Diagnosis Of Acute Respiratory Infections Research Articles

How AI Could Help Us in the Epidemiology and Diagnosis of Acute Respiratory Infections?

Acute respiratory infections (ARIs) represent a significant global health burden, contributing to high morbidity and mortality rates, particularly in vulnerable populations. Traditional methods for diagnosing and tracking ARIs often face limitations in terms of speed, accuracy, and scalability. The advent of artificial intelligence (AI) has the potential to revolutionize these processes by enhancing early detection, precise diagnosis, and effective epidemiological tracking. This review explores the integration of AI in the epidemiology and diagnosis of ARIs, highlighting its capabilities, current applications, and future prospects. By examining recent advancements and existing studies, this paper provides a comprehensive understanding of how AI can improve ARI management, offering insights into its practical applications and the challenges that must be addressed to realize its full potential.

Validation of an acute respiratory infection phenotyping algorithm to support robust computerised medical record-based respiratory sentinel surveillance, England, 2023.

IntroductionRespiratory sentinel surveillance systems leveraging computerised medical records (CMR) use phenotyping algorithms to identify cases of interest, such as acute respiratory infection (ARI). The Oxford-Royal College of General Practitioners Research and Surveillance Centre (RSC) is the English primary care-based sentinel surveillance network.AimThis study describes and validates the RSC's new ARI phenotyping algorithm.MethodsWe developed the phenotyping algorithm using a framework aligned with international interoperability standards. We validated our algorithm by comparing ARI events identified during the 2022/23 influenza season in England through use of both old and new algorithms. We compared clinical codes commonly used for recording ARI.ResultsThe new algorithm identified an additional 860,039 cases and excluded 52,258, resulting in a net increase of 807,781 cases (33.84%) of ARI compared to the old algorithm, with totals of 3,194,224 cases versus 2,386,443 cases. Of the 860,039 newly identified cases, the majority (63.7%) were due to identification of symptom codes suggestive of an ARI diagnosis not detected by the old algorithm. The 52,258 cases incorrectly identified by the old algorithm were due to inadvertent identification of chronic, recurrent, non-infectious and other non-ARI disease.ConclusionWe developed a new ARI phenotyping algorithm that more accurately identifies cases of ARI from the CMR. This will benefit public health by providing more accurate surveillance reports to public health authorities. This new algorithm can serve as a blueprint for other CMR-based surveillance systems wishing to develop similar phenotyping algorithms.

Evaluasi Penggunaan Antibiotik pada Pasien ISPA Non-pneumonia di Puskesmas Senduro Kabupaten Lumajang Tahun 2019

Acute Respiratory Infection (ARI) is an infectious disease of the upper and lower respiratory tract. Non-pneumonic ARI is mostly caused by viral infections so symptomatic therapy can be given, but it can also be caused by bacterial infections so antibiotic therapy is needed. Unwise use of antibiotics can increase bacterial resistance, thereby increasing morbidity and mortality rates. Regular evaluations need to be carried out to reduce the unwise use of antibiotics. The evaluation method that can be used is a quantitative method (ATC/DDD) to determine trends in antibiotic use. This research was conducted on 278 outpatient non-pneumonic ARI patients at the Senduro Lumajang Community Health Center in 2019, with the aim of knowing patient characteristics, antibiotic use profile, and description of antibiotic use using the ATC/DDD method. The results showed that female patients (n=154; 55.4%), were more dominant than male (n=124; 44.6%), patients with the highest age range being 36-45 years (n=70; 25, 2%), the highest diagnosis of ARI was other acute infections of the upper respiratory tract (J06) (n=147; 52.9%), the most commonly used antibiotic was amoxicillin (n=227; 81.6%) and the most rarely used was cefadroxil (n=13; 4.7%). Based on the evaluation results using the ATC/DDD method, it shows that amoxicillin is the antibiotic with the highest DDD value of 7.5 DDD/1000 patients/day and the antibiotic levofloxacin with the lowest DDD value of 0.3 DDD/1000 patients/day.

Metagenomic profiling of nasopharyngeal samples from adults with acute respiratory infection.

Diagnosis of acute respiratory infections (ARIs) is challenging due to the broad diversity of potential microbial causes. We used metagenomic next-generation sequencing (mNGS) to analyze the nasopharyngeal virome of ARI patients, who had undergone testing with a clinical multiplex PCR panel (Amplisens ARVI-screen-FRT). We collected nasopharyngeal swabs from 49 outpatient adults, 32 of whom had ARI symptoms and were PCR-positive, and 4 asymptomatic controls in Kazakhstan during Spring 2021. We assessed the biodiversity of the mNGS-derived virome and concordance with PCR results. PCR identified common ARI viruses in 65% of the symptomatic cases. mNGS revealed viral taxa consisting of human, non-human eukaryotic and bacteriophage groups, comprising 15, 11 and 28 genera, respectively. Notable ARI-associated human viruses included rhinovirus (16.3%), betaherpesvirus 7 (14.3%) and Epstein-Barr virus (8.16%). The primary phage hosts were Streptococcus spp. (32.7%), Pseudomonas aeruginosa (24.5%) and Burkholderia spp. (20.4%). In total, 47% of ARIs were linked solely to bacterial pathogens, a third to viral-bacterial co-infections, and less than 10% to only viral infections by mNGS. PCR showed low concordance with mNGS, except for rhinovirus. These results underscore the importance of broad diagnostic methods and question the effectiveness of commonly used PCR panels in ARI diagnosis.

Ambulatory antibiotic prescription rates for acute respiratory infection rebound two years after the start of the COVID-19 pandemic.

During the COVID-19 pandemic, acute respiratory infection (ARI) antibiotic prescribing in ambulatory care markedly decreased. It is unclear if antibiotic prescription rates will remain lowered. We used trend analyses of antibiotics prescribed during and after the first wave of COVID-19 to determine whether ARI antibiotic prescribing rates in ambulatory care have remained suppressed compared to pre-COVID-19 levels. Retrospective data was used from patients with ARI or UTI diagnosis code(s) for their encounter from 298 primary care and 66 urgent care practices within four academic health systems in New York, Wisconsin, and Utah between January 2017 and June 2022. The primary measures included antibiotic prescriptions per 100 non-COVID ARI encounters, encounter volume, prescribing trends, and change from expected trend. At baseline, during and after the first wave, the overall ARI antibiotic prescribing rates were 54.7, 38.5, and 54.7 prescriptions per 100 encounters, respectively. ARI antibiotic prescription rates saw a statistically significant decline after COVID-19 onset (step change -15.2, 95% CI: -19.6 to -4.8). During the first wave, encounter volume decreased 29.4% and, after the first wave, remained decreased by 188%. After the first wave, ARI antibiotic prescription rates were no longer significantly suppressed from baseline (step change 0.01, 95% CI: -6.3 to 6.2). There was no significant difference between UTI antibiotic prescription rates at baseline versus the end of the observation period. The decline in ARI antibiotic prescribing observed after the onset of COVID-19 was temporary, not mirrored in UTI antibiotic prescribing, and does not represent a long-term change in clinician prescribing behaviors. During a period of heightened awareness of a viral cause of ARI, a substantial and clinically meaningful decrease in clinician antibiotic prescribing was observed. Future efforts in antibiotic stewardship may benefit from continued study of factors leading to this reduction and rebound in prescribing rates.

Sistem Pakar Diagnosis Penyakit ISPA Pada Anak

Acute Respiratory Tract Infections (ARTIs) in children are often challenging to diagnose due to their similar and varied symptoms. Hence, the development of an expert system for diagnosing ARTIs in children is crucial. The aim of this research is to develop an expert system that can assist in the rapid and accurate diagnosis of ARTIs in children. The method employed is the forward chaining approach, where observed symptoms are linked to specific ARTIs through inference rules. Initially, the symptoms of ARTIs and related diseases are identified, forming the knowledge base. Subsequently, the forward chaining algorithm is implemented in the system to facilitate the dissemination of information from observed symptoms to the correct diagnosis. The user interface is designed to facilitate input from users, whether doctors or parents, regarding their child's symptoms. Internal testing is conducted to validate the system's accuracy, involving medical professionals to evaluate and provide feedback on the generated diagnoses. The results indicate that bronchitis is the most likely disease in children based on the total scores of observed symptoms. Treatment recommendations focus on symptomatic care and complication prevention. Thus, the use of an expert system with a forward chaining approach positively contributes to supporting the diagnosis of ARTIs in children by providing faster and more accurate diagnoses and appropriate treatment recommendations.

Burden of respiratory syncytial virus, human metapneumovirus and influenza virus infections in Japanese adults in the Hospitalized Acute Respiratory Tract Infection study

BackgroundRespiratory syncytial virus (RSV), human metapneumovirus (hMPV), and influenza virus are responsible for acute respiratory tract infections (ARTIs) in adults. We assessed the clinical burden of RSV, hMPV and influenza virus infection among Japanese adults hospitalized with ARTIs. MethodsThe Hospitalized Acute Respiratory Tract Infection (HARTI) study was a multinational, prospective cohort study in adults with ARTIs across the 2017–2019 epidemic seasons. Enrolment in Japan began in Sept 2018 and ran until Oct 2019. The clinical diagnosis of ARTI and the decision to hospitalize the patient were made according to local standard of care practices. Viral testing was performed by reverse transcription polymerase chain reaction. ResultsOf the 173 adults hospitalized with ARTI during this period at the Japan sites, 7 (4.0%), 9 (5.2%), and 11 (6.4%) were positive for influenza virus, RSV, and hMPV, respectively. RSV season was observed from Oct 2018 to Jan 2019, followed by influenza from Dec 2018 to Apr 2019. hMPV was detected across both the RSV and influenza seasons. Two patients with RSV and 1 patient with hMPV required ICU admission whereas none with influenza. Use of antibiotics, bronchodilators and inhaled corticosteroids was high amongst patients with RSV and hMPV at 1, 2, and 3 months’ post-discharge compared with patients with influenza, with few exceptions. ConclusionThese findings highlight the need for a high degree of clinical suspicion for RSV and hMPV infection in adults hospitalized with ARTIs.

Epidemiological analysis to identify predictors of X-linked hypophosphatemia (XLH) diagnosis in an Italian pediatric population: the EPIX project

PurposeX-linked hypophosphatemia (XLH) is a rare multi-systemic disease characterized by low plasma phosphate levels. The aim of this study was to investigate the annual XLH prevalence and internally evaluate predictive algorithms’ application performance for the early diagnosis of XLH.MethodsThe PediaNet database, containing data on more than 400,000 children aged up to 14 years, was used to identify a cohort of XLH patients, which were matched with up to 10 controls by date of birth and gender. The annual prevalence of XLH cases per 100,000 patients registered in PediaNet database was estimated. To identify possible predictors associated with XLH diagnosis, a logistic regression model and two machine learning algorithms were applied. Predictive analyses were separately carried out including patients with at least 1 or 2 years of database history in PediaNet.ResultsAmong 431,021 patients registered in the PediaNet database between 2007–2020, a total of 12 cases were identified with a mean annual prevalence of 1.78 cases per 100,000 patients registered in PediaNet database. Overall, 8 cases and 60 matched controls were included in the analysis. The random forest algorithm achieved the highest area under the receiver operating characteristic curve (AUC) value both in the one-year prior ID (AUC = 0.99, 95% CI = 0.99–1.00) and the two-year prior ID (AUC = 1.00, 95% CI = 1.00–1.00) analysis. Overall, the XLH predictors selected by the three predictive methods were: the number of vitamin D prescriptions, the number of recorded diagnoses of acute respiratory infections, the number of prescriptions of antihistamine for systemic use, the number of prescriptions of X-ray of the lower limbs and pelvis and the number of allergology visits.ConclusionFindings showed that data-driven machine learning models may play a prominent role for the prediction of the diagnosis of rare diseases such as XLH.

Application of MALDI-TOF MS and machine learning for the detection of SARS-CoV-2 and non-SARS-CoV-2 respiratory infections.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) could aid the diagnosis of acute respiratory infections (ARIs) owing to its affordability and high-throughput capacity. MALDI-TOF MS has been proposed for use on commonly available respiratory samples, without specialized sample preparation, making this technology especially attractive for implementation in low-resource regions. Here, we assessed the utility of MALDI-TOF MS in differentiating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vs non-COVID acute respiratory infections (NCARIs) in a clinical lab setting in Kazakhstan. Nasopharyngeal swabs were collected from inpatients and outpatients with respiratory symptoms and from asymptomatic controls (ACs) in 2020-2022. PCR was used to differentiate SARS-CoV-2+ and NCARI cases. MALDI-TOF MS spectra were obtained for a total of 252 samples (115 SARS-CoV-2+, 98 NCARIs, and 39 ACs) without specialized sample preparation. In our first sub-analysis, we followed a published protocol for peak preprocessing and machine learning (ML), trained on publicly available spectra from South American SARS-CoV-2+ and NCARI samples. In our second sub-analysis, we trained ML models on a peak intensity matrix representative of both South American (SA) and Kazakhstan (Kaz) samples. Applying the established MALDI-TOF MS pipeline "as is" resulted in a high detection rate for SARS-CoV-2+ samples (91.0%), but low accuracy for NCARIs (48.0%) and ACs (67.0%) by the top-performing random forest model. After re-training of the ML algorithms on the SA-Kaz peak intensity matrix, the accuracy of detection by the top-performing support vector machine with radial basis function kernel model was at 88.0%, 95.0%, and 78% for the Kazakhstan SARS-CoV-2+, NCARI, and AC subjects, respectively, with a SARS-CoV-2 vs rest receiver operating characteristic area under the curve of 0.983 [0.958, 0.987]; a high differentiation accuracy was maintained for the South American SARS-CoV-2 and NCARIs. MALDI-TOF MS/ML is a feasible approach for the differentiation of ARI without specialized sample preparation. The implementation of MALDI-TOF MS/ML in a real clinical lab setting will necessitate continuous optimization to keep up with the rapidly evolving landscape of ARI.IMPORTANCEIn this proof-of-concept study, the authors used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and machine learning (ML) to identify and distinguish acute respiratory infections (ARI) caused by SARS-CoV-2 versus other pathogens in low-resource clinical settings, without the need for specialized sample preparation. The ML models were trained on a varied collection of MALDI-TOF MS spectra from studies conducted in Kazakhstan and South America. Initially, the MALDI-TOF MS/ML pipeline, trained exclusively on South American samples, exhibited diminished effectiveness in recognizing non-SARS-CoV-2 infections from Kazakhstan. Incorporation of spectral signatures from Kazakhstan substantially increased the accuracy of detection. These results underscore the potential of employing MALDI-TOF MS/ML in resource-constrained settings to augment current approaches for detecting and differentiating ARI.

Differential Diagnosis in the Management of Acute Respiratory Infections through Point-of-Care Rapid Testing in a Post-Pandemic Scenario in Latin America: Special Focus on COVID-19, Influenza, and Respiratory Syncytial Virus

This review provides a comprehensive summary of evidence to explore the role and value of differential diagnosis in the management of Acute Respiratory Infections (ARIs) through point-of-care (POC) rapid testing in a post-pandemic scenario, paying particular attention to coronavirus disease 2019 (COVID-19), influenza, and respiratory syncytial virus (RSV). The document builds on a review of literature and policies and a process of validation and feedback by a group of seven experts from Latin America (LATAM). Evidence was collected to understand scientific and policy perspectives on the differential diagnosis of ARIs and POC rapid testing, with a focus on seven countries: Argentina, Brazil, Chile, Colombia, Costa Rica, Mexico, and Peru. The evidence indicates that POC rapid testing can serve to improve ARI case management, epidemiological surveillance, research and innovation, and evidence-based decision-making. With multiple types of rapid tests available for POC, decisions regarding which tests to use require the consideration of the testing purpose, available resources, and test characteristics regarding accuracy, accessibility, affordability, and results turnaround time. Based on the understanding of the current situation, this document provides a set of recommendations for the implementation of POC rapid testing in LATAM, supporting decision-making and guiding efforts by a broad range of stakeholders.

Off-Label Drug Use in Acute Respiration Infection Patient at Pangandaran Hospital, Pangandaran District, West Java - Indonesia

Acute respiratory infections (ARIs) are infectious diseases of the upper or lower respiratory tract that cause a spectrum of illnesses from mild to severe infections. ARI is one of the leading causes of death in children in developing countries. The high incidence of ARI in children results in the use of off-label drugs. Off-label medicine is the use of drugs outside the provisions of the license relating to dose, age, route of administration, contraindications. This study aims to determine the use of off-label drugs in children with a diagnosis of ARI at Pandega Pangandaran Hospital, Pangandaran District, West Java - Indonesia. This study was an observational study with a cross sectional design and data collection was done retrospectively using Chi-square data analysis with a significance level of 0.05. Of the 84 patients who fit the inclusion criteria, there was an off-label drug use of 16.01% with the categories of off-label age (11.16%), off-label dose (4.37%), and off-label indication (0.48%) while in the category of route of administration and contraindications no off-label drug use was found. The most common type of off-label drug used was cetirizine antihistamine. Based on the results, pharmacist’s supervision related to the risk of drug use is strongly recommended.

Dynamic indicators of acute respiratory diseases treatment in children after correction.

Aim: To study the Respiratory pathology of the upper respiratory tract, markers of the inflammatory response of the organism, Oxidative stress, Metabolic adaptation and possibilities of correction. Materials and Methods: The study group (n=111) included school-aged children (10-14 years old). The general group of inflammatory diseases of the respiratory tract (J000-J06) was considered, with a diagnosis of acute respiratory infection (ARI) of viral and bacterial origin and included local inflammationof the upper respiratory tract with presentation of acute pharyngitis (68.0%), acute bronchitis (22,0%), acute tonsillitis (10,0%). Results: Dynamic observation of groups of children who received optimized (group 1, n=60) and basic (group 2, n=51) treatment was carried out. The level of the erythrocyte pool correlated with IL-1 (r=-0,29, p=0,03), IL-4 (r=0,32, p=0,01), TNF-α (r=-0,35 , p=0,006). Creatinine value correlated with IL-10 (r=0,3, p=0,005), γ-IFN (r=0,42, p=0,001), TNF-α (r=0,25, p=0,05). Correlations of ferritin presented positive correlation values with the level of total protein (r=0,26, p=0,04) and TNF-α (r=0,41, p=0,001). Conclusions: After the optimized treatment, there was a significant decrease in the reliable levels of CRP and γ-IFN by 7 and 4,4 times (by groups) and 5,8 and 3,2 times (by groups), respectively. Correlation relationships of urea levels with IL-2,4 were detected. The level of the erythrocyte pool correlated with IL-1,4, TNF-α, Ferritin presented positive correlation values with the level of total protein,TNF-α .

Microfluidic methods for the diagnosis of acute respiratory tract infections.

Acute respiratory tract infections (ARTIs) are caused by sporadic or pandemic outbreaks of viral or bacterial pathogens, and continue to be a considerable socioeconomic burden for both developing and industrialized countries alike. Diagnostic methods and technologies serving as the cornerstone for disease management, epidemiological tracking, and public health interventions are evolving continuously to keep up with the demand for higher sensitivity, specificity and analytical throughput. Microfluidics is becoming a key technology in these developments as it allows for integrating, miniaturizing and automating bioanalytical assays at an unprecedented scale, reducing sample and reagent consumption and improving diagnostic performance in terms of sensitivity, throughput and response time. In this article, we describe relevant ARTIs-pneumonia, influenza, severe acute respiratory syndrome, and coronavirus disease 2019-along with their pathogenesis. We provide a summary of established methods for disease diagnosis, involving nucleic acid amplification techniques, antigen detection, serological testing as well as microbial culture. This is followed by a short introduction to microfluidics and how flow is governed at low volume and reduced scale using centrifugation, pneumatic pumping, electrowetting, capillary action, and propagation in porous media through wicking, for each of these principles impacts the design, functioning and performance of diagnostic tools in a particular way. We briefly cover commercial instruments that employ microfluidics for use in both laboratory and point-of-care settings. The main part of the article is dedicated to emerging methods deriving from the use of miniaturized, microfluidic systems for ARTI diagnosis. Finally, we share our thoughts on future perspectives and the challenges associated with validation, approval, and adaptation of microfluidic-based systems.

Used paper tissues for pathogen identification in acute respiratory infection.

During the Belgian winter and spring season 2022-2023, we investigated the potential of used paper tissue (UPT) as a noninvasive sampling method for the diagnosis of acute respiratory infections. Screening for respiratory pathogens was done using an in-house developed respiratory panel for simultaneous detection of 22 respiratory viruses and sevennonviral pathogens. The method allowed the identification and typing of respiratory pathogens in symptomatic individuals, as well as in collective samples taken at a community level. Pathogens that were identified in nasal swabs could also be detected in concurrent UPT from the same patient. In all cases that tested positive on an antigen-detection rapid diagnostic test, the corresponding virus could be detected in UPT. The collection of UPT could be useful in epidemiological surveillance of severe acute respiratory syndrome coronavirus 2 and other coronaviruses, as well as other respiratory pathogens such as influenzavirus, respiratory syncytial virus, entero/rhinoviruses including EV-D68, parainfluenzaviruses, and Streptococcus pneumoniae. Multiple respiratory pathogens could be detected in UPTs of collectivities, confirming its applicability for community testing. This is especially interesting for screening in nursing homes, centers for the disabled, schools or other settings were taking nasal or nasopharyngeal samples is cumbersome.

A Study of the Clinical Profile and Respiratory Index of Severity in Children (RISC) Score in Infants Admitted With Acute Respiratory Infections at a Tertiary Care Hospital.

Background Pneumonia is a major infectious cause of mortality in young children worldwide. The Respiratory Index of Severity in Children (RISC) score was designed with the intent to provide an objective mean to quantify the severity of lower respiratory tract infection in young children based on their risk of mortality. Knowledge about the clinical profile of acute respiratory infections and the scoring system predicting the risk of mortality helps in modifying treatment strategies. This study was undertaken at a resource-limited, tertiary-care public hospital in southern India with the objectives of describing the clinical profile of infants admitted with acute respiratory infections and determining the association of the RISC score with mortality. Method This was a retrospective observational study conducted over six months. Case records of infants admitted with acute respiratory infections were reviewed. The socio-demographic and clinical details of each case were recorded. The RISC score was calculated using clinical parameters which included the history of refusal of feeds, oxygen saturation lower than 90%, chest in-drawing, wheezing, and low weight-for-age. The maximum score was six. Descriptive data was represented using mean, standard deviation, and percentage or proportion. The association between any two categorical variables was analyzed using the chi-square test. The differences between any two continuous variables were analyzed using the independent sample t-test. A p-value of < 0.05 was considered statistically significant. Results A total of 75 infants were admitted with a diagnosis of acute respiratory infection during the study period. Of these, 68 were included in the study. The mean age of infants was 6.69 ± 3.96 months; 58.8% were male, 41 (60%) were exclusively breastfed, and 51 (75%) were up-to-date immunized. Twenty (29.4%) infants had a history of exposure to indoor smoke. The majority (67.6%) had pneumonia. Nine (13.2%) were mechanically ventilated. The mean duration of hospital stay was 8.16 ± 5.45 days. Sixty-three (92.64%) infants recovered and there were five deaths. The presence of less than 90% oxygen saturation (p-value=0.004), a diagnosis of severe pneumonia (p-value <0.001), and the need for mechanical ventilation (p-value <0.001) were significantly associated with mortality. A statistically significant (p-value=0.001) association was observed between the RISC score and mortality. Conclusions Addressable factors like the absence of exclusive breastfeeding, partial-immunization status, exposure to indoor smoke, and malnutrition were observed in infants with acute respiratory infections, which reinforces the importance of protective and preventive strategies for the control of pneumonia. The RISC score was observed to be beneficial in predicting mortality in an infant with acute respiratory infection. Triaging and early identification of infants at risk of mortality using this score could be very helpful in initiating timely treatment to reduce mortality, especially in resource-limited settings.

Use of antibiotics, in a pediatric hospital, for respiratory infection and diarrheal disease

The World Health Organization (WHO) reports an increasing unjustified use of antibiotics in the treatment of Acute Respiratory Infections (ARI) and Acute Diarrheal Diseases (ADD) in children under five years of age. This has generated problems such as polypharmacy and the inappropriate use of antibiotics; characterized by incorrect dosage, use in viral infections, prescription inconsistent with clinical guidelines. To analyze the prescription of antibiotics, their diagnostic-therapeutic congruence, as well as the correct filling of the medical prescription, in a tertiary level hospital in Mexico. Observational, descriptive cross-sectional study. The electronic medical prescriptions made during the period January-December 2017 with a clinical diagnosis of ARI and EDA were analyzed. Of a total of 21,446 boys and girls under five years of age, 10,233 prescriptions were issued for the treatment of ARI and ADD diagnoses. 80% of the prescriptions complied with the items indicated in the electronic file. The prescription of antibiotics showed a prudent use of antibiotics both in the management of acute diarrheal diseases and in the management of acute respiratory diseases. Diagnostic-therapeutic congruence was found in most of the cases in the prescriptions analyzed.

Diagnostic models predicting paediatric viral acute respiratory infections: a systematic review

ObjectivesTo systematically review and evaluate diagnostic models used to predict viral acute respiratory infections (ARIs) in children.DesignSystematic review.Data sourcesPubMed and Embase were searched from 1 January 1975 to 3 February...

EVALUATION OF A MOTHER'S KNOWLEDGE AND PRACTICE INTERVENTION PROGRAM FOR ACUTE RESPIRATORY INFECTIONS IN INDIAN CHILDREN

Acute respiratory Infection (ARI) causes approximately 3.9 million deaths yearly in children under ve years of age. In developing countries, where malnutrition is prevalent, and indoor air pollution is high, pneumonia is the leading cause of death. A structured questionnaire is used to collect data from 205 mothers. In addition, their practice regarding identifying, managing, and treating ARI is suboptimal due to inadequate knowledge about the signs and symptoms, prevalence, causes, diagnosis, and treatment of ARI. A signicant correlation is found between education and age, whereas a signicant correlation is found between joint family status and knowledge. The study highlights the importance of health education for mothers and suggests that nursing personnel can be crucial in counseling mothers in hospital and community settings

Deepening Analysis on Factors Related to the Mothers’ Practices and Acute Respiratory Infection Disease in Children Under 5 Years Old in The Rural Area, Viet Nam

Objective: The study aimed at identify some factors related to practices of mothers and acute respiratory infection disease in children under 5 years old in rural area, Vietnam. Material and methods: A cross-sectional study was conducted on among 194 mothers and their children under 5 years old in the rural area of Vu Ban District, Nam Dinh province, Vietnam from October 2020 to June 2021. The questionnaire includes 16 items and 3 technique checklists was used which was comprised of sociodemographic factors and information about practices of mothers in prevention and caring for children with acute respiratory infection. The questionnaire and diagnosis of acute respiratory infection (ARI) was based on the revised WHO guidelines. Then the data was collected, analyzed and entered into the SPSS 25.0 program. Using Chi-Square statistics and the odds ratio OR with 95% CI confidence to analyze and determine the relation factors between the two variables in the study. Results: Unsatisfactory practices of mothers in prevention and caring for children with ARI accounted for high percentage (61.9%). In addition, the incidence of ARI in children under 5 years old was 43.8% (85/194 children). There were some relationships between the mothers’ education level, receiving counseling information, number of children, the incidence of ARI in children and mothers' practices about ARI. The difference was statistically significant with p &lt;0.05. There were some relationships between the mothers’ education level, receiving counseling information about ARI, mothers’ practical skills in caring and the incidence of ARI in their children. The difference was statistically significant with p &lt; 0.01. Conclusions: The practices of mothers in prevention and caring for their children with ARI were low. The study revealed that some factors related to practices of mothers and ARI disease in children under 5 years old.

Respiratory culture organism isolation and test characteristics in children with tracheostomies with and without acute respiratory infection.

Among children with tracheostomies, little is known about how respiratory culture results differ between states with and without acute respiratory infections (ARI), or the overall test performance of respiratory cultures. To determine the association of respiratory culture organism isolation with diagnosis of ARI in children with tracheostomies, and assess test characteristics of respiratory cultures in the diagnosis of bacterial ARI (bARI). This single-center, retrospective cohort study included respiratory cultures of children with tracheostomies obtained between 2010 and 2018. The primary predictor was ARI diagnosis code at the time of culture; the primary outcomes were respiratory culture organism isolation and species identified. Generalized estimating equations were used to assess for association between ARI diagnosis and isolation of any organism while controlling for potential confounders and accounting for within-patient clustering. A multinomial logistic regression equation assessed for association with specific species. Test characteristics were calculated using bARI diagnosis as the reference standard. Among 3578 respiratory cultures from 533 children (median 4 cultures/child, interquartile range (IQR): 1-9), 25.9% were obtained during ARI and 17.2% had ≥1 organism. Children with ARI diagnosis had higher odds of organism identification (adjusted odds ratio 1.29, 95% confidence interval [CI] 1.16-1.44). When controlling for covariates, ARI was associated with isolation of Haemophilus influenzae, Moraxella catarrhalis, Streptococcus pneumoniae, and Streptococcus pyogenes. Test characteristics revealed a 24.3% sensitivity, 85.2% specificity, 36.5% positive predictive value, and 76.3% negative predictive value in screening for bARI. The utility of respiratory culture testing to screen for, diagnose, and direct treatment of ARI in children with tracheostomies is limited.