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Signs and Symptoms, Respiratory

Most cited protocols related to «Signs and Symptoms, Respiratory»

Assessing Psychological Impact of COVID-19

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Publication 2020

Anxiety Chinese COVID 19 diacetoxyscirpenol Ethnicity Health Personnel Patients Physical Examination Post-Traumatic Stress Disorder Psychological Distress Sex Characteristics Signs and Symptoms, Respiratory

Validating COPD Diagnosis in Primary Care

The study population consisted of a random sample of individuals selected from all participants registered in CPRD with the cohort entry being on or after 1 January 2004. At cohort entry, people included had to be: over 35 years old, with at least 1 year historical data, and a possible diagnosis of COPD defined as evidence of having ever smoked and a record of at least one specific or possible COPD code or respiratory symptoms suggestive of COPD. The presence of the algorithms was ascertained during a period between patient cohort entry and 31 December 2012. Patients had to be alive within 4 months of the last collection date of CPRD data for the January 2013 data build for inclusion in the analysis so that CPRD could access their medical records and additional information. For the main analysis, a patient could contribute to one algorithm only. It was possible for an individual to be eligible for more than one algorithm depending on the codes used in their medical record over the study period. Individuals were randomly selected from the algorithm with the fewest number of participants first and then removed from the cohort so that they could not be selected for another algorithm.
CPRD mailed a short, structured questionnaire to GPs in charge of randomly selected patients requesting confirmation of COPD status as well as any available specific information from the individual's medical record including spirometry printouts and hospital respiratory outpatient letters (see online supplementary material). Data were ‘twice encrypted’ within CPRD to ensure anonymity, first between practices and CPRD and second from CPRD to researchers. In the questionnaire, the GP was asked whether or not the patient had a diagnosis of COPD, what that diagnosis was based on, whether or not the patient had seen a respiratory physician and if they had, whether there were any other respiratory diagnoses. A pilot set of 20 questionnaires were sent to GPs to assess the quality of the questionnaire. In total, 951 questionnaires were sent out, assuming an 80% response rate.

Quint J.K., Müllerova H., DiSantostefano R.L., Forbes H., Eaton S., Hurst J.R., Davis K, & Smeeth L. (2014). Validation of chronic obstructive pulmonary disease recording in the Clinical Practice Research Datalink (CPRD-GOLD). BMJ Open, 4(7), e005540.

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Publication 2014

Chronic Obstructive Airway Disease Diagnosis Outpatients Patients Physicians Respiratory Rate Signs and Symptoms, Respiratory Spirometry Vision

Korean Multicenter COPD Cohort Study

Recruitment and measurement occurred between December 2011 and October 2014. There are 45 study centers throughout Korea (Seoul, Pusan, Daegu, Incheon, Chungcheong-do, Gyeonggi-do, Gangwon-do, Gyeongsang-do, and Jeju-do) that are enrolling patients. Inclusion criteria are diagnosis of COPD by a pulmonologist, age ≥ 40 years, symptoms including cough, sputum, dyspnea, and post-bronchodilator forced expiratory volume in one second (FEV₁)/forced vital capacity (FVC) of 70% less than normal predicted value. The medical history at the first visit included frequency and severity of exacerbations in the previous 12 months, smoking status, patient-reported education level, medications, including those already prescribed for COPD, and comorbidities. For diagnosis of depression, we used Beck Depression Inventory (BDI), which confirmed of its validity and reliability (7 (link)). The medical research council (mMRC) dyspnea score was recorded, as were results of the COPD assessment test (CAT) and the COPD-specific version of St. George’s Respiratory Questionnaire (SGRQ-C). A 6-minute walk distance (6MWD) test was also performed. All of the data were reported using case-report forms (CRFs) completed by physicians or trained nurses, and patients were to be evaluated at regular 6-month intervals after the initial examination. The initial data sets were analyzed to identify the baseline patient characteristics that are reported in this study. Major exclusion criteria were asthma, other obstructive lung diseases including bronchiectasis, tuberculosis destroyed lung, inability to complete pulmonary function test, myocardial infarction or cerebrovascular event within the previous 3 months, pregnancy, rheumatoid disease, malignancy, irritable bowel disease, and steroid use for conditions other than COPD exacerbation within 8 weeks before enrollment. Exacerbations were defined as worsening of any respiratory symptom, such as increased sputum volume, purulence, or increased dyspnea, which required treatment with systemic corticosteroids, antibiotics, or both.

Lee J.Y., Chon G.R., Rhee C.K., Kim D.K., Yoon H.K., Lee J.H., Yoo K.H., Lee S.H., Lee S.Y., Kim T.E., Kim T.H., Park Y.B., Hwang Y.I., Kim Y.S, & Jung K.S. (2016). Characteristics of Patients with Chronic Obstructive Pulmonary Disease at the First Visit to a Pulmonary Medical Center in Korea: The KOrea COpd Subgroup Study Team Cohort. Journal of Korean Medical Science, 31(4), 553-560.

Publication 2016

Adrenal Cortex Hormones Antibiotics Asthma Bronchiectasis Bronchodilator Agents Chronic Obstructive Airway Disease Cough Diagnosis Dyspnea Education of Patients Forced Vital Capacity Irritable Bowel Syndrome Lung Lung Diseases, Obstructive Malignant Neoplasms Myocardial Infarction Nurses Patients Pharmaceutical Preparations Physicians Pregnancy Pulmonologists Respiratory Rate Signs and Symptoms, Respiratory Sputum Steroids Tests, Pulmonary Function Tuberculosis Volumes, Forced Expiratory

Laboratory Confirmation of SARS-CoV-2 Infection

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Publication 2020

Blood Chest Chinese Complete Blood Count Cough COVID 19 Creatine Kinase Dyspnea Electrolytes Enzymes Ferritin Fever Inpatient Interleukin-6 Kidney Lactate Dehydrogenase Liver Lung Myocardium Patient Discharge Pharynx Physical Examination Physicians Procalcitonin Radiography, Thoracic Real-Time Polymerase Chain Reaction Respiratory Rate SARS-CoV-2 Serum Signs and Symptoms, Respiratory Tests, Blood Coagulation X-Ray Computed Tomography

Influenza Transmission Dynamics in Households

We estimated secondary attack rates, based on the proportion of household contacts in whom influenza developed (as determined by RT-PCR assay), as well as rates of acute respiratory illness and influenza-like illness. We calculated 95% confidence intervals for the crude secondary attack rates using a cluster bootstrap method with 1000 resamples.¹⁵ Households in which one or more household contacts had RT-PCR–confirmed influenza at the baseline home visit (i.e., households with one or more potential co-index patients) were excluded from the analysis of secondary attack rates.
We calculated standardized daily scores for three groups of signs and symptoms — systemic signs and symptoms (temperature ≥37.8°C, headache, and myalgia), upper respiratory symptoms (sore throat and runny nose), and lower respiratory symptoms (cough and phlegm) — by adding up the total number of signs and symptoms that were present and dividing by the highest possible score (3, 2, and 2, respectively).^{16 (link),17 (link)} We plotted average symptom scores according to the time since the onset of acute respiratory illness, which was defined as the first day when the subject reported at least two of the seven signs or symptoms listed above.^{16 (link),18 (link)}We defined the serial interval as the time between the onset of illness in an index patient and the onset of illness in a household contact. We estimated serial interval distributions on the basis of an underlying Weibull distribution, using methods that have been described previously.^{18 (link)} We estimated 95% confidence intervals for the mean serial interval, using a parametric bootstrap approach with 1000 resamples.^{18 (link),19}We estimated geometric mean antibody titers and used Wilcoxon signed-rank tests to compare groups. Antibody titers below the lower limit of 1:10 were estimated to be 1:5 for calculations of geometric mean titers. Statistical analyses were performed with the use of R software, version 2.8.1 (R Development Core Team). Raw data from the study and R syntax to permit additional statistical analyses are available by contacting the corresponding author.

Cowling B.J., Chan K.H., Fang V.J., Lau L.L., So H.C., Fung R.O., Ma E.S., Kwong A.S., Chan C.W., Tsui W.W., Ngai H.Y., Chu D.W., Lee P.W., Chiu M.C., Leung G.M, & Peiris J.S. (2010). Comparative Epidemiology of Pandemic and Seasonal Influenza A in Households. The New England journal of medicine, 362(23), 2175-2184.

Publication 2010

Biological Assay Cough Headache Households Immunoglobulins Myalgia Patients Respiratory Rate Reverse Transcriptase Polymerase Chain Reaction Rhinorrhea Signs and Symptoms, Respiratory Sore Throat Virus Vaccine, Influenza

Most recents protocols related to «Signs and Symptoms, Respiratory»

Respiratory Illness Improvement with Mineral Supplement

Not available on PMC !

Example 2

Five subjects (males, ages 34 to 52 years old) each with a respiratory illness and having SpO₂less than 92% were administered a composition comprising 1200 mg of potassium nitrate, 200 mg of elemental magnesium, 50 mg of elemental zinc in one capsule, co-administered with another capsule containing 1000 mg of citric acid. Their blood oxygen saturation level was measured between 15 to 80 minutes after ingestion of the composition. Their symptoms related to the respiratory illness were also recorded before and after ingestion of the composition. Table 2 summarizes the results.

TABLE 2

Improvement of respiratory symptoms after treatment.

Subject AgeSpO₂(%)Alleviated

(years)BeforeAfterSymptomsSymptoms

349298FatigueFatigue

469398HeadacheHeadache

399297Fatigue,Cloudy head

cloudy head

459095DifficultyDifficulty

breathingbreathing

528998Body aches,Anxiety

anxiety

US11865139B2. Method of treating migraines and headaches (2024-01-09). ThermoLife International, LLC [US]. Inventors: Ronald Kramer [US], Alexandros Nikolaidis [GR].

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Patent 2024

Ache Anxiety Blood Oxygen Levels Capsule Citric Acid Fatigue Head Headache Human Body Magnesium Males Migraine Disorders potassium nitrate Respiratory Rate Saturation of Peripheral Oxygen Signs and Symptoms, Respiratory Zinc

Breath-based Tuberculosis Diagnosis Model

We conducted a cross-sectional study from 1 March 2020 to 31 March 2021 at The Third People's Hospital of Shenzhen. The study was approved by the Ethics Committee of The Third People's Hospital of Shenzhen (number: 2020-012). Written informed consent was obtained from all participants.
The total participants consisted of a case group and a control group. For the case group, confirmed PTB patients were prospectively and consecutively recruited based on the following criteria: (1) aged 18–70 years old; (2) diagnosed by Xpert and/or culture, with suggestive clinical and radiological findings; (3) anti-TB treatment not initiated or started less than 2 weeks. The control group consists of two parts: healthy controls with no pulmonary diseases (HC) and patients with pulmonary diseases (unhealthy controls, UHC) which could be noninfectious diseases or infectious diseases other than PTB. HCs were simultaneously recruited and underwent a physical examination with the following criteria: (1) aged 18–70 years old; (2) no respiratory symptoms (e.g., cough, sputum, hemoptysis, shortness of breath, dyspnea, or chest pain); (3) no pulmonary lesions by chest imaging (chest X-ray or computed tomography). For UHC, they should: (1) aged 18–70 years old; (2) have pathogenic confirmed infectious diseases or treatment response suggestive of pulmonary infectious diseases, or have chronic noninfectious diseases, without evidence of infection. Both the case group and the control group would be excluded if the airbag leaked or were unable to take enough breath volume. The participant enrollment flow is illustrated in Fig. 1a. A total of 518 PTB patients and 887 controls with 77 UHC and 810 HC were enrolled in this study.Fig. 1

The flow of participants enrollment and PTB detection model construction and test

The physicians were responsible for making a clinical diagnosis and for the collection of the breath samples. The other researchers performed the VOCs detection and ML modeling and were blinded to clinical data and other test results. Additionally, the physicians were also blinded to the breath test results. The demographic and clinical characteristics of all participants were collected and summarized in Table 1, including age, sex, and antituberculosis therapy.Table 1

Demographic characteristics of participants

	Discovery data set			Test data set
	PTB (N = 361)	Control (N = 614)	p-value	PTB (N = 157)	Control (N = 273)	p-value
Age
Median (min.–max.)	36 (18–70)	28 (18–69)	< 0.001	32 (18–70)	28 (18–70)	< 0.001
< 30 (%)	115 (31.9)	345 (56.2)	0.008	64 (40.8)	169 (61.9)	0.258
≥ 30 (%)	246 (68.1)	269 (43.8)	< 0.001	93 (59.2)	104 (38.1)	0.009
Sex
Male (%)	223 (61.8)	325 (52.9)	0.009	101 (64.3)	142 (52.0)	0.004
Female (%)	138 (38.2)	289 (47.1)	–	56 (35.7)	131 (48.0)	–

Bold p-value shows that there are significant differences between PTB and controls

Fu L., Wang L., Wang H., Yang M., Yang Q., Lin Y., Guan S., Deng Y., Liu L., Li Q., He M., Zhang P., Chen H, & Deng G. (2023). A cross-sectional study: a breathomics based pulmonary tuberculosis detection method. BMC Infectious Diseases, 23, 148.

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Publication 2023

Breath Tests Chest Chest Pain Communicable Diseases Cough Diagnosis Disease, Chronic Dyspnea Ethics Committees, Clinical Hemoptysis Infection Lung Lung Diseases Males Noncommunicable Diseases pathogenesis Patients Physical Examination Physicians Radiography, Thoracic Signs and Symptoms, Respiratory Specimen Collection Sputum Therapeutics Woman X-Ray Computed Tomography X-Rays, Diagnostic

Assessing COVID-19 Severity and Risk Factors

Clinical, laboratory, and chest imaging data obtained during COVID-19, other risk factors for severe COVID-19 (Rodrigues et al., 2020 (link); Zhang et al., 2020a (link), 2022a (link); Bennett et al., 2021 (link); Bourgeois et al., 2021 (link); Kooistra et al., 2021 (link); Navaratnam et al., 2021 (link); O’Driscoll et al., 2021 (link); Westblade et al., 2021 (link); Martin et al., 2022a (link); Schober et al., 2022 (link); Woodruff et al., 2022 (link)), and family history were collected for each patient in the survey. Concomitant infections were also recorded, when supported by clinical suspicion, positive cultures, and/or chest x-ray images. Adults with a body mass index (BMI) over 25 were considered to be overweight, and those with a BMI over 30 were considered to be obese. Children aged between 5 and 19 yr were considered to be obese if their BMI-for-age-and-sex was more than 2 SD above the WHO Growth Reference median. Children under 5 yr of age were considered to be obese if their weight-for-height was more than 3 SD above the WHO Child Growth Standard median (WHO, 2021 ).
COVID-19 severity was assessed according to the Human Genetic Effort clinical score (Asano et al., 2021 (link)). SARS-CoV-2 infection was classified as mild/non-confirmed pneumonia (for patients who were asymptomatic, presented upper respiratory tract disease with no signs of pneumonia on x ray or with respiratory symptoms not suggestive of a lower respiratory tract infection and therefore not requiring x ray), moderate (non-hypoxemic pneumonia, not requiring oxygen therapy), severe (hypoxemic pneumonia requiring therapy with oxygen <6 liters O₂/min, without meeting the criteria for critical pneumonia) or critical (hypoxemic pneumonia requiring high-flow oxygen >6 liters O₂/min, ventilatory support with or without intubation, or ECMO [extracorporeal membrane oxygenation]).
Laboratory values were recorded when available. Normal ranges of laboratory values were reported according to age and are expressed in standard units (Hollowell et al., 2005 (link); Mayo Clinic, 2022 ).

García-García A., Pérez de Diego R., Flores C., Rinchai D., Solé-Violán J., Deyà-Martínez À., García-Solis B., Lorenzo-Salazar J.M., Hernández-Brito E., Lanz A.L., Moens L., Bucciol G., Almuqamam M., Domachowske J.B., Colino E., Santos-Perez J.L., Marco F.M., Pignata C., Bousfiha A., Turvey S.E., Bauer S., Haerynck F., Ocejo-Vinyals J.G., Lendinez F., Prader S., Naumann-Bartsch N., Pachlopnik Schmid J., Biggs C.M., Hildebrand K., Dreesman A., Cárdenes M.Á., Ailal F., Benhsaien I., Giardino G., Molina-Fuentes A., Fortuny C., Madhavarapu S., Conway D.H., Prando C., Schidlowski L., Martínez de Saavedra Álvarez M.T., Alfaro R., Rodríguez de Castro F., Meyts I., Hauck F., Puel A., Bastard P., Boisson B., Jouanguy E., Abel L., Cobat A., Zhang Q., Casanova J.L., Alsina L, & Rodríguez-Gallego C. (2023). Humans with inherited MyD88 and IRAK-4 deficiencies are predisposed to hypoxemic COVID-19 pneumonia. The Journal of Experimental Medicine, 220(5), e20220170.

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Publication 2023

Adult Chest Child Clinical Laboratory Services COVID 19 Extracorporeal Membrane Oxygenation Index, Body Mass Infection Intubation Obesity Patients Pneumonia Radiography Respiratory Tract Diseases Respiratory Tract Infections Signs and Symptoms, Respiratory Therapies, Oxygen Inhalation

Diagnosing Bacterial and Fungal Infections

Bacterial infections are classified as bacteremia or site-specific infections. Multiple positive blood cultures for different organisms on the same day are considered distinct events. If bacterial isolates were a possible skin contaminant (diphtheria, bacillus or coagulase-negative staphylococci) and were isolated in only one blood culture, they were excluded unless systemic antibiotics were given. Infections were recorded if there was a microbiologic or histopathologic diagnosis, and the date of onset of infection was defined as the date on which diagnostic testing was performed. A second event was considered if repeated positive cultures and intermediate cultures were negative >21 days after the initial diagnosis. Site-specific bacterial infection was defined as evidence of bacterial infection by the culture of a normally sterile site or culture of a nonsterile site and evidence of tissue invasion. Lower respiratory tract infection was defined as the detection of a respiratory virus in bronchoalveolar lavage fluid with new or changing pulmonary infiltrates and lower respiratory tract symptoms. Invasive mycosis may be present, and fungal infection is documented. Infections caused by respiratory viruses were classified as upper respiratory tract infections if the virus was detected in nasopharyngeal/throat washes or swabs, sinuses or sputum without symptoms or clinical evidence of lower respiratory tract infection.

Gao Z., Lian Y., Ti J., Ren R, & Ma L. (2023). Therapeutic efficacy and infectious complications of CD19-targeted chimeric antigen receptor-modified T cell immunotherapy. Anti-Cancer Drugs, 34(4), 551-557.

Publication 2023

Antibiotics Bacteremia Bacteria Bacterial Infections Blood Culture Bronchoalveolar Lavage Fluid Coagulase Diagnosis Diphtheria Infection Lacticaseibacillus casei Lung Mycoses Nasopharynx Pharynx Respiratory Rate Respiratory Tract Infections Signs and Symptoms, Respiratory Sinuses, Nasal Skin Sputum Staphylococcus Sterility, Reproductive Tissues Upper Respiratory Infections Virus

COVID-19 Outcomes in Rheumatic Diseases

Demographic, clinical and laboratory data pertaining to both COVID-19 and RMD were recorded for all included patients according to a predesigned proforma. Clinical symptoms attributable to COVID-19, vital signs, treatment(s) administered for COVID-19 (antivirals and/or immunomodulatory therapies) and the final outcome (death or recovery) were noted. Severe and critical disease as defined by the World Health Organization (WHO) were grouped together as severe disease for the purpose of the present study and defined as the presence of oxygen saturation <90% on room air or signs of severe respiratory distress in addition to signs of pneumonia or presence of ARDS, sepsis, septic shock or other conditions that would normally require the provision of life-sustaining therapies, such as mechanical ventilation (invasive or non-invasive) or vasopressor therapy [18 ]. In addition, based on national guidelines [19 ], non-severe disease was categorized further as moderate disease (defined by a respiratory rate >24/min or a peripheral oxygen saturation between 90 and 94%) and as mild disease when patients with RT-PCR-confirmed SARS-CoV-2 had only upper respiratory tract symptoms without any hypoxaemia or tachypnoea. Laboratory parameters recorded included haemogram, liver function tests (total and direct bilirubin, aspartate transaminase, alanine transaminase, γ-glutamyl transferase, alkaline phosphatase and serum albumin), renal function tests, CRP, ferritin, D-dimer, fibrinogen, international normalized ratio and procalcitonin (hospitalized patients only). The neutrophil-to-lymphocyte ratio was also calculated from the differential leucocyte count. Data pertaining to the type of underlying RMD, disease activity status (active vs remission) at the time of acquisition of SARS-CoV-2, and ongoing treatment [supportive, NSAIDs, glucocorticoids (GCs), conventional synthetic DMARDs (including HCQ, MTX, LEF, SSZ, AZA, MMF and CYC), biologic DMARDs (rituximab or anti TNF), antifibrotics (nintedanib or pirfenidone) or IVIG] were also noted, along with details of underlying medical co-morbidities. DMARDs were also categorized into immunomodulators (MTX, LEF and SSZ) and immunosuppressants (CYC, AZA, MMF and biologic DMARDs) for the purpose of predictor analysis.
Outcomes of interest included the proportion of patients with severe COVID-19, mortality (as a percentage), hospitalization (as a percentage), intensive care unit (ICU) stay (as a percentage), the requirement for respiratory support (as a percentage) and its level (oxygen delivered by face mask or nasal prongs, non-rebreathing mask, high-flow nasal cannula, non-invasive ventilation or invasive mechanical ventilation). Predictors of COVID-19 severity, mortality and hospitalization were determined.

Mathew J., Jain S., Susngi T., Naidu S., Dhir V., Sharma A., Jain S, & Sharma S.K. (2023). Predictors of COVID-19 severity and outcomes in Indian patients with rheumatic diseases: a prospective cohort study. Rheumatology Advances in Practice, 7(1), rkad025.

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Publication 2023

Alanine Transaminase Alkaline Phosphatase Anti-Inflammatory Agents, Non-Steroidal Antirheumatic Drugs, Disease-Modifying Antiviral Agents Bilirubin Biological Response Modifiers Biopharmaceuticals COVID 19 Face Ferritin fibrin fragment D Fibrinogen gamma-Glutamyl Transpeptidase Glucocorticoids Hospitalization Immunomodulation Immunosuppressive Agents International Normalized Ratio Intravenous Immunoglobulins Kidney Function Tests Leukocyte Counts, Differential Liver Function Tests Lymphocyte Mechanical Ventilation Nasal Cannula Neutrophil nintedanib Noninvasive Ventilation Nose Oxygen Oxygen Saturation Patients pirfenidone Pneumonia Procalcitonin Respiratory Distress Syndrome, Adult Respiratory Rate Reverse Transcriptase Polymerase Chain Reaction Rituximab SARS-CoV-2 Saturation of Peripheral Oxygen Septicemia Septic Shock Serum Albumin Signs, Vital Signs and Symptoms, Respiratory Transaminase, Serum Glutamic-Oxaloacetic Vasoconstrictor Agents

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What are the common signs and symptoms of respiratory issues?

The most common signs and symptoms of respiratory system dysfunction include breathing difficulties, coughing, chest pain, and abnormal lung sounds. These can indicate a variety of underlying respiratory conditions, from asthma and COPD to pneumonia and lung cancer. Understanding the specific signs and symptoms can help researchers optimize their respiratory research protocols and ensure accurate, reproducible results.

How can PubCompare.ai help with respiratory research?

PubCompare.ai allows researchers to screen respiratory protocol literature more efficiently and leverage AI to pinpoint critical insights. The platform's AI-driven analysis can help researchers identify the most effective protocols related to signs and symptoms of respiratory issues for their specific research goals. By highlighting key differences in protocol effectiveness, PubCompare.ai enables researchers to choose the best option for reproducibility and accuracy in their respiratory studies.

What are some variations or types of respiratory signs and symptoms?

Respiratory signs and symptoms can vary widely, from shortness of breath and wheezing to chest congestion and coughing up mucus. Some patients may experience pain or tightness in the chest, while others may have difficulty taking deep breaths. Abnormal lung sounds, such as crackles or rhonchi, can also be indicative of respiratory problems. Researchers need to be aware of these different variations to select the most appropriate protocols for their work.

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PubCompare.ai's comprehensive respiratory signs and symptoms tool is a one-stop shop for researchers looking to optimize their research protocols. The platform's AI-driven comparisons can help researchers locate the best protocols, products, and pre-prints from literature, patents, and more. This allows them to make informed decisions about the most effective methods for measuring and analyzing respiratory signs and symptoms, improving their research outcomes and the reproducibility of their studies.

What are some specific applications of respiratory signs and symptoms data?

Respiratory signs and symptoms data can be used in a variety of applications, such as diagnosing respiratory conditions, monitoring disease progression, and evaluating the effectiveness of treatment interventions. Researchers may also use this data to develop new diagnostic tools, test novel therapies, or better understand the underlying mechanisms of respiratory diseases. By leveraging PubCompare.ai's AI-driven insights, researchers can ensure they are using the most appropriate protocols and methods for their specific applications.

More about "Signs and Symptoms, Respiratory"

Respiratory signs and symptoms are indications of respiratory system dysfunction, including breathing difficulties, coughing, chest pain, and abnormal lung sounds.
This comprehensive resource helps researchers optimize respiratory research protocols, leveraging AI-driven comparisons to locate the best protocols, products, and pre-prints from literature, patents, and more.
Improve your research outcomes with PubCompare.ai's respiratory signs and symptoms tool - a one-stop shop for reproducible, accurate respiratory research.
Signs and symptoms of respiratory disorders can include shortness of breath (dyspnea), wheezing, coughing, chest discomfort or pain, and abnormal breath sounds like rales, rhonchi, or stridor.
These indications can be caused by a variety of underlying conditions affecting the lungs, airways, or respiratory muscles, such as asthma, COPD, pneumonia, lung cancer, or pulmonary fibrosis.
Leveraging advanced statistical software like SAS 9.4, Stata 12.0, Stata 14, SPSS version 23, and Stata version 13 and 16, researchers can analyze respiratory sign and symptom data to identify patterns, risk factors, and treatment outcomes.
Proper protocol design and data analysis are crucial for producing high-quality, reproducible respiratory research.
PubCompare.ai's respiratory signs and symptoms tool can help optimize research protocols by providing AI-driven comparisons of the latest literature, patents, and pre-prints.
This comprehensive resource allows researchers to quickly identify the best practices, products, and methodologies to improve the accuracy and reproducibility of their work, leading to better research outcomes.