Uso do SAPS 3 no escore NUTrition RIsk in the Critically ill modificado tem precisão preditiva comparável ao uso do APACHE II como marcador de gravidade / SAPS 3 in the modified NUTrition RIsk in the Critically ill score has comparable predictive accuracy to APACHE II as a severity marker

RESUMO Objetivo: Avaliar o Simplified Acute Physiology Score 3 (SAPS 3) como substituto do Acute Physiology and Chronic Health Evaluation II (APACHE II) como marcador de gravidade na versão modificada do escore NUTrition RIsk in the Critically ill (mNUTRIC; sem interleucina 6), com base em uma análise de sua capacidade discriminativa para predição de mortalidade hospitalar. Métodos: Este estudo de coorte retrospectiva avaliou 1.516 pacientes adultos internados em uma unidade de terapia intensiva de um hospital geral privado entre abril de 2017 e janeiro de 2018. A avaliação de desempenho incluiu as análises Kappa de Fleiss e correlação de Pearson. A capacidade discriminativa para estimar a mortalidade hospitalar foi avaliada com a curva Característica de Operação do Receptor. Resultados: A amostra foi dividida aleatoriamente em dois terços para o desenvolvimento do modelo (n = 1.025; idade 72 [57 - 83]; 52,4% masculino) e um terço para avaliação do desempenho (n = 490; idade 72 [57 - 83]; 50,8 % masculino). A concordância com o mNUTRIC foi Kappa de 0,563 (p < 0,001), e a correlação entre os instrumentos foi correlação de Pearson de 0,804 (p < 0,001). A ferramenta mostrou bom desempenho para prever a mortalidade hospitalar (área sob a curva de 0,825 [0,787 - 0,863] p < 0,001). Conclusão: A substituição do APACHE II pelo SAPS 3 como marcador de gravidade no escore mNUTRIC mostrou bom desempenho para predizer a mortalidade hospitalar. Esses dados fornecem a primeira evidência sobre a validade da substituição do APACHE II pelo SAPS 3 no mNUTRIC como marcador de gravidade. São necessários estudos multicêntricos e análises adicionais dos parâmetros de adequação nutricional.

ABSTRACT Objective: To evaluate the substitution of Acute Physiology and Chronic Health Evaluation II (APACHE II) by Simplified Acute Physiology Score 3 (SAPS 3) as a severity marker in the modified version of the NUTrition RIsk in the Critically ill score (mNUTRIC); without interleukin 6) based on an analysis of its discriminative ability for in-hospital mortality prediction. Methods: This retrospective cohort study evaluated 1,516 adult patients admitted to an intensive care unit of a private general hospital from April 2017 to January 2018. Performance evaluation included Fleiss' Kappa and Pearson correlation analysis. The discriminative ability for estimating in-hospital mortality was assessed with the Receiver Operating Characteristic curve. Results: The sample was randomly divided into two-thirds for model development (n = 1,025; age 72 [57 - 83]; 52.4% male) and one-third for performance evaluation (n = 490; age 72 [57 - 83]; 50.8% male). The agreement with mNUTRIC was Kappa of 0.563 (p < 0.001), and the correlation between the instruments was Pearson correlation of 0.804 (p < 0.001). The tool showed good performance in predicting in-hospital mortality (area under the curve 0.825 [0.787 - 0.863] p < 0.001). Conclusion: The substitution of APACHE II by SAPS 3 as a severity marker in the mNUTRIC score showed good performance in predicting in-hospital mortality. These data provide the first evidence regarding the validity of the substitution of APACHE II by SAPS 3 in the mNUTRIC as a marker of severity. Multicentric studies and additional analyses of nutritional adequacy parameters are required.

SAPS 3 in the modified NUTrition RIsk in the Critically ill score has comparable predictive accuracy to APACHE II as a severity marker. / Uso do SAPS 3 no escore NUTrition RIsk in the Critically ill modificado tem precisão preditiva comparável ao uso do APACHE II como marcador de gravidade.

OBJECTIVE: To evaluate the substitution of Acute Physiology and Chronic Health Evaluation II (APACHE II) by Simplified Acute Physiology Score 3 (SAPS 3) as a severity marker in the modified version of the NUTrition RIsk in the Critically ill score (mNUTRIC); without interleukin 6) based on an analysis of its discriminative ability for in-hospital mortality prediction. METHODS: This retrospective cohort study evaluated 1,516 adult patients admitted to an intensive care unit of a private general hospital from April 2017 to January 2018. Performance evaluation included Fleiss' Kappa and Pearson correlation analysis. The discriminative ability for estimating in-hospital mortality was assessed with the Receiver Operating Characteristic curve. RESULTS: The sample was randomly divided into two-thirds for model development (n = 1,025; age 72 [57 - 83]; 52.4% male) and one-third for performance evaluation (n = 490; age 72 [57 - 83]; 50.8% male). The agreement with mNUTRIC was Kappa of 0.563 (p < 0.001), and the correlation between the instruments was Pearson correlation of 0.804 (p < 0.001). The tool showed good performance in predicting in-hospital mortality (area under the curve 0.825 [0.787 - 0.863] p < 0.001). CONCLUSION: The substitution of APACHE II by SAPS 3 as a severity marker in the mNUTRIC score showed good performance in predicting in-hospital mortality. These data provide the first evidence regarding the validity of the substitution of APACHE II by SAPS 3 in the mNUTRIC as a marker of severity. Multicentric studies and additional analyses of nutritional adequacy parameters are required.

OBJETIVO: Avaliar o Simplified Acute Physiology Score 3 (SAPS 3) como substituto do Acute Physiology and Chronic Health Evaluation II (APACHE II) como marcador de gravidade na versão modificada do escore NUTrition RIsk in the Critically ill (mNUTRIC; sem interleucina 6), com base em uma análise de sua capacidade discriminativa para predição de mortalidade hospitalar. MÉTODOS: Este estudo de coorte retrospectiva avaliou 1.516 pacientes adultos internados em uma unidade de terapia intensiva de um hospital geral privado entre abril de 2017 e janeiro de 2018. A avaliação de desempenho incluiu as análises Kappa de Fleiss e correlação de Pearson. A capacidade discriminativa para estimar a mortalidade hospitalar foi avaliada com a curva Característica de Operação do Receptor. RESULTADOS: A amostra foi dividida aleatoriamente em dois terços para o desenvolvimento do modelo (n = 1.025; idade 72 [57 - 83]; 52,4% masculino) e um terço para avaliação do desempenho (n = 490; idade 72 [57 - 83]; 50,8 % masculino). A concordância com o mNUTRIC foi Kappa de 0,563 (p < 0,001), e a correlação entre os instrumentos foi correlação de Pearson de 0,804 (p < 0,001). A ferramenta mostrou bom desempenho para prever a mortalidade hospitalar (área sob a curva de 0,825 [0,787 - 0,863] p < 0,001). CONCLUSÃO: A substituição do APACHE II pelo SAPS 3 como marcador de gravidade no escore mNUTRIC mostrou bom desempenho para predizer a mortalidade hospitalar. Esses dados fornecem a primeira evidência sobre a validade da substituição do APACHE II pelo SAPS 3 no mNUTRIC como marcador de gravidade. São necessários estudos multicêntricos e análises adicionais dos parâmetros de adequação nutricional.

Metabarcoding reveals that a non-nutritive sweetener and sucrose yield similar gut microbiota patterns in Wistar rats.

The effects of non-nutritive sweeteners (NNS) on the gut microbiota are an area of increasing research interest due to their potential influence on weight gain, insulin resistance, and inflammation. Studies have shown that mice and rats fed saccharin develop weight gain and metabolic alterations, possibly related to changes in gut microbiota. Here, we hypothesized that chronic exposure to a commercial NNS would change the gut microbiota composition in Wistar rats when compared to sucrose exposure. To test this hypothesis, Wistar rats were fed either NNS- or sucrose-supplemented yogurt for 17 weeks alongside standard chow (ad libitum). The gut microbiome was assessed by 16S rDNA deep sequencing. Assembly and quantification were conducted using the Brazilian Microbiome Project pipeline for Ion Torrent data with modifications. Statistical analyses were performed in the R software environment. We found that chronic feeding of a commercial NNS-sweetened yogurt to Wistar rats, within the recommended dose range, did not significantly modify gut microbiota composition in comparison to sucrose-sweetened yogurt. Our findings do not support the hypothesis that moderate exposure to NNS is associated with changes in gut microbiota pattern compared to sucrose, at least in this experimental model.

Long-term intake of saccharin decreases post-absortive energy expenditure at rest and is associated to greater weight gain relative to sucrose in wistar rats.

BACKGROUND: Non-nutritive sweeteners (NNS) have been associated with increased prevalence of obesity. In previous studies, we demonstrated that saccharin could induce an increase in weight gain either when compared to sucrose or to a non-sweetened control at a similar total caloric intake. These data raised the hypothesis that reduced energy expenditure (EE) could be a potential mechanism explaining greater weight gain with saccharin use in rats. The aim of the present study was to compare long-term energy expenditure at rest between rats using saccharin or sucrose and correlate it with weight gain. . METHODS: In the present study, we examine the potential impact of saccharin compared to sucrose in the EE of Wistar rats. In a controlled experiment of 17 weeks, 24 Wistar rats were divided into 2 groups: saccharin-sweetened yogurt (SAC) or sucrose-sweetened yogurt (SUC), plus a free chow diet. Only rats that consumed at least 70% of the offered yogurt were included. EE (kcal/day) was determined at rest through open circuit indirect calorimetry system in the early post-absorptive period with determinations of both VO2 consumption and CO2 production. Measurements were evaluated at baseline, 5 and 12 weeks of dietary intervention. Weight gain, caloric intake (from yogurt, from chow and total) were determined weekly. RESULTS: Body weight and EE were similar between groups at baseline: (p = .35) and (p = .67) respectively. At the end of the study, SAC increased total weight gain significantly more in relation to SUC (p = .03). Cumulative total caloric intake (yogurt plus chow) was similar between groups during the whole period (p = .54). At 12 weeks, the EE was smaller in SAC compared to SUC (p = .009). Considering both groups, there was a strong negative correlation between total weight gain and change in EE observed [r(20) = -.61, p = .003]. However, when analyzing the groups separately we found that SUC maintained this inverse correlation [r(8) = -.68, p = .03], while SAC did not [r(10) = -.33, p = .29]. CONCLUSION: These data support the hypothesis that long-term use of saccharin may blunt post-absorptive EE at rest in Wistar rats, which is related to weight gain. On the other hand, long-term sucrose intake can increase energy expenditure in rats. This effect combined can explain, at least partially, the weight gain increases associated to saccharin in relation to sucrose in these animals.

Sweet taste of saccharin induces weight gain without increasing caloric intake, not related to insulin-resistance in Wistar rats.

In a previous study, we showed that saccharin can induce weight gain when compared with sucrose in Wistar rats despite similar total caloric intake. We now question whether it could be due to the sweet taste of saccharin per se. We also aimed to address if this weight gain is associated with insulin-resistance and to increases in gut peptides such as leptin and PYY in the fasting state. In a 14 week experiment, 16 male Wistar rats received either saccharin-sweetened yogurt or non-sweetened yogurt daily in addition to chow and water ad lib. We measured daily food intake and weight gain weekly. At the end of the experiment, we evaluated fasting leptin, glucose, insulin, PYY and determined insulin resistance through HOMA-IR. Cumulative weight gain and food intake were evaluated through linear mixed models. Results showed that saccharin induced greater weight gain when compared with non-sweetened control (p = 0.027) despite a similar total caloric intake. There were no differences in HOMA-IR, fasting leptin or PYY levels between groups. We conclude that saccharin sweet taste can induce mild weight gain in Wistar rats without increasing total caloric intake. This weight gain was not related with insulin-resistance nor changes in fasting leptin or PYY in Wistar rats.

Fasting ghrelin but not PYY(3-36) is associated with insulin-resistance independently of body weight in Wistar rats.

OBJECTIVE: The objective of this study was to evaluate the association between insulin-resistance and fasting levels of ghrelin and PYY in Wistar rats. MATERIALS AND METHODS: A total of 25 male Wistar rats, weighing 200-300 g, was included in this study. The animals were maintained in cages with a 12/12h light-dark cycle and fed standard chow and water ad libitum. After 12-h overnight fasting, ghrelin, PYY, insulin and glucose values were determined. Insulin resistance was assessed by means of the HOMA-IR, which was ranked and the median was used as a cut-off value to categorize insulin-resistance. HOMA-IR values equal and above 2.62 were considered insulin-resistant (IR) while values below 2.62 were considered insulin sensitive (IS). Differences between means were determined using the Student t-test. Multiple regression and Pearson's correlation test were used to evaluate the association between variables. RESULTS: HOMA-IR median IQ range values for IS and IR groups were, respectively, 1.56 (0.89 - 2.16) vs. [4.06 (3.50 - 4.61); p < 0.001]. The IR group presented increased levels of fasting ghrelin, PYY and insulin respectively: [50.35 (25.99 - 74.71) pg/mL vs. 12.33 (8.77 - 15.89) pg/mL; p = 0.001]; [54.38 (37.50 - 71.26) pg/mL vs. 33.17 (22.34 - 43.99) pg/mL; p = 0.016]; [18.04 (14.48 - 21.60) uU/mL vs. 7.09 (4.83 - 9.35) uU/mL; p = 0.001]. Ghrelin, but not PYY, correlated linearly and positively with HOMA-IR: ghrelin vs. HOMA-IR (r = 0.52; p = 0.008), and PYY vs. HOMA-IR (r = 0.22; p = 0.200). This correlation was independent of body weight. CONCLUSION: Fasting ghrelin and PYY serum levels are increased in lean, relatively insulin resistant Wistar rats, and this increase is independent of weight.

Fasting ghrelin but not PYY(3-36) is associated with insulin-resistance independently of body weight in Wistar rats / A grelina, mas não PYY(3-36), está associada com a resistência à insulina independente do peso corporal em ratos Wistar

Objective: The objective of this study was to evaluate the association between insulin-resistance and fasting levels of ghrelin and PYY in Wistar rats. Materials and methods: A total of 25 male Wistar rats, weighing 200-300 g, was included in this study. The animals were maintained in cages with a 12/12h light-dark cycle and fed standard chow and water ad libitum. After 12-h overnight fasting, ghrelin, PYY, insulin and glucose values were determined. Insulin resistance was assessed by means of the HOMA-IR, which was ranked and the median was used as a cut-off value to categorize insulin-resistance. HOMA-IR values equal and above 2.62 were considered insulin-resistant (IR) while values below 2.62 were considered insulin sensitive (IS). Differences between means were determined using the Student t-test. Multiple regression and Pearson’s correlation test were used to evaluate the association between variables. Results: HOMA-IR median IQ range values for IS and IR groups were, respectively, 1.56 (0.89 – 2.16) vs. [4.06 (3.50 – 4.61); p < 0.001]. The IR group presented increased levels of fasting ghrelin, PYY and insulin respectively: [50.35 (25.99 – 74.71) pg/mL vs. 12.33 (8.77 – 15.89) pg/mL; p = 0.001]; [54.38 (37.50 – 71.26) pg/mL vs. 33.17 (22.34 – 43.99) pg/mL; p = 0.016]; [18.04 (14.48 – 21.60) uU/mL vs. 7.09 (4.83 – 9.35) uU/mL; p = 0.001]. Ghrelin, but not PYY, correlated linearly and positively with HOMA-IR: ghrelin vs. HOMA-IR (r = 0.52; p = 0.008), and PYY vs. HOMA-IR (r = 0.22; p = 0.200). This correlation was independent of body weight. Conclusion: Fasting ghrelin and PYY serum levels are increased in lean, relatively insulin resistant Wistar rats, and this increase is independent of weight. .

Objetivo: O objetivo deste estudo foi avaliar a associação entre a resistência à insulina e os níveis de grelina e PYY em jejum em ratos Wistar. Materiais e métodos: Um total de 25 ratos Wistar machos, pesando 200-300 g, foi usado neste estudo. Os animais foram mantidos em gaiolas com um ciclo de luz escuro de 12/12h e alimentados com ração padrão e água ad libitum. Depois de um jejum de 12h, os valores de grelina, PYY, insulina e glicose foram determinados. A resistência à insulina foi avaliada pelo HOMA-IR que foi ordenado e a mediana utilizada como valor de corte para categorizar a resistência à insulina. Os valores de HOMA-IR iguais ou acima de 2,62 foram considerados resistentes à insulina (RI), enquanto valores abaixo de 2,62 foram considerados sensíveis (SI). As diferenças entre as médias foram determinadas usando-se o teste t de Student. A análise de regressões múltiplas e o teste de correlação de Pearson foram usados para se avaliar a associação entre as variáveis. Resultados: A mediana e a variação IQ do HOMA-IR para os grupos RI e SI foram, respectivamente, 1,56 (0,89 – 2,16) contra [4,06 (3,50 – 4,61); p < 0,001]. O grupo RI apresentou níveis aumentados de grelina, PYY e insulina em jejum, respectivamente, [50,35 (25,99 – 74,71) pg/mL contra 12,33 (8,77 – 15,89) pg/mL; p = 0,001]; [54,38 (37,50 – 71,26) pg/mL contra 33,17 (22,34 – 43,99) pg/mL; p = 0,016]; [18,04 (14,48 – 21,60) uU/mL contra 7,09 (4,83 – 9,35) uU/mL; p = 0.001]. A grelina, mas não PYY, se correlacionou de forma linear e positiva com o HOMA-IR: a grelina contra HOMA-IR (r = 0,52; p = 0,008), e PYY contra HOMA-IR (r = 0,22; p = 0,200). Essa correlação foi independente do peso corporal. Conclusão: Os níveis séricos de jejum de grelina ...

Saccharin and aspartame, compared with sucrose, induce greater weight gain in adult Wistar rats, at similar total caloric intake levels.

It has been suggested that the use of nonnutritive sweeteners (NNSs) can lead to weight gain, but evidence regarding their real effect in body weight and satiety is still inconclusive. Using a rat model, the present study compares the effect of saccharin and aspartame to sucrose in body weight gain and in caloric intake. Twenty-nine male Wistar rats received plain yogurt sweetened with 20% sucrose, 0.3% sodium saccharin or 0.4% aspartame, in addition to chow and water ad libitum, while physical activity was restrained. Measurements of cumulative body weight gain, total caloric intake, caloric intake of chow and caloric intake of sweetened yogurt were performed weekly for 12 weeks. Results showed that addition of either saccharin or aspartame to yogurt resulted in increased weight gain compared to addition of sucrose, however total caloric intake was similar among groups. In conclusion, greater weight gain was promoted by the use of saccharin or aspartame, compared with sucrose, and this weight gain was unrelated to caloric intake. We speculate that a decrease in energy expenditure or increase in fluid retention might be involved.