Development and Internal Validation of a Prediction Model to Risk Stratify Children With Suspected Community-Acquired Pneumonia

Abstract Background Although community-acquired pneumonia (CAP) is one of the most common infections in children, no tools exist to risk stratify children with suspected CAP. We developed and validated a prediction model to risk stratify and inform hospitalization decisions in children with suspected CAP. Methods We performed a prospective cohort study of children aged 3 months to 18 years with suspected CAP in a pediatric emergency department. Primary outcome was disease severity, defined as mild (discharge home or hospitalization for <24 hours with no oxygen or intravenous [IV] fluids), moderate (hospitalization <24 hours with oxygen or IV fluids, or hospitalization >24 hours), or severe (intensive care unit stay for >24 hours, septic shock, vasoactive agents, positive-pressure ventilation, chest drainage, extracorporeal membrane oxygenation, or death). Ordinal logistic regression and bootstrapped backwards selection were used to derive and internally validate our model. Results Of 1128 children, 371 (32.9%) developed moderate disease and 48 (4.3%) severe disease. Severity models demonstrated excellent discrimination (optimism-corrected c-indices of 0.81) and outstanding calibration. Severity predictors in the final model included respiratory rate, systolic blood pressure, oxygenation, retractions, capillary refill, atelectasis or pneumonia on chest radiograph, and pleural effusion. Conclusions We derived and internally validated a score that accurately predicts disease severity in children with suspected CAP. Once externally validated, this score has potential to facilitate management decisions by providing individualized risk estimates that can be used in conjunction with clinical judgment to improve the care of children with suspected CAP.

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Predicting severe pneumonia in the emergency department: a global study of the Pediatric Emergency Research Networks (PERN)—study protocol

BMJ Open ◽

10.1136/bmjopen-2020-041093 ◽

2020 ◽

Vol 10 (12) ◽

pp. e041093

Author(s):

Todd Adam Florin ◽

Daniel Joseph Tancredi ◽

Lilliam Ambroggio ◽

Franz E Babl ◽

Stuart R Dalziel ◽

...

Keyword(s):

Emergency Department ◽

Prediction Model ◽

Severe Disease ◽

Pediatric Emergency ◽

Global Network ◽

Clinical Prediction ◽

Emergency Research ◽

Research Networks ◽

Clinical Prediction Model ◽

Severity Scores

IntroductionPneumonia is a frequent and costly cause of emergency department (ED) visits and hospitalisations in children. There are no evidence-based, validated tools to assist physicians in management and disposition decisions for children presenting to the ED with community-acquired pneumonia (CAP). The objective of this study is to develop a clinical prediction model to accurately stratify children with CAP who are at risk for low, moderate and severe disease across a global network of EDs.Methods and analysisThis study is a prospective cohort study enrolling up to 4700 children with CAP at EDs at ~80 member sites of the Pediatric Emergency Research Networks (PERN; https://pern-global.com/). We will include children aged 3 months to <14 years with a clinical diagnosis of CAP. We will exclude children with hospital admissions within 7 days prior to the study visit, hospital-acquired pneumonias or chronic complex conditions. Clinical, laboratory and imaging data from the ED visit and hospitalisations within 7 days will be collected. A follow-up telephone or text survey will be completed 7–14 days after the visit. The primary outcome is a three-tier composite of disease severity. Ordinal logistic regression, assuming a partial proportional odds specification, and recursive partitioning will be used to develop the risk stratification models.Ethics and disseminationThis study will result in a clinical prediction model to accurately identify risk of severe disease on presentation to the ED. Ethics approval was obtained for all sites included in the study. Cincinnati Children’s Hospital Institutional Review Board (IRB) serves as the central IRB for most US sites. Informed consent will be obtained from all participants. Results will be disseminated through international conferences and peer-reviewed publications. This study overcomes limitations of prior pneumonia severity scores by allowing for broad generalisability of findings, which can be actively implemented after model development and validation.

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Validation of prediction models of severe disease course and non-achievement of remission in juvenile idiopathic arthritis: part 1—results of the Canadian model in the Nordic cohort

Arthritis Research & Therapy ◽

10.1186/s13075-019-2060-2 ◽

2019 ◽

Vol 21 (1) ◽

Cited By ~ 4

Author(s):

Veronika Rypdal ◽

◽

Jaime Guzman ◽

Andrew Henrey ◽

Thomas Loughin ◽

...

Keyword(s):

Juvenile Idiopathic Arthritis ◽

Prediction Model ◽

Prediction Models ◽

Severe Disease ◽

Disease Onset ◽

Fine Tuning ◽

Disease Course ◽

Internal Validation ◽

Long Term Outcome

Abstract Background Models to predict disease course and long-term outcome based on clinical characteristics at disease onset may guide early treatment strategies in juvenile idiopathic arthritis (JIA). Before a prediction model can be recommended for use in clinical practice, it needs to be validated in a different cohort than the one used for building the model. The aim of the current study was to validate the predictive performance of the Canadian prediction model developed by Guzman et al. and the Nordic model derived from Rypdal et al. to predict severe disease course and non-achievement of remission in Nordic patients with JIA. Methods The Canadian and Nordic multivariable logistic regression models were evaluated in the Nordic JIA cohort for prediction of non-achievement of remission, and the data-driven outcome denoted severe disease course. A total of 440 patients in the Nordic cohort with a baseline visit and an 8-year visit were included. The Canadian prediction model was first externally validated exactly as published. Both the Nordic and Canadian models were subsequently evaluated with repeated fine-tuning of model coefficients in training sets and testing in disjoint validation sets. The predictive performances of the models were assessed with receiver operating characteristic curves and C-indices. A model with a C-index above 0.7 was considered useful for clinical prediction. Results The Canadian prediction model had excellent predictive ability and was comparable in performance to the Nordic model in predicting severe disease course in the Nordic JIA cohort. The Canadian model yielded a C-index of 0.85 (IQR 0.83–0.87) for prediction of severe disease course and a C-index of 0.66 (0.63–0.68) for prediction of non-achievement of remission when applied directly. The median C-indices after fine-tuning were 0.85 (0.80–0.89) and 0.69 (0.65–0.73), respectively. Internal validation of the Nordic model for prediction of severe disease course resulted in a median C-index of 0.90 (0.86–0.92). Conclusions External validation of the Canadian model and internal validation of the Nordic model with severe disease course as outcome confirm their predictive abilities. Our findings suggest that predicting long-term remission is more challenging than predicting severe disease course.

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Predictors of disease severity in children presenting from the community with febrile illnesses: a systematic review of prognostic studies

BMJ Global Health ◽

10.1136/bmjgh-2020-003451 ◽

2021 ◽

Vol 6 (1) ◽

pp. e003451

Author(s):

Arjun Chandna ◽

Rainer Tan ◽

Michael Carter ◽

Ann Van Den Bruel ◽

Jan Verbakel ◽

...

Keyword(s):

At Risk ◽

Prognostic Factors ◽

Prediction Model ◽

Disease Severity ◽

Prediction Models ◽

Severe Disease ◽

Risk Of Bias ◽

Clinical Prediction ◽

Children At Risk ◽

Clinical Prediction Models

IntroductionEarly identification of children at risk of severe febrile illness can optimise referral, admission and treatment decisions, particularly in resource-limited settings. We aimed to identify prognostic clinical and laboratory factors that predict progression to severe disease in febrile children presenting from the community.MethodsWe systematically reviewed publications retrieved from MEDLINE, Web of Science and Embase between 31 May 1999 and 30 April 2020, supplemented by hand search of reference lists and consultation with an expert Technical Advisory Panel. Studies evaluating prognostic factors or clinical prediction models in children presenting from the community with febrile illnesses were eligible. The primary outcome was any objective measure of disease severity ascertained within 30 days of enrolment. We calculated unadjusted likelihood ratios (LRs) for comparison of prognostic factors, and compared clinical prediction models using the area under the receiver operating characteristic curves (AUROCs). Risk of bias and applicability of studies were assessed using the Prediction Model Risk of Bias Assessment Tool and the Quality In Prognosis Studies tool.ResultsOf 5949 articles identified, 18 studies evaluating 200 prognostic factors and 25 clinical prediction models in 24 530 children were included. Heterogeneity between studies precluded formal meta-analysis. Malnutrition (positive LR range 1.56–11.13), hypoxia (2.10–8.11), altered consciousness (1.24–14.02), and markers of acidosis (1.36–7.71) and poor peripheral perfusion (1.78–17.38) were the most common predictors of severe disease. Clinical prediction model performance varied widely (AUROC range 0.49–0.97). Concerns regarding applicability were identified and most studies were at high risk of bias.ConclusionsFew studies address this important public health question. We identified prognostic factors from a wide range of geographic contexts that can help clinicians assess febrile children at risk of progressing to severe disease. Multicentre studies that include outpatients are required to explore generalisability and develop data-driven tools to support patient prioritisation and triage at the community level.PROSPERO registration numberCRD42019140542.

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Proadrenomedullin Predicts Severe Disease in Children with Suspected Community-Acquired Pneumonia

Clinical Infectious Diseases ◽

10.1093/cid/ciaa1138 ◽

2020 ◽

Author(s):

Todd A Florin ◽

Lilliam Ambroggio ◽

Cole Brokamp ◽

Yin Zhang ◽

Eric S Nylen ◽

...

Keyword(s):

Disease Severity ◽

Odds Ratio ◽

Severe Disease ◽

Antibiotic Use ◽

Supplemental Oxygen ◽

Community Acquired Pneumonia ◽

C Reactive Protein ◽

Chest Drainage ◽

Reactive Protein ◽

Complicated Pneumonia

Abstract Background Proadrenomedullin (proADM), a vasodilatory peptide with antimicrobial and anti-inflammatory properties, predicts severe outcomes in adults with community-acquired pneumonia (CAP) to a greater degree than C-reactive protein and procalcitonin. We evaluated the ability of proADM to predict disease severity across a range of clinical outcomes in children with suspected CAP. Methods We performed a prospective cohort study of children 3 months to 18 years with CAP in the emergency department (ED). Disease severity was defined as: mild (discharged home), mild-moderate (hospitalized but not moderate-severe or severe), moderate-severe (e.g., hospitalized with supplemental oxygen, broadening of antibiotics, complicated pneumonia), and severe (e.g., vasoactive infusions, chest drainage, severe sepsis). Outcomes were examined using proportional odds logistic regression within the cohort with suspected CAP and in a subset with radiographic CAP. Results Among 369 children, median proADM increased with disease severity [mild: median 0.53 nmol/L (IQR:0.43, 0.73), mild-moderate: 0.56 nmol/L (IQR:0.45, 0.71), moderate-severe: 0.61 nmol/L (IQR:0.47, 0.77), severe: 0.70 nmol/L (IQR:0.55, 1.04) (p=.002)]. ProADM was significantly associated with increased odds of developing severe outcomes (suspected CAP odds ratio (OR) 1.68 [95% CI, 1.2, 2.36], radiographic CAP OR 2.11 [95% CI, 1.36, 3.38]) adjusted for age, fever duration, antibiotic use, and pathogen. ProADM had an area under the ROC curve (AUC) of 0.64 (95%CI, 0.56,0.72) in those with suspected CAP and AUC 0.77 (95% CI, 0.68,0.87) in radiographic CAP. Conclusions ProADM was associated with severe disease and discriminated moderately well children who developed severe disease from those who did not, particularly in radiographic CAP.

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Serum β2-microglobulin levels in Coronavirus disease 2019 (Covid-19): Another prognosticator of disease severity?

PLoS ONE ◽

10.1371/journal.pone.0247758 ◽

2021 ◽

Vol 16 (3) ◽

pp. e0247758

Author(s):

Walter Conca ◽

Mayyadah Alabdely ◽

Faisal Albaiz ◽

Michael Warren Foster ◽

Maha Alamri ◽

...

Keyword(s):

Disease Severity ◽

Viral Infections ◽

Linear Trend ◽

Severe Disease ◽

Tertiary Care ◽

Care Hospital ◽

Mhc I ◽

Mild Disease ◽

Moderate Disease ◽

Single Center Study

β2-microglobulin (β2-m), a 11.8 kDa protein, pairs non-covalently with the α3 domain of the major histocompatibility class (MHC) I α-chain and is essential for the conformation of the MHC class I protein complex. Shed β2-m is measurable in circulation, and various disorders are accompanied by increases in β2-m levels, including several viral infections. Therefore, we explored whether β2-m levels could also be elevated in Coronavirus disease 2019 (Covid-19) and whether they predict disease severity. Serum β2-m levels were measured in a cohort of 34 patients infected with SARS-CoV-2 on admission to a tertiary care hospital in Riyadh, Saudi Arabia, as well as in an approximately age-sex matched group of 34 uninfected controls. Mean β2-m level was 3.25±1.68 mg/l (reference range 0.8–2.2 mg/l) in patients (mean age 48.2±21.6) and 1.98±0.61 mg/l in controls (mean age 48.2±21.6). 17 patients (mean age 36.9± 18.0) with mean β2-m levels of 2.27±0.64 mg/l had mild disease by WHO severity categorization, 12 patients (mean age 53.3±18.1) with mean β2-m levels of 3.57±1.39 mg/l had moderate disease, and five patients (of whom 2 died; mean age 74.4±13.8) with mean β2-m levels of 5.85±1.85 mg/l had severe disease (P < = 0.001, by ANOVA test for linear trend). In multivariate ordinal regression β2-m levels were the only significant predictor of disease severity. Our findings suggest that higher β2-m levels could be an early indicator of severity of disease and predict outcome of Covid-19. As the main limitations of the study are a single-center study, sample size and ethnicity, these results need confirmation in larger cohorts outside the Arabian Peninsula in order to delineate the value of β2-m measurements. The role of β2-m in the etiology and pathogenesis of severe Covid-19 remains to be elucidated.

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IL-16 and BCA-1 Serum Levels Are Associated with Disease Severity of C. difficile Infection

Pathogens ◽

10.3390/pathogens10050631 ◽

2021 ◽

Vol 10 (5) ◽

pp. 631

Author(s):

Dor Gotshal ◽

Maya Azrad ◽

Zohar Hamo ◽

Orna Nitzan ◽

Avi Peretz

Keyword(s):

Disease Severity ◽

Severe Disease ◽

Serum Levels ◽

Serum Samples ◽

Clostridioides Difficile ◽

Cytokines And Chemokines ◽

Laboratory Confirmation ◽

Moderate Disease ◽

Clostridioides Difficile Infection ◽

Healthcare Epidemiology

Clostridioides difficile infection (CDI) is associated with a high risk for complications and death, which requires identifying severe patients and treating them accordingly. We examined the serum level of six cytokines and chemokines (IL-16, IL-21, IL-23, IL-33, BCA-1, TRAIL) and investigated the association between them and patients’ disease severity. Concentrations of six cytokines and chemokines were measured using the MILLIPLEX®MAP kit (Billerica, MA, USA) in serum samples attained from CDI patients within 24–48 h after laboratory confirmation of C. difficile presence. Demographic and clinical data were collected from medical records. The disease severity score was determined according to guidelines of the “Society for Healthcare Epidemiology of America and the Infectious Diseases Society of America” (SHEA-IDSA). Out of 54 patients, 20 (37%) had mild to moderate disease and 34 (63%) had severe disease. IL-16 (p = 0.005) and BCA-1 (p = 0.012) were associated with a more severe disease. In conclusion, IL-16 and BCA-1, along with other cytokines and chemokines, may serve as biomarkers for the early prediction of CDI severity in the future. An improved and more accessible assessment of CDI severity will contribute to the adjustment of the medical treatment, which will lead to a better patient outcome.

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P110 ASSOCIATION OF FECAL CALPROTECTIN WITH ENDOSCOPIC AND HISTOLOGY ACTIVITY IN PEDIATRIC INFLAMMATORY BOWEL DISEASE PATIENTS

Inflammatory Bowel Diseases ◽

10.1093/ibd/zaa010.038 ◽

2020 ◽

Vol 26 (Supplement_1) ◽

pp. S16-S16

Author(s):

Erin Crawford ◽

Catherine Gestrich ◽

Sindhoosha Malay ◽

Thomas Sferra ◽

Shahrazad Saab ◽

...

Keyword(s):

Inflammatory Bowel Disease ◽

Disease Severity ◽

Bowel Disease ◽

Severe Disease ◽

Fecal Calprotectin ◽

Mucosal Healing ◽

Control Population ◽

Moderate Disease ◽

Endoscopic Remission ◽

Inflammatory Bowel

Abstract Background Inflammatory bowel disease (IBD) treatment strategies have evolved to target mucosal healing, which has been shown to be associated with clinical remission and reduced complications. Fecal calprotectin (FC) is a non-invasive marker of intestinal inflammation, and has been shown to correlate with disease activity in IBD patients, though values which correlate with mucosal healing vary across studies. We aim to examine the association of quantitative FC levels with endoscopic and histologic severity, and compare FC in IBD patients with endoscopic remission with a control population. Methods We conducted a retrospective chart review of patients who had a FC completed between 30 and 1 days before colonoscopy at UH Rainbow Babies and Children’s Hospital between 2014 and 2018. IBD patients had disease severity endoscopically graded using the SES-CD or Mayo UC score, and had disease severity histologically graded using the Geboes method. Severity was classed as no disease, mild, moderate or severe. FC values of IBD patients with mucosal healing and the control population (those without gastrointestinal pathology or diagnosis on evaluation) were compared. Results 331 cases were included in the study; 107 IBD cases and 224 controls. 63 patients (19%) had a diagnosis of Crohn’s disease (CD) and 44 patients (13%) had ulcerative colitis (UC). When assessing endoscopic scoring of IBD patients, the median FC was lowest in those with no disease (181 ug/g), followed by those with mild and moderate disease (499, 599 ug/g) and highest in those with severe disease (921 ug/g). There was significance comparing no disease to moderate and severe disease (p=0.019, 0.003), and between mild and severe disease (p=0.012). When assessing histology, the median FC was lowest in IBD patients with no disease (328 ug/g), followed by those with mild and moderate disease (399 ug/g, 674 ug/g) and highest in those with severe disease (895 ug/g). There was significance comparing no disease to moderate and severe disease (p=0.021, 0.018). In CD patients, there was significance in FC between no disease and moderate and severe disease (p=0.047, 0.0047) on endoscopic scoring. In UC patients, there was significance in FC between no disease and moderate disease (p=0.023) for histologic scoring. When comparing FC of endoscopically normal patients, the control group had a significantly lower median FC than the IBD population with endoscopic remission (43 ug/g vs 181 ug/g, p=0.018). Conclusion FC showed association with disease severity on gross endoscopy and histology and significance between severities in our IBD cohort. Additionally, normal cut-off values of FC may depend on the presence or absence of underlying disease. While larger studies are needed, this noninvasive test may help mitigate frequency of invasive procedures.

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Definition of fibromyalgia severity: findings from a cross-sectional survey of 2339 Italian patients

Rheumatology ◽

10.1093/rheumatology/keaa355 ◽

2020 ◽

Cited By ~ 1

Author(s):

Fausto Salaffi ◽

Marco Di Carlo ◽

Laura Bazzichi ◽

Fabiola Atzeni ◽

Marcello Govoni ◽

...

Keyword(s):

Disease Severity ◽

Severe Disease ◽

Fibromyalgia Impact Questionnaire ◽

Cross Sectional Survey ◽

External Criterion ◽

Cross Sectional ◽

Mild Disease ◽

Moderate Disease ◽

Definition Of ◽

Distress Scale

Abstract Objective To establish optimal cut-off values for the scores of the revised Fibromyalgia Impact Questionnaire (FIQR), the modified Fibromialgia Assessment Scale (FAS 2019mod), and the Polysymptomatic Distress Scale (PDS) in order to distinguish five levels of FM disease severity. Methods Consecutive FM patients were evaluated with the three clinimetric indices, and each patient was required to answer the anchor question: ‘In general, would you say your health is 1 = very good, 2 = good, 3 = fair, 4 = poor, or 5 = very poor?’—which represented the external criterion. Cut-off points were established through the interquartile reconciliation approach. Results The study sample consisted of 2181 women (93.2%) and 158 men (6.8%), with a mean age of 51.9 (11.5) years, and mean disease duration was 7.3 (6.9) years. The overall median FIQR, FAS 2019 mod and PDS scores (25th–75th percentiles) were respectively 61.16 (41.16–77.00), 27.00 (19.00–32.00) and 19.0 (13.00–24.00). Reconciliation of the mean 75th and 25th percentiles of adjacent categories defined the severity states for FIQR: 0–23 for remission, 24–40 for mild disease, 41–63 for moderate disease, 64–82 for severe disease and >83 for very severe disease; FAS 2019 mod: 0–12 for remission, 13–20 for mild disease, 21–28 for moderate disease, 29–33 for severe disease and >33 for very severe disease; PDS: 0–5 for remission, 6–15 for mild disease, 16–20 for moderate disease, 21–25 for severe disease and >25 for very severe disease. Conclusions Disease severity cut-offs can represent an important improvement in interpreting FM.

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A Prediction Model of Sufficient Filter Lifespan in Anticoagulation-free CRRT Patients

10.21203/rs.3.rs-73156/v1 ◽

2020 ◽

Author(s):

Wei Zhang ◽

Ming Bai ◽

Ling Zhang ◽

Yan Yu ◽

Yangping Li ◽

...

Keyword(s):

Prediction Model ◽

Predictive Value ◽

Primary Outcome ◽

Area Under The Curve ◽

Bleeding Risk ◽

Multivariable Logistic Regression Analysis ◽

Clinical Prediction ◽

Internal Validation ◽

Clinical Prediction Model ◽

Final Model

Abstract Background: Anticoagulation-free continuous renal replacement therapy (CRRT) was recommended by the current clinical guideline for patients with increased bleeding risk and contraindications of citrate and resulted in heterogeneous filter lifespan. There was no prediction model to identify the patients would have sufficient filter lifespan when they have to accept CRRT without the use of any anticoagulation. The purpose of our present study is to develop a clinical prediction model of sufficient filter lifespan in anticoagulation-free CRRT patients.Method: Patients who underwent anticoagulation-free CRRT in our center between June 2013 and June 2019 were retrospectively included. The primary outcome was sufficient filter lifespan (≥ 24 hours). The final model was established by using multivariable logistic regression analysis. And, the prediction model was validated in an external cohort. Results: A total of 170 patients were included in the development cohort. Sufficient filter lifespan were observed in 80 patients. The probability of sufficient filter lifespan could be calculated using the following regression formula: P (%) = exp (Z)/1 + exp (Z), where Z = 0.49896-(0.08552*BMI)+(0.44107*T)+(0.03373*MAP)-(0.03389*WBC)+(1.51579*[vasopressor=1])-(0.01132*PLT)+(0.00422*ALP)-(2.66910*pH)-(0.00214*UA)+(0.05992*BUN)+(0.00400*Db)–(0.00014*D-dimer)+(0.02818*APTT). The area under the curve (AUC) of the stepwise model and internal validation model was 0.82 (95%CI [0.76-0.88]) and 0.8 (95%CI [0.74-0.87]), respectively. At the optimal cut-off value of -0.1052, the positive predictive value and the negative predictive value of the stepwise model was 0.77 and 0.79, respectively. The AUC of the external model was 0.82 (95%CI [0.69-0.96]). Conclusion: The use of a prediction model instead of an assessment based only on coagulation parameters could facilitate the identification of the patients with filter lifespan of ≥ 24 hours when they accepted anticoagulation-free CRRT.

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Shift of lung macrophage composition is associated with COVID-19 disease severity and recovery

10.1101/2022.01.11.475918 ◽

2022 ◽

Author(s):

Steven Tiwen Chen ◽

Matthew D Park ◽

Diane Marie Del Valle ◽

Mark Buckup ◽

Alexandra Tabachnikova ◽

...

Keyword(s):

Disease Severity ◽

Inflammatory Diseases ◽

Severe Disease ◽

Unmet Need ◽

Myeloid Cell ◽

Health Crisis ◽

Inflammatory Monocytes ◽

Lung Macrophage ◽

Moderate Disease ◽

Immature Myeloid Cells

Though it has been 2 years since the start of the Coronavirus Disease 19 (COVID-19) pandemic, COVID-19 continues to be a worldwide health crisis. Despite the development of preventive vaccines, very little progress has been made to identify curative therapies to treat COVID-19 and other inflammatory diseases which remain a major unmet need in medicine. Our study sought to identify drivers of disease severity and death to develop tailored immunotherapy strategies to halt disease progression. Here we assembled the Mount Sinai COVID-19 Biobank which was comprised of ~600 hospitalized patients followed longitudinally during the peak of the pandemic. Moderate disease and survival were associated with a stronger antigen (Ag) presentation and effector T cell signature, while severe disease and death were associated with an altered Ag presentation signature, increased numbers of circulating inflammatory, immature myeloid cells, and extrafollicular activated B cells associated with autoantibody formation. Strikingly, we found that in severe COVID-19 patients, lung tissue resident alveolar macrophages (AM) were not only severely depleted, but also had an altered Ag presentation signature, and were replaced by inflammatory monocytes and monocyte-derived macrophages (MoMϕ). Notably, the size of the AM pool correlated with recovery or death, while AM loss and functionality were restored in patients that recovered. These data therefore suggest that local and systemic myeloid cell dysregulation is a driver of COVID-19 severity and that modulation of AM numbers and functionality in the lung may be a viable therapeutic strategy for the treatment of critical lung inflammatory illnesses.

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