223 Evaluation of Pneumonia Scores in Patients Hospitalized for COVID-19-Related Dyspnea

Ortiz, Damaris; Díaz, Aurora de la Peña; Almasary, A.; Rafique, Zubaid

doi:10.1016/j.annemergmed.2020.09.236

Cited by 2 publications

(4 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…61,62 Scores like qSOFA and NEWS2 rely on a classic sepsis presentation, which may hinder their performance for predicting poor outcomes from COVID-19. 40,47,63 The Shock Index also prioritizes vital signs that may not be as strongly While imputation can be used to address missing data, we could not reliably perform imputation of GCS due to its high proportion of missingness; therefore, we assumed missing was normal. Although patients who had at least one GCS were older with a greater degree of comorbidities, there were few differences in patient outcomes.…”

Section: Discussionmentioning

confidence: 99%

“…For example, qSOFA may have suffered from poor performance because it incorporates hemodynamic instability and altered mentation, symptoms which are not as commonly reported among COVID‐19 patients at ED presentation 61,62 . Scores like qSOFA and NEWS2 rely on a classic sepsis presentation, which may hinder their performance for predicting poor outcomes from COVID‐19 40,47,63 . The Shock Index also prioritizes vital signs that may not be as strongly associated with poor outcomes in COVID‐19 patients.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Performance of point‐of‐care severity scores to predict prognosis in patients admitted through the emergency department with COVID‐19

Prasad

Correia

Fang

et al. 2023

Journal of Hospital Medicine

View full text Add to dashboard Cite

Background Identifying COVID‐19 patients at the highest risk of poor outcomes is critical in emergency department (ED) presentation. Sepsis risk stratification scores can be calculated quickly for COVID‐19 patients but have not been evaluated in a large cohort. Objective To determine whether well‐known risk scores can predict poor outcomes among hospitalized COVID‐19 patients. Designs, Settings, and Participants A retrospective cohort study of adults presenting with COVID‐19 to 156 Hospital Corporation of America (HCA) Healthcare EDs, March 2, 2020, to February 11, 2021. Intervention Quick Sequential Organ Failure Assessment (qSOFA), Shock Index, National Early Warning System‐2 (NEWS2), and quick COVID‐19 Severity Index (qCSI) at presentation. Main Outcome and Measures The primary outcome was in‐hospital mortality. Secondary outcomes included intensive care unit (ICU) admission, mechanical ventilation, and vasopressors receipt. Patients scored positive with qSOFA ≥ 2, Shock Index > 0.7, NEWS2 ≥ 5, and qCSI ≥ 4. Test characteristics and area under the receiver operating characteristics curves (AUROCs) were calculated. Results We identified 90,376 patients with community‐acquired COVID‐19 (mean age 64.3 years, 46.8% female). 17.2% of patients died in‐hospital, 28.6% went to the ICU, 13.7% received mechanical ventilation, and 13.6% received vasopressors. There were 3.8% qSOFA‐positive, 45.1% Shock Index‐positive, 49.8% NEWS2‐positive, and 37.6% qCSI‐positive at ED‐triage. NEWS2 exhibited the highest AUROC for in‐hospital mortality (0.593, confidence interval [CI]: 0.588–0.597), ICU admission (0.602, CI: 0.599–0.606), mechanical ventilation (0.614, CI: 0.610–0.619), and vasopressor receipt (0.600, CI: 0.595–0.604). Conclusions Sepsis severity scores at presentation have low discriminative power to predict outcomes in COVID‐19 patients and are not reliable for clinical use. Severity scores should be developed using features that accurately predict poor outcomes among COVID‐19 patients to develop more effective risk‐based triage.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Performance of point‐of‐care severity scores to predict prognosis in patients admitted through the emergency department with COVID‐19

Prasad

Correia

Fang

et al. 2023

Journal of Hospital Medicine

View full text Add to dashboard Cite

show abstract

“…Considering the effects of COVID-19 on respiratory function are more marked than its cardiovascular impacts, 12 it is unsurprising that most of the studies listed in online supplemental table 1 show respiratory parameters such as RR in CURB-65 to be independently more indicative of mortality than blood pressure and confusion, which are more related to haemodynamics. qSOFA’s focus on blood pressure and mental state may explain its lower AUROC and poorer predictive performance.…”

Section: Discussionmentioning

confidence: 99%

“…Ortiz et al 12 demonstrated A-DROP, a modified version of CURB-65, to provide more accurate mortality prediction than Pneumonia Severity Index (PSI), CURB-65, CRB-65, SMART-COP, qSOFA and National Early Warning Score 2 (NEWS2). Its superior discrimination may be due to its more accurate respiratory function evaluation (oxygen saturation [SpO 2 ] >90% / arterial oxygen tension [PaO2] <60 mm Hg in A-DROP vs respiratory rate ≥30/min in CURB-65).…”

Section: Discussionmentioning

confidence: 99%

Evaluating risk stratification scoring systems to predict mortality in patients with COVID-19

Chu

Alharahsheh

Garg

et al. 2021

BMJ Health Care Inform

View full text Add to dashboard Cite

BackgroundThe COVID-19 pandemic has necessitated efficient and accurate triaging of patients for more effective allocation of resources and treatment.ObjectivesThe objectives are to investigate parameters and risk stratification tools that can be applied to predict mortality within 90 days of hospital admission in patients with COVID-19.MethodsA literature search of original studies assessing systems and parameters predicting mortality of patients with COVID-19 was conducted using MEDLINE and EMBASE.Results589 titles were screened, and 76 studies were found investigating the prognostic ability of 16 existing scoring systems (area under the receiving operator curve (AUROC) range: 0.550–0.966), 38 newly developed COVID-19-specific prognostic systems (AUROC range: 0.6400–0.9940), 15 artificial intelligence (AI) models (AUROC range: 0.840–0.955) and 16 studies on novel blood parameters and imaging.DiscussionCurrent scoring systems generally underestimate mortality, with the highest AUROC values found for APACHE II and the lowest for SMART-COP. Systems featuring heavier weighting on respiratory parameters were more predictive than those assessing other systems. Cardiac biomarkers and CT chest scans were the most commonly studied novel parameters and were independently associated with mortality, suggesting potential for implementation into model development. All types of AI modelling systems showed high abilities to predict mortality, although none had notably higher AUROC values than COVID-19-specific prediction models. All models were found to have bias, including lack of prospective studies, small sample sizes, single-centre data collection and lack of external validation.ConclusionThe single parameters established within this review would be useful to look at in future prognostic models in terms of the predictive capacity their combined effect may harness.

show abstract

223 Evaluation of Pneumonia Scores in Patients Hospitalized for COVID-19-Related Dyspnea

Cited by 2 publications

References 0 publications

Performance of point‐of‐care severity scores to predict prognosis in patients admitted through the emergency department with COVID‐19

Performance of point‐of‐care severity scores to predict prognosis in patients admitted through the emergency department with COVID‐19

Evaluating risk stratification scoring systems to predict mortality in patients with COVID-19

Contact Info

Product

Resources

About