Effects of Global Warming on Patients with Dementia, Motor Neuron or Parkinson's Diseases: A Comparison among Cortical and Subcortical Disorders

Exposure to global warming can be dangerous for health and can lead to an increase in the prevalence of neurological diseases worldwide. Such an effect is more evident in populations that are less prepared to cope with enhanced environmental temperatures. In this work, we extend our previous research on the link between climate change and Parkinson's disease (PD) to also include Alzheimer's Disease and other Dementias (AD/D) and Amyotrophic Lateral Sclerosis/Motor Neuron Diseases (ALS/MND). One hundred and eighty-four world countries were clustered into four groups according to their climate indices (warming and annual average temperature). Variations between 1990 and 2016 in the diseases' indices (prevalence, deaths, and disability-adjusted life years) and climate indices for the four clusters were analyzed. Unlike our previous work on PD, we did not find any significant correlation between warming and epidemiological indices for AD/D and ALS/MND patients. A significantly lower increment in prevalence in countries with higher temperatures was found for ALS/MND patients. It can be argued that the discordant findings between AD/D or ALS/MND and PD might be related to the different features of the neuronal types involved and the pathophysiology of thermoregulation. The neurons of AD/D and ALS/MND patients are less vulnerable to heat-related degeneration effects than PD patients. PD patients' substantia nigra pars compacta (SNpc), which are constitutively frailer due to their morphology and function, fall down under an overwhelming oxidative stress caused by climate warming.

Climate change and neurodegenerative diseases

The climate change induced global warming, and in particular the increased frequency and intensity of heat waves, have been linked to health problems. Among them, scientific works have been reporting an increased incidence of neurological diseases, encompassing also neurodegenerative ones, such as Dementia of Alzheimer's type, Parkinson's Disease, and Motor Neuron Diseases. Although the increase in prevalence of neurodegenerative diseases is well documented by literature reports, the link between global warming and the enhanced prevalence of such diseases remains elusive. This is the main theme of our work, which aims to examine the connection between high temperature exposure and neurodegenerative diseases. Firstly, we evaluate the influence of high temperatures exposure on the pathophysiology of these disorders. Secondly, we discuss its effects on the thermoregulation, already compromised in affected patients, and its interference with processes of excitotoxicity, oxidative stress and neuroinflammation, all of them related with neurodegeneration. Finally, we investigate chronic versus acute stressors on body warming, and put forward a possible interpretation of the beneficial or detrimental effects on the brain, which is responsible for the incidence or progression of neurological disorders.

Two-parameter leak estimation in non-invasive ventilation

In this paper we present a method for the estimation of leaks in non-invasive ventilation. Accurate estimation of leaks is a key component of a ventilator, since it determines the ventilator performance in terms of patient-ventilator synchrony and air volume delivery. In particular, in non-invasive ventilation, the patient flow is significantly different from the flow measured at the ventilator outlet. This is mostly due to the vent orifice along the tube that is used for exhalation, but also to the non-intentional leaks that occur elsewhere in the circuit (e.g., at the mask). Such leaks are traditionally quantified via a model with two parameters, but only one of them is continually updated - the other is fixed. The new algorithm allows for breath-by-breath update of both parameters. This was made possible by leveraging a model describing the patient respiratory mechanics.

End-inspiratory occlusion in the presence of intrinsic PEEP

Typical modern mechanical ventilators offer the clinician the possibility of automatically performing end-inspiratory occlusion maneuvers. The static conditions induced by such maneuvers are indeed favorable to estimating patient's respiratory mechanics in terms of total resistance (R) and elastance (E). These are parameters of wide clinical interest. However, in the presence of intrinsic PEEP, the standard formula used to compute E via the occlusion maneuver is known to be inaccurate. In this paper we propose an alternative method for the estimation of E via the occlusion maneuver that eliminates the bias by leveraging concepts derived from physiological modeling of the respiratory system dynamics. The proposed method is also capable of accounting for respiratory efforts triggering the breath, and hence can be applied in both passive and spontaneously breathing conditions.

Noninvasive estimation of alveolar pressure

This paper presents an algorithm for noninvasive estimation of alveolar pressure in mechanically ventilated patients who are spontaneously breathing. Continual monitoring of alveolar pressure is desirable to prevent ventilator-induced lung injury and to assess the intrinsic positive end-expiratory pressure (PEEPi), which is a parameter of clinical relevance in respiratory care and difficult to measure noninvasively. The algorithm is based on a physiological model of the respiratory system and, as such, it also provides insight into the respiratory mechanics of the patient under mechanical ventilation. In particular, the algorithm allows one to correctly estimate other clinical parameters of interest such as the patient's respiratory resistance and elastance, even in the presence of PEEPi.