be confirmed by further studies. CONCLUSIONS: Combining a diverse set of individual prediction models, the ensemble method can synergize a robust and well-performing model by choosing the most competent ones for individual patients.


Subject(s)
COVID-19/mortality , Models, Statistical , Prognosis , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19/prevention & control , China/epidemiology , Female , Humans , Male , Middle Aged , Risk Assessment/methods , SARS-CoV-2 , United Kingdom/epidemiology
17.
Lancet Glob Health ; 8(8): e1003-e1017, 2020 08.
Article in English | MEDLINE | ID: covidwho-598578

ABSTRACT

BACKGROUND: The risk of severe COVID-19 if an individual becomes infected is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 and how this varies between countries should inform the design of possible strategies to shield or vaccinate those at highest risk. METHODS: We estimated the number of individuals at increased risk of severe disease (defined as those with at least one condition listed as "at increased risk of severe COVID-19" in current guidelines) by age (5-year age groups), sex, and country for 188 countries using prevalence data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 and UN population estimates for 2020. The list of underlying conditions relevant to COVID-19 was determined by mapping the conditions listed in GBD 2017 to those listed in guidelines published by WHO and public health agencies in the UK and the USA. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity. To help interpretation of the degree of risk among those at increased risk, we also estimated the number of individuals at high risk (defined as those that would require hospital admission if infected) using age-specific infection-hospitalisation ratios for COVID-19 estimated for mainland China and making adjustments to reflect country-specific differences in the prevalence of underlying conditions and frailty. We assumed males were twice at likely as females to be at high risk. We also calculated the number of individuals without an underlying condition that could be considered at increased risk because of their age, using minimum ages from 50 to 70 years. We generated uncertainty intervals (UIs) for our estimates by running low and high scenarios using the lower and upper 95% confidence limits for country population size, disease prevalences, multimorbidity fractions, and infection-hospitalisation ratios, and plausible low and high estimates for the degree of clustering, informed by multimorbidity studies. FINDINGS: We estimated that 1·7 billion (UI 1·0-2·4) people, comprising 22% (UI 15-28) of the global population, have at least one underlying condition that puts them at increased risk of severe COVID-19 if infected (ranging from <5% of those younger than 20 years to >66% of those aged 70 years or older). We estimated that 349 million (186-787) people (4% [3-9] of the global population) are at high risk of severe COVID-19 and would require hospital admission if infected (ranging from <1% of those younger than 20 years to approximately 20% of those aged 70 years or older). We estimated 6% (3-12) of males to be at high risk compared with 3% (2-7) of females. The share of the population at increased risk was highest in countries with older populations, African countries with high HIV/AIDS prevalence, and small island nations with high diabetes prevalence. Estimates of the number of individuals at increased risk were most sensitive to the prevalence of chronic kidney disease, diabetes, cardiovascular disease, and chronic respiratory disease. INTERPRETATION: About one in five individuals worldwide could be at increased risk of severe COVID-19, should they become infected, due to underlying health conditions, but this risk varies considerably by age. Our estimates are uncertain, and focus on underlying conditions rather than other risk factors such as ethnicity, socioeconomic deprivation, and obesity, but provide a starting point for considering the number of individuals that might need to be shielded or vaccinated as the global pandemic unfolds. FUNDING: UK Department for International Development, Wellcome Trust, Health Data Research UK, Medical Research Council, and National Institute for Health Research.


Subject(s)
Chronic Disease/epidemiology , Coronavirus Infections/epidemiology , Global Health/statistics & numerical data , Pneumonia, Viral/epidemiology , Severity of Illness Index , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19 , Child , Child, Preschool , Female , Humans , Male , Middle Aged , Models, Statistical , Pandemics , Risk Assessment , United Kingdom/epidemiology , United States/epidemiology , Young Adult
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