International society of oncology pharmacy practitioners (ISOPP) position statement: The role of oncology pharmacy practitioners in immunotherapy treatment with immune checkpoint inhibitors for malignant conditions.

Oncology pharmacists, pharmacy technicians and assistants are key members of the multidisciplinary health care team (MHT) caring for patients receiving immunotherapy with immune checkpoint inhibitors. The International Society of Oncology Pharmacy Practitioners (ISOPP) developed this position statement to provide guidance on the role of oncology pharmacy practitioners in caring for patients receiving immune checkpoint inhibitors.Four key recommendations were identified: 1) participation as an integrated, collaborative member of the MHT;2) provision of education and training for patients, students, residents, fellows and other members of the MHT;3) involvement in clinical governance to optimise the use of immune checkpoint inhibitors and4) involvement in research and development in the field of immunotherapy.In summary, oncology pharmacy practitioners play essential roles within the MHT in caring for patients receiving immune checkpoint inhibitors.

Psychosocial and personality trait associates of phubbing and being phubbed in hispanic emerging adult college students.

Phubbing is when one uses their smartphone in a social interaction instead of interacting with the other individual(s) in their presence. Phubbing and being phubbed are growing concerns as the number of smartphones and frequency of smartphone use increases. This study assessed the relationships between phubbing, being phubbed, psychosocial constructs, and socially adverse personality traits among Hispanic emerging adult college students. Hispanic college students (n = 452) completed a survey assessing: sociodemographics, phubbing, being phubbed, depression, anxiety, stress, Machiavellianism, narcissism, psychopathy, and need for drama (interpersonal manipulation, impulsive outspokenness, persistent perceived victimhood). Hispanic emerging adult college students reported low-to-moderate levels of phubbing and being phubbed. Regarding phubbing findings, nomophobia (fear of separation from one's phone), interpersonal conflict, and problem acknowledgement were positively associated with negative affect. Moreover, interpersonal conflict, self-isolation, and problem acknowledgement were positively associated with interpersonal manipulation. Regarding being phubbed findings, perceived norms, feeling ignored, and interpersonal conflict were positively associated with persistent perceived victimhood. Findings indicate that Hispanic college students may use their smartphones in social settings to alleviate negative affect. Moreover, a virtual environment on a smartphone may be easier to manipulate and can be used to continue garnering attention and portraying oneself as the victim, fulfilling one's need for drama. Regarding exploratory mediations, phubbing and being phubbed mediated the relationships between multiple socially adverse personality traits and negative affect. The clinical implications of these results are discussed. Prospective studies are warranted to determine temporality. Supplementary information: The online version contains supplementary material available at 10.1007/s12144-023-04767-y.

Mechanical complications of weekly care and maintenance versus once every 10 days of the peripherally inserted central catheter line insertion site in newborns: A propensity score-matched cohort study in Mexico.

PURPOSE: To evaluate the mechanical complications of weekly care and maintenance versus once every 10 days of the peripherally inserted central catheter (PICC) line insertion site versus once every 10 days in newborns. DESIGN AND METHODS: Prospective propensity score matched cohort study. Care and maintenance of the PICC line insertion site were performed on days 7 and 10 during January 2018 to December 2019. To compare mechanical complications, propensity score matching was performed. Propensity scores were used to determine the relative risks and hazard ratios by using logistic regressions with log-link function and Cox regressions, respectively. RESULTS: We included 175 newborns hospitalized in the neonatal intensive care unit (NICU) who underwent insertion of a PICC line. Ninety-six received weekly care and maintenance, and 79 received care and maintenance every 10 days. Weekly care and maintenance were associated with more breakage (RR 1.98, 95% CI 1.68-2.34); occlusions (RR 0.81, 95% CI 0.46-1.42) and accidental withdrawals (RR 1.31, 95% CI 0.93-1.84) were not different between care and maintenance every 7 and 10 days. A survival analysis was performed, showing that weekly care and maintenance are a risk factor for removal for mechanical complications (HR 7.61, 95% CI 3.05-19.01). CONCLUSION: We concluded that care and maintenance of the PICC in newborns every 10 days have fewer complications than when performing care and maintenance every 7 days. PRACTICE IMPLICATIONS: Newborns requiring intravenous therapy will benefit from care and maintenance every 10 days, and this practice could potentially spread to other NICUs.

Protective and risk factors for increased alcohol use in Latinx college students on the U.S./Mexico border.

Alcohol use is prevalent among undergraduates, however, limited research on drinking among Latinx college students exists. This study examined potential risk and protective factors of alcohol use and consequences. Participants (n = 382) completed multiple measures including alcohol use frequency and the Rutgers Alcohol Problem Index (RAPI). Linear regression models identified predictors of monthly and yearly drinking days and RAPI. Findings indicated that alcohol use frequency was associated with increasing age, parental alcohol use disorder, greater anger, and lower self-efficacy. Alcohol-related consequences were positively associated with anxiety and adverse childhood experiences. Early alcohol prevention and intervention efforts appear warranted.

Assessment of Nocturnal Autonomic Cardiac Imbalance in Positional Obstructive Sleep Apnea. A Multiscale Nonlinear Approach.

Positional obstructive sleep apnea (POSA) is a major phenotype of sleep apnea. Supine-predominant positional patients are frequently characterized by milder symptoms and less comorbidity due to a lower age, body mass index, and overall apnea-hypopnea index. However, the bradycardia-tachycardia pattern during apneic events is known to be more severe in the supine position, which could affect the cardiac regulation of positional patients. This study aims at characterizing nocturnal heart rate modulation in the presence of POSA in order to assess potential differences between positional and non-positional patients. Patients showing clinical symptoms of suffering from a sleep-related breathing disorder performed unsupervised portable polysomnography (PSG) and simultaneous nocturnal pulse oximetry (NPO) at home. Positional patients were identified according to the Amsterdam POSA classification (APOC) criteria. Pulse rate variability (PRV) recordings from the NPO readings were used to assess overnight cardiac modulation. Conventional cardiac indexes in the time and frequency domains were computed. Additionally, multiscale entropy (MSE) was used to investigate the nonlinear dynamics of the PRV recordings in POSA and non-POSA patients. A total of 129 patients (median age 56.0, interquartile range (IQR) 44.8-63.0 years, median body mass index (BMI) 27.7, IQR 26.0-31.3 kg/m2) were classified as POSA (37 APOC I, 77 APOC II, and 15 APOC III), while 104 subjects (median age 57.5, IQR 49.0-67.0 years, median BMI 29.8, IQR 26.6-34.7 kg/m2) comprised the non-POSA group. Overnight PRV recordings from positional patients showed significantly higher disorderliness than non-positional subjects in the smallest biological scales of the MSE profile (τ = 1: 0.25, IQR 0.20-0.31 vs. 0.22, IQR 0.18-0.27, p < 0.01) (τ = 2: 0.41, IQR 0.34-0.48 vs. 0.37, IQR 0.29-0.42, p < 0.01). According to our findings, nocturnal heart rate regulation is severely affected in POSA patients, suggesting increased cardiac imbalance due to predominant positional apneas.

Assessment of oximetry-based statistical classifiers as simplified screening tools in the management of childhood obstructive sleep apnea.

PURPOSE: A variety of statistical models based on overnight oximetry has been proposed to simplify the detection of children with suspected obstructive sleep apnea syndrome (OSAS). Despite the usefulness reported, additional thorough comparative analyses are required. This study was aimed at assessing common binary classification models from oximetry for the detection of childhood OSAS. METHODS: Overnight oximetry recordings from 176 children referred for clinical suspicion of OSAS were acquired during in-lab polysomnography. Several training and test datasets were randomly composed by means of bootstrapping for model optimization and independent validation. For every child, blood oxygen saturation (SpO2) was parameterized by means of 17 features. Fast correlation-based filter (FCBF) was applied to search for the optimum features. The discriminatory power of three statistical pattern recognition algorithms was assessed: linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and logistic regression (LR). The performance of each automated model was evaluated for the three common diagnostic polysomnographic cutoffs in pediatric OSAS: 1, 3, and 5 events/h. RESULTS: Best screening performances emerged using the 1 event/h cutoff for mild-to-severe childhood OSAS. LR achieved 84.3% accuracy (95% CI 76.8-91.5%) and 0.89 AUC (95% CI 0.83-0.94), while QDA reached 96.5% PPV (95% CI 90.3-100%) and 0.91 AUC (95% CI 0.85-0.96%). Moreover, LR and QDA reached diagnostic accuracies of 82.7% (95% CI 75.0-89.6%) and 82.1% (95% CI 73.8-89.5%) for a cutoff of 5 events/h, respectively. CONCLUSIONS: Automated analysis of overnight oximetry may be used to develop reliable as well as accurate screening tools for childhood OSAS.

Evaluating the patient-perceived impact of clinical pharmacy services and proactive follow-up care in an ambulatory chemotherapy unit.

Purpose To evaluate the patient-perceived impact of delivery of clinical pharmacy services, including a proactive follow-up program, on patient understanding, satisfaction, and toxicity management. Methods Patients who had received clinical pharmacy services at their initial chemotherapy treatment were identified and asked to complete a 20-point survey at the second or subsequent treatment. The services that the survey evaluated consist of face-to-face education during the first treatment and proactive telephone follow-up 3 to 7 days later. Results A total of 107 of the 112 respondents (95.5%) indicated that the time with the pharmacist at the first treatment was worthwhile and 92.6% of respondents reported that the interaction with the pharmacist increased their understanding of the medication regimen. Of the 113 respondents, the majority was either "Very Satisfied" or "Satisfied" with the time the pharmacist spent with them (94.7%), and the pharmacist's ability to answer their questions (92.9%). In addition, survey results indicate that the clinical pharmacy input provided in the pharmacist call-back program is valuable, with 92.6% of the 82 respondents indicating that this service is worthwhile, and 91.4% of 93 respondents stating that the pharmacist input helped them to manage side-effects at home. Conclusions Survey results indicate that patients value clinical pharmacy services in the ambulatory oncology chemotherapy setting. These services contribute to improve patient understanding of the medication regimen, a high level of patient satisfaction, and self-management of treatment-related toxicities. These results support the provision of clinical pharmacy services and proactive follow-up programs in ambulatory chemotherapy units.

Influence of suicidality on adult perceptions of COVID-19 risk and guideline adherence.

BACKGROUND: Suicide rates have been increasing for decades, and the challenges of a global pandemic seem to have worsened suicide risk factors. The relationship between suicidality, COVID-19 risk perceptions, and guideline adherence was examined to inform potential barriers to the implementation of behavioral interventions aimed at preventing future pandemics. METHODS: A national sample of 159 MTurk participants (Mage = 37.64 years, SD = 11.92; 48.4% female) completed an online survey containing the following: demographics, Suicidal Ideation Attributes Scale, Broadly Applicable Measure of Risk Perception of COVID-19, and Adherence to COVID-19 Guidelines and Perceived Risk Scale. RESULTS: Multiple linear regressions assessed how suicidality related to perceived risk subscales and each adherence indicator while controlling for biological sex, age, and essential worker status. Over 25% of participants reported suicidality over the past month, and 19% were at high risk of suicidal behavior. Greater suicidality was associated with lower general COVID-19 risk perceptions (ß = -0.326, p < .001), decreased handwashing (ß = -0.423, p < .001), lower likelihood of planning to self-quarantine if infected with COVID-19 (ß = -0.400, p < .001), less social distancing (ß = -0.457, p < .001), and increased attendance of large gatherings (ß = 0.405, p < .001). LIMITATIONS: Temporal relationships were unable to be assessed due to the cross-sectional nature of the data used. The low internal reliability of the risk probability subscale precluded its inclusion in analyses. CONCLUSION: Given suicidality's associations with decreased risk perceptions and low adherence, it may present as a barrier to the sustained behavior change that will be necessary in preventing the occurrence of future pandemics.

Comparison of Use of Neoadjuvant Systemic Treatment for Breast Cancer and Short-term Outcomes Before vs During the COVID-19 Era in Ontario, Canada.

Importance: In response to an increase in COVID-19 infection rates in Ontario, several systemic treatment (ST) regimens delivered in the adjuvant setting for breast cancer were temporarily permitted for neoadjuvant-intent to defer nonurgent breast cancer surgical procedures. Objective: To examine the use and compare short-term outcomes of neoadjuvant-intent vs adjuvant ST in the COVID-19 era compared with the pre-COVID-19 era. Design, Setting, and Participants: This was a retrospective population-based cohort study in Ontario, Canada. Patients with cancer starting selected ST regimens in the COVID-19 era (March 11, 2020, to September 30, 2020) were compared to those in the pre-COVID-19 era (March 11, 2019, to March 10, 2020). Patients were diagnosed with breast cancer within 6 months of starting systemic therapy. Main Outcomes and Measures: Estimates were calculated for the use of neoadjuvant vs adjuvant ST, the likelihood of receiving a surgical procedure, the rate of emergency department visits, hospital admissions, COVID-19 infections, and all-cause mortality between treatment groups over time. Results: Among a total of 10 920 patients included, 7990 (73.2%) started treatment in the pre-COVID-19 era and 7344 (67.3%) received adjuvant ST; the mean (SD) age was 61.6 (13.1) years. Neoadjuvant-intent ST was more common in the COVID-19 era (1404 of 2930 patients [47.9%]) than the pre-COVID-19 era (2172 of 7990 patients [27.2%]), with an odds ratio of 2.46 (95% CI, 2.26-2.69; P < .001). This trend was consistent across a range of ST regimens, but differed according to patient age and geography. The likelihood of receiving surgery following neoadjuvant-intent chemotherapy was similar in the COVID-19 era compared with the pre-COVID-19 era (log-rank P = .06). However, patients with breast cancer receiving neoadjuvant-intent hormonal therapy were significantly more likely to receive surgery in the COVID-19 era (log-rank P < .001). After adjustment, there were no significant changes in the rate of emergency department visits over time between patients receiving neoadjuvant ST, adjuvant ST, or ST only during the ST treatment period or postoperative period. Hospital admissions decreased in the COVID-19 era for patients who received neoadjuvant ST compared with adjuvant ST or ST alone (P for interaction = .01 for both) in either setting. Conclusions and Relevance: In this cohort study, patients were more likely to start neoadjuvant ST in the COVID-19 era, which varied across the province and by indication. There was limited evidence to suggest any substantial impact on short-term outcomes.

The emergence of insulin resistance following a chronic high-fat diet regimen coincides with an increase in the reinforcing effects of nicotine in a sex-dependent manner.

The present study assessed the sex-dependent effects of insulin resistance on the reinforcing effects of nicotine. Female and male rats received a chronic high-fat diet (HFD) or regular diet (RD) for 8 weeks. A subset of rats then received vehicle or a dose of streptozotocin (STZ; 25 mg/kg) that induces insulin resistance. To assess insulin resistance, glucose levels were measured 15, 30, 60, 120, and 180 min after an insulin injection (0.75 U/kg). Nine days later, the rats were given extended access to intravenous self-administration (IVSA) of nicotine (0.015, 0.03, 0.06 mg/kg) in an operant box where they consumed their respective diet ad libitum and performed responses for water deliveries. Each nicotine dose was delivered for 4 days with 3 intermittent days of abstinence in their home cage. The day after the last IVSA session, physical signs were compared following administration of mecamylamine (3.0 mg/kg) to precipitate nicotine withdrawal. The results revealed that there were no changes in insulin resistance or nicotine intake in HFD alone rats regardless of sex. Insulin resistance was observed in HFD-fed rats that received STZ, and the magnitude of this effect was greater in males versus females. Our major finding was that nicotine intake was greater among HFD + STZ female rats as compared to males. Lastly, the physical signs of withdrawal were similar across all groups. Our results suggest that females diagnosed with disorders that disrupt insulin signaling, such as diabetes may be at risk of greater vulnerability to nicotine use due to enhanced reinforcing effects of this drug.

Updates in using a molecular classifier to identify usual interstitial pneumonia in conventional transbronchial lung biopsy samples.

A molecular classifier using a machine-learning algorithm based on genomic data could provide an objective method to aid clinicians and multidisciplinary teams to establish the diagnosis of IPF in less-invasive transbronchial lung biopsy samples https://bit.ly/2QLdWim.

In the spotlight: Early Career Member Awardee 2020, ERS Lung Science Conference 2021, and Sleep and Breathing 2021.

Interview with @EarlyCareerERS Awardee 2020 @burtin_chris, and a preview of #LungScienceConference and #SleepandBreathing 2021 https://bit.ly/3fUXs1M.

ERS International Congress, Madrid, 2019: highlights from the Sleep and Clinical Physiology Assembly.

The 2019 European Respiratory Society (ERS) International Congress took place in Madrid, Spain, and served as a platform to find out the latest advances in respiratory diseases research. The research aims are to understand the physiology and consequences of those diseases, as well as the improvement in their diagnoses, treatments and patient care. In particular, the scientific sessions arranged by ERS Assembly 4 provided novel insights into sleep-disordered breathing and new knowledge in respiratory physiology. This article, divided by session, will summarise the most relevant studies presented at the ERS International Congress. Each section has been written by Early Career Members specialising in the different fields of this interdisciplinary assembly.

Automatic Assessment of Pediatric Sleep Apnea Severity Using Overnight Oximetry and Convolutional Neural Networks.

In this study, we use the overnight blood oxygen saturation (SpO2) signal along with convolutional neural networks (CNN) for the automatic estimation of pediatric sleep apnea-hypopnea syndrome (SAHS) severity. The few preceding studies have focused on the application of conventional feature extraction methods to obtain information from the SpO2 signal, which may omit relevant data related to the illness. In contrast, deep learning techniques are able to automatically learn features from raw input signal. Thus, we propose to assess whether CNN, a deep learning algorithm, could automatically estimate the apnea-hypopnea index (AHÍ) from nocturnal oximetry to help establish pediatric SAHS presence and severity. A database of 746 SpO2 recordings is involved in the study. CNN was trained using 20-min segments from the SpO2 signal in the training set (400 subjects). Hyperparameters of the CNN architecture were tuned using a validation set (100 subjects). This model was applied to a test set (246 subjects), in which the final AHI of each patient was obtained as the average of the output of the CNN for all the segments of the corresponding SpO2 signal. The AHI estimated by the CNN showed a promising diagnostic performance, with 74.8%, 90.7%, and 95.1% accuracies for the common AHI severity thresholds of 1, 5, and 10 events per hour (e/h), respectively. Furthermore, this model reached 28.6, 32.9, and 120.0 positive likelihood ratios for the above-mentioned AHI thresholds. This suggests that the information extracted from the oximetry signal by deep learning techniques may be useful to both establish pediatric SAHS and its severity.

A machine learning-based test for adult sleep apnoea screening at home using oximetry and airflow.

The most appropriate physiological signals to develop simplified as well as accurate screening tests for obstructive sleep apnoea (OSA) remain unknown. This study aimed at assessing whether joint analysis of at-home oximetry and airflow recordings by means of machine-learning algorithms leads to a significant diagnostic performance increase compared to single-channel approaches. Consecutive patients showing moderate-to-high clinical suspicion of OSA were involved. The apnoea-hypopnoea index (AHI) from unsupervised polysomnography was the gold standard. Oximetry and airflow from at-home polysomnography were parameterised by means of 38 time, frequency, and non-linear variables. Complementarity between both signals was exhaustively inspected via automated feature selection. Regression support vector machines were used to estimate the AHI from single-channel and dual-channel approaches. A total of 239 patients successfully completed at-home polysomnography. The optimum joint model reached 0.93 (95%CI 0.90-0.95) intra-class correlation coefficient between estimated and actual AHI. Overall performance of the dual-channel approach (kappa: 0.71; 4-class accuracy: 81.3%) significantly outperformed individual oximetry (kappa: 0.61; 4-class accuracy: 75.0%) and airflow (kappa: 0.42; 4-class accuracy: 61.5%). According to our findings, oximetry alone was able to reach notably high accuracy, particularly to confirm severe cases of the disease. Nevertheless, oximetry and airflow showed high complementarity leading to a remarkable performance increase compared to single-channel approaches. Consequently, their joint analysis via machine learning enables accurate abbreviated screening of OSA at home.

Evaluation of Machine-Learning Approaches to Estimate Sleep Apnea Severity From At-Home Oximetry Recordings.

Complexity, costs, and waiting list issues demand a simplified alternative for sleep apnea-hypopnea syndrome (SAHS) diagnosis. The blood oxygen saturation signal (SpO2) carries useful information about SAHS and can be easily acquired from overnight oximetry. In this study, SpO2 single-channel recordings from 320 subjects were obtained at patients' homes and were used to automatically obtain statistical, spectral, nonlinear, and clinical SAHS-related information. Relevant, nonredundant data from these analyses were subsequently used to train and validate four machine-learning methods with the ability to classify SpO2 signals into one of the four SAHS-severity degrees (no-SAHS, mild, moderate, and severe). All the models trained (linear discriminant analysis, 1-vs-all logistic regression, Bayesian multilayer perceptron, and AdaBoost) outperformed the diagnostic ability of the conventionally used 3% oxygen desaturation index. An AdaBoost model built with linear discriminants as base classifiers reached the highest figures. It achieved 0.479 Cohen's κ in the SAHS severity classification, as well as 92.9%, 87.4%, and 78.7% accuracies in binary classification tasks using increasing severity thresholds (apnea-hypopnea index: 5, 15, and 30 events/hour, respectively). These results suggest that machine-learning can be used along with SpO2 information acquired at a patients' home to help in SAHS diagnosis simplification.

Early glycemic control and incretin improvement after gastric bypass: the role of oral and gastrostomy route.

BACKGROUND: Patients with obesity have a suppressed incretin effect and a consequent imbalance of glycemic homeostasis. Several studies have shown improved type 2 diabetes after Roux-en-Y gastric bypass (RYGB). The mechanisms of early action are linked to caloric restriction, improvement of insulin resistance, pancreatic beta cell function, and the incretin effect of glycogen-like protein 1 and gastric inhibitory polypeptide, but reported data are conflicting. OBJECTIVE: The objective of this study was to evaluate glycemic metabolism, including the oral glucose tolerance test and enterohormonal profile in the early postoperative period in severely obese patients who underwent RYGB with gastrostomy, comparing the preoperative supply of a standard bolus of nutrient against the postoperative administration through an oral and a gastrostomy route. SETTING: Clinics Hospital of University of São Paulo, Brazil. METHODS: Eleven patients with obesity and diabetes underwent RYGB with a gastrostomy performed in the excluded gastric remnant. Patients were given preoperative assessments of glycemic and enterohormone profiles and an oral glucose tolerance test; these were compared with early postoperative assessments after oral and gastrostomy route administrations. RESULTS: The mean preoperative body mass index of the group was 44.1 ± 6.6 kg/m2, mean fasting blood glucose of 194.5 ± 62.4 mg/dL, and glycated hemoglobin 8.7 ± 1.6%. In 77.7% of the patients, there was normalization of the glycemic curve in the early postoperative period as evaluated by the oral glucose tolerance test. Significant decreases in glycemia, insulinemia, and homeostatic model assessment-insulin resistance were also observed, regardless of the route of administration. There was significant increase in glycogen-like protein 1 by the postoperative oral route and reduction of gastric inhibitory polypeptide in both routes. Ghrelin did not change. CONCLUSION: Glycemia and peripheral insulin resistance reductions were observed in early-postoperative RYGB, independent of the oral or gastrostomy route. Incretin improvement, mediated by glycogen-like protein 1 increased was observed only in the postoperative oral route, while GIP reduced for both routes.

Improving the Safety and Quality of Systemic Treatment Regimens in Computerized Prescriber Order Entry Systems.

PURPOSE: Systemic treatment (ST) computerized prescriber order entry (CPOE) and preprinted orders (PPO) are proven to reduce errors. There is no known guidance in oncology to facilitate high-quality, accurate regimen development and review; hence, this was identified as a system-wide gap. This provincial initiative aimed to improve the quality of oncology regimens through a comprehensive review of systemic treatment (ST) regimens and the development of standards. METHODS: A system-wide analysis of all active regimens (both CPOE and PPO) to ensure they were built as intended was conducted in 2015. Thirty-five hospitals (on behalf of 75 treatment facilities) were asked to report any unintentional discrepancies and details of the maintenance review process. Discrepancies were compiled, categorized, and analyzed for potential to cause harm. In addition, a multidisciplinary expert working group was formed to create best practice recommendations. RESULTS: The review yielded a 94% response rate and took a total of 18 months to complete (70% completed within 9 months). The average number of regimens reviewed was 336 (range, 15 to 700; n = 9). Unintentional discrepancies were reported by nine hospitals (27%). A total of 369 discrepancies were reported (average, 55 per hospital), and 28 were deemed to have a moderate potential for harm. Only two hospitals (6%) had an established maintenance process; now, all have standard processes for review. Consensus-based recommendations for ST-CPOE and PPO regimen development and maintenance were developed. CONCLUSION: The review identified unintentional discrepancies and, because of the potential for patient harm, corrective action has been taken. Identified discrepancies have been amended, and standard regimen development and maintenance review processes are now implemented system-wide to improve the quality and safety of systemic treatment delivery.

Oximetry use in obstructive sleep apnea.

INTRODUCTION: Overnight oximetry has been proposed as an accessible, simple, and reliable technique for obstructive sleep apnea syndrome (OSAS) diagnosis. From visual inspection to advanced signal processing, several studies have demonstrated the usefulness of oximetry as a screening tool. However, there is still controversy regarding the general application of oximetry as a single screening methodology for OSAS. Areas covered: Currently, high-resolution portable devices combined with pattern recognition-based applications are able to achieve high performance in the detection of this disease. In this review, recent studies involving automated analysis of oximetry by means of advanced signal processing and machine learning algorithms are analyzed. Advantages and limitations are highlighted and novel research lines aimed at improving the screening ability of oximetry are proposed. Expert commentary: Oximetry is a cost-effective tool for OSAS screening in patients showing high pretest probability for the disease. Nevertheless, exhaustive analyses are still needed to further assess unattended oximetry monitoring as a single diagnostic test for sleep apnea, particularly in the pediatric population and in populations with significant comorbidities. In the following years, communication technologies and big data analyses will overcome current limitations of simplified sleep testing approaches, changing the detection and management of OSAS.

Symbolic dynamics to enhance diagnostic ability of portable oximetry from the phone oximeter in the detection of paediatric sleep apnoea.

OBJECTIVE: This study is aimed at assessing symbolic dynamics as a reliable technique to characterise complex fluctuations of portable oximetry in the context of automated detection of childhood obstructive sleep apnoea-hypopnoea syndrome (OSAHS). APPROACH: Nocturnal oximetry signals from 142 children with suspected OSAHS were acquired using the Phone Oximeter: a portable device that integrates a pulse oximeter with a smartphone. An apnoea-hypopnoea index (AHI) ≥5 events/h from simultaneous in-lab polysomnography was used to confirm moderate-to-severe childhood OSAHS. Symbolic dynamics was used to parameterise non-linear changes in the overnight oximetry profile. Conventional indices, anthropometric measures, and time-domain linear statistics were also considered. Forward stepwise logistic regression was used to obtain an optimum feature subset. Logistic regression (LR) was used to identify children with moderate-to-severe OSAHS. MAIN RESULTS: The histogram of 3-symbol words from symbolic dynamics showed significant differences (p <0.01) between children with AHI <5 events/h and moderate-to-severe patients (AHI ≥5 events/h). Words representing increasing oximetry values after apnoeic events (re-saturations) showed relevant diagnostic information. Regarding the performance of individual characterization approaches, the LR model composed of features from symbolic dynamics alone reached a maximum performance of 78.4% accuracy (65.2% sensitivity; 86.8% specificity) and 0.83 area under the ROC curve (AUC). The classification performance improved combining all features. The optimum model from feature selection achieved 83.3% accuracy (73.5% sensitivity; 89.5% specificity) and 0.89 AUC, significantly (p-value <0.01) outperforming the other models. SIGNIFICANCE: Symbolic dynamics provides complementary information to conventional oximetry analysis enabling reliable detection of moderate-to-severe paediatric OSAHS from portable oximetry.