Alterações da estrutura e função respiratórias durante a vigília e o sono na agromegalia

Abstract

Introdução: Pacientes com acromegalia apresentam índice de mortalidade respiratória mais elevados que os encontrados na população. A hipoxemia secundária a apnéia do sono é comumente encontrada na acromegalia e parece ser a alteração sobre a qual se estabelece considerável morbidade e mortalidade. Este estudo pretende reconhecer sua presença a partir de dados clínicos, avaliar o peso relativo de fatores patogênicos na sua determinação e observar possíveis alterações da estrutura pulmonar, relacionando-as a testes funcionais respiratórios. Métodos: Foram estudados transversalmente 36 pacientes com acromegalia, os quais foram submetidos a oximetria durante o sono e avaliados quanto à presença de roncos, a medida do índice de massa corporal (IMC), da circunferência do pescoço, da sonolência pela escala de Epworth. A hipoxemia durante o sono foi definida como mais de 5 episódios de dessaturação por hora. Também foram submetidos à tomografia do canal rinolaríngeo e do tórax, oximetria de esforço, espirometria e medidas dos volumes pulmonares, capacidade de difusão pelo monóxido de carbono (DLCO) e pressões inspiratórias e expiratórias máximas. Foi constituído um grupo controle de 24 pacientes para comparações de achados na tomografia de tórax. Dosagens de GH e IGF-I e valores de ULNV foram obtidos de todos os pacientes. O índice de parâmetros lineares (IPL) foi criado para expressar o conjunto de anormalidades do aspecto crânio-facial. Foi construído um modelo de regressão logística para predição de hipoxemia durante o sono com variáveis indicadoras de obesidade, anormalidade crânio facial e de alteração hormonal, sendo seus coeficientes padronizados para observação de suas magnitudes relativas frente ao desfecho. Resultados: A sensibilidade e especificidade para predizer hipoxemia durante o sono foram respectivamente: IMC > 28,5 Kg/m2 (71,4% e 60%); circunferência do pescoço >44 cm (28,6% e 95%); Epworth > 10 pontos (42,9% e 70%); roncos (92,9% e 35%). Se presente circunferência do pescoço maior que 44 cm, a probabilidade de hipoxemia aumenta de 41% (pré-teste) para 80% (pós-teste). Se ausente este dado, a presença de dois ou três dos demais (ronco, Epworth > 10, IMC > 28,5 Kg/m2) eleva a probabilidade pósteste para 62%, enquanto a presença de no máximo um deles é capaz de reduzir para 8%. O modelo construído se mostrou significativo (p<0,01) e compreendeu as variáveis sexo, idade, IPL, IMC e ULNV. Na ausência das variáveis idade e sexo, a razão de chances do IPL (1,60) se mostrou pouco superior ao IMC (1,49) e a ULNV (1,40). Quando os dados foram controlados pela idade, a ULNV apresentou pouca alteração (1,49), porém o IPL (1,21) diminuiu muito e o IMC (2,18) aumentou muito. O peso relativo do IPL foi dependente da idade. A variável sexo não introduziu alterações de relevância nas demais. Comparado ao controle, não houve achados à tomografia em proporção significativa. Sete pacientes (21%) apresentaram hipoxemia, dos quais 6 apresentavam outras doenças pulmonares, 8 (22%) apresentaram distúrbio ventilatório, 5 dos quais com diagnósticos de outras doenças, 3 (8%) redução de pressão inspiratória e 5 (14%) de pressão expiratória máxima. Todos apresentaram DLCO normal Conclusões: Os achados clínicos avaliados permitem com alta probabilidade predizer ou não hipoxemia durante o sono na acromegalia. O aspecto crânio-facial, a obesidade e as alterações hormonais contribuem em magnitude similar para a hipoxemia durante o sono. As alterações funcionais pulmonares são explicáveis em grande parte por diagnósticos alternativos, não apresentando relação plausível com o aspecto da estrutura pulmonar. _______________________________________________________________________________ ABSTRACT

Purposes: Patients with acromegaly have increased mortality due to respiratory disease when compared to whole population. Hypoxemia secondary to sleep apnea is commonly seen in patients with acromegaly, and this alteration apparently leads to considerable morbidity and mortality among such patients. This research has the objective of identifying hypoxemia based on clinical data, of knowing pathogenic factors proportion in its establishment and to realize pulmonary structure, connecting it to respiratory function tests. Methods: We conducted a cross-sectional study of 36 patients with acromegaly, all of whom were submitted to nocturnal oximetry and evaluation of snoring, as well as to the determination of body mass index (BMI) and neck circumference. In addition, daytime sleepiness was evaluated using the Epworth Sleepiness Scale (ESS). In this study, sleep hypoxemia was defined as five or more episodes of desaturation per hour. They also were submitted to an upper airway and chest computerized tomography, spirometry, lung volumes measure, oximetry during exercise, diffusion capacity (DLCO) and maximal inspiratory and expiratory pressure. A control group of 24 patients were used to compare chest tomography. Serum levels of GH, IGF-I and ULNV were obtained from all patients. An index that measure craniofacial abnormalities (CAI) was created, as well as a logistic regression model with standardized coefficients to predict hypoxemia using variables which represent obesity, craniofacial abnormalities and hormone dysfunction. Results: The sensitivity and specificity of the various parameters in predicting such hypoxemia were, respectively, as follows: snoring (92.9% and 35%); BMI > 28.5 kg/m2 (71.4% and 60%); neck circumference > 44 cm (28.6% and 95%); ESS score > 10 (42.9% and 70%). For patients with a neck circumference of more than 44 cm, the probability of sleep hypoxemia was found to increase from 41% (pre-test) to 80% (post-test). For patients with a neck circumference of less than 44 cm, positivity for two or three of the other parameters (snoring, ESS score > 10 and BMI > 28.5 kg/m2) increased the post-test probability to 62%, whereas positivity for only one (or none) reduced post-test probability to 8%. A logistic model was shown to be significant (p<0,01) and was created with age, sex, BMI, CAI and ULNV. In the absence of age and sex, the CAI odds ratio (1,60) was a bit higher than BMI (1,49) and ULNV (1,40). When the data were controlled by age, ULNV remained almost the same (1,49), but the CAI decreased (1,21) and the BMI increased (2,18). The CAI`s influence in sleeping hypoxemia was age dependent. Control by sex variable didn’t change other variables significantly. There weren’t any change in the chest tomography, when compared to control group. Seven patients (21%) showed awakening hypoxemia, although six of whom had another respiratory disease. Eight (22%) showed obstructive dysfunction, but five of whom had another respiratory disease. Three (8%) showed low inspiratory and five (14%) low maximal expiratory pressure. No one had an abnormal DLCO. Conclusions: We can conclude that the clinical parameters evaluated allowed us to predict, with considerable accuracy, whether or not sleep hypoxemia would occur in patients with acromegaly. Craniofacial abnormalities, obesity and hormone dysfunction contribute in a similar way to produce sleep hypoxemia. The majority of respiratory function disorders founded in these patients were explained by another disease than acromegaly and there isn’t any relationship with lung structure. with a neck circumference of less than 44 cm, positivity for two or three of the other parameters (snoring, ESS score > 10 and BMI > 28.5 kg/m2) increased the post-test probability to 62%, whereas positivity for only one (or none) reduced post-test probability to 8%. A logistic model was shown to be significant (p<0,01) and was created with age, sex, BMI, CAI and ULNV. In the absence of age and sex, the CAI odds ratio (1,60) was a bit higher than BMI (1,49) and ULNV (1,40). When the data were controlled by age, ULNV remained almost the same (1,49), but the CAI decreased (1,21) and the BMI increased (2,18). The CAI`s influence in sleeping hypoxemia was age dependent. Control by sex variable didn’t change other variables significantly. There weren’t any change in the chest tomography, when compared to control group. Seven patients (21%) showed awakening hypoxemia, although six of whom had another respiratory disease. Eight (22%) showed obstructive dysfunction, but five of whom had another respiratory disease. Three (8%) showed low inspiratory and five (14%) low maximal expiratory pressure. No one had an abnormal DLCO. Conclusions: We can conclude that the clinical parameters evaluated allowed us to predict, with considerable accuracy, whether or not sleep hypoxemia would occur in patients with acromegaly. Craniofacial abnormalities, obesity and hormone dysfunction contribute in a similar way to produce sleep hypoxemia. The majority of respiratory function disorders founded in these patients were explained by another disease than acromegaly and there isn’t any relationship with lung structure.