Respiratory rate and pulse oximetry derived information as predictors of hospital admission in young children in Bangladesh: a prospective observational study

Garde, Ainara; Zhou, Guohai; Raihana, Shahreen; Dunsmuir, Dustin; Karlen, Walter; Dekhordi, Parastoo; Huda, Tanvir; Arifeen, Shams El; Larson, Charles P.; Kissoon, Niranjan; Dumont, Guy A.; Ansermino, J. Mark

doi:10.1136/bmjopen-2016-011094

Cited by 27 publications

(31 citation statements)

References 35 publications

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“…This simple model is derived from predictors that are readily available globally at relatively low cost and can be easily measured by low skilled frontline health workers. The predictors included in the model reflect what has been observed in previous studies [28][29][30] and what is often included in international guidelines 31 . After internal validation, the model affords high discrimination, with an AUC of 0.88 (95% CI 0.82 to 0.94) and good calibration (p = 0.715).…”

Section: Key Resultsmentioning

confidence: 99%

“…The digital platform also allows for real time monitoring of user performance and compliance and optimization of work flows. In addition, pulse oximetry can be conducted with mobile device by attaching low-cost sensors to enable objective measurements and alleviate the need to perform manual data entry of values read from a separate monitor 30,33,34 . The inclusion of RRate, an app for measure respiratory rate by tapping on the screen also enables faster collection of respiratory rate with less effort than counting breaths 12 .…”

Section: Strengths and Limitationsmentioning

confidence: 99%

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Derivation and internal validation of a data-driven prediction model to guide frontline health workers in triaging children under-five in Nairobi, Kenya

Mawji¹,

Akech²,

Mwaniki³

et al. 2019

Wellcome Open Res

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Background: Many hospitalized children in developing countries die from infectious diseases. Early recognition of those who are critically ill coupled with timely treatment can prevent many deaths. A data-driven, electronic triage system to assist frontline health workers in categorizing illness severity is lacking. This study aimed to develop a data-driven parsimonious triage algorithm for children under five years of age. Methods: This was a prospective observational study of children under-five years of age presenting to the outpatient department of Mbagathi Hospital in Nairobi, Kenya between January and June 2018. A study nurse examined participants and recorded history and clinical signs and symptoms using a mobile device with an attached low-cost pulse oximeter sensor. The need for hospital admission was determined independently by the facility clinician and used as the primary outcome in a logistic predictive model. We focused on the selection of variables that could be quickly and easily assessed by low skilled health workers. Results: The admission rate (for more than 24 hours) was 12% (N=138/1,132). We identified an eight-predictor logistic regression model including continuous variables of weight, mid-upper arm circumference, temperature, pulse rate, and transformed oxygen saturation, combined with dichotomous signs of difficulty breathing, lethargy, and inability to drink or breastfeed. This model predicts overnight hospital admission with an area under the receiver operating characteristic curve of 0.88 (95% CI 0.82 to 0.94). Low- and high-risk thresholds of 5% and 25%, respectively were selected to categorize participants into three triage groups for implementation. Conclusion: A logistic regression model comprised of eight easily understood variables may be useful for triage of children under the age of five based on the probability of need for admission. This model could be used by frontline workers with limited skills in assessing children. External validation is needed before adoption in clinical practice.

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Section: Key Resultsmentioning

confidence: 99%

Section: Strengths and Limitationsmentioning

confidence: 99%

Derivation and internal validation of a data-driven prediction model to guide frontline health workers in triaging children under-five in Nairobi, Kenya

Mawji¹,

Akech²,

Mwaniki³

et al. 2019

Wellcome Open Res

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“…Thus, PaO 2 variability could be a surrogate marker for relative ischemiareperfusion injury in the brain, which could cause secondary brain injury. Indeed, in pediatric intensive care, oxygen variability measured on the plethysmography has recently been shown to predict chronic lung disease [11,12] or the need for hospitalization [12].…”

Section: Resultsmentioning

confidence: 99%

“…In fact, PaO 2 levels > 100 mmHg seem to have deleterious effects on outcome in critically ill patients overall [6,7] and the threshold changes only slightly in specific subpopulations such as post-cardiac arrest (PaO 2 levels > 120 mmHg) [8,9] or aneurysmal subarachnoid hemorrhage (aSAH) (PaO 2 > 200 mmHg) patients [10]. Moreover, the concept of PaO 2 variability, defined as the daily difference between the highest and the lowest PaO 2 values, has recently been identified as a potential surrogate marker for relative ischemiareperfusion injury [11,12].…”

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confidence: 99%

Oxygenation derangements after subarachnoid hemorrhage: incidence and impact on the outcome. Data from a large multicenter, retrospective study.

Citerio¹,

Aurelien²,

Chiara³

et al. 2019

Preprint

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BackgroundHypoxemia and hyperoxemia are frequent after acute subarachnoid hemorrhage (aSAH) and are associated with an increase in morbidity and mortality. Among the pulmonary complications causing oxygen derangements, acute respiratory distress syndrome (ARDS) seems to be crucial, with a reported incidence ranging from 11 to 50%. MethodsWe designed a multicentric, retrospective cohort study in tree intensive care in Europe. We collected data between January 2009 and December 2017. We included adult patients (≥18 years) with a diagnosis of aSAH. Hypoxemia was defined as PaO2 <60mmHg, mild hyperoxemia as PaO2>120mmHg, and severe hyperoxemia as PaO2>200mmHg. The primary aim of this study was to assess the incidence of episodes of hypoxemia, hyperoxemia, and the oxygen variability values (calculated as the daily difference between the highest and the lowest arterial partial pressure of oxygen (PaO2)) during the first week after the intensive care unit (ICU) admission. Secondary aims included the evaluation of the incidence of ARDS according to the Berlin criteria, and the assessment of the effect of oxygen derangements on patients’ outcomes.Results855 patients fulfilled the inclusion criteria. 6.4% of the patients presented at least one episode of hypoxemia (PaO2 <60mmHg), 56.6% of mild hyperoxemia (PaO2 >120mmHg), and 16.8% of severe hyperoxemia (PaO2 >200mmHg). The cumulative incidence of ARDS resulted in 2.2% on the first day since ICU admission, 3.2% by three days, and 3.6% by seven days. A lower Glasgow Coma Scale score (GCS) at admission, longer duration of mechanical ventilation, higher PaO2 variability, hypoxemia, and ARDS occurrence were independently associated with poor outcome.ConclusionsHypoxemia and hyperoxemia episodes are frequent in the first 7-days of ICU stay after aSAH, whereas ARDS has a low incidence. The severity of aSAH but also ARDS occurrence, oxygenation parameters, and duration of MV are associated with patients’ outcomes

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“…For pneumonia, (one of the most common causes of hypoxemia especially in children), hypoxemia is primarily caused by obstruction of oxygen exchange in the alveoli of the lungs. A systematic review found that hypoxemia is a strong predictor of mortality for pneumonia in children, and other studies have also found hypoxemia to be associated with mortality and other poor outcomes for other diseases [1][2][3][4][5][6]. Patients in low-and middle-income countries (LMICs) are disproportionately affected as oxygen therapy, an effective treatment of hypoxemia, is not widely accessible [7,8].…”

Section: Introductionmentioning

confidence: 99%

The prevalence of hypoxemia among pediatric and adult patients presenting to healthcare facilities in low- and middle-income countries: protocol for a systematic review and meta-analysis

et al. 2020

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Background: Hypoxemia is a severe condition associated with high rates of mortality, particularly in low-and middle-income countries (LMICs) with poor access to oxygen therapy. Despite its clinical significance, there have been few studies to describe the burden of hypoxemia. Thus, the primary objective of this study is to systematically describe the prevalence of hypoxemia among pediatric and adult patients in low-and middle-income countries. Methods/design: Standard systematic review methods will be used. Bibliographic databases (MEDLINE, EMBASE, CINAHL) will be searched from 1998 onwards. The search strategy aims to identify studies that have measured peripheral blood oxygen saturation (SpO 2) in children and adults presenting to health facilities in LMICs. Studies will be included if oxygen saturation measurements by pulse oximetry were measured. No studies will be excluded based on study design though patients recruited from intensive care units and post-operative care will be excluded. The primary outcome is the prevalence of hypoxemia on presentation to the healthcare facility. We define hypoxemia on the basis of SpO 2 measurements, and use a threshold of SpO 2 less than 90% at sea level though allow for a lower threshold for studies conducted at higher altitude and where justified. Standardized tools will be used to extract data on number of patients with SpO 2 measurements, number of patients with hypoxemia, patient population characteristics, and study characteristics. Quality of the included studies will be assessed using the "Checklist for Prevalence Studies" developed by the Joanna Briggs Institute. If there are enough studies to do so, we will conduct meta-analysis using a random effects model to estimate prevalence of hypoxemia and conduct subgroup analyses by age and disease groups.

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Respiratory rate and pulse oximetry derived information as predictors of hospital admission in young children in Bangladesh: a prospective observational study

Cited by 27 publications

References 35 publications

Derivation and internal validation of a data-driven prediction model to guide frontline health workers in triaging children under-five in Nairobi, Kenya

Derivation and internal validation of a data-driven prediction model to guide frontline health workers in triaging children under-five in Nairobi, Kenya

Oxygenation derangements after subarachnoid hemorrhage: incidence and impact on the outcome. Data from a large multicenter, retrospective study.

The prevalence of hypoxemia among pediatric and adult patients presenting to healthcare facilities in low- and middle-income countries: protocol for a systematic review and meta-analysis

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