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LD TECHNOLOGY
VASCULAR FUNCTION AND AUTONOMIC NERVOUS SYSTEM DATA MANAGEMENT
The New version 7 of the TM-Flow uses the CCS Cloud to build effective teamwork between the performing physician and qualified interpreting physician (e.g., specialists). It is a must in today’s healthcare environment due to increasing patient comorbidities and the complexity of specialization care required
The TM-Flow comprises:
Part 1: Three Devices
The TBL-ABI is:
The TBL-ABI is:
The Sweat C is:
The Sweat C is:
The Oxi_W is:
The Oxi W is:
Part 2: TM-Flow software
Software features
CCS Cloud data management
Why TM-Flow/CCS Cloud Platform?
The 3 medical devices (TBL ABI, OXI W, SweatC) are used by physicians to assess patients who have suffered from complications of chronic diseases.
The devices allow for the early detection of chronic disease complications.
If there is no early diagnostic then there is no timely treatment, and time is of the essence when considering treatment for chronic disease complications.
Peer reviews and clinical studies demonstrate that chronic diseases, as well as their treatments, affect both vascular (endothelial function and Lower extremity artery) and autonomic nervous system (ANS) function (sudomotor and cardiac autonomic function).
How are the data managed with CCS Cloud?
After each device is used and the measurements are recorded, the software then sends the data to the CCS cloud. The online and secure cloud software allows the invited qualified physicians (neurologist, cardiologist, or vascular specialist), and also billing experts, to provide an interpretation and guidance regarding the device test results related to vascular or ANS functions and billing.
What is the Vision of the TM Flow/CCS Cloud Platform
Collaborating as a team to improve patient care.
Effective teamwork between the performing physician and qualified interpreting physician (e.g., specialists) is a must in today’s healthcare environment due to increasing patient comorbidities and the complexity of specialization care required.
The CCS cloud data management platform enables the formation of effective teamwork by helping align primary and specialty care physicians to deliver better patient care.
CCS ASSESMENTS
BLOOD PRESSURE AND ARTERIAL STIFFNESS ANALYSIS
Monitoring and treatment.
Management of hypertension
PHOTOPLETHYSMOGRAPHY
Mathematical Analysis of the pulse Ox wave
ANKLE BRAKIAL INDEX (ABI)
Peripheral Artery Disease (PAD). Blood flow blockage or calcification
HEART RATE VARIABILITY (HRV)
Cardiac Autonomic Dysfunction Assessment
CARDIAC AUTOMATIC REFLEX TESTs (CARTs)
Cardiac Autonomic Neuropathy assessment
SUDOMOTOR FUNCTION TESTS
Skin Microcirculation and small fiber Assessments
MAIN SYMPTOMS OF AUTONOMIC NEUROPATHY AND VASCULAR DYSFUNCTION
Population over 50 years old
with cardiovascular risk factors
(Hypertensive, Overweight, Smoker, Diabetic)
Population over 70 years old.
USA POPULATION THAT SHOULD BE TESTED BY LD TECHNOLOGY PRODUCTS
USA POPULATION THAT SHOULD BE TESTED BY LD TECHNOLOGY PRODUCTS
50+
Population over 50 years old
with cardiovascular risk factors
(Hypertensive, Overweight, Smoker, Diabetic)
70+
Population over 70 years old.
VASCULAR FUNCTION ASSESSMENT
AUTONOMIC NERVOUS SYSTEM ASSESSMENT
See results in page Clinical Studies
Oxi_W clinical studies:
The ROC curves showed that the most relevant cutoff to the whole study group was a PTG-TP > 406.2. This cut-off had a sensitivity = 95.7%, specificity = 84,4% and the area under the ROC curve (AUC) = 0.929 for identifying insulin resistance. All AUC ROC curve analysis were significant (p < 0.0001).
the PTG CVD score had a sensitivity of 82.5% and specificity of 96.8%, at a cutoff of 2, when used to detect CAD (P=0.0001; area under the receiver operating characteristic curve =0.967). The PTG spectral analysis markers were well-correlated to other autonomic nervous system and endothelial function markers. CAD diabetic patients (n=27) had a lower PTGi value compared with the CAD non-diabetic patients (n=38): and patients that underwent CABG (n=18) had a higher PTGi value compared with the CAD without CABG surgery patients (n=47).
Comparisons between the healthy subjects and type 2 diabetes mellitus patients
The PTGi had a sensitivity of 92% and specificity of 80% (cut-off score > 35.5) with the area under the curve = 0.92 (SE = 0.04; 95% CI = 0.84, 1.0) and an asymptotic significance < 0.001. The PTGVLFi had a sensitivity of 92% and specificity of 87% (cut-off score > 25.5) with the area under the curve = 0.91 (SE = 0.05; 95% CI = 0.81, 1.0) and an asymptotic significance < 0.001.
Stress Index marker correlated with CRP (ρ = −0.38, p < 0.0001 and PTG VLFi correlated with fibrinogen (ρ = 0.43, p < 0.0001).
was also significantly different between groups, with vitamin D insufficient individuals having lower TP values compared to vitamin D sufficient participants (P = 0.045)
Sweat C Clinical study:
inversely correlated with the severity of symptoms on the peripheral neuropathy scale (ρ = −0.56, p < 0.0001).
had a sensitivity of 88% and a specificity of 68% (Area Under the Curve = 0.81, p < 0.0001) to detect retinopathy. The NO Sweat Peak response marker inversely correlated with BUN (ρ = −0.41, p < 0.0001), homocysteine (ρ = −0.44, p < 0.0001), fibrinogen (ρ = −0.41, p < 0.0001), the Cardiac Autonomic Neuropathy score (ρ = −0.68, p < 0.0001), and the heart rate variability Total Power (ρ = −0.57, p < 0.0001)
TBL-ABI Clinical study
The overall ABI gave the same specificity and sensitivity values of 77.8%, with a cutoff ≤ 0.9 (P = 0.024 and AUC = 0.747) for detecting vascular color Doppler ultrasound biphasic and monophasic waveforms versus triphasic waveforms.
The overall TBI gave a specificity of 55.6% and sensitivity of 100%, with a cutoff ≤ 0.55. (P = 0.001 and AUC = 0.824) for detecting vascular color Doppler ultrasound biphasic and monophasic waveforms versus triphasic waveforms.
The overall PTG index marker gave a specificity of 83.3% and a sensitivity of 100%, with a cutoff ≤ 26 (P = 0.001 and AUC = 0.917) for detecting vascular color Doppler ultrasound biphasic and monophasic waveforms versus triphasic waveforms
The overall sum the ABI and TBI (SBI) values gave a specificity of 88.9% and a sensitivity of 100% with a cutoff ≤ 1.36 (P = 0.001 and AUC = 0.960) for detecting vascular color Doppler ultrasound biphasic and monophasic waveforms versus triphasic waveforms