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 Immediate Outcomes of Traumatic Brain Injury at a Tertiary Care Hospital Of Pakistan- A Retrospective Study

2020 ◽  
Author(s):  
Maria Khan ◽  
Uzair Yaqoob ◽  
Zair Hassan ◽  
Muhammad Muizz Uddin
Keyword(s):  
Traumatic Brain Injury ◽  
Retrospective Study ◽  
Brain Injury ◽  
Tertiary Care ◽  
Epidemiological Data ◽  
Initial Assessment ◽  
Care Hospital ◽  
Hospital Data ◽  
Epidemiological Characteristics ◽  
The Impact

Abstract Background: Traumatic Brain Injury (TBI) which is the leading cause of morbidity and mortality all over the world and the impact is much worse in Pakistan. The objective of the study is to describe the epidemiological characteristics of patients with TBI in our country and to determine the immediate outcomes of patients with TBI after the presentation.Method: This retrospective study was conducted at the Lady Reading Hospital. Data were extracted from the medical record room from January 1st to December 31st, 2019. The severity of TBI was based on Glasgow Coma Scale (GCS) and was divided into mild (GCS 13-15), moderate (GCS 9-12), and severe TBI (GCS <8) based on the GCS. SPSS v.23 was used for data analysis. Results: Out of 5047 patients, 3689 (73.1%) males and 1358 (26.9%) females. The most commonly affected age group was 0-10 years (25.6%) and 21-30 years (20.1%). was the predominant cause of injury (38.8%, n=1960) followed by fall (32.7%, n=1649). Most (93.6%, n=4710) of the TBIs were mild. After the full initial assessment and workup, and completing all first-aid management, the immediate outcome was divided into four, most frequent (67.2%, n=3393) of which was “disposed (discharged)”, and 9.3% (n=470) were admitted for further management.Conclusion: Our study represents a relatively conclusive picture of epidemiological data on the burden of TBI in Pakistan. Although a large proportion of patients had a mild TBI, they may likely be under-diagnosed. This warrants for further investigation of MTBI in population-based studies across the globe.

scholarly journals Immediate Outcomes of Traumatic Brain Injury at a Tertiary Care Hospital Of Pakistan- A Retrospective Study

2021 ◽  
Author(s):  
Maria Khan ◽  
Uzair Yaqoob ◽  
Zair Hassan ◽  
Muhammad Muizz Uddin
Keyword(s):  
Traumatic Brain Injury ◽  
Retrospective Study ◽  
Brain Injury ◽  
Road Traffic ◽  
Tertiary Care ◽  
Initial Assessment ◽  
Care Hospital ◽  
Hospital Data ◽  
Epidemiological Characteristics ◽  
The Impact

Abstract Background: Traumatic Brain Injury (TBI) is the leading cause of morbidity and mortality all over the world and the impact is much worse in Pakistan. The objective here is to describe the epidemiological characteristics of patients with TBI in our country and to determine the immediate outcomes of patients with TBI after the presentation.Method: This retrospective study was conducted at the Lady Reading Hospital. Data were extracted from the medical record room from January 1st to December 31st, 2019. The severity of TBI was based on Glasgow Coma Scale (GCS) and was divided into mild (GCS 13-15), moderate (GCS 9-12), and severe TBI (GCS <8) based on the GCS. SPSS v.23 was used for data analysis. Results: Out of 5047 patients, 3689 (73.1%) males and 1358 (26.9%) females. The most commonly affected age group was 0-10 years (25.6%) and 21-30 years (20.1%). Road Traffic accident was the predominant cause of injury (38.8%, n=1960) followed by fall (32.7%, n=1649). Most (93.6%, n=4710) of the TBIs were mild. After the full initial assessment and workup, and completing all first-aid management, the immediate outcome was divided into four, most frequent (67.2%, n=3393) of which was “disposed (discharged)”, and 9.3% (n=470) were admitted for further management.Conclusion: Our study represents a relatively conclusive picture of epidemiological data on the burden of TBI in Pakistan. Although a large proportion of patients had a mild TBI, they may likely be under-diagnosed. This warrants further investigation of MTBI in population-based studies across the globe.

scholarly journals Influenza and Community-acquired Pneumonia Interactions: The Impact of Order and Time of Infection on Population Patterns

2012 ◽  
Vol 175 (5) ◽  
pp. 363-367 ◽  
Author(s):  
Brian M. Davis ◽  
Allison E. Aiello ◽  
Suzanne Dawid ◽  
Pejman Rohani ◽  
Sourya Shrestha ◽  
...  
Keyword(s):  
Influenza A ◽  
Animal Studies ◽  
Severe Disease ◽  
Severity Of Illness ◽  
Population Level ◽  
Community Acquired Pneumonia ◽  
Swine Flu ◽  
1918 Influenza ◽  
The Impact

AbstractDiscoveries made during the 1918 influenza A pandemic and reports of severe disease associated with coinfection during the 2009 hemagglutinin type 1 and neuraminidase type 1 (commonly known as H1N1 or swine flu) pandemic have renewed interest in the role of coinfection in disease pathogenesis. The authors assessed how various timings of coinfection with influenza virus and pneumonia-causing bacteria could affect the severity of illness at multiple levels of interaction, including the biologic and population levels. Animal studies most strongly support a single pathway of coinfection with influenza inoculation occurring approximately 7 days before inoculation with Streptococcus pneumoniae, but less-examined pathways of infection also may be important for human disease. The authors discussed the implications of each pathway for disease prevention and what they would expect to see at the population level if there were sufficient data available. Lastly, the authors identified crucial gaps in the study of timing of coinfection and proposed related research questions.

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 Disease Severity, Clinical Characteristics and Outcome of Patients Hospitalized with Novel Coronavirus Disease at a Tertiary Care Hospital, Rawalpindi

2021 ◽  
Vol 2 (4) ◽  
pp. 6
Author(s):  
Muhammad Mahtab Shabir ◽  
Shazia Nisar ◽  
Zobia Urooj ◽  
Uzma Qayyum ◽  
Fozia Fatima ◽  
...  
Keyword(s):  
Kidney Disease ◽  
Pulmonary Disease ◽  
Disease Severity ◽  
Clinical Characteristics ◽  
Severe Disease ◽  
Tertiary Care ◽  
Care Hospital ◽  
Cross Sectional ◽  
Number Of Patients ◽  
Novel Coronavirus

Objective: To describe the clinical characteristics, signs & symptoms, disease severity, and outcome of patientsadmitted with novel coronavirus infection.Study Design: Comparative cross-sectional study.Place and Duration of Study: The study was conducted in the Department of Medicine of Pak-Emirates Militaryst th Hospital, (PEMH), Rawalpindi from May 1 , 2020 to June 30 , 2020.Materials and Methods: Patients hospitalized with novel corona virus infection during the study period wereprospectively enrolled in this study. Patients at least 15 years and above, either gender, hospitalized withconfirmed diagnosis of covid-19 (SARS-CoV-2) were eligible to be enrolled. The study outcomes includeddisease presentation, severity at time of reporting, admission to critical care or intensive care unit andmortality. Patients were identified as mild, moderate, severe and critical in accordance with World HealthOrganization guidelines, based on symptom severity, laboratory and imaging findings.Results: There were 400 hospitalized patients with confirmed SARS-CoV-2, out of which 51 (12.8%) werefemales, while 349 (87.3%) were males with overall mean age of 48.45±16.2 years. There were 300 (75.0%)patients with mild disease severity, while 65 (16.3%), 20 (5.0%) and 15 (3.8%) with moderate, severe and criticaldisease condition, respectively. The number of patients died were 22, with fatality rate of 5.5%. Age andpresence of comorbidities (cardiac disease, diabetes, hypertension, pulmonary disease, kidney disease) weresignificantly associated with disease severity and death due to novel coronavirus infection.Conclusion: Patients with older age, diabetes, hypertension, pulmonary disease, kidney disease were at higherrisk of developing severe disease condition and death due to novel coronavirus infection.

scholarly journals Impact of frailty on 30-day and 1-year mortality in hospitalised elderly patients with community-acquired pneumonia: a prospective observational study

BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e038370
Author(s):  
Jia Luo ◽  
Wen Tang ◽  
Ying Sun ◽  
Chunyan Jiang
Keyword(s):  
Elderly Patients ◽  
Mortality Risk ◽  
Cox Regression ◽  
Tertiary Care ◽  
Community Acquired Pneumonia ◽  
Care Hospital ◽  
Frailty Phenotype ◽  
Cox Regression Analysis ◽  
Frail Patients ◽  
The Impact

ObjectivesThis study evaluates the impact of frailty, which is a state of increased vulnerability to stressors, on 30-day and 1-year mortality among elderly patients with community-acquired pneumonia (CAP). The main hypothesis is that frailty is an independent predictor of prognosis in elderly CAP patients.DesignProspective, observational, follow-up cohort study.SettingA 2000-bed tertiary care hospital in Beijing, China.ParticipantsConsecutive CAP patients aged ≥65 years admitted to the geriatric department of our hospital between September 2017 and February 2019.Main outcome measuresThe primary outcomes were all-cause mortality at 30 days and 1 year after hospital admission. The impact of frailty (defined by frailty phenotype) on 30-day and 1-year mortality of elderly patients with CAP was assessed by Cox regression analysis.ResultsThe cohort included 256 patients. The median (IQR) age was 86 (81–90) years, and 180 (70.3%) participants were men. A total of 171/256 (66.8%) patients were frail. The prevalence of frailty was significantly associated with older age, female gender, lower body mass index, comorbidities, limitations in activities of daily living (ADLs) and poor nutritional status. Frail participants were significantly more likely to have severe CAP (SCAP) than non-frail counterparts (28.65% vs 9.41%, p<0.001). The 1-year mortality risk was approximately threefold higher in frail patients (adjusted HR, 2.70; 95% CI, 1.69 to 4.39) than non-frail patients. Subgroup analysis of patients with SCAP showed that the 1-year mortality risk was approximately threefold higher in the frail group (adjusted HR, 2.87; 95% CI, 1.58 to 4.96) than in the non-frail group. The association between frailty and 30-day mortality was not significant.ConclusionsThese findings suggest that frailty is strongly associated with SCAP and higher 1-year mortality in elderly patients with CAP, and frailty should be detected early to improve the management of these patients.

scholarly journals Chest computed tomography and chest X-ray in the diagnosis of community-acquired pneumonia: a retrospective observational study

2021 ◽  
Vol 49 (8) ◽  
pp. 030006052110397
Author(s):  
Dima Ibrahim ◽  
Abdul Rahman Bizri ◽  
Mohammad Ali El Amine ◽  
Zeina Halabi
Keyword(s):  
Computed Tomography ◽  
Medical Records ◽  
Community Acquired Pneumonia ◽  
Chest Ct ◽  
Chest Computed Tomography ◽  
X Ray ◽  
Combined Use ◽  
Chest X Ray ◽  
Large Benefit ◽  
The Impact

Objectives To compare the yield of early combined use of chest X-ray (CXR) and chest computed tomography (CT) in patients diagnosed with community-acquired pneumonia (CAP) presenting to the emergency department (ED) and assess the impact of chest CT on the initial diagnosis. Methods The medical records of 900 patients who presented to the ED and were diagnosed with CAP over a 1-year period were reviewed, and 130 patients who underwent CXR and chest CT within 48 hours were selected. CXR findings were classified as positive, negative, or inconclusive for CAP. Chest CT findings were defined as positive, negative, inconclusive, or positive with add-on to the CXR findings. CT was classified as having no benefit, large benefit, or moderate benefit based on the chest CT and CXR findings. Results Chest CT results were positive in 90.7% of patients, with 41.5% being newly diagnosed after negative or inconclusive CXR and 21.5% being diagnosed with add-on to the CXR findings. CT had large, moderate, and no benefit over CXR in diagnosing or excluding CAP in 45.3%, 21.5%, and 33.1% of patients, respectively. Conclusion Early chest CT may be used to compliment CXR in the early diagnosis of CAP among patients in the ED.

scholarly journals Comparison of the clinical characteristics and outcomes of hospitalized adult COVID-19 and influenza patients – a prospective observational study

2020 ◽  
Author(s):  
Raija Auvinen ◽  
Hanna Nohynek ◽  
Ritva Syrjänen ◽  
Jukka Ollgren ◽  
Tuija Kerttula ◽  
...  
Keyword(s):  
Observational Study ◽  
Clinical Characteristics ◽  
Prospective Observational Study ◽  
Severe Disease ◽  
Ground Glass ◽  
Current Smoking ◽  
Public Health Policies ◽  
X Ray ◽  
Chest X Ray

AbstractObjectiveWe compared the clinical characteristics, findings and outcomes of hospitalized patients with coronavirus disease 2019 (COVID-19) or influenza to detect relevant differences.MethodsFrom December 2019 to April 2020, we recruited all eligible hospitalized adults with respiratory infection to a prospective observational study at the HUS Jorvi Hospital, Finland. Influenza and SARS-CoV-2 infections were confirmed by RT-PCR. Follow-up lasted for at least 30 days from admission.ResultsWe included 61 patients, of whom 28 were COVID-19 and 33 influenza patients with median ages of 53 and 56 years. Majority of both COVID-19 and influenza patients were men (61% vs 67%) and had at least one comorbidity (68% vs 85%). Pulmonary diseases and current smoking were less common among COVID-19 than influenza patients (5 [18%] vs 15 [45%], P=0.03 and 1 [4%] vs 10 [30%], P=0.008). In chest x-ray at admission, ground-glass opacities and consolidations were more frequent among COVID-19 than influenza patients (19 [68%] and 7 [21%], P < 0.001). Severe disease and intensive care unit (ICU) admission occurred more often among COVID-19 than influenza patients (26 [93%] vs 19 [58%], P=0.003 and 8 [29%] vs 2 [6%], P=0.034). COVID-19 patients were hospitalized longer than influenza patients (6 days [IQR 4-21] vs 3 [2-4], P<0.001).ConclusionBilateral ground-glass opacities and consolidations in chest X-ray may help to differentiate COVID-19 from influenza. Hospitalized COVID-19 patients had more severe disease, required longer hospitalization and were admitted to ICU more often than influenza patients, which has important implications for public health policies.

scholarly journals Automation of Lung Ultrasound Interpretation via Deep Learning for the Classification of Normal versus Abnormal Lung Parenchyma: A Multicenter Study

Diagnostics ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2049
Author(s):  
Robert Arntfield ◽  
Derek Wu ◽  
Jared Tschirhart ◽  
Blake VanBerlo ◽  
Alex Ford ◽  
...  
Keyword(s):  
Deep Learning ◽  
Multicenter Study ◽  
Lung Ultrasound ◽  
External Validation ◽  
Lung Parenchyma ◽  
Receiver Operating Curve ◽  
Validation Dataset ◽  
Care Hospital ◽  
Thoracic Imaging ◽  
The Impact

Lung ultrasound (LUS) is an accurate thoracic imaging technique distinguished by its handheld size, low-cost, and lack of radiation. User dependence and poor access to training have limited the impact and dissemination of LUS outside of acute care hospital environments. Automated interpretation of LUS using deep learning can overcome these barriers by increasing accuracy while allowing point-of-care use by non-experts. In this multicenter study, we seek to automate the clinically vital distinction between A line (normal parenchyma) and B line (abnormal parenchyma) on LUS by training a customized neural network using 272,891 labelled LUS images. After external validation on 23,393 frames, pragmatic clinical application at the clip level was performed on 1162 videos. The trained classifier demonstrated an area under the receiver operating curve (AUC) of 0.96 (+/−0.02) through 10-fold cross-validation on local frames and an AUC of 0.93 on the external validation dataset. Clip-level inference yielded sensitivities and specificities of 90% and 92% (local) and 83% and 82% (external), respectively, for detecting the B line pattern. This study demonstrates accurate deep-learning-enabled LUS interpretation between normal and abnormal lung parenchyma on ultrasound frames while rendering diagnostically important sensitivity and specificity at the video clip level.

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