scholarly journals Characteristics of COVID-19 patients admitted to a tertiary care hospital in Pune, India, and cost-effective predictors of intensive care treatment requirement

2020 ◽  
Author(s):  
Urvi Bhooshan Shukla ◽  
Sharvari Rahul Shukla ◽  
Sachin Bhaskar Palve ◽  
Rajiv Chintaman Yeravdekar ◽  
Vijay Madhusoothan Natarajan ◽  
...  
Keyword(s):  
Severe Disease ◽  
Cost Effective ◽  
Intensive Care Treatment ◽  
List Type ◽  
Care Hospital ◽  
X Ray ◽  
Abnormal Chest ◽  
Chest X Ray ◽  
Lower Spo2 ◽  
Icu Treatment

AbstractBackgroundMaharashtra is one of the worst affected states in this pandemic.2 As of 30th September, Maharashtra has in total 1.4 million cases with 38,000 deaths. Objective was to study associations of severity of disease and need for ICU treatment in COVID-19 patients.MethodsA retrospective study of clinical course in 800 hospitalized COVID-19 patients, and a predictive model of need for ICU treatment. Eight hundred consecutive patients admitted with confirmed COVID-19 disease.ResultsAverage age was 41 years, 16% were <20 years of age, 55% were male, 50% were asymptomatic and 16% had at least one comorbidity. Using MoHFW India severity guidelines, 73% patients had mild, 6% moderate and 20% severe disease. Severity was associated with higher age, symptomatic presentation, elevated neutrophil and reduced lymphocyte counts and elevated inflammatory markers. Seventy-seven patients needed ICU treatment: they were older (56 years), more symptomatic and had lower SpO2 and abnormal chest X-ray and deranged hematology and biochemistry at admission. A model trained on the first 500 patients, using above variables predicted need for ICU treatment with sensitivity 80%, specificity 88% in subsequent 300 patients; exclusion of expensive laboratory tests did not affect accuracy.ConclusionIn the early phase of COVID- 19 epidemic, a significant proportion of hospitalized patients were young and asymptomatic. Need for ICU treatment was predicted by simple measures including higher age, symptomatic onset, low SpO2 and abnormal chest X-ray. We propose a cost-effective model for referring patients for treatment at specialized COVID-19 hospitals.Key MessagesOf 800 patients, 73% had mild, 6% moderate and 20% had severe disease.Seventy-seven patients (9.6%) required ICU treatment, 25 (3%) died.ICU treatment was predicted by higher age, more symptomatic presentation, lower SpO2 and pneumonia on chest X-ray at admission.A machine learning model features in first 500 patients accurately predicted ICU treatment in subsequent 300 patients.A good clinical protocol, SpO2 and chest X-ray are adequate to predict and triage COVID-19 patients for hospital admissions in resource poor environments.

scholarly journals Incidence of Bloodstream Infections in Patients with COVID-19: A Retrospective Cohort Study of Risk Factors and Outcomes

2021 ◽  
Author(s):  
Claudia Villatoro Santos ◽  
Elisa Akagi Fukushima ◽  
Wei Zhao ◽  
Mamta Sharma ◽  
Dima Youssef ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Severe Disease ◽  
Bloodstream Infections ◽  
X Ray ◽  
Abnormal Chest ◽  
Chest X Ray ◽  
Male Sex

Abstract Objective: To describe the incidence, risk factors, and outcomes of bloodstream infections (BSIs) in patients with coronavirus disease 19 (COVID-19).Methods: This was a single-center retrospective cohort study of adults admitted for COVID-19 with BSIs. Data were collected by electronic medical record review. BSIs were defined as positive blood cultures (BCs) with a known pathogen in one or more BCs or the same commensal organism in two or more BCs. Results: Of 565 eligible patients, 290 (51.3%) had BCs done, with 39 (13.4%) having a positive result. In univariable analysis, male sex, black/African American race, admission from a facility, hemiplegia, altered mental status, and a higher Charlson Comorbidity Index were positively associated with a positive BC, whereas obesity and low systolic blood pressure (SBP) were negatively associated. Patients with positive BCs were more likely to have severe disease, be admitted to the Intensive Care Unit (ICU), require mechanical ventilation, have septic shock, and higher mortality. In multivariable logistic regression, factors that were independent predictors of a positive BC were male sex (OR=2.75, p=0.03), hypoalbuminemia (OR=3.3, p=0.01), ICU admission (OR=5.3, p<0.0001), SBP < 100 (OR=3.7, p=0.03) and having a procedure (OR=10.5, p<0.0001). Patients with an abnormal chest x-ray on admission were less likely to have a positive BC (OR=0.25, p=0.007). Conclusions: We found that independent predictors of BSIs in COVID-19 patients included male sex, abnormal chest x-ray, hypoalbuminemia, admission to ICU, low SBP, and having a procedure during hospital stay.

Clinical Impact of Combined Viral and Bacterial Infection in Pediatric Mycoplasmal Community-Acquired Pneumonia in Western China

2020 ◽  
Vol 12 (11) ◽  
pp. 1315-1322
Author(s):  
Zhuoxin Liang ◽  
Wenqiang Zhang ◽  
Yongjiang Jiang ◽  
Ping Wu ◽  
Senxiong Zhang ◽  
...  
Keyword(s):  
Clinical Characteristics ◽  
Severe Disease ◽  
Lung Parenchyma ◽  
Community Acquired Pneumonia ◽  
Western China ◽  
Care Hospital ◽  
Hospital Data ◽  
Chest X Ray ◽  
Ventilation Rates ◽  
The Impact

Community-acquired pneumonia (CAP) refers to an infection contracted outside the hospital that leads to lung parenchyma inflammation. The clinical characteristics of Mycoplasma pneumoniae (M. pneumoniae) infection in CAP patients were rarely reported. The aim of this study was to describe the clinical characteristic and the impact of co-infections of M. pneumoniae with viral and bacterial pathogens in hospitalized children with CAP in Liuzhou, China. This study retrospects children diagnosed with CAP due to M. pneumoniae infection at a tertiary maternal and child health care hospital. Data related to co-infection pathogens, demographics, clinical characteristics, and hospitalization cost were collected from the electronic medical system in this hospital. A total of 983 children were diagnosed with mycoplasmal CAP in 2017. Among them, 18.2% had a bacterial-M. pneumoniae co-infection and 11.3% had a viral-M. pneumoniae co-infection. The highest infection rate of M. pneumoniae was 19.1% in February and March, while the highest rates of bacterial-M. pneumoniae and viral-M. pneumoniae co-infections were 3.6% in December and 2.3% in January, respectively. The prevalence of coughing and wheezing had significant differences between the bacterial- or viral-M. pneumoniae co-infections and the mono-infection groups. Furthermore, the chest X-ray progression, pleural effusions, respiratory failure, and ventilation rates were higher in the respiratory viral- and bacterial-M. pneumoniae co-infection groups than in the mono-infection group. Children with a bacterial or respiratory viral co-infection had a longer hospitalization and spent more on treatment fees than those with a M. pneumoniae mono-infection (P value <0.001). We conclude that children with mycoplasmal CAP, either with a bacterial or viral co-infection, who show signs of coughing and wheezing and have a radiographic progression, will have a severe disease progression and should be specifically treated and managed.

scholarly journals Abnormal chest X-ray in a patient with carcinoma of the cervix.

1997 ◽  
Vol 73 (864) ◽  
pp. 671-673
Author(s):  
P. Aggarwal ◽  
R. Handa ◽  
J. P. Wali ◽  
N. Wig ◽  
A. Kumar
Keyword(s):  
X Ray ◽  
Abnormal Chest ◽  
Chest X Ray

Portable Ventilation/Perfusion Scanning is Useful for Evaluating Clinically Significant Pulmonary Embolism in the ICU Despite Abnormal Chest Radiography

2018 ◽  
Vol 35 (10) ◽  
pp. 1032-1038 ◽  
Author(s):  
Aaron S. Weinberg ◽  
William Chang ◽  
Grace Ih ◽  
Alan Waxman ◽  
Victor F. Tapson
Keyword(s):  
Pulmonary Embolism ◽  
Chest Radiograph ◽  
High Probability ◽  
Hemodynamic Instability ◽  
X Rays ◽  
X Ray ◽  
Abnormal Chest ◽  
Chest X Ray ◽  
Low Probability ◽  
Clinically Significant

Objective: Computed tomography angiography is limited in the intensive care unit (ICU) due to renal insufficiency, hemodynamic instability, and difficulty transporting unstable patients. A portable ventilation/perfusion (V/Q) scan can be used. However, it is commonly believed that an abnormal chest radiograph can result in a nondiagnostic scan. In this retrospective study, we demonstrate that portable V/Q scans can be helpful in ruling in or out clinically significant pulmonary embolism (PE) despite an abnormal chest x-ray in the ICU. Design: Two physicians conducted chart reviews and original V/Q reports. A staff radiologist, with 40 years of experience, rated chest x-ray abnormalities using predetermined criteria. Setting: The study was conducted in the ICU. Patients: The first 100 consecutive patients with suspected PE who underwent a portable V/Q scan. Interventions: Those with a portable V/Q scan. Results: A normal baseline chest radiograph was found in only 6% of patients. Fifty-three percent had moderate, 24% had severe, and 10% had very-severe radiographic abnormalities. Despite the abnormal x-rays, 88% of the V/Q scans were low probability for a PE despite an average abnormal radiograph rating of moderate. A high-probability V/Q for PE was diagnosed in 3% of the population despite chest x-ray ratings of moderate to severe. Six patients had their empiric anticoagulation discontinued after obtaining the results of the V/Q scan, and no anticoagulation was started for PE after a low-probability V/Q scan. Conclusion: Despite the large percentage of moderate-to-severe x-ray abnormalities, PE can still be diagnosed (high-probability scan) in the ICU with a portable V/Q scan. Although low-probability scans do not rule out acute PE, it appeared less likely that any patient with a low-probability V/Q scan had severe hypoxemia or hemodynamic instability due to a significant PE, which was useful to clinicians and allowed them to either stop or not start anticoagulation.

Acute Abdominal Pain and an Abnormal Chest X-ray

1982 ◽  
Vol 17 (4) ◽  
pp. 65-70
Author(s):  
Lawrence Kaplan ◽  
Michael Young ◽  
Leonard Krilov
Keyword(s):  
Abdominal Pain ◽  
Acute Abdominal Pain ◽  
X Ray ◽  
Abnormal Chest ◽  
Chest X Ray

scholarly journals 1184. Making Pneumonia Surveillance Easy: Automation of Pneumonia Case Detection

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S424-S425
Author(s):  
Dan Ding ◽  
Anna Stachel ◽  
Eduardo Iturrate ◽  
Michael Phillips
Keyword(s):  
Language Processing ◽  
Cost Effective ◽  
The United States ◽  
Surveillance Data ◽  
X Rays ◽  
Healthcare Facilities ◽  
X Ray ◽  
Chest X Ray ◽  
Sensitivity Specificity ◽  
Time Critical

Abstract Background Pneumonia (PNU) is the second most common nosocomial infection in the United States and is associated with substantial morbidity and mortality. While definitions from CDC were developed to increase the reliability of surveillance data, reduce the burden of surveillance in healthcare facilities, and enhance the utility of surveillance data for improving patient safety - the algorithm is still laborious. We propose an implementation of a refined algorithm script which combines two CDC definitions with the use of natural language processing (NLP), a tool which relies on pattern matching to determine whether a condition of interest is reported as present or absent in a report, to automate PNU surveillance. Methods Using SAS v9.4 to write a query, we used a combination of National Healthcare Safety Network’s (NHSN) PNU and ventilator-associated event (VAE) definitions that use discrete fields found in electronic medical records (EMR) and trained an NLP tool to determine whether chest x-ray report was indicative of PNU (Fig1). To validate, we assessed sensitivity/specificity of NLP tool results compared with clinicians’ interpretations. Results The NLP tool was highly accurate in classifying the presence of PNU in chest x-rays. After training the NLP tool, there were only 4% discrepancies between NLP tool and clinicians interpretations of 223 x-ray reports - sensitivity 92.2% (81.1–97.8), specificity 97.1% (93.4–99.1), PPV 90.4% (79.0–96.8), NPV 97.7% (94.1–99.4). Combining the automated use of discrete EMR fields with NLP tool significantly reduces the time spent manually reviewing EMRs. A manual review for PNU without automation requires approximately 10 minutes each day per admission. With a monthly average of 2,350 adult admissions at our hospital and 16,170 patient-days for admissions with at least 2 days, the algorithm saves approximately 2,695 review hours. Conclusion The use of discrete EMR fields with an NLP tool proves to be a timelier, cost-effective yet accurate alternative to manual PNU surveillance review. By allowing an automated algorithm to review PNU, timely reports can be sent to units about individual cases. Compared with traditional CDC surveillance definitions, an automated tool allows real-time critical review for infection and prevention activities. Disclosures All authors: No reported disclosures.

scholarly journals Early clinical predictors of severe acute respiratory syndrome in the emergency department

CJEM ◽  
2004 ◽  
Vol 6 (01) ◽  
pp. 12-21 ◽  
Author(s):  
W.N. Wong ◽  
Antonio C.H. Sek ◽  
Rick F.L. Lau ◽  
K.M. Li ◽  
Joe K.S. Leung ◽  
...  
Keyword(s):  
Emergency Department ◽  
Severe Acute Respiratory Syndrome ◽  
Lymphocyte Count ◽  
Case Definition ◽  
World Health ◽  
Clinical Predictors ◽  
X Ray ◽  
Abnormal Chest ◽  
Contact Exposure ◽  
Chest X Ray

ABSTRACT Objectives: To assess the association of diagnostic predictors available in the emergency department (ED) with the outcome diagnosis of severe acute respiratory syndrome (SARS). Methods: This retrospective cohort study describes all patients from the Amoy Garden complex who presented to an ED SARS screening clinic during a 2-month outbreak. Clinical and diagnostic predictors were recorded, along with ED diagnoses. Final diagnoses were established independently based on diagnostic tests performed after the ED visit. Associations of key predictors with the final diagnosis of SARS were described. Results: Of 821 patients, 205 had confirmed SARS, 35 undetermined SARS and 581 non-SARS. Multivariable logistic regression showed that the strongest predictors of SARS were abnormal chest x-ray (odds ratio [OR] = 17.4), subjective fever (OR = 9.7), temperature &gt;38°C (OR = 6.4), myalgias (OR = 5.5), chills and rigors (OR = 4.0) and contact exposure (OR = 2.6). In a subset of 176 patients who had a complete blood cell count performed, the strongest predictors were temperature ≥38ºC (OR = 15.5), lymphocyte count &lt;1000 (OR = 9.3) and abnormal chest x-ray (OR = 5.7). Diarrhea was a powerful negative predictor (OR = 0.03) of SARS. Conclusions: Two components of the World Health Organization case definition — fever and contact exposure — are helpful for ED decision-making, but respiratory symptoms do not discriminate well between SARS and non-SARS. Emergency physicians should consider the presence of diarrhea, chest x-ray findings, the absolute lymphocyte count and the platelet count as significant modifiers of disease likelihood. Prospective validation of these findings in other clinical settings is desirable.

‘My Doctor Said I Had an Abnormal Chest X-Ray...’

Respiration ◽  
2003 ◽  
Vol 70 (2) ◽  
pp. 224-228
Author(s):  
Hector E. Mateo ◽  
Alpha A. Fowler
Keyword(s):  
X Ray ◽  
Abnormal Chest ◽  
Chest X Ray

scholarly journals Characteristics and outcomes of admitted patients infected with SARS-CoV-2 in Uganda

2020 ◽  
Vol 7 (1) ◽  
pp. e000646 ◽  
Author(s):  
Bruce Kirenga ◽  
Winters Muttamba ◽  
Alex Kayongo ◽  
Christopher Nsereko ◽  
Trishul Siddharthan ◽  
...  
Keyword(s):  
Statistical Significance ◽  
Sub Saharan Africa ◽  
Detailed Data ◽  
X Ray ◽  
Mild Disease ◽  
Clinical Recovery ◽  
Abnormal Chest ◽  
Chest X Ray ◽  
Sub Saharan ◽  
Muscle Ache

RationaleDetailed data on the characteristics and outcomes of patients with COVID-19 in sub-Saharan Africa are limited.ObjectiveWe determined the clinical characteristics and treatment outcomes of patients diagnosed with COVID-19 in Uganda.MeasurementsAs of the 16 May 2020, a total of 203 cases had been confirmed. We report on the first 56 patients; 29 received hydroxychloroquine (HCQ) and 27 did not. Endpoints included admission to intensive care, mechanical ventilation or death during hospitalisation.Main resultsThe median age was 34.2 years; 67.9% were male; and 14.6% were <18 years. Up 57.1% of the patients were asymptomatic. The most common symptoms were fever (21.4%), cough (19.6%), rhinorrhea (16.1%), headache (12.5%), muscle ache (7.1%) and fatigue (7.1%). Rates of comorbidities were 10.7% (pre-existing hypertension), 10.7% (diabetes) and 7.1% (HIV), Body Mass Index (BMI) of ≥30 36.6%. 37.0% had a blood pressure (BP) of >130/90 mm Hg, and 27.8% had BP of >140/90 mm Hg. Laboratory derangements were leucopenia (10.6%), lymphopenia (11.1%) and thrombocytopenia (26.3%). Abnormal chest X-ray was observed in 14.3%. No patients reached the primary endpoint. Time to clinical recovery was shorter among patients who received HCQ, but this difference did not reach statistical significance.ConclusionMost of the patients with COVID-19 presented with mild disease and exhibited a clinical trajectory not similar to other countries. Outcomes did not differ by HCQ treatment status in line with other concluded studies on the benefit of using HCQ in the treatment of COVID-19.

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