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1.
J Assoc Physicians India ; 70(4): 11-12, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1801779

ABSTRACT

The recent outbreak of COVID 19 is a great threat to public health. Because of limitation of resources, the number of patients that can be monitored and treated in Intensive Care Units is restricted. Hence identifying medical patients at risk of deterioration at the initial stage by means of simple protocols based on physiological parameters is crucial. The qSOFA score was introduced as a rapid bedside clinical score to identify patients with a suspected infection that are at greater risk for a poor outcome. The National Early Warning Score (NEWS) was developed to improve the detection of and response to clinical deterioration in patients with acute illness. There is paucity of literature regarding the use of these scores in patients with COVID 19 infection. This study aims at comparing the scoring systems qSOFA and NEWS in the setting of COVID-19 infection and its correlation with the final outcome of the illness. MATERIAL: It is a retrospective study in which patients presenting with COVID 19 infection(diagnosed by RT-PCR testing of nasopharyngeal and oral swab) between April 2021 to June 2021 were included. Scoring was done using both the scores at admission and the patients were followed up till the outcome. Outcome was defined as 5-day, 10-day and 15-day mortality after presentation. Predictive performance was expressed as discrimination (AUC). Subsequently, sensitivity and specificity were calculated. OBSERVATION: A total of 100 patients were included in the study, of whom 17 died within 5 days and 37 died within 10 days and 30 died within 15 days after presentation. q SOFA had the best performance, compared to NEWS (5 day auc : .668, .621, 10-day auc: .580, .569, 15-day auc: .625, .511) with q SOFA having sensitivity of 90.2% while that of news being 95.1% where as specificity of q SOFA is 40.7% and that of NEWS is 47.5%. CONCLUSION: qSOFA score is more accurate in predicting 5, 10 and 15-day mortality than NEWS score in COVID 19 patients. In resource limited settings, it is an inexpensive and simple tool for early identification of high risk COVID 19 patients.


Subject(s)
COVID-19 , Early Warning Score , Sepsis , COVID-19/diagnosis , Hospital Mortality , Humans , Intensive Care Units , Organ Dysfunction Scores , Prognosis , Retrospective Studies , Sepsis/diagnosis
3.
Nurs Open ; 9(1): 519-526, 2022 01.
Article in English | MEDLINE | ID: covidwho-1594117

ABSTRACT

AIM: Early warning scores are commonly used in hospital settings, but little is known about their use in care homes. This study aimed to evaluate the impacts of National Early Warning Scores alongside other measures in this setting. DESIGN: Convergent parallel design. METHODS: Quantitative data from 276 care home residents from four care homes were used to analyse the relationship between National Early Warning Scores score, resident outcome and functional daily living (Barthel ADL (Barthel Index for Activities of Daily Living)) and Rockwood (frailty). Interviews with care home staff (N = 13) and care practitioners (N = 4) were used to provide qualitative data. RESULTS: A statistically significant link between National Early Warning Scores (p = .000) and Barthel ADL (p = .013) score and hospital admissions was found, while links with Rockwood were insignificant (p = .551). Care home staff reported many benefits of National Early Warning Scores, including improved communication, improved decision-making and role empowerment. Although useful, due to the complexity of the resident population's existing health conditions, National Early Warning Scores alone could not act as a diagnostic tool.


Subject(s)
Early Warning Score , Activities of Daily Living , Hospitalization , Humans , Referral and Consultation
4.
J Med Internet Res ; 23(2): e24246, 2021 02 10.
Article in English | MEDLINE | ID: covidwho-1573886

ABSTRACT

BACKGROUND: Predicting early respiratory failure due to COVID-19 can help triage patients to higher levels of care, allocate scarce resources, and reduce morbidity and mortality by appropriately monitoring and treating the patients at greatest risk for deterioration. Given the complexity of COVID-19, machine learning approaches may support clinical decision making for patients with this disease. OBJECTIVE: Our objective is to derive a machine learning model that predicts respiratory failure within 48 hours of admission based on data from the emergency department. METHODS: Data were collected from patients with COVID-19 who were admitted to Northwell Health acute care hospitals and were discharged, died, or spent a minimum of 48 hours in the hospital between March 1 and May 11, 2020. Of 11,525 patients, 933 (8.1%) were placed on invasive mechanical ventilation within 48 hours of admission. Variables used by the models included clinical and laboratory data commonly collected in the emergency department. We trained and validated three predictive models (two based on XGBoost and one that used logistic regression) using cross-hospital validation. We compared model performance among all three models as well as an established early warning score (Modified Early Warning Score) using receiver operating characteristic curves, precision-recall curves, and other metrics. RESULTS: The XGBoost model had the highest mean accuracy (0.919; area under the curve=0.77), outperforming the other two models as well as the Modified Early Warning Score. Important predictor variables included the type of oxygen delivery used in the emergency department, patient age, Emergency Severity Index level, respiratory rate, serum lactate, and demographic characteristics. CONCLUSIONS: The XGBoost model had high predictive accuracy, outperforming other early warning scores. The clinical plausibility and predictive ability of XGBoost suggest that the model could be used to predict 48-hour respiratory failure in admitted patients with COVID-19.


Subject(s)
COVID-19/physiopathology , Hospitalization , Intubation, Intratracheal/statistics & numerical data , Machine Learning , Respiration, Artificial/statistics & numerical data , Respiratory Insufficiency/epidemiology , Aged , COVID-19/complications , Clinical Decision Rules , Early Warning Score , Emergency Service, Hospital , Female , Hospitals , Humans , Logistic Models , Male , Middle Aged , Patient Admission , ROC Curve , Respiratory Insufficiency/etiology , Retrospective Studies , SARS-CoV-2 , Triage
5.
J Med Virol ; 94(1): 272-278, 2022 01.
Article in English | MEDLINE | ID: covidwho-1544342

ABSTRACT

Data pertaining to risk factor analysis in coronavirus disease 2019 (COVID-19) is confounded by the lack of data from an ethnically diverse population. In addition, there is a lack of data for young adults. This study was conducted to assess risk factors predicting COVID-19 severity and mortality in hospitalized young adults. A retrospective observational study was conducted at two centers from China and India on COVID-19 patients aged 20-50 years. Regression analysis to predict adverse outcomes was performed using parameters including age, sex, country of origin, hospitalization duration, comorbidities, lymphocyte count, and National Early Warning Score 2 (NEWS2) score at admission. A total of 420 patients (172 East Asians and 248 South Asians) were included. The predictive model for intensive care unit (ICU) admission with variables NEWS2 Category II and higher, diabetes mellitus, liver dysfunction, and low lymphocyte counts had an area under the curve (AUC) value of 0.930 with a sensitivity of 0.931 and a specificity of 0.784. The predictive model for mortality with NEWS2 Category III, cancer, and decreasing lymphocyte count had an AUC value of 0.883 with a sensitivity of 0.903 and a specificity of 0.701. A combined predictive model with bronchial asthma and low lymphocyte count, in contrast, had an AUC value of 0.768 with a sensitivity of 0.828 and a specificity of 0.719 for NEWS2 score (5 or above) at presentation. NEWS2 supplemented with comorbidity profile and lymphocyte count could help identify hospitalized young adults at risk of adverse COVID-19 outcomes.


Subject(s)
COVID-19/diagnosis , COVID-19/ethnology , Adult , COVID-19/mortality , COVID-19/physiopathology , China , Comorbidity , Disease Progression , Early Warning Score , Female , Hospitalization , Humans , India , Intensive Care Units , Lymphocyte Count , Male , Middle Aged , Prognosis , Retrospective Studies , Risk Factors , Severity of Illness Index , Young Adult
6.
Emerg Med J ; 38(12): 901-905, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1495501

ABSTRACT

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.


Subject(s)
COVID-19/diagnosis , Critical Illness , Early Warning Score , Adult , Aged , Aged, 80 and over , COVID-19/classification , Female , Humans , Intensive Care Units , Male , Middle Aged , Patient Admission , Predictive Value of Tests , ROC Curve , Triage
7.
Br J Radiol ; 94(1126): 20210187, 2021 Oct 01.
Article in English | MEDLINE | ID: covidwho-1430508

ABSTRACT

OBJECTIVES: The World Health Organization (WHO) has declared coronavirus disease 2019 (COVID-19) as pandemic in March 2020. Currently there is no specific effective treatment for COVID-19. The major cause of death in COVID-19 is severe pneumonia leading to respiratory failure. Radiation in low doses (<100 cGy) has been known for its anti-inflammatory effect and therefore, low dose radiation therapy (LDRT) to lungs can potentially mitigate the severity of pneumonia and reduce mortality. We conducted a pilot trial to study the feasibility and clinical efficacy of LDRT to lungs in the management of patients with COVID-19. METHODS: From June to Aug 2020, we enrolled 10 patients with COVID-19 having moderate to severe risk disease [National Early Warning Score (NEWS) of ≥5]. Patients were treated as per the standard COVID-19 management guidelines along with LDRT to both lungs with a dose of 70cGy in single fraction. Response assessment was done based on the clinical parameters using the NEWS. RESULTS: All patients completed the prescribed treatment. Nine patients had complete clinical recovery mostly within a period ranging from 3 to 7 days. One patient, who was a known hypertensive, showed clinical deterioration and died 24 days after LDRT. No patients showed the signs of acute radiation toxicity. CONCLUSION: The results of our pilot study suggest that LDRT is feasible in COVID-19 patients having moderate to severe disease. Its clinical efficacy may be tested by conducting randomized controlled trials. ADVANCES IN KNOWLEDGE: LDRT has shown promising results in COVID-19 pneumonia and should be researched further through randomized controlled trials.


Subject(s)
COVID-19/radiotherapy , Pneumonia, Viral/radiotherapy , Adult , Aged , Early Warning Score , Feasibility Studies , Female , Humans , Male , Middle Aged , Pandemics , Pilot Projects , Pneumonia, Viral/virology , Radiotherapy Dosage , SARS-CoV-2
8.
BMJ Open ; 11(9): e045579, 2021 09 13.
Article in English | MEDLINE | ID: covidwho-1406655

ABSTRACT

OBJECTIVES: To investigate whether National Early Warning Scores (NEWS/NEWS2) could contribute to COVID-19 surveillance in care homes. SETTING: 460 care home units using the same software package to collect data on residents, from 46 local authority areas in England. PARTICIPANTS: 6464 care home residents with at least one NEWS recording. EXPOSURE MEASURE: 29 656 anonymised person-level NEWS from 29 December 2019 to 20 May 2020 with component physiological measures: systolic blood pressure, respiratory rate, pulse rate, temperature and oxygen saturation. Baseline values for each measure calculated using 80th and 20th centile scores before March 2020. OUTCOME MEASURE: Cross-correlation comparison of time series with Office for National Statistics weekly reported registered deaths of care home residents where COVID-19 was the underlying cause of death, and all other deaths (excluding COVID-19) up to 10 May 2020. RESULTS: Deaths due to COVID-19 were registered from 23 March 2020 in the local authority areas represented in the study. Between 23 March 2020 and 10 May 2020, there were 5753 deaths (1532 involving COVID-19 and 4221 other causes). We observed a rise in the proportion of above-baseline NEWS beginning 16 March 2020, followed 2 weeks later by an increase in registered deaths (cross-correlation of r=0.82, p<0.05 for a 2 week lag) in corresponding local authorities. The proportion of above-baseline oxygen saturation, respiratory rate and temperature measurements also increased approximately 2 weeks before peaks in deaths. CONCLUSIONS: NEWS could contribute to COVID-19 disease surveillance in care homes during the pandemic. Oxygen saturation, respiratory rate and temperature could be prioritised as they appear to signal rise in mortality almost as well as NEWS. This study reinforces the need to collate data from care homes, to monitor and protect residents' health. Further work using individual level outcome data is needed to evaluate the role of NEWS in the early detection of resident illness.


Subject(s)
COVID-19 , Early Warning Score , England/epidemiology , Humans , Pandemics , SARS-CoV-2
9.
BMC Health Serv Res ; 21(1): 957, 2021 Sep 13.
Article in English | MEDLINE | ID: covidwho-1405306

ABSTRACT

BACKGROUND: The novel coronavirus SARS-19 produces 'COVID-19' in patients with symptoms. COVID-19 patients admitted to the hospital require early assessment and care including isolation. The National Early Warning Score (NEWS) and its updated version NEWS2 is a simple physiological scoring system used in hospitals, which may be useful in the early identification of COVID-19 patients. We investigate the performance of multiple enhanced NEWS2 models in predicting the risk of COVID-19. METHODS: Our cohort included unplanned adult medical admissions discharged over 3 months (11 March 2020 to 13 June 2020 ) from two hospitals (YH for model development; SH for external model validation). We used logistic regression to build multiple prediction models for the risk of COVID-19 using the first electronically recorded NEWS2 within ± 24 hours of admission. Model M0' included NEWS2; model M1' included NEWS2 + age + sex, and model M2' extends model M1' with subcomponents of NEWS2 (including diastolic blood pressure + oxygen flow rate + oxygen scale). Model performance was evaluated according to discrimination (c statistic), calibration (graphically), and clinical usefulness at NEWS2 ≥ 5. RESULTS: The prevalence of COVID-19 was higher in SH (11.0 %=277/2520) than YH (8.7 %=343/3924) with a higher first NEWS2 scores ( SH 3.2 vs YH 2.8) but similar in-hospital mortality (SH 8.4 % vs YH 8.2 %). The c-statistics for predicting the risk of COVID-19 for models M0',M1',M2' in the development dataset were: M0': 0.71 (95 %CI 0.68-0.74); M1': 0.67 (95 %CI 0.64-0.70) and M2': 0.78 (95 %CI 0.75-0.80)). For the validation datasets the c-statistics were: M0' 0.65 (95 %CI 0.61-0.68); M1': 0.67 (95 %CI 0.64-0.70) and M2': 0.72 (95 %CI 0.69-0.75) ). The calibration slope was similar across all models but Model M2' had the highest sensitivity (M0' 44 % (95 %CI 38-50 %); M1' 53 % (95 %CI 47-59 %) and M2': 57 % (95 %CI 51-63 %)) and specificity (M0' 75 % (95 %CI 73-77 %); M1' 72 % (95 %CI 70-74 %) and M2': 76 % (95 %CI 74-78 %)) for the validation dataset at NEWS2 ≥ 5. CONCLUSIONS: Model M2' appears to be reasonably accurate for predicting the risk of COVID-19. It may be clinically useful as an early warning system at the time of admission especially to triage large numbers of unplanned hospital admissions.


Subject(s)
COVID-19 , Early Warning Score , Adult , Hospitals , Humans , Patient Admission , Retrospective Studies , SARS-CoV-2
10.
Fam Pract ; 38(Suppl 1): i3-i8, 2021 Aug 27.
Article in English | MEDLINE | ID: covidwho-1376297

ABSTRACT

BACKGROUND: Primary care has played a central role in the community response to the coronavirus disease-19 (COVID-19) pandemic. The use of the National Early Warning Score 2 (NEWS2) has been advocated as a tool to guide escalation decisions in the community. The performance of this tool applied in this context is unclear. AIM: To evaluate the process of escalation of care to the hospital within a primary care assessment centre (PCAC) designed to assess patients with suspected COVID-19 in the community. DESIGN AND SETTING: A retrospective service evaluation of all adult patients assessed between 30 March and 22 April 2020 within a COVID-19 primary care assessment centre within Sandwell West Birmingham CCG. METHOD: A database of patient demographics, healthcare interactions and physiological observations was constructed. NEWS2 and CRB65 scores were calculated retrospectively. The proportion of patients escalated was within risk groups defined by NHSE guidelines in place during the evaluation period was determined. RESULTS: A total of 150 patients were identified. Following assessment 13.3% (n = 20) patients were deemed to require escalation. The proportion of patients escalated with a NEWS2 greater than or equal to 3 was 46.9% (95% CI 30.8-63.6%). The proportion of patients escalated to secondary care using NHSE defined risk thresholds was 0% in the green group, 22% (n = 4) in the amber group, and 81.3% (n = 13) in the red group. CONCLUSION: Clinical decisions to escalate care to the hospital did not follow initial guidance written for the COVID-19 outbreak but were demonstrated to be safe.


In most cases, coronavirus disease-19 (COVID-19) is a mild illness that resolves on its own. Some patients develop severe disease requiring hospital treatment. Identifying which patients are likely to need hospital treatment is a challenge. Many GP practices have developed specific services designed to assess patients with suspected COVID-19 and establish whether hospital treatment is necessary. We evaluated a service providing this function in Birmingham. We examined the care pathway of 150 patients assessed within the service to established factors associated with the need for hospital assessment. We found a national decision tool designed to aid the process was a poor descriptor of what happened in practice.


Subject(s)
COVID-19/epidemiology , Early Warning Score , Hospitalization/statistics & numerical data , Primary Health Care , Referral and Consultation/statistics & numerical data , Adult , England/epidemiology , Female , Guideline Adherence , Health Services Research , Humans , Male , Middle Aged , Pandemics , Retrospective Studies , Risk Assessment , SARS-CoV-2
12.
BMJ Open ; 11(7): e045469, 2021 07 27.
Article in English | MEDLINE | ID: covidwho-1329054

ABSTRACT

BACKGROUND: The COVID-19 pandemic has taken a heavy toll on the care home sector, with residents accounting for up to half of all deaths in Europe. The response to acute illness in care homes plays a particularly important role in the care of residents during a pandemic. Digital recording of a National Early Warning Score (NEWS), which involves the measurement of physical observations, started in care homes in one area of England in 2016. Implementation of a NEWS intervention (including equipment, training and support) was accelerated early in the pandemic, despite limited evidence for its use in the care home setting. OBJECTIVES: To understand how a NEWS intervention has been used in care homes in one area of North-East England during the COVID-19 pandemic, and how it has influenced resident care, from the perspective of stakeholders involved in care delivery and commissioning. METHODS: A qualitative interview study with care home (n=10) and National Health Service (n=7) staff. Data were analysed using thematic analysis. RESULTS: Use of the NEWS intervention in care homes in this area accelerated during the COVID-19 pandemic. Stakeholders felt that NEWS, and its associated education and support package, improved the response of care homes and healthcare professionals to deterioration in residents' health during the pandemic. Healthcare professionals valued the ability to remotely monitor resident observations, which facilitated triage and treatment decisions. Care home staff felt empowered by NEWS, providing a common clinical language to communicate concerns with external services, acting as an adjunct to staff intuition of resident deterioration. CONCLUSIONS: The NEWS intervention formed an important part of the care home response to COVID-19 in the study area. Positive staff perceptions now need to be supplemented with data on the impact on resident health and well-being, workload, and service utilisation, during the pandemic and beyond.


Subject(s)
COVID-19 , Early Warning Score , England/epidemiology , Europe , Humans , Nursing Homes , Pandemics , SARS-CoV-2 , State Medicine
13.
Infection ; 50(2): 359-370, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1316346

ABSTRACT

PURPOSE: While more advanced COVID-19 necessitates medical interventions and hospitalization, patients with mild COVID-19 do not require this. Identifying patients at risk of progressing to advanced COVID-19 might guide treatment decisions, particularly for better prioritizing patients in need for hospitalization. METHODS: We developed a machine learning-based predictor for deriving a clinical score identifying patients with asymptomatic/mild COVID-19 at risk of progressing to advanced COVID-19. Clinical data from SARS-CoV-2 positive patients from the multicenter Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) were used for discovery (2020-03-16 to 2020-07-14) and validation (data from 2020-07-15 to 2021-02-16). RESULTS: The LEOSS dataset contains 473 baseline patient parameters measured at the first patient contact. After training the predictor model on a training dataset comprising 1233 patients, 20 of the 473 parameters were selected for the predictor model. From the predictor model, we delineated a composite predictive score (SACOV-19, Score for the prediction of an Advanced stage of COVID-19) with eleven variables. In the validation cohort (n = 2264 patients), we observed good prediction performance with an area under the curve (AUC) of 0.73 ± 0.01. Besides temperature, age, body mass index and smoking habit, variables indicating pulmonary involvement (respiration rate, oxygen saturation, dyspnea), inflammation (CRP, LDH, lymphocyte counts), and acute kidney injury at diagnosis were identified. For better interpretability, the predictor was translated into a web interface. CONCLUSION: We present a machine learning-based predictor model and a clinical score for identifying patients at risk of developing advanced COVID-19.


Subject(s)
COVID-19 , Early Warning Score , Area Under Curve , COVID-19/diagnosis , Humans , Machine Learning , Retrospective Studies , SARS-CoV-2
14.
Eur J Clin Invest ; 51(12): e13626, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1273086

ABSTRACT

BACKGROUND: Fever-7 is a test evaluating host mRNA expression levels of IFI27, JUP, LAX, HK3, TNIP1, GPAA1 and CTSB in blood able to detect viral infections. This test has been validated mostly in hospital settings. Here we have evaluated Fever-7 to identify the presence of respiratory viral infections in a Community Health Center. METHODS: A prospective study was conducted in the "Servicio de Urgencias de Atención Primaria" in Salamanca, Spain. Patients with clinical signs of respiratory infection and at least one point in the National Early Warning Score were recruited. Fever-7 mRNAs were profiled on a Nanostring nCounter® SPRINT instrument from blood collected upon patient enrolment. Viral diagnosis was performed on nasopharyngeal aspirates (NPAs) using the Biofire-RP2 panel. RESULTS: A respiratory virus was detected in the NPAs of 66 of the 100 patients enrolled. Median National Early Warning Score was 7 in the group with no virus detected and 6.5 in the group with a respiratory viral infection (P > .05). The Fever-7 score yielded an overall AUC of 0.81 to predict a positive viral syndromic test. The optimal operating point for the Fever-7 score yielded a sensitivity of 82% with a specificity of 71%. Multivariate analysis showed that Fever-7 was a robust marker of viral infection independently of age, sex, major comorbidities and disease severity at presentation (OR [CI95%], 3.73 [2.14-6.51], P < .001). CONCLUSIONS: Fever-7 is a promising host immune mRNA signature for the early identification of a respiratory viral infection in the community.


Subject(s)
RNA, Messenger/blood , Respiratory Tract Infections/diagnosis , Virus Diseases/diagnosis , Adaptor Proteins, Vesicular Transport/genetics , Aged , Aged, 80 and over , Cathepsin B/genetics , DNA-Binding Proteins/genetics , Early Warning Score , Female , Gene Expression Profiling , Humans , Male , Membrane Glycoproteins/genetics , Membrane Proteins/genetics , Nasopharynx/virology , Respiratory Tract Infections/blood , Respiratory Tract Infections/genetics , Transcriptome , Virus Diseases/blood , Virus Diseases/genetics , gamma Catenin/genetics
15.
J Infect Dev Ctries ; 15(5): 639-345, 2021 05 31.
Article in English | MEDLINE | ID: covidwho-1262631

ABSTRACT

Venous thromboembolism (VTE) represents an important clinical complication of patients with SARS-CoV-2 infection, and high plasma D-dimer levels could suggest a higher risk of hypercoagulability. We aimed to analyse if laboratory exams, risk assessment scores, comorbidity scores were useful in predicting the VTE in SARS-CoV-2 patients admitted in internal medicine (IM). We evaluated 49 older adults with suspected VTE analysing history and blood chemistry, besides we calculated the Padua Prediction Score, the modified early warning scoring (MEWS) and the modified Elixhauser index (mEI). All patients underwent venous color-doppler ultrasounds of the lower limbs. Out of the 49 patients enrolled (mean age 79.3±14 years), 10 (20.4%) had deep vein thrombosis (DVT), and they were more frequently female (80% vs 20%, p = 0.04). We could not find any association with the Padua Prediction Score, the MEWS, and the mEI. D-dimer plasma levels were also not associated with DVT. In elderly people hospitalized with SARS-CoV-2 infection hospitalized in IM, our data, although limited by the sample size, suggest that prediction and diagnosis of VTE is difficult, due to lack of precise biomarkers and scores.


Subject(s)
COVID-19/complications , Venous Thromboembolism/diagnosis , Aged , Aged, 80 and over , Biomarkers/blood , Case-Control Studies , Early Warning Score , Female , Fibrin Fibrinogen Degradation Products/metabolism , Humans , Lower Extremity/diagnostic imaging , Male , Middle Aged , Retrospective Studies , Risk Assessment , SARS-CoV-2 , Ultrasonography, Doppler, Color , Venous Thromboembolism/blood , Venous Thromboembolism/etiology
16.
Medicine (Baltimore) ; 100(19): e25917, 2021 May 14.
Article in English | MEDLINE | ID: covidwho-1262274

ABSTRACT

ABSTRACT: The coronavirus disease (COVID-19) has become a global pandemic. Invasive mechanical ventilation is recommended for the management of patients with COVID-19 who have severe respiratory symptoms. However, various complications can develop after its use. The efficient and appropriate management of patients requires the identification of factors associated with an aggravation of COVID-19 respiratory symptoms to a degree where invasive mechanical ventilation becomes necessary, thereby enabling clinicians to prevent such ventilation. This retrospective study included 138 inpatients with COVID-19 at a tertiary hospital. We evaluated the differences in the demographic and clinical data between 27 patients who required invasive mechanical ventilation and 111 patients who did not. Multivariate logistic regression analysis indicated that the duration of fever, national early warning score (NEWS), and lactate dehydrogenase (LDH) levels on admission were significantly associated with invasive mechanical ventilation in this cohort. The optimal cut-off values were: fever duration ≥1 day (sensitivity 100.0%, specificity 54.95%), NEWS ≥7 (sensitivity 72.73%, specificity 92.52%), and LDH >810 mg/dL (sensitivity 56.0%, specificity 90.29%). These findings can assist in the early identification of patients who will require invasive mechanical ventilation. Further studies in larger patient populations are recommended to validate our findings.


Subject(s)
COVID-19/physiopathology , Early Warning Score , Respiration, Artificial/statistics & numerical data , Adult , Age Factors , Aged , Aged, 80 and over , Antiviral Agents/therapeutic use , COVID-19/drug therapy , Female , Fever/physiopathology , Humans , Hydroxychloroquine/therapeutic use , L-Lactate Dehydrogenase/blood , Logistic Models , Male , Middle Aged , Pandemics , Real-Time Polymerase Chain Reaction , Republic of Korea , Retrospective Studies , Risk Assessment , Risk Factors , SARS-CoV-2 , Sex Factors , Socioeconomic Factors , Tertiary Care Centers , Young Adult
17.
Emerg Med J ; 38(8): 587-593, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1261191

ABSTRACT

BACKGROUND: The WHO and National Institute for Health and Care Excellence recommend various triage tools to assist decision-making for patients with suspected COVID-19. We aimed to compare the accuracy of triage tools for predicting severe illness in adults presenting to the ED with suspected COVID-19. METHODS: We undertook a mixed prospective and retrospective observational cohort study in 70 EDs across the UK. We collected data from people attending with suspected COVID-19 and used presenting data to determine the results of assessment with the WHO algorithm, National Early Warning Score version 2 (NEWS2), CURB-65, CRB-65, Pandemic Modified Early Warning Score (PMEWS) and the swine flu adult hospital pathway (SFAHP). We used 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome. RESULTS: We analysed data from 20 891 adults, of whom 4611 (22.1%) died or received organ support (primary outcome), with 2058 (9.9%) receiving organ support and 2553 (12.2%) dying without organ support (secondary outcomes). C-statistics for the primary outcome were: CURB-65 0.75; CRB-65 0.70; PMEWS 0.77; NEWS2 (score) 0.77; NEWS2 (rule) 0.69; SFAHP (6-point rule) 0.70; SFAHP (7-point rule) 0.68; WHO algorithm 0.61. All triage tools showed worse prediction for receipt of organ support and better prediction for death without organ support. At the recommended threshold, PMEWS and the WHO criteria showed good sensitivity (0.97 and 0.95, respectively) at the expense of specificity (0.30 and 0.27, respectively). The NEWS2 score showed similar sensitivity (0.96) and specificity (0.28) when a lower threshold than recommended was used. CONCLUSION: CURB-65, PMEWS and the NEWS2 score provide good but not excellent prediction for adverse outcome in suspected COVID-19, and predicted death without organ support better than receipt of organ support. PMEWS, the WHO criteria and NEWS2 (using a lower threshold than usually recommended) provide good sensitivity at the expense of specificity. TRIAL REGISTRATION NUMBER: ISRCTN56149622.


Subject(s)
COVID-19/therapy , Emergency Service, Hospital , Pneumonia, Viral/therapy , Triage/methods , Aged , COVID-19/epidemiology , Early Warning Score , Female , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , Predictive Value of Tests , Prognosis , Prospective Studies , Retrospective Studies , SARS-CoV-2 , United Kingdom
19.
Emerg Med J ; 38(7): 543-548, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1238541

ABSTRACT

INTRODUCTION: COVID-19 has an unpredictable clinical course, so prognostic biomarkers would be invaluable when triaging patients on admission to hospital. Many biomarkers have been suggested using large observational datasets but sample timing is crucial to ensure prognostic relevance. The DISCOVER study prospectively recruited patients with COVID-19 admitted to a UK hospital and analysed a panel of putative prognostic biomarkers on the admission blood sample to identify markers of poor outcome. METHODS: Consecutive patients admitted to hospital with proven or clinicoradiological suspected COVID-19 were consented. Admission bloods were extracted from the clinical laboratory. A panel of biomarkers (interleukin-6 (IL-6), soluble urokinase plasminogen activator receptor (suPAR), Krebs von den Lungen 6, troponin, ferritin, lactate dehydrogenase, B-type natriuretic peptide, procalcitonin) were performed in addition to routinely performed markers (C reactive protein (CRP), neutrophils, lymphocytes, neutrophil:lymphocyte ratio). Age, National Early Warning Score (NEWS2), CURB-65 and radiographic severity score on initial chest radiograph were included as comparators. All biomarkers were tested in logistic regression against a composite outcome of non-invasive ventilation, intensive care admission or death, with area under the curve (AUC) (figures calculated). RESULTS: 187 patients had 28-day outcomes at the time of analysis. CRP (AUC: 0.69, 95% CI: 0.59 to 0.78), lymphocyte count (AUC: 0.62, 95% CI: 0.53 to 0.72) and other routine markers did not predict the primary outcome. IL-6 (AUC: 0.77, 0.65 to 0.88) and suPAR (AUC: 0.81, 0.72 to 0.88) showed some promise, but simple clinical features alone such as NEWS2 score (AUC: 0.70, 0.60 to 0.79) or age (AUC: 0.70, 0.62 to 0.77) performed nearly as well. DISCUSSION: Admission blood biomarkers have only moderate predictive value for predicting COVID-19 outcomes, while simple clinical features such as age and NEWS2 score outperform many biomarkers. IL-6 and suPAR had the best performance, and further studies should focus on the additive value of these biomarkers to routine care.


Subject(s)
Biomarkers/blood , COVID-19/mortality , Age Factors , Aged , Cohort Studies , Early Warning Score , Female , Hospitalization , Humans , Interleukin-6/blood , Male , Middle Aged , Prognosis , Receptors, Urokinase Plasminogen Activator/blood , United Kingdom/epidemiology
20.
Infection ; 49(5): 1033-1038, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1220597

ABSTRACT

PURPOSE: Clinical scores to rapidly assess the severity illness of Coronavirus Disease 2019 (COVID-19) could be considered of help for clinicians. Recently, a specific score (named COVID-GRAM) for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection, based on a nationwide Chinese cohort, has been proposed. We routinely applied the National Early Warning Score 2 (NEWS2) to predict critical COVID-19. Aim of this study is to compare NEWS2 and COVID-GRAM score. METHODS: We retrospectively analysed data of 121 COVID-19 patients admitted in two Clinics of Infectious Diseases in the Umbria region, Italy. The primary outcome was critical COVID-19 illness defined as admission to the intensive care unit, invasive ventilation, or death. Accuracy of the scores was evaluated with the area under the receiver-operating characteristic curve (AUROC). Differences between scores were confirmed used Hanley-McNeil test. RESULTS: The NEWS2 AUROC curve measured 0.87 (standard error, SE 0.03; 95% CI 0.80-0.93; p < 0.0001). The COVID-GRAM score AUROC curve measured 0.77 (SE 0.04; 95% CI 0.68-0.85; p < 0.0001). Hanley-McNeil test showed that NEWS2 better predicted severe COVID-19 (Z = 2.03). CONCLUSIONS: The NEWS2 showed superior accuracy to COVID-GRAM score for prediction of critical COVID-19 illness.


Subject(s)
COVID-19 , Early Warning Score , Critical Illness , Humans , Retrospective Studies , SARS-CoV-2
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