Towards a better diagnosis of mouth breathing: validity and reliability of a protocol for assessing the awake breathing pattern in preschool children.

PURPOSE: The Awake Breathing Pattern Assessment (ABPA) is a prototypical clinical grid recently designed through an international consensus of Speech and Language Pathologists (SLPs) to categorize the awake and habitual breathing pattern during the orofacial myofunctional assessment. This cross-sectional study aims to explore the psychometric properties of the ABPA in a preschool population. METHODS: 133 children from 2;11 to 6 years old were assessed with the ABPA. The percentage of time spent breathing through the mouth was objectively measured by a CO2 sensor and used as a baseline measurement. We first performed a multivariate Latent Profile Analysis based on the CO2 measurement and a parental questionnaire to define the number of categories that best characterize the breathing pattern. Subsequently, we assessed the intra- and inter-rater reliability, internal consistency criterion validity, construct validity and sensitivity and specificity. RESULTS: The awake breathing pattern can best be described by two groups: nasal and mouth breathing. The ABPA, initially designed in three groups, was adjusted accordingly. This final version showed excellent intra-rater and inter-rater reliability. There was a significant correlation between the ABPA and the CO2 measurement. The ABPA showed a fair sensitivity and a good specificity. CONCLUSION: The reference tool based on CO2 data was used in children for the first time and was found to be reliable. The ABPA is a suitable tool for SLPs to confirm the diagnosis of mouth breathing in preschool children if more sensitive screening tools, like parental questionnaires, are used beforehand.

Spatio-temporal electroencephalographic power distribution in experimental pigs receiving propofol.

INTRODUCTION: When assessing the spatio-temporal distribution of electroencephalographic (EEG) activity, characteristic patterns have been identified for several anesthetic drugs in humans. A shift in EEG power from the occipital to the prefrontal regions has been widely observed during anesthesia induction. This has been called "anteriorization" and has been correlated with loss of consciousness in humans. The spatio-temporal distribution of EEG spectral power in pigs and its modulation by anesthetics have not been described previously. The aim of the present study was to analyze EEG power across an anterior-posterior axis in pigs receiving increasing doses of propofol to 1) characterize the region of highest EEG power during wakefulness, 2) depict its spatio-temporal modification during propofol infusion, and 3) determine the region demonstrating the most significant modulations across different doses administered. MATERIALS AND METHODS: Six pigs with a body weight of 33.3 ± 3.6 kg and aged 11.3 ± 0.5 weeks were included in a prospective experimental study. Electroencephalographic activity was collected at the occipital, parietal and prefrontal regions at increasing doses of propofol (starting at 10 mg kg-1 h-1 and increasing it by 10 mg kg-1 h-1 every 15 minutes). The EEG power was assessed using a generalized linear mixed model in which propofol doses and regions were treated as fixed effects, whereas pig was used as a random effect. Pairwise comparisons of marginal linear predictions were used to assess the change in power when the specific propofol dose (or region) was considered. RESULTS: During both wakefulness and propofol infusion, the highest EEG power was located in the prefrontal region (p<0.001). The EEG power, both total and for each frequency band, mostly followed the same pattern, increasing from awake until propofol 20 mg kg-1 h-1 and then decreasing at propofol 30 mg kg-1 h-1. The region showing the strongest differences in EEG power across propofol doses was the prefrontal. CONCLUSION: In juvenile pigs receiving increasing doses of propofol, the prefrontal region showed the highest EEG power both during wakefulness and propofol administration and was the area in which the largest frequency-band specific variations were observed across different anesthetic doses. The assessment of the spectral EEG activity at this region could be favorable to distinguish DoA levels in pigs.

An update on tests used for intraoperative monitoring of cognition during awake craniotomy.

PURPOSE: Mapping higher-order cognitive functions during awake brain surgery is important for cognitive preservation which is related to postoperative quality of life. A systematic review from 2018 about neuropsychological tests used during awake craniotomy made clear that until 2017 language was most often monitored and that the other cognitive domains were underexposed (Ruis, J Clin Exp Neuropsychol 40(10):1081-1104, 218). The field of awake craniotomy and cognitive monitoring is however developing rapidly. The aim of the current review is therefore, to investigate whether there is a change in the field towards incorporation of new tests and more complete mapping of (higher-order) cognitive functions. METHODS: We replicated the systematic search of the study from 2018 in PubMed and Embase from February 2017 to November 2023, yielding 5130 potentially relevant articles. We used the artificial machine learning tool ASReview for screening and included 272 papers that gave a detailed description of the neuropsychological tests used during awake craniotomy. RESULTS: Comparable to the previous study of 2018, the majority of studies (90.4%) reported tests for assessing language functions (Ruis, J Clin Exp Neuropsychol 40(10):1081-1104, 218). Nevertheless, an increasing number of studies now also describe tests for monitoring visuospatial functions, social cognition, and executive functions. CONCLUSIONS: Language remains the most extensively tested cognitive domain. However, a broader range of tests are now implemented during awake craniotomy and there are (new developed) tests which received more attention. The rapid development in the field is reflected in the included studies in this review. Nevertheless, for some cognitive domains (e.g., executive functions and memory), there is still a need for developing tests that can be used during awake surgery.

Nocturnal exposure to a preferred ambient scent does not affect dream emotionality or post-sleep core affect valence in young adults.

Emotions experienced within sleep mentation (dreaming) affect mental functioning in waking life. There have been attempts at enhancing dream emotions using olfactory stimulation. Odors readily acquire affective value, but to profoundly influence emotional processing, they should bear personal significance for the perceiver rather than be generally pleasant. The main objective of the present sleep laboratory study was to examine whether prolonged nocturnal exposure to self-selected, preferred ambient room odor while asleep influences emotional aspects of sleep mentation and valence of post-sleep core affect. We asked twenty healthy participants (12 males, mean age 25 ± 4 years) to pick a commercially available scented room diffuser cartridge that most readily evoked positively valenced mental associations. In weekly intervals, the participants attended three sessions. After the adaptation visit, they were administered the odor exposure and odorless control condition in a balanced order. Participants were awakened five minutes into the first rapid eye movement (REM) stage that took place after 2:30 a.m. and, if they had been dreaming, they were asked to rate their mental sleep experience for pleasantness, emotional charge, and magnitude of positive and negative emotions and also to evaluate their post-sleep core affect valence. With rs < 0.20, no practically or statistically significant differences existed between exposure and control in any outcome measures. We conclude that in young, healthy participants, the practical value of olfactory stimulation with self-selected preferred scents for enhancement of dream emotions and post-sleep core affect valence is very limited.

A multi-task learning model using RR intervals and respiratory effort to assess sleep disordered breathing.

BACKGROUND: Sleep-disordered breathing (SDB) affects a significant portion of the population. As such, there is a need for accessible and affordable assessment methods for diagnosis but also case-finding and long-term follow-up. Research has focused on exploiting cardiac and respiratory signals to extract proxy measures for sleep combined with SDB event detection. We introduce a novel multi-task model combining cardiac activity and respiratory effort to perform sleep-wake classification and SDB event detection in order to automatically estimate the apnea-hypopnea index (AHI) as severity indicator. METHODS: The proposed multi-task model utilized both convolutional and recurrent neural networks and was formed by a shared part for common feature extraction, a task-specific part for sleep-wake classification, and a task-specific part for SDB event detection. The model was trained with RR intervals derived from electrocardiogram and respiratory effort signals. To assess performance, overnight polysomnography (PSG) recordings from 198 patients with varying degree of SDB were included, with manually annotated sleep stages and SDB events. RESULTS: We achieved a Cohen's kappa of 0.70 in the sleep-wake classification task, corresponding to a Spearman's correlation coefficient (R) of 0.830 between the estimated total sleep time (TST) and the TST obtained from PSG-based sleep scoring. Combining the sleep-wake classification and SDB detection results of the multi-task model, we obtained an R of 0.891 between the estimated and the reference AHI. For severity classification of SBD groups based on AHI, a Cohen's kappa of 0.58 was achieved. The multi-task model performed better than a single-task model proposed in a previous study for AHI estimation, in particular for patients with a lower sleep efficiency (R of 0.861 with the multi-task model and R of 0.746 with single-task model with subjects having sleep efficiency < 60%). CONCLUSION: Assisted with automatic sleep-wake classification, our multi-task model demonstrated proficiency in estimating AHI and assessing SDB severity based on AHI in a fully automatic manner using RR intervals and respiratory effort. This shows the potential for improving SDB screening with unobtrusive sensors also for subjects with low sleep efficiency without adding additional sensors for sleep-wake detection.

Multimodal MRI reveals brainstem connections that sustain wakefulness in human consciousness.

Consciousness is composed of arousal (i.e., wakefulness) and awareness. Substantial progress has been made in mapping the cortical networks that underlie awareness in the human brain, but knowledge about the subcortical networks that sustain arousal in humans is incomplete. Here, we aimed to map the connectivity of a proposed subcortical arousal network that sustains wakefulness in the human brain, analogous to the cortical default mode network (DMN) that has been shown to contribute to awareness. We integrated data from ex vivo diffusion magnetic resonance imaging (MRI) of three human brains, obtained at autopsy from neurologically normal individuals, with immunohistochemical staining of subcortical brain sections. We identified nodes of the proposed default ascending arousal network (dAAN) in the brainstem, hypothalamus, thalamus, and basal forebrain. Deterministic and probabilistic tractography analyses of the ex vivo diffusion MRI data revealed projection, association, and commissural pathways linking dAAN nodes with one another and with DMN nodes. Complementary analyses of in vivo 7-tesla resting-state functional MRI data from the Human Connectome Project identified the dopaminergic ventral tegmental area in the midbrain as a widely connected hub node at the nexus of the subcortical arousal and cortical awareness networks. Our network-based autopsy methods and connectivity data provide a putative neuroanatomic architecture for the integration of arousal and awareness in human consciousness.

Automatic sleep-wake classification and Parkinson's disease recognition using multifeature fusion with support vector machine.

AIMS: Sleep disturbance is a prevalent nonmotor symptom of Parkinson's disease (PD), however, assessing sleep conditions is always time-consuming and labor-intensive. In this study, we performed an automatic sleep-wake state classification and early diagnosis of PD by analyzing the electrocorticography (ECoG) and electromyogram (EMG) signals of both normal and PD rats. METHODS: The study utilized ECoG power, EMG amplitude, and corticomuscular coherence values extracted from normal and PD rats to construct sleep-wake scoring models based on the support vector machine algorithm. Subsequently, we incorporated feature values that could act as diagnostic markers for PD and then retrained the models, which could encompass the identification of vigilance states and the diagnosis of PD. RESULTS: Features extracted from occipital ECoG signals were more suitable for constructing sleep-wake scoring models than those from frontal ECoG (average Cohen's kappa: 0.73 vs. 0.71). Additionally, after retraining, the new models demonstrated increased sensitivity to PD and accurately determined the sleep-wake states of rats (average Cohen's kappa: 0.79). CONCLUSION: This study accomplished the precise detection of substantia nigra lesions and the monitoring of sleep-wake states. The integration of circadian rhythm monitoring and disease state assessment has the potential to improve the efficacy of therapeutic strategies considerably.

Association of Visual-Based Signals with Electroencephalography Patterns in Enhancing the Drowsiness Detection in Drivers with Obstructive Sleep Apnea.

Individuals with obstructive sleep apnea (OSA) face increased accident risks due to excessive daytime sleepiness. PERCLOS, a recognized drowsiness detection method, encounters challenges from image quality, eyewear interference, and lighting variations, impacting its performance, and requiring validation through physiological signals. We propose visual-based scoring using adaptive thresholding for eye aspect ratio with OpenCV for face detection and Dlib for eye detection from video recordings. This technique identified 453 drowsiness (PERCLOS ≥ 0.3 || CLOSDUR ≥ 2 s) and 474 wakefulness episodes (PERCLOS < 0.3 and CLOSDUR < 2 s) among fifty OSA drivers in a 50 min driving simulation while wearing six-channel EEG electrodes. Applying discrete wavelet transform, we derived ten EEG features, correlated them with visual-based episodes using various criteria, and assessed the sensitivity of brain regions and individual EEG channels. Among these features, theta-alpha-ratio exhibited robust mapping (94.7%) with visual-based scoring, followed by delta-alpha-ratio (87.2%) and delta-theta-ratio (86.7%). Frontal area (86.4%) and channel F4 (75.4%) aligned most episodes with theta-alpha-ratio, while frontal, and occipital regions, particularly channels F4 and O2, displayed superior alignment across multiple features. Adding frontal or occipital channels could correlate all episodes with EEG patterns, reducing hardware needs. Our work could potentially enhance real-time drowsiness detection reliability and assess fitness to drive in OSA drivers.

Glia are powerhouses for sleep.

Glia take up and detoxify neurotoxic lipids on a wake-sleep cycle, in turn promoting healthy sleep.

Improved data quality and statistical power of trial-level event-related potentials with Bayesian random-shift Gaussian processes.

Studies of cognitive processes via electroencephalogram (EEG) recordings often analyze group-level event-related potentials (ERPs) averaged over multiple subjects and trials. This averaging procedure can obscure scientifically relevant variability across subjects and trials, but has been necessary due to the difficulties posed by inference of trial-level ERPs. We introduce the Bayesian Random Phase-Amplitude Gaussian Process (RPAGP) model, for inference of trial-level amplitude, latency, and ERP waveforms. We apply RPAGP to data from a study of ERP responses to emotionally arousing images. The model estimates of trial-specific signals are shown to greatly improve statistical power in detecting significant differences in experimental conditions compared to existing methods. Our results suggest that replacing the observed data with the de-noised RPAGP predictions can potentially improve the sensitivity and accuracy of many of the existing ERP analysis pipelines.

Evaluation of calibrated and uncalibrated optical imaging approaches for relative cerebral oxygen metabolism measurements in awake mice.

Objective. The continuous delivery of oxygen is critical to sustain brain function, and therefore, measuring brain oxygen consumption can provide vital physiological insight. In this work, we examine the impact of calibration and cerebral blood flow (CBF) measurements on the computation of the relative changes in the cerebral metabolic rate of oxygen consumption (rCMRO2) from hemoglobin-sensitive intrinsic optical imaging data. Using these data, we calculate rCMRO2, and calibrate the model using an isometabolic stimulus.Approach. We used awake head-fixed rodents to obtain hemoglobin-sensitive optical imaging data to test different calibrated and uncalibrated rCMRO2models. Hypercapnia was used for calibration and whisker stimulation was used to test the impact of calibration.Main results. We found that typical uncalibrated models can provide reasonable estimates of rCMRO2with differences as small as 7%-9% compared to their calibrated models. However, calibrated models showed lower variability and less dependence on baseline hemoglobin concentrations. Lastly, we found that supplying the model with measurements of CBF significantly reduced error and variability in rCMRO2change calculations.Significance. The effect of calibration on rCMRO2calculations remains understudied, and we systematically evaluated different rCMRO2calculation scenarios that consider including different measurement combinations. This study provides a quantitative comparison of these scenarios to evaluate trade-offs that can be vital to the design of blood oxygenation sensitive imaging experiments for rCMRO2calculation.

Distinct lateral hypothalamic CaMKIIα neuronal populations regulate wakefulness and locomotor activity.

For nearly a century, evidence has accumulated indicating that the lateral hypothalamus (LH) contains neurons essential to sustain wakefulness. While lesion or inactivation of LH neurons produces a profound increase in sleep, stimulation of inhibitory LH neurons promotes wakefulness. To date, the primary wake-promoting cells that have been identified in the LH are the hypocretin/orexin (Hcrt) neurons, yet these neurons have little impact on total sleep or wake duration across the 24-h period. Recently, we and others have identified other LH populations that increase wakefulness. In the present study, we conducted microendoscopic calcium imaging in the LH concomitant with EEG and locomotor activity (LMA) recordings and found that a subset of LH neurons that express Ca2+/calmodulin-dependent protein kinase IIα (CaMKIIα) are preferentially active during wakefulness. Chemogenetic activation of these neurons induced sustained wakefulness and greatly increased LMA even in the absence of Hcrt signaling. Few LH CaMKIIα-expressing neurons are hypocretinergic or histaminergic while a small but significant proportion are GABAergic. Ablation of LH inhibitory neurons followed by activation of the remaining LH CaMKIIα neurons induced similar levels of wakefulness but blunted the LMA increase. Ablated animals showed no significant changes in sleep architecture but both spontaneous LMA and high theta (8 to 10 Hz) power during wakefulness were reduced. Together, these findings indicate the existence of two subpopulations of LH CaMKIIα neurons: an inhibitory population that promotes locomotion without affecting sleep architecture and an excitatory population that promotes prolonged wakefulness even in the absence of Hcrt signaling.

Asleep versus awake GPi DBS surgery for Parkinson's disease: A systematic review and meta-analysis.

BACKGROUND: Patients with Parkinson's Disease (PD) who receive either asleep image-guided subthalamic nucleus deep brain stimulation (DBS) or the traditional awake technique have comparable motor outcomes. However, there are fewer studies regarding which technique should be chosen for globus pallidus internus (GPi) DBS. This systematic review and meta-analysis aims to compare the accuracy of lead placement and motor outcomes of asleep versus awake GPi DBS PD population. METHODS: We systematically searched PubMed, Embase, and Cochrane for studies comparing asleep vs. awake GPi DBS lead placement in patients with PD. Outcomes were spatial accuracy of lead placement, measured by radial error between intended and actual location, motor improvement measured using (UPDRS III), and postoperative stimulation parameters. Statistical analysis was performed with Review Manager 5.1.7. and OpenMeta [Analyst]. RESULTS: Three studies met inclusion criteria with a total of 247 patients. Asleep DBS was used to treat 192 (77.7 %) patients. Follow-up ranged from 6 to 48 months. Radial error was not statistically different between groups (MD -0.49 mm; 95 % CI -1.0 to 0.02; I2 = 86 %; p = 0.06), with a tendency for higher target accuracy with the asleep technique. There was no significant difference between groups in change on motor function, as measured by UPDRS III, from pre- to postoperative (MD 8.30 %; 95 % CI -4.78 to 21.37; I2 = 67 %, p = 0.2). There was a significant difference in postoperative stimulation voltage, with the asleep group requiring less voltage than the awake group (MD -0.27 V; 95 % CI -0.46 to - 0.08; I2 = 0 %; p = 0.006). CONCLUSION: Our meta-analysis indicates that asleep image-guided GPi DBS presents a statistical tendency suggesting superior target accuracy when compared with the awake standard technique. Differences in change in motor function were not statistically significant between groups.

Electrophysiological Properties of the Medial Mammillary Bodies across the Sleep-Wake Cycle.

The medial mammillary bodies (MBs) play an important role in the formation of spatial memories; their dense inputs from hippocampal and brainstem regions makes them well placed to integrate movement-related and spatial information, which is then extended to the anterior thalamic nuclei and beyond to the cortex. While the anatomical connectivity of the medial MBs has been well studied, much less is known about their physiological properties, particularly in freely moving animals. We therefore carried out a comprehensive characterization of medial MB electrophysiology across arousal states by concurrently recording from the medial MB and the CA1 field of the hippocampus in male rats. In agreement with previous studies, we found medial MB neurons to have firing rates modulated by running speed and angular head velocity, as well as theta-entrained firing. We extended the characterization of MB neuron electrophysiology in three key ways: (1) we identified a subset of neurons (25%) that exhibit dominant bursting activity; (2) we showed that ∼30% of theta-entrained neurons exhibit robust theta cycle skipping, a firing characteristic that implicates them in a network for prospective coding of position; and (3) a considerable proportion of medial MB units showed sharp-wave ripple (SWR) responsive firing (∼37%). The functional heterogeneity of MB electrophysiology reinforces their role as an integrative node for mnemonic processing and identifies potential roles for the MBs in memory consolidation through propagation of SWR-responsive activity to the anterior thalamus and prospective coding in the form of theta cycle skipping.

Comparative evaluation of nebulized versus intravenous dexmedetomidine on intubating conditions during awake fiberoptic nasotracheal intubation.

BACKGROUND: There is a search for an ideal agent to facilitate awake fiberoptic intubation (AFOI). Dexmedetomidine is a selective α2 agonist which can be administered through intravenous, intramuscular, buccal, intranasal & inhalational routes. It provides good intubation conditions without oxygen desaturation but may cause hypotension and bradycardia when administered intravenously. Hence, alternative routes of administering dexmedetomidine which may improve its safety profile are worth exploring. METHODS: In this randomised, controlled, double-blind trial, 46 ASA I/II adult participants scheduled for elective ENT surgery were randomly allocated to Group ND (Nebulised Dexmedetomidine) (n = 23) to receive nebulisation with dexmedetomidine 1µg.kg-1 and Group ID (Intravenous Dexmedetomidine) (n = 23) to receive intravenous dexmedetomidine 1µg.kg-1 before AFOI. All the patients received injection midazolam 1 mg i.v. as premedication before anaesthesia was initiated. The primary outcome was the cough score. The secondary outcomes were the RSS, SAYGO boluses, post-intubation score, hemodynamic parameters, recall of the procedure, patient satisfaction score and any side effects. RESULTS: The cough score was significantly lower in nebulized group (2.43 ± 0.992 vs 3.52 ± 1.082) with p = 0.001. RSS(3.30 ± 0.926 vs 4.22 ± 1.126; p = 0.004), number of SAYGO boluses required (2.74 ± 0.864 vs 3.57 ± 1.161; p = 0.009) & the post intubation score (1.48 ± 0.593 vs 2.17 ± 0.778; p = 0.001) were also significantly lower in nebulized group. CONCLUSIONS: Nebulisation with dexmedetomidine results in desirable degree of sedation and better tolerance of the procedure with adequate attenuation of the haemodynamic responses to intubation.

Modulate the impact of the drowsiness on the resting state functional connectivity.

This research explores different methodologies to modulate the effects of drowsiness on functional connectivity (FC) during resting-state functional magnetic resonance imaging (RS-fMRI). The study utilized a cohort of students (MRi-Share) and classified individuals into drowsy, alert, and mixed/undetermined states based on observed respiratory oscillations. We analyzed the FC group difference between drowsy and alert individuals after five different processing methods: the reference method, two based on physiological and a global signal regression of the BOLD time series signal, and two based on Gaussian standardizations of the FC distribution. According to the reference method, drowsy individuals exhibit higher cortico-cortical FC than alert individuals. First, we demonstrated that each method reduced the differences between drowsy and alert states. The second result is that the global signal regression was quantitively the most effective, minimizing significant FC differences to only 3.3% of the total FCs. However, one should consider the risks of overcorrection often associated with this methodology. Therefore, choosing a less aggressive form of regression, such as the physiological method or Gaussian-based approaches, might be a more cautious approach. Third and last, using the Gaussian-based methods, cortico-subcortical and intra-default mode network (DMN) FCs were significantly greater in alert than drowsy subjects. These findings bear resemblance to the anticipated patterns during the onset of sleep, where the cortex isolates itself to assist in transitioning into deeper slow wave sleep phases, simultaneously disconnecting the DMN.

Impact of specific electromagnetic radiation on wakefulness in mice.

Electromagnetic radiation (EMR) in the environment, particularly in the microwave range, may constitute a public health concern. Exposure to 2.4 GHz EMR modulated by 100 Hz square pulses was recently reported to markedly increase wakefulness in mice. Here, we demonstrate that a similar wakefulness increase can be induced by the modulation frequency of 1,000 Hz, but not 10 Hz. In contrast to the carrier frequency of 2.4 GHz, 935 MHz EMR of the same power density has little impact on wakefulness irrespective of modulation frequency. Notably, the replacement of the 100 Hz square-pulsed modulation by sinusoidal-pulsed modulation of 2.4 GHz EMR still allows a marked increase of wakefulness. In contrast, continuous sinusoidal amplitude modulation of 100 Hz with the same time-averaged power output fails to trigger any detectable change of wakefulness. Therefore, alteration of sleep behavior by EMR depends upon not just carrier frequency but also frequency and mode of the modulation. These results implicate biological sensing mechanisms for specific EMR in animals.

Awake Prone Positioning In COVID Positive Patients: A Retrospective Study.

BACKGROUND: While the advanced health care settings are struggling hard to handle the sudden surge of COVID-19 cases, resource poor settings in developing countries like Nepal can barely stand to fight the increasing number of severe cases. Easily available cost effective interventions would be great blessing for such settings. This study aimed to study if awake prone positioning can be used as such intervention in COVID 19. METHODS: The retrospective study involved 150 patients admitted between November 2020 and January 2021 at Nepal Armed Police Force Hospital and met specific inclusion criteria. Data was obtained at four different time points in relation to prone position and was analysed using International Business Machines Statistical Package for the Social Sciences (SPSS) version 23. RESULTS: It was found that among 150 patients, majority (109; 72.7%) were males and 60(40%) had some comorbidities. The mean oxygen saturation was found to increase significantly from 87.18 %(SD 3.531) to 91.08(SD 2.206) after fifteen minutes of prone positioning. One way ANOVA test showed that there was significant difference in oxygen saturation between at least two time points. (F (3,596) = [180.005], p=0.000). Games Howell Post Hoc test for multiple comparisons showed that the mean value of SPO-2 was significantly different across all four time points, at significance level 0.05. CONCLUSIONS: This study found Awake Prone positioning as a promising cost effective and feasible intervention for improving oxygenation in COVID 19 and thus could be a blessing to the resource poor health care settings.