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D012769: Shock

Developed by Shray Alag, The Harker School
Sections: Correlations, Clinical Trials, and HPO

Correlations computed by analyzing all clinical trials.

Navigate: Clinical Trials and HPO


Correlated Drug Terms (13)


Name (Synonyms) Correlation
drug291 Assessment of coagulopathy, Platelets activation and Platelets-Neutrophils interplay Wiki 0.38
drug3419 Transpulmonary thermodilution Wiki 0.38
drug129 AZVUDINE placebo Wiki 0.38
Name (Synonyms) Correlation
drug2158 Nitazoxanide with ivermectin Wiki 0.38
drug128 AZVUDINE Wiki 0.38
drug3389 Toraymyxin PMX-20R (PMX Cartridge) Wiki 0.38
drug591 COVID-19 FACILITY Wiki 0.38
drug712 Cerebral compliance and hemodynamics monitoring Wiki 0.38
drug1542 ICU treatment Wiki 0.27
drug3005 Seraph 100 Wiki 0.27
drug1120 Echocardiography Wiki 0.22
drug3742 convalescent plasma Wiki 0.15
drug1705 Ivermectin Wiki 0.08

Correlated MeSH Terms (17)


Name (Synonyms) Correlation
D012772 Shock, Septic NIH 0.53
D012770 Shock, Cardiogenic NIH 0.38
D019446 Endotoxemia NIH 0.38
Name (Synonyms) Correlation
D019586 Intracranial Hypertension NIH 0.38
D018754 Ventricular Dysfunction NIH 0.19
D018487 Ventricular Dysfunction, Left NIH 0.19
D004211 Disseminated Intravascular Coagulation NIH 0.17
D018805 Sepsis NIH 0.13
D020141 Hemostatic Disorders NIH 0.10
D001778 Blood Coagulation Disorders NIH 0.10
D000860 Hypoxia NIH 0.07
D012128 Respiratory Distress Syndrome, Adult NIH 0.06
D016638 Critical Illness NIH 0.05
D012127 Respiratory Distress Syndrome, Newborn NIH 0.03
D055371 Acute Lung Injury NIH 0.03
D045169 Severe Acute Respiratory Syndrome NIH 0.02
D018352 Coronavirus Infections NIH 0.01

Correlated HPO Terms (6)


Name (Synonyms) Correlation
HP:0030149 Cardiogenic shock HPO 0.38
HP:0002516 Increased intracranial pressure HPO 0.38
HP:0005521 Disseminated intravascular coagulation HPO 0.17
Name (Synonyms) Correlation
HP:0100806 Sepsis HPO 0.13
HP:0001928 Abnormality of coagulation HPO 0.10
HP:0012418 Hypoxemia HPO 0.07

Clinical Trials

Navigate: Correlations   HPO

There are 7 clinical trials


1 Prospective Evaluation of PLatelets Acetyl-CoA Carboxylase Phosphorylation State in SEPtic Shock Patients. Impact of Platelets Metabolism to Inflammatory Response.

Knowing the dramatic increase in thrombin generation during sepsis, our research hypothesis is that AMPK-induced ACC phosphorylation in platelets is increased and that this might modulate platelets metabolism and more particularly platelets inflammatory mediators content, coming from AA and lipids.

NCT04107402
Conditions
  1. Septic Shock
  2. Platelet Signal Processing Defect
  3. Inflammatory Response
  4. Disseminated Intravascular Coagulation
  5. Covid19
  6. Neutrophil Extracellular Trap Formation
Interventions
  1. Other: Assessment of coagulopathy, Platelets activation and Platelets-Neutrophils interplay
MeSH:Shock, Septic Disseminated Intravascular Coagulation Shock
HPO:Disseminated intravascular coagulation

Primary Outcomes

Description: ACC phosphorylation on Ser79 (phosphoACC) in platelets of patients will be assessed using western blotting. Results will be expressed in arbitrary units (A.U). A signal above 0.5 A.U. has already been shown to be above 2 standard deviation in a healthy population.

Measure: Platelets Acetyl-CoA Carboxylase phosphorylation rate

Time: At the time of inclusion

Secondary Outcomes

Description: Sepsis severity will be assessed using the SOFA score (Sepsis-related Organ Failure Assessment). Range from 0( less severe) to 24 (more severe).

Measure: Sepsis severity

Time: At the time of inclusion

Description: Sepsis severity will be assessed using the APACHE II score) Acute Physiology And Chronic Health Evaluation) Range 0 (less severe) to 299 (more severe).

Measure: Sepsis severity

Time: At the time of inclusion

Measure: Mortality rate

Time: 30 days and 1-year follow-up

Description: Platelet function will be assessed using platelets aggregometry. The Aggregation (in AU), the maximum height of the curve during the measurement period will be assessed.

Measure: Platelet function assessment

Time: At the time of inclusion

Description: Platelet function will be assessed using platelets aggregometry. Area Under the aggregation Curve (AUC) will be assessed and recorded as Units or U.

Measure: Platelet function assessment

Time: At the time of inclusion

Description: Platelet function will be assessed using platelets aggregometry. Velocity (in AU/min), the maximum slope of the curve will be assessed.

Measure: Platelet function assessment

Time: At the time of inclusion

Description: D-Dimers (ng/ml)

Measure: Thrombin generation marker rate

Time: At the time of inclusion

Description: Urinary Thrombin-antithrombin complex (ng/mL)

Measure: Thrombin generation marker rate

Time: At the time of inclusion

Description: Tubulin acetylation will be assessed using western blotting. Results will be expressed in arbitrary units (A.U).

Measure: Tubulin acetylation rate

Time: At the time of inclusion

Description: Total platelets lipid content and composition will be assessed using metabolomics approach by Mass Spectrometry. Fold-change estimates and corresponding P values were derived from regression models for each lipid species and each predictor. To control for multiple testing, all P values will be further adjusted for Benjamini-Hochberg false discovery rate (FDR), with a FDR <0.05 considered statistically significant

Measure: Total platelets lipid content and composition

Time: At the time of inclusion

Description: Myeloperoxidase MPO (ng/mL)

Measure: Neutrophils extracellular trap formation

Time: At the time of inclusion

Description: Citrulinated Histon 3 H3-Cit (ng/mL)

Measure: Neutrophils extracellular trap formation

Time: At the time of inclusion

Description: Soluble CD62P (ng/mL)

Measure: Platelets activation

Time: At the time of inclusion

Description: PaO2/FiO2

Measure: Respiratory failure

Time: At the time of inclusion and through study completion up to day 30
2 Hemodynamic Characteristics of Patients With SARS-CoV-2: PiCCOVID Study

The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been declared a public health emergency of international concern. Hospitalized COVID-19-positive patients requiring ICU care is increasing along with the course of epidemic. A large number of these patients developed acute respiratory distress syndrome (ARDS) according to current data. However, the related hemodynamic characteristic has so far been rarely described.

NCT04337983
Conditions
  1. Coronavirus
  2. SARS-CoV-2
  3. COVID-19
  4. Acute Respiratory Distress Syndrome
  5. Shock
  6. Acute Circulatory Failure
  7. Left Ventricular Dysfunction
  8. Fluid Overload
Interventions
  1. Device: Transpulmonary thermodilution
  2. Device: Echocardiography
MeSH:Respiratory Distress Syndrome, Newborn Respiratory Distress Syndrome, Adult Acute Lung Injury Ventricular Dysfunction Ventricular Dysfunction, Left Shock

Primary Outcomes

Description: Body temperature(°C)

Measure: Body temperature

Time: Through study completion, an estimation of 6 months

Description: Blood pressure in mmHg

Measure: Blood pressure

Time: Through study completion, an estimation of 6 months

Description: Pulse (heart rate) in times/minute

Measure: Pulse (heart rate)

Time: Through study completion, an estimation of 6 months

Description: Respiratory rate in times/minute

Measure: Respiratory rate

Time: Through study completion, an estimation of 6 months

Description: Cardiac index (L/min/m2)

Measure: Data provided by transpulmonary thermodilution-CI

Time: Through study completion, an estimation of 6 months

Description: Global end-diastolic volume(mL/m2)

Measure: Data provided by transpulmonary thermodilution-GEDV

Time: Through study completion, an estimation of 6 months

Description: Extravascular lung water (mL/kg)

Measure: Data provided by transpulmonary thermodilution-EVLW

Time: Through study completion, an estimation of 6 months

Description: Pulmonary vascular permeability index

Measure: Data provided by transpulmonary thermodilution-PVPI

Time: Through study completion, an estimation of 6 months

Measure: Incidence of abnormal laboratory test results

Time: Through study completion, an estimation of 6 months

Secondary Outcomes

Description: Left ventricle ejection fraction, Segmental left ventricle contractility, Speckle tracking data of the left and right ventricles, Dimensions of right and left cavities and Diastolic function of left ventricle

Measure: Incidence of new-onset or reversible systolic left ventricular dysfunction

Time: Through study completion, an estimation of 6 months

Description: The worst extravascular lung water

Measure: Changes of extravascular lung water measured by transpulmonary thermodilution

Time: Change from baseline extravascular lung water at 6 months

Description: The worst pulmonary vascular permeability index

Measure: Changes of pulmonary vascular permeability index measured by transpulmonary thermodilution

Time: Change from baseline extravascular lung water at 6 months

Measure: Correlation between the hemodynamic characteristics and 90-day mortality

Time: Up to 90th day after inclusion
3 Evaluating the Use of Polymyxin B Cartridge Hemoperfusion for Patients With Septic Shock and COVID 19

Prospective, observational, clinical investigation of PMX cartridge use in COVID 19 patients with septic shock

NCT04352985
Conditions
  1. Septic Shock
  2. Endoto
  3. Endotoxemia
  4. COVID
  5. Corona Virus Infection
  6. Sepsis, Severe
Interventions
  1. Device: Toraymyxin PMX-20R (PMX Cartridge)
MeSH:Shock, Septic Endotoxemia Sepsis Coronavirus Infections Severe Acute Respiratory Syndrome Shock
HPO:Sepsis

4 The RIsk Stratification in COVID-19 Patients in the ICU Registry

The Risk stratification in COVID-19 patients in the ICU (RISC-19-ICU) registry was founded during the emerging SARS-CoV-2 pandemic. COVID-19 is a novel disease caused by infection with the SARS-CoV-2 virus that was first described in December 2019. The disease has spread exponentially in many countries and has reached global pandemic status within three months. According to first experience, hospitalization was required in approximately 20 % of cases and severe, life-threatening illness resulted in approximately 10 %. In some countries, health care systems were overwhelmed by the rapid increase in critically ill patients that far exceeded their capacity. It is thus of utmost importance to gain knowledge about the characteristics and course of critically ill patients with COVID-19 and to stratify these patients according to their risk for further deterioration. A key part of fighting this pandemic is to exchange scientific information and advance our understanding of the disease. The Risk stratification in COVID-19 patients in the ICU (RISC-19-ICU) registry aims to collect an anonymized dataset to characterize patients that develop life-threatening critical illness due to COVID-19 and make it accessible to collaborative analysis. The data collected may be composed of a core dataset and/or an extended dataset. The core dataset consists of a basic set of parameters, of which many are commonly generated during treatment of critically ill patients with COVID-19 in an intensive care unit (the individual parameters are marked yellow in the attached case report forms, and are clearly marked on the electronic case report forms during data entry). The extended dataset consists of parameters that may be measured during treatment of critically ill patients with COVID-19 in an intensive care unit, depending on clinical practice, indication and availability of the measurement method. The data accumulating in the registry as the pandemic or subsequent waves develop are made available to the collaborators to support an optimal response to the pandemic threat. The information gained on the initial characteristics and disease course via the RISC-19-ICU registry may contribute to a better understanding of the risk factors for developing critical illness due to COVID-19 and for an unfavorable disease course, and thus support informed patient triage and management decisions. Initial research questions are (I) to perform risk stratification of critically ill patients with COVID-19 to find predictors associated with the development of critical illness due to COVID-19: characterization of the study population, which are critically ill patients with COVID-19: inflammation, oxygenation, circulatory function, among other parameters collected in the registry, and (II) to perform risk stratification of critically ill patients with COVID-19 to predict outcome after ICU admission (ICU mortality, ICU length of stay): characterization of patients grouped by disease course in the ICU, based on inflammation, oxygenation, circulatory function, and other parameters collected in the registry.

NCT04357275
Conditions
  1. Critical Illness
  2. ARDS
  3. Inflammatory Response
  4. COVID-19
  5. Circulatory Shock
Interventions
  1. Other: ICU treatment
MeSH:Critical Illness Shock

Primary Outcomes

Measure: ICU mortality

Time: During inclusion period

Secondary Outcomes

Measure: Hospital mortality

Time: During inclusion period

Measure: ICU length of stay

Time: During inclusion period
5 European/Euro-ELSO Survey on Adult and Neonatal/ Pediatric COVID Patients in ECMO

In the last 10 years, severe acute respiratory infection (SARI) was responsible of multiple outbreaks putting a strain on the public health worldwide. Indeed, SARI had a relevant role in the development of pandemic and epidemic with terrible consequences such as the 2009 H1N1 pandemic which led to more than 200.000 respiratory deaths globally. In late December 2019, in Wuhan, Hubei, China, a new respiratory syndrome emerged with clinical signs of viral pneumonia and person-to-person transmission. Tests showed the appearance of a novel coronavirus, namely the 2019 novel coronavirus (COVID-19). Two other strains, the severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) have caused severe respiratory illnesses, sometimes fatal. In particular, the mortality rate associated with SARS-CoV and MERS-CoV, was of 10% and 37% respectively. Even though COVID-19 appeared from the first time in China, quickly it spread worldwide and cases have been described in other countries such as Thailand, Japan, South Korea, Germany, Italy, France, Iran, USA and many other countries. An early paper reported 41 patients with laboratory-confirmed COVID-19 infection in Wuhan. The median age of the patients was 49 years and mostly men (73%). Among those, 32% were admitted to the ICU because of the severe hypoxemia. The most associated comorbidities were diabetes (20%), hypertension (15%), and cardiovascular diseases (15%). On admission, 98% of the patients had bilateral multiple lobular and sub-segmental areas of consolidation. Importantly, acute respiratory distress syndrome (ARDS) developed in 29% of the patients, while acute cardiac injury in 12%, and secondary infection in 10%. Invasive mechanical ventilation was required in 10% of those patients, and two of these patients (5%) had refractory hypoxemia and received extracorporeal membrane oxygenation (ECMO). In a later retrospective report by Wang and collaborators, clinical characteristics of 138 patients with COVID-19 infection were described. ICU admission was required in 26.1% of the patients for acute respiratory distress syndrome (61.1%), arrhythmia (44.4%), and shock (30.6%). ECMO support was needed in 11% of the patients admitted to the ICU. During the period of follow-up, overall mortality was 4.3%. The use of ECMO in COVID-19 infection is increasing due to the high transmission rate of the infection and the respiratory-related mortality. Therefore, the investigators believe that ECMO in case of severe interstitial pneumonia caused by COVID could represent a valid solution in order to avoid lung injuries related to prolonged treatment with non-invasive and invasive mechanical ventilation. In addition, ECMO could have a role for the systemic complications such as septic and cardiogenic shock as well myocarditis scenarios. Potential clinical effects and outcomes of the ECMO support in the novel coronavirus pandemic will be recorded and analyzed in our project. The researchers hypothesize that a significant percentage of patients with COVID-19 infection will require the utilize of ECMO for refactory hypoxemia, cardiogenic shock or septic shock. This study seeks to prove this hypothesis by conducting an observational retrospective/prospective study of patients in the ICU who underwent ECMO support and describe clinical features, severity of pulmonary dysfunction and risk factors of COVID-patients who need ECMO support, the incidence of ECMO use, ECMO technical characteristics, duration of ECMO, complications and outcomes of COVID-patients requiring ECMO support.

NCT04366921
Conditions
  1. COVID
  2. SARS-CoV-2
  3. ARDS, Human
  4. Refractory Hypoxemia
  5. Cardiogenic Shock
  6. Septic Shock
  7. Extracorporeal Membrane Oxygenation
MeSH:Respiratory Distress Syndrome, Adult Shock, Cardiogenic Shock Hypoxia
HPO:Cardiogenic shock Hypoxemia

Primary Outcomes

Description: age in years

Measure: Age

Time: at baseline

Description: male/female

Measure: Gender

Time: at baseline

Description: in kilograms

Measure: Weight

Time: at baseline

Description: in meters

Measure: Height

Time: at baseline

Description: weight and height combined to calculate BMI in kg/m^2

Measure: BMI

Time: at baseline

Description: Asthma y/n, cystic fibrosis y/n, chronic obstructive pulmonary disease y/n, pulmonary hypertension y/n, pulmonary fibrosis y/n, chronic restrictive lung disease y/n

Measure: Pre-existing pulmonary disease y/n

Time: at baseline

Description: diabetes mellitus y/n, chronic renal failure y/n, ischemic heart disease y/n, heart failure y/n, chronic liver failure y/n, neurological impairment y/n

Measure: Main co-morbidities y/n

Time: at baseline

Description: in dd-mm-yyyy or mm-dd-yyyy

Measure: Date of signs of COVID-19 infection

Time: at baseline or date of occurence

Description: in dd-mm-yyyy or mm-dd-yyyy

Measure: Date of positive swab

Time: at baseline or date of occurence

Description: in days

Measure: Pre-ECMO length of hospital stay

Time: at or during ECMO-implant

Description: in days

Measure: Pre-ECMO length of ICU stay

Time: at or during ECMO-implant

Description: in days

Measure: Pre-ECMO length of mechanical ventilation days

Time: at or during ECMO-implant

Description: y/n, what kind

Measure: Use of antibiotics

Time: up to 6 months

Description: y/n, what kind

Measure: Use of anti-viral treatment

Time: up to 6 months

Description: y/n, what kind (eg prone-position, recruitment manoeuvers, neuromuscular blockade etc)

Measure: Use of second line treatment

Time: up to 6 months

Description: respiratory or cardiac

Measure: Indications for ECMO-implant

Time: at ECMO-implant

Description: veno-venous, veno-arterial or veno-venoarterial

Measure: Type of ECMO-implant

Time: at ECMO-implant

Description: peripheral or central

Measure: Type of access

Time: at ECMO-implant

Description: in dd-mm-yyyy or mm-dd-yyyy

Measure: Date of ECMO implant

Time: at ECMO-implant

Description: l/min

Measure: ECMO blood flow rate

Time: from day of ECMO-implant for every 24 hours until date of weaning or death, up to 6 months

Description: l/min

Measure: ECMO gas flow rate

Time: from day of ECMO-implant for every 24 hours until date of weaning or death, up to 6 months

Description: y/n

Measure: ECMO configuration change

Time: up to 6 months

Description: in dd-mm-yyyy or mm-dd-yyyy

Measure: Date of ECMO configuration change

Time: up to 6 months

Description: veno-venous, veno-arterial, veno-venoarterial, other

Measure: New ECMO configuration

Time: up to 6 months

Description: right ventricular failure, left ventricular failure, refractory hypoxemia

Measure: Indications for ECMO configuration change

Time: up to 6 months

Description: settings of ventilator

Measure: Ventilator setting on ECMO

Time: from day of ECMO-implant for every 24 hours until date of weaning or death, up to 6 months

Description: heparin, bivalirudin, nothing

Measure: Anticoagulation during ECMO

Time: from day of ECMO-implant for every 24 hours until date of weaning or death, up to 6 months

Description: amount of ECMO circuit changes (1, 2, 3 etc.)

Measure: Frequency of ECMO circuit change

Time: up to 6 months

Description: Hemorrhagic, infection, other complications

Measure: ECMO complications

Time: up to 6 months

Description: y/n

Measure: ECMO Weaning

Time: from day of ECMO-implant for every 24 hours until date of weaning or death, up to 6 months

Description: y/n, date

Measure: ICU discharge

Time: from day of ICU-admission for every 24 hours until date of discharge or death, up to 6 months

Measure: Main cause of death

Time: 6 months

Description: Ward, another ICU, rehabilitation center, home

Measure: Type of discharge

Time: up to 6 months

Measure: Alive/deceased

Time: 6 months
6 Assessment of Cerebral Compliance and Hemodynamics in Severe COVID-19

Several recent studies point to the possibility of the new coronavirus (SARS-Cov2), which currently causes pandemic COVID-19, to infiltrate the central nervous system (CNS) and cause primary damage to neural tissues, increasing the morbidity and mortality of these patients. A pathophysiological hypothesis for insulting the CNS would be the impairment of cerebral compliance (CC), because elevation of intracranial pressure (ICP), but due to the invasive nature of the methods available for ICP evaluation, this hypothesis has so far not been verified. Recently, a noninvasive technique was developed to evaluate CC (B4C sensor), making it possible to analyse CC in patients outside the neurosurgical environment. Therefore, the main objective of this study was to assess the presence of CC impairment in patients with COVID-19, and observe potential influences of this syndrome on cerebral hemodynamics.

NCT04429477
Conditions
  1. Intracranial Hypertension
  2. Cerebral Circulatory Failure
Interventions
  1. Device: Cerebral compliance and hemodynamics monitoring
MeSH:Intracranial Hypertension Shock
HPO:Increased intracranial pressure

Primary Outcomes

Description: Observe alteration in cerebral compliance due to potential intracranial hypertension during severe COVID-19. This situation is indicated when the relation P2/P1 given by the B4C sensor is >1.

Measure: Detection of cerebral compliance impairment by the B4C sensor

Time: During critical care, around 15 days/patient

Description: Observe disturbances in cerebral circulation during severe COVID-19, given by blood flow velocities in middle cerebral arteries (with normal range 40-70 cm/s) and the pulsatility index (normal <1.2) calculated by transcranial Doppler.

Measure: Detection of cerebral hemodynamics impairment by transcranial Doppler

Time: During critical care, around 15 days/patient

Secondary Outcomes

Description: Observe whether disturbances in cerebral compliance and hemodynamics assessed in this population is significantly associated with higher mortality.

Measure: Calculate mortality in this population

Time: 3 months
7 Uppföljning av Patienter Som intensivvårdats för COVID-19

The study will follow COVID-19 patients who required intensive care after 3-6 months and one year after discharge from the ICU with functional level as well as organ function to assess recovery after COVID-19. Blood and urine will be collected for biobanking.

NCT04474249
Conditions
  1. COVID19
  2. ARDS
  3. AKI
  4. Circulatory Failure
  5. Coagulation Disorder
  6. Inflammatory Response
MeSH:Hemostatic Disorders Blood Coagulation Disorders Shock
HPO:Abnormality of coagulation Abnormality of the coagulation cascade

Primary Outcomes

Description: Death

Measure: Mortality

Time: Within 90 days after admission to ICU.

Description: Death

Measure: Mortality

Time: Within 1 year after admission to ICU.

Description: Return of renal function measured as CKD stage.

Measure: Renal recovery

Time: At follow-up three to six months after ICU discharge.

Description: Return of renal function measured as CKD stage.

Measure: Renal recovery

Time: At follow-up one year after ICU discharge.

Description: Respiratory function as assessed by a clinician

Measure: Respiratory recovery

Time: Three to six months from discharge from ICU

Description: 6 min walk test

Measure: Working capacity

Time: Three to six months from discharge from ICU

Description: Quality of Life assessed using the 36-item short form survey by RAND.

Measure: Quality of life score

Time: Three to six months from discharge from ICU

Description: Cognitive screening using the Montreal Cognitive Assessment.

Measure: Cognitive recovery

Time: Three to six months from discharge from ICU

Description: Screening for frailty using the Clinical Frailty Scale-9.

Measure: Frailty

Time: Three to six months from discharge from ICU

Description: Screening of functional level for Activities of Daily Life using the 5-level EQ-5D.

Measure: Activities of Daily Life

Time: Three to six months from discharge from ICU

Description: Screening for anxiety using the Generalised Anxiety Disorder 7-item scale.

Measure: Anxiety

Time: Three to six months from discharge from ICU

Description: Screening for depression using the Patient Health Questionnaire 9.

Measure: Depression

Time: Three to six months from discharge from ICU

Description: Neurological function as assessed by a clinician

Measure: Neurological recovery

Time: Three to six months from discharge from ICU

HPO Nodes


HPO

Alphabetical listing of all HPO terms. Navigate: Correlations   Clinical Trials


HPO Nodes


Reports

Data processed on December 13, 2020.

An HTML report was created for each of the unique drugs, MeSH, and HPO terms associated with COVID-19 clinical trials. Each report contains a list of either the drug, the MeSH terms, or the HPO terms. All of the terms in a category are displayed on the left-hand side of the report to enable easy navigation, and the reports contain a list of correlated drugs, MeSH, and HPO terms. Further, all reports contain the details of the clinical trials in which the term is referenced. Every clinical trial report shows the mapped HPO and MeSH terms, which are also hyperlinked. Related HPO terms, with their associated genes, protein mutations, and SNPs are also referenced in the report.

Drug Reports   MeSH Reports   HPO Reports  

Interventions

4,818 reports on interventions/drugs

MeSH

706 reports on MeSH terms

HPO

306 reports on HPO terms

All Terms

Alphabetical index of all Terms

Google Colab

Python example via Google Colab Notebook