The GooD Pregnancy Network: An Alternative Approach for Gestational Diabetes

Basildon and Thurrock University Hospital in the East of England region of the United Kingdom (UK) witnessed rapidly increasing numbers of pregnant women with diabetes, causing overburdened specialist clinics, poorer patient experience and worsening clinical outcomes. This prompted the multidisciplinary team’s remodelling of care pathways, launching the General ownership of Diabetes (GooD) Pregnancy Network in 2014. Contrary to the conventional limitation of care to specialist diabetes antenatal clinics, this novel initiative highlights the contemporary necessity to equip and empower all maternity stakeholders to deliver the basic care of gestational diabetes (GDM). It strategically connects a Midwife Tele-Clinic “hub” to Educating Gestational Diabetics Group Sessions (EGGS) and standard antenatal clinics. Patients were key partners, regularly participating in feedback surveys and promoting public awareness by co-producing local newspaper articles that served up their stories as case studies. Furthermore, the EGGS “faculty” includes a former GDM patient whose video testimony has inspired almost 2000 patients and their families, aiming to foster long term healthy lifestyle changes. The final summative evaluation in November 2019 showed the new culture of wider consciousness has shortened the “diagnosis to first consultation” intervals and eliminated overbooked specialist clinics (none since January 2016), without further worsening of clinical outcomes. It also boosted research recruitment and avoided additional running costs to the tune of GBP 66,384 a year.

Perspectives on Light-Based Disinfection to Reduce the Risk of COVID-19 Transmission during Dental Care

Severe Acute Respiratory Syndrome 2 (SARS-CoV-2) is a positive-sense single-stranded RNA coronavirus capable of causing potentially lethal pneumonia-like infectious diseases in mammals and birds. The main mechanisms by which SARS-CoV-2 spreads include airborne transmission (aerosols and droplets) and the direct exposure of tissues (conjunctival, nasal, and oral mucosa) to contaminated fluids. The aerosol formation is universal in dentistry due to the use of rotary instruments (handpieces), ultrasonic scalers, and air–water syringes. Several layers of infection control should protect key stakeholders such as dentists, dental staff, and patients. These include the utilization of personal protective equipment, high-volume evacuation systems, pre-procedural mouthwashes, rubber dam, and more recently, antimicrobial photodynamic therapy and intra-oral visible light irradiation. These non-specific light-based approaches are relatively simple, inexpensive, and effective against viruses, bacteria, and fungi. Therefore, the present perspective review discusses the current efforts and limitations on utilizing biophotonic approaches as adjunct infection control methods to prevent the transmission of SARS-CoV-2 in dental settings. In addition, the present perspective review may positively impact subsequent developments in the field, as it offers relevant information regarding the intricacies and complexities of infection control in dental settings.

Improving and Externally Validating Mortality Prediction Models for COVID-19 Using Publicly Available Data

We conducted a systematic survey of COVID-19 endpoint prediction literature to: (a) identify publications that include data that adhere to FAIR (findability, accessibility, interoperability, and reusability) principles and (b) develop and reuse mortality prediction models that best generalize to these datasets. The largest such cohort data we knew of was used for model development. The associated published prediction model was subjected to recursive feature elimination to find a minimal logistic regression model which had statistically and clinically indistinguishable predictive performance. This model could still not be applied to the four external validation sets that were identified, due to complete absence of needed model features in some external sets. Thus, a generalizable model (GM) was built which could be applied to all four external validation sets. An age-only model was used as a benchmark, as it is the simplest, effective, and robust predictor of mortality currently known in COVID-19 literature. While the GM surpassed the age-only model in three external cohorts, for the fourth external cohort, there was no statistically significant difference. This study underscores: (1) the paucity of FAIR data being shared by researchers despite the glut of COVID-19 prediction models and (2) the difficulty of creating any model that consistently outperforms an age-only model due to the cohort diversity of available datasets.

Association of Oxidative Stress Markers with Vascular Stiffness Parameters in Patients with Diabetic Neuropathy

Introduction: One of the most common chronic complications of diabetes mellitus is diabetic neuropathy. The aim of the study was to elucidate the association between selected markers of oxidative stress and markers of vascular stiffness and to contribute to the understanding of the pathophysiological links between oxidative stress and micro- and macrovascular complications of diabetes. Methods: We enrolled patients with type 2 DM (n = 49), with moderate to severe diabetic polyneuropathy of lower extremities, and a control group without microvascular complications (n = 29). The neuropathy group received alpha-lipoic acid infusion therapy. Sampling was performed before and after treatment to determine the level of oxidative markers (advanced glycation end-products—AGEs, glycation products of AOPP proteins, MDA malondialdehyde and oxidized LDL), parameters of metabolic control and parameters of vascular wall stiffness were measured by sphygmomanometry. Results: After the administration of alpha-lipoic acid, we demonstrated a significant reduction in the level of three selected oxidation markers (AOPP: p < 0.001, AGE: p < 0.001, oxLDL: p < 0.05). In contrast, the level of MDA did not change significantly (p = 0.83). Throughout the group, oxLDL was significantly correlated with central BP (SBP and DBP in the aorta, p < 0.05 and <0.01) and with the augmentation index (AiX/75 bpm, p < 0.01). AOPP significantly correlated with systolic BP in the aorta (p < 0.05). We did not find significant associations in the remaining oxidation markers. Conclusion: In our study, we demonstrated a reduction in the level of oxidative markers after alpha-lipoic acid administration and also an association between markers of oxidative damage to lipids and proteins (oxLDL and AOPP) and some parameters of vascular stiffness.

Mast Cell Tryptase and Implications for SARS-CoV-2 Pathogenesis

Mast cells (MCs) are heterogenous innate leukocytes producing many inflammatory mediators during viral infections that can be protective or damaging to the host, as is seen in the infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen responsible for the coronavirus disease that was first identified in 2019 (COVID-19). MCs can sense viruses by diverse mechanisms. They express angiotensin-converting enzyme 2 (ACE2), known as the principal entry receptor for SARS-CoV-2, and tryptase that can promote SARS-CoV-2 infection. Tryptase is one of the most abundant serine proteases released by MCs during degranulation and is reported to have both beneficial and detrimental roles in respiratory diseases. Reviewed here are the potential roles of MC-derived tryptase during COVID-19, the implications it has in the pathogenesis of SARS-CoV-2, and the possibility of treating COVID-19 by targeting tryptase.

High Flow in the Storm. Early Administration of High-Flow Nasal Cannula in Patients with Severe Acute Hypoxic Respiratory Failure Due to Clinically Suspected COVID-19

Background: The worldwide COVID-19 pandemic has created a shortage of ICU beds and ventilators. The objective was to assess whether administration of high-flow nasal cannula (HFNC) in patients with acute hypoxic respiratory failure due to COVID-19 averted mechanical ventilation (MV). Methods: Prospective observational study performed at Hospital Universitario HM Puerta del Sur (Madrid). The protocol included early administration of HFNC in clinically suspected COVID-19 patients with progressive desaturation. Results: Twenty patients were started on respiratory support with HFNC. Hospital admission took place after a median of 7 days since symptom onset and clinical deterioration was apparent at 9 days after symptom onset. Anti-inflammatory treatment with methylprednisolone and tocilizumab was initiated at 9 days (6.5–12), followed by HFNC at 9.5 days (7–12). HFNC was maintained for an average of 4.5 days (2.8–6.3), was successful in eighteen patients (90%), as defined by not needing invasive MV, and failed in two cases (10%) resulting in death. Since HFNC was implemented, there has been a decrease in the number of patients admitted to the ICU and treated with MV for acute hypoxic respiratory failure. Conclusions: HFNC administration may represent a viable therapeutic option for patients in the early stages of severe respiratory failure due to clinically suspected COVID-19.

COVID-19 Prognosis and Mortality Risk Predictions from Symptoms: A Cloud-Based Smartphone Application

The coronavirus pandemic overwhelmed many countries and their healthcare systems. Shortage of testing kits and Intensive-Care-Unit (ICU) beds for critical patients have become a norm in most developing countries. This has prompted the need to rapidly identify the COVID-19 patients to stop the spread of the virus and also to find critical patients. The latter is imperative for determining the state of critically ill patients as quickly as possible. This will lower the number of deaths from the infection. In this paper, we propose a cloud-based smartphone application for the early prognosis of COVID-19 infected patients and also predict their mortality risk using their symptoms. Moreover, we heuristically identified the most important symptoms necessary for making such predictions. We have successfully reduced the number of features by almost half for the prognosis and by more than a third for forecasting the mortality risk, compared to the contemporary studies. The application makes the real-time analysis using machine learning models, designed and stored in the cloud. Our machine learning model demonstrates an accuracy, precision, recall, and F1 score of 97.72%, 100%, 95.55%, and 97.70%, respectively, in identifying the COVID-19 infected patients and with an accuracy, precision, recall, and F1 score of 90.83%, 88.47%, 92.94%, and 90.65%, respectively, in forecasting the mortality risk from the infection. The real-time cloud-based approach yields faster responses, which is critical in the time of pandemic for mitigating the infection spread and aiding in the efficient management of the limited ICU resources.

The Rationale for the Automation of a New Diagnostic Thermography Protocol to Confirm a Chronic-Low-Back-Pain Subtype Related to Nociplastic Pain

Gluteal syndrome (GS), a new low-back-pain subtype mimicking sciatica, has been included in the 11th Revision of the International Classification of Diseases (ICD-11). Low back pain is a symptom, not a disease, and the main problem associated with it is pain complexity. A plausible pain generator of gluteal syndrome is the central sensitization process and the therapeutic target area, which are trigger points located within the gluteal muscles. It has been hypothesized that dysregulated immune and autonomic nervous systems (ANS) are involved in central sensitization development. Changes in ANS regulation, mainly through the sympathetic branch, provoke nociceptor activation indirectly by a vasoconstriction–vasodilatation imbalance, or directly by sympathetic–nociceptor activation resulting in widespread pain, hyperalgesia, and allodynia. The minimally invasive procedure (MIP) uses thermography to confirm a completely new biological phenomenon, which suggests a pathological autonomic response to noxious stimuli and can possibly become an objective marker of some nociplastic pain subtypes related to trigger points. This review provides the biological and technical rationale for the automation of the MIP—a possible future diagnostic tool for an objective gluteal syndrome confirmation.

Plasma Renin Concentration in Critically Ill COVID-19 Patients

Investigations of plasma renin concentration as a marker of organ perfusion in several intensive care settings have shown a significant correlation between its increase and a lack of perfusion in critical tissues, especially in septic patients. Castillo et al. proposed that activation of the non-canonical pathway of the renin–angiotensin–aldosterone system could improve cardiovascular homeostasis under COVID-19. During the first wave of COVID-19, we preliminarily enrolled a small cohort of subjects admitted to the Intensive Care Unit with a diagnosis of COVID-19 and acute respiratory distress syndrome. Their plasma renin value was measured in the first 24 h (T0), in the following 72 h (T1), and after one week (T2). In eight patients, we observed a higher plasma renin concentration—patients with difficulty weaning and in non-survivors. This is a preliminary observation. The variation of plasma renin levels in a septic condition is known, but settings such as COVID-19 infection have recently been investigated, showing a correlation with angiotensin-converting enzyme 2 receptor expression and functionality; in the near future, it will be interesting to have more data about its variation and value in COVID-19 patients.

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