6-Month Outcomes of PEMF to Nucleotide Sources Revealing Cell Sensory Experience in Pain Relief Stress Relief and Anti Ageing Restoration

Description

Introduction

Electro resonance (PEMF) therapy is relatively new, despite the fact that it is considered a gold standard approach in healthcare application.

The base premise of PEMF is to apply field (inducing force) energies to a host, producing a spectrum of physiological benefits (Bagnato et al., 2015). The advantages of PEMF approaches are the vast modalities available in which an inducing force is applied and is configured (low to high hz intensity, frequency and polarity). The disadvantages are, however, dissonances in paradigm trajectory and PEMF seldom interrogation of the in-situ / in-vivo metrics of change in recipient (Funk et al., 2008; Peterchev et al., 2012).

PEMF data in healthcare enables an exercise of compelled judgement(s) across all critical level (pre-clinical, phase I, phase II, phase III, phase IV) system activity. Today there is an apparent disjoint of insight between systems-derived data (imaging) and treatment applied data (remedial action). Some example settings of this include i) electro resonance / surgery as an evidence based tool in clinical decision making (Phelps et al., 2018 and Strauch et al., 2009); ii) in-vitro electro resonance in skin equivalence model (Mitchell et al., 2015 and Mitchell et al., 2016) and bone stimulus model (Ferroni et al., 2018) modelling in-vivo benefit; iii) phase IV anticoagulation and prothrombin ratio 'observations and stratification' using principle component positions, and observing all contributing variances in play (Sawhney et al., 2018).

The unprecedented contribution of pandemic variance (Huang et al., 2020), is heightening a public awareness of how manifold real world evidence is in resolving the insight disjoints. Biomedical problems occur in forms where remote or aseptic application and self observation is paramount to care; particularly in the cases of infection, healing wounds and hydro-electrolyte restoration(s).

In plentiful coverage, PEMF homeostatic benefits on Immunity compromise, Pain, Stress and Ageing are extensively reviewed with Mun et al., (2018); and although the mechanisms of actions are underpinned; our literature search shows that there are seldom real world initiatives, recording wide-spread physiological improvements that PEMF therapy enacts.

Aim

Here we describe the calibration proforma of PEMF correspondence scoring in longitudinal, physiological and observational outcomes. This study will serve as method development for downstream real world evidence observations of PEMF in the field.

Method

Ethics statement

All participants provided written informed consent in the online basket checkout at hzclinic.co.uk opting to be therapy subjects. The registry is being conducted in accordance with local regulatory requirements, and the International Conference on Harmonisation-Good Pharmacoepidemiological and Clinical Practice Guidelines.

Procedures and outcomes measures

Baseline data collected at screening included participant characteristics (like age), type of clinical-problem (Stress, Pain, Immunity compromise), date and method of diagnosis if any formal, symptoms, and PEMF treatment (delocalised resonance over nucleotide source inducing post transcription modification (PTM) to ubiquitous properties (U.P.)) 2 hz PTM; 3 hz PTM; 4 hz PTM; 5 hz PTM [request appendix for additional I.P. support].

Data on all components of (and) the McGill Life (Sensory, Affectory, Evaluative, Miscellaneous) Index Chart (recordings) were collected to assess the sensitivities of Pain, Stress, Ageing and Immunity compromise states retrospectively.

hz data were collected using a proprietary electronic case report form (eCRF) captured by trained personnel. Oversight of the operations and data management are managed by the coordinating centre hz Clinic, with supporting entities PropDesk (London, UK) and East London Electric Company (ELEC) (London, UK); and resourcing centres MedCity in conjunction with UCL Partners, Imperial College Health Partners and the Health Innovation Network.

The hz protocol requires that 20% of all eCRFs are monitored against source documentation, that there is an electronic audit trail for all data modifications, and that critical variables are subjected to additional audit (Cohen et al., 2015).

Statistical analysis

This article describes the baseline characteristics, treatment patterns and 6 month outcomes based on national data and for participants included in the UK; data for these analyses were extracted from the registry database on 12th February 2020. Continuous variables are expressed as mean standard deviation (SD) and categorical variables as frequency and percentage. Utility of PEMF at baseline was analysed by McGill Life Chart Index scores, calculated retrospectively from the data collected. Participants with missing values were not removed from the study. National normalised ratio (NNR) readings during the 6 months follow up were included in the analysis. We adapted the international normalised ratio (Bonar and Favaloro., 2016) with the acquisition and processing of urine samples for participant metabolome mass fingerprinting and hydration readings as an index, performed (request appendix for additional NNR guidelines). Implausible NNR value of less than 0.8 or greater than 20 were excluded. The distribution of NNR values are described by counts and percentages below, within, and above the therapeutic range, and by the mean, SD, median, and interquartile range (IQR).

Occurrence of major clinical response (primarily, Pain-relief, Stress-relief, anti-oxidation (/ageing) and quenched inflammation) is described using the number of events, the proportion of participants with the event divided by the population at burden at the beginning of the follow-up-period, person-time event rate (per 100 person-years), and 95% confidence interval (CI). We estimated person-year rates using a Poisson model, with the number of events. Only the first occurrences of each event were taken into account. Data analysis was performed at the PropDesk with MatLab (MathsWorks, Massachusetts, USA).

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