Accuracy of Fitbit Charge 2 Worn At Different Wrist Locations During Exercise

Many newly released activity monitors use heart rate measured at the wrist to estimate exercise intensity, however, where the device is placed on the wrist may affect accuracy of the measurement. PURPOSE: To determine whether the Pure Pulse technology on the Fitbit Charge 2 will show different heart rate readings when placed on the recommended exercise position compared to the all-day wear position at various exercise intensities. METHODS: Thirty-five participants (MEAN ± SD; 22.0 ± 2.9yrs; 23.9 ± 2.6kg/m2; 18 male) consented to participate in a single visit where two Fitbit Charge 2 devices were placed on the non-dominant wrist. Fitbit A was placed 2-3 fingers above the wrist bone. Fitbit B was placed directly above the wrist bone. The treadmill was set at 3 mph with 0% grade. Participants remained at this speed for 4 minutes. Heart rate measurements were taken at the last 10 seconds of each stage from both Fitbits and a polar heart rate monitor (chest strap). The same procedure was followed for 5 and 6 mph. Statistical analyses were performed using IBM SPSS 23.0. A Two-way (speed x location) Repeated Measures ANOVA was used to examine mean differences. Pairwise comparisons with Bonferroni correction were used in post-hoc analysis. Pearson correlations and mean bias between polar heart rate monitor and activity monitors were also calculated for each speed. RESULTS: Repeated Measures ANOVA found significant differences between speeds (p\u3c0.01) and location (p\u3c0.01), but not for the interaction (p=0.234). Pairwise comparisons indicated significant differences between each speed (p\u3c0.01) and between the polar monitor and Fitbit B (p\u3c0.05), but not between the polar monitor and Fitbit A (p=0.608). Pearson correlations indicated strong correlations between each Fitbit and the polar monitor (r= .58-.91; all p\u3c0.01). Mean bias decreased as speed increased for Fitbit A (mean bias BPM ± SD; -1.1 ± 5.4; -1.9 ± 9.5; -0.4 ± 6.9; -0.3 ± 7.3 for resting, 3mph, 5mph, 6mph respectively) while mean bias for Fitbit B increased as speed increased (-2.8 ± 8.8; -3.1 ± 11.1; -3.9 ± 14.6; -6.7 ± 14.3 for resting, 3mph, 5mph, 6mph respectively). CONCLUSION: Wrist-worn heart rate monitors appear to provide values adequate for recreational use, however, following recommended guidelines on wear-position may impact heart rate readings

Clinical spectrum and severity of hemolytic anemia in glucose 6-phosphate dehydrogenase-deficient children receiving dapsone

Drug-induced acute hemolytic anemia led to the discovery of G6PD deficiency. However, most clinical data are from isolated case reports. In 2 clinical trials of antimalarial preparations containing dapsone (4,4′-diaminodiphenylsulfone; 2.5 mg/kg once daily for 3 days), 95 G6PD-deficient hemizygous boys, 24 G6PD-deficient homozygous girls, and 200 girls heterozygous for G6PD deficiency received this agent. In the first 2 groups, there was a maximum decrease in hemoglobin averaging -2.64 g/dL (range -6.70 to +0.30 g/dL), which was significantly greater than for the comparator group receiving artemether-lumefantrine (adjusted difference -1.46 g/dL; 95% confidence interval -1.76, -1.15). Hemoglobin concentrations were decreased by ≥ 40% versus pretreatment in 24/119 (20.2%) of the G6PD-deficient children; 13/119 (10.9%) required blood transfusion. In the heterozygous girls, the mean maximum decrease in hemoglobin was -1.83 g/dL (range +0.90 to -5.20 g/dL); 1 in 200 (0.5%) required blood transfusion. All children eventually recovered. All the G6PD-deficient children had the G6PD A- variant, ie, mutations V68MandN126D. Drug-induced acutehemolytic anemia in G6PD A- subjects can be life-threatening, depending on the nature and dosage of the drug trigger. Therefore, contrary to current perception, in clinical terms the A- type of G6PD deficiency cannot be regarded as mild. This study is registered at http://www.clinicaltrials.gov as NCT00344006 and NCT00371735. © 2012 by The American Society of Hematology

Clinical spectrum and severity of hemolytic anemia in glucose 6-phosphate dehydrogenase-deficient children receiving dapsone

Drug-induced acute hemolytic anemia led to the discovery of G6PD deficiency. However, most clinical data are from isolated case reports. In 2 clinical trials of antimalarial preparations containing dapsone (4,4′-diaminodiphenylsulfone; 2.5 mg/kg once daily for 3 days), 95 G6PD-deficient hemizygous boys, 24 G6PD-deficient homozygous girls, and 200 girls heterozygous for G6PD deficiency received this agent. In the first 2 groups, there was a maximum decrease in hemoglobin averaging -2.64 g/dL (range -6.70 to +0.30 g/dL), which was significantly greater than for the comparator group receiving artemether-lumefantrine (adjusted difference -1.46 g/dL; 95% confidence interval -1.76, -1.15). Hemoglobin concentrations were decreased by ≥ 40% versus pretreatment in 24/119 (20.2%) of the G6PD-deficient children; 13/119 (10.9%) required blood transfusion. In the heterozygous girls, the mean maximum decrease in hemoglobin was -1.83 g/dL (range +0.90 to -5.20 g/dL); 1 in 200 (0.5%) required blood transfusion. All children eventually recovered. All the G6PD-deficient children had the G6PD A- variant, ie, mutations V68MandN126D. Drug-induced acutehemolytic anemia in G6PD A- subjects can be life-threatening, depending on the nature and dosage of the drug trigger. Therefore, contrary to current perception, in clinical terms the A- type of G6PD deficiency cannot be regarded as mild. This study is registered at http://www.clinicaltrials.gov as NCT00344006 and NCT00371735. © 2012 by The American Society of Hematology

Validity of Daily Physical Activity Measurements of Fitbit Charge 2

Physical activity monitors collect continuous data to provide a summary of daily activity. The Fitbit Charge 2 monitors heart rate as well as steps, calories, and active minutes throughout the day. There is currently no research validating the Fitbit Charge 2 at measuring daily physical activity levels in a real life setting. PURPOSE: To compare measures of daily steps and active minutes of Fitbit Charge 2 with a research-grade accelerometer. METHODS: Sixteen active college students (Mean±SD; 23±4.9yrs; 16.43±10.19%fat; 9 male) consented to be part of the study. Participants wore an ActiGraph GT3X accelerometer and Fitbit Charge 2 concurrently for seven consecutive days. Both devices were programed with each participant’s information and the participants were instructed to perform their daily activities wearing both devices and only remove them to shower and to sleep. Data were considered valid when participants wore both devices for at least 10 hours on 4 or more days of the week. Steps and active minutes (moderate-vigorous physical activity) were recorded by each device. Mean bias was calculated by subtracting ActiGraph steps and active minutes from those obtained from the Fitbit Charge 2 for each day and an average daily mean bias was calculated using values from all seven days. Absolute percentage error was also calculated [100(|Fitbit Charge 2 - ActiGraph|)/ActiGraph] to indicate the overall 7-day difference between the Fitbit Charge 2 and ActiGraph. Pearson correlations and paired sample t-test were performed to compare Fitbit Charge 2 measurements with the corresponding ActiGraph measurements with significance considered at p\u3c0.05. RESULTS: The Fitbit Charge 2 overestimated steps by 2,451.3±2085.4 compared to the ActiGraph using the daily average steps over the seven days. This was 32.2±40.7% above the ActiGraph measurement. Average mean bias for daily active minutes was -52.1±58.9 with the Fitbit Charge 2 underestimating compared to the ActiGraph. Active minutes for the Fitbit Charge 2 were an average of 69±26.1% away from the ActiGraph. Steps for the Fitbit Charge 2 were significantly correlated to ActiGraph steps (r=0.575, p=0.02) while active minutes were not significantly correlated (r= -0.255, p=0.34). Paired sample t-test results showed a significant difference between the Fitbit Charge 2 steps and active minutes compared with the ActiGraph (p\u3c0.01 for both). CONCLUSION: The Fitbit Charge 2 may be useful for measuring steps in a free-living environment, however active minutes are significantly underestimated

Accuracy of Fitbit Charge 2 at Estimating VO2max, Calories, and Steps on a Treadmill

Current fitness activity trackers can account for steps, calories burned, heart rate, and distance traveled. A new feature has recently been introduced on the Fitbit Charge 2, “Cardio Fitness Level,” which is comparable to a VO2max score in that it allows consumers to be aware of their aerobic fitness level. PURPOSE: To assess the accuracy of the Fitbit Charge 2 at estimating VO2 score (“Cardio Fitness Level”), calories, and steps when compared to indirect calorimetry and video analyzed steps, respectively. METHODS: Twenty-two healthy adults (Mean±SD; 24.1±4.2yrs; 16.9±9.0%fat; 15 male) completed two separate visits. On the first visit, anthropometric measurements were taken followed by a 10-minute outdoor run. Participants ran for 10 minutes at their own pace on flat terrain as recommended by Fitbit to generate a Cardio Fitness score. On the second visit, participants came fasted, at least 8 hours, and completed a standardized VO2max protocol (Arizona State protocol) using a PARVO TrueOne2400 metabolic cart. The treadmill was set at 3mph for the first 3 minutes with 0% grade. Following the first stage, the speed was raised to the participant’s pre-selected speed (between 5-8mph) with 0% grade. After stage 2 the grade increased every minute by 1.5% and speed was kept constant until fatigue was reached. Calories and step counts from the Fitbits were correlated with the metabolic cart and tally counter respectively, using 2-tailed Pearson correlations. Significance was set at pRESULTS: Participants completed the VO2max test in an average of 11:05. Eight of the 22 estimated VO2max ranges given by Fitbit included the value given by the metabolic cart. Fitbit ranges for seven participants were below the metabolic cart values and the Fitbit ranges for the remaining seven participants were above the metabolic cart values. Calories were correlated between the Fitbit and metabolic cart (r = 0.874, pCONCLUSION: VO2 scores given by the Fitbit Charge 2 did not always match values given by the metabolic cart but may serve as a rough estimate of fitness level. Fitbit Charge 2 may also be useful in tracking calories and steps in a controlled setting, but results may differ in real world conditions

Accuracy of Fitbit Activity Trackers During Walking in a Controlled Setting

Activity trackers are widely used to measure daily physical activity. Many devices have been shown to measure steps more accurately at higher intensities, however, it is also important to determine the accuracy of these new devices at measuring steps while walking at a pace similar to that used during most daily activities. PURPOSE: To assess the accuracy of 6 popular activity trackers at measuring steps while walking on a treadmill. METHODS: Twenty-six college students (Mean±SD; 22.1±3.7yrs; 25.1±4.0kg/m2; 13 male) walked 500 steps at 3mph on a treadmill while wearing 6 different activity trackers (Pedometer, Fitbit Blaze, Charge HR, Alta, Flex, Zip, One). The Charge HR was placed two fingers above the right wrist while the Flex was next to the wrist bone. The Blaze was placed two fingers above the left wrist while the Alta was next to the wrist bone. The Fitbit Zip and the One were aligned with the hipbone on the left and right waistband respectively. Steps were counted by a trained researcher using a hand tally counter. Missing values were replaced with the mean value for that device. Step counts were correlated between Fitbit devices and the pedometer and tally counter using Pearson correlations. Significance was set at p\u3c0.05. Mean bias scores were calculated between the step counts for each device and the tally counter. Mean Absolute Percent Error (MAPE) values were also calculated for each device relative to the tally counter. RESULTS: Fitbit Zip and One were significantly correlated with the tally counter (r=0.50, p\u3c0.05; r=0.68, p\u3c0.01, respectively) while the other devices were not significantly correlated. Mean bias and MAPE values were as follows: Device (Mean Bias/MAPE) Pedometer (-0.2±39.2/3.8±6.8), Blaze (34.5±67.1/9.9±11.3), Charge HR (-12.6±61.5/7.0±10.3), Alta (-85.0±70.8/17.1±14.1), Flex (49.5±242.4/19.7±45.3), Zip (1.8±3.4/0.4±0.6), One (0.2±2.1/0.3±0.3). Fitbit Zip and One were within one half percent of actual steps while wrist-worn Fitbits ranged from 7.0-19.7% from actual step counts. CONCLUSION: Consistent with previous research, activity trackers worn at the waist provide the most accurate step counts compared to wrist-worn models. Differences found in wrist-worn models may result in significant over- or underestimation of activity levels when worn for long periods of time

Comparison of Smartphone Pedometer Apps on a Treadmill versus Outdoors

Previous research has focused on the accuracy of smartphone pedometer apps in laboratory settings, however less information is available in outdoor (free living) environments. PURPOSE: Determine the accuracy of 5 smartphone apps at recording steps at a walking speed in a laboratory versus an outdoor setting. METHODS: Twenty-three healthy college students consented (Mean±SD; 22±3.8yrs; BMI 24.9±4.13kg/m2) to participate in 2 separate visits. During the first visit participants walked 500 steps at 3mph on a treadmill while wearing a pedometer and a smartphone placed in the pocket using 5 pedometer apps concurrently (Moves, Google Fit (G-Fit), Runtastic, Accupedo, S-Health). During the second visit, participants walked 400 meters at 3mph on a sidewalk outside. Actual steps for each visit were recorded using a hand tally counter device. Zero and negative values were replaced with the mean value for that trial. Statistical analyses were performed using IBM SPSS 23.0. Mean bias scores were calculated between the step count for each app and the respective tally count for each trial. Mean bias scores were correlated between trials for each app using Pearson correlations and significance was set at p\u3c0.05. Mean Absolute Percent Error (MAPE) values were also calculated for each app for both trials. RESULTS: G-Fit recorded 2 zero values and 2 negative values and Moves recorded 1 zero value. Mean bias scores were significantly correlated between the indoor and outdoor protocols for the pedometer (r=0.67, p\u3c0.01) and S-Health (r=0.46, p\u3c0.5). The remaining apps were not correlated between protocols. The outdoor protocol producing a greater mean bias for the outdoor protocol for G-Fit, Runtastic, and Accupedo (mean bias ± SD indoor, outdoor; -4.3±53.1, -19.3±120.0; -10.7±63.3, -33.4±118.7; 16.0±143.6, 79.0±75.0; respectively) and a greater mean bias for the indoor protocol for the pedometer, Moves, and S-Health (mean bias indoor, outdoor; -1.4±41.5, 0.0±34.1; -117.4±196.7, -42.2±209.6; 11.3±28.4, 0.0±58.7; respectively). MAPE was below 5% for the pedometer and S-Health for both trials. CONCLUSION: Apps with the lowest error in a controlled setting may be less affected when used in other settings, while apps with greater variation in a controlled setting may be affected when used in a different environment

Anemia ferropriva na infância: aspectos epidemiológicos, fisiopatológicos e manejo terapêutico / Iron deficiency anemia in childhood: epidemiological, physiopathological aspects and therapeutic management

As anemias afetam cerca de um terço da população mundial e contribuem para o aumento da morbidade e mortalidade, bem como a diminuição da produtividade no trabalho em adultos. Nas crianças, as anemias cursam com comprometimento do desenvolvimento natural do organismo, principalmente em relação à maturação do sistema neurológico. Devido a essas características, muito se tem feito para elucidar as etiologias da anemia por deficiência de ferro (ADF), a fim de aprimorar os métodos diagnósticos bem como o tratamento da doença. As etiologias de deficiência de ferro são diversas e na faixa etária pediátrica, as causas de deficiência de ferro estão principalmente relacionadas à desnutrição, perda de sangue através do trato gastrointestinal ou absorção diminuída - geralmente devido a infecções parasitárias e inflamações crônicas. O diagnóstico da doença baseia-se principalmente no rastreio da mesma, já que muitas vezes seu quadro é assintomático e suas consequências, tardias. O tratamento envolve abordagens específicas para cada causa da anemia e reposição de ferro medicamentosa, além de mudanças na alimentação. A despeito da grande quantidade de material científico existente sobre o assunto, novas fronteiras no diagnóstico e na terapia surgem a cada dia. A anemia continua a ser um problema de saúde global e novas perspectivas de prevenção,diagnóstico precoce e tratamento são necessárias para a devida abordagem da doença.