ith an FTP score of 1 had an AHI value lower than 16.0/hour; in most of them (64.0%), the AHI value was 5.0/hour to 10.0/hour. Most patients with an FTP score of 2 (58.7%) had an AHI value of 10.0/hour to 20.0/hour. Two patients had normal values, and only 5 had an AHI value of 30.0/hour (all of them with a uvula index of 3). The FTP scores and AHI categories are shown in Table 3.
One patient with an FTP score of 3 had an AHI value of 13.4/hour, but all the others had an AHI value of 16.0/hour. The AHI value in most patients with an FTP score of 3 ranged from 32 to 48, with 3 patients showing an AHI value higher than 60.0/hour. All patients with an FTP score of 4 had an AHI value higher than 30.0/hour, corresponding to severe OSAS. The relation between FTP score and AHI is plotted in Figure 3.
Just over three-quarters of patients (77.4%) had TS scores of 1 and 2 and only 15 had a TS score of 3 (5.0%). None had a TS score of 4. Tonsil size scores of 3 and 4 are common in the pediatric population but are rare in adult OSAS. Fifty-two of the 301 patients (17.3%) had previously undergone tonsillectomy (Table 1). Figure 4 shows the progression of OSAS severity related to TS.
All patients with TS scores of 2 and 3 had an AHI value higher than 15.0/hr; AHI values were higher in the group with a TS score of 3. Curiously, AHI values in patients who had undergone tonsillectomy were higher than in those with a TS score of 1 and quite similar to those with a TS score of 2. Most of these patients were classified as having moderate to severe OSAS. Fifty-two (67%) had an AHI value higher than 15.0/hour, and only 4 (7.6%) had an AHI value lower than 5.0/hour. Uvula scores of 2 and 3 were found in 90.7% of the population (Table 1).
Table 4 shows the correlation of the AHI with the explanatory variables. The model with the lowest Cp value included the FTP score, FL150, the cervical perimeter, age, and the TS score (Table 4). Despite the high correlation coefficient, the TS score did not enter into the model when using the stepwise selection procedure because it did not reach the specified significance level of 0.10. Both 2-way and 3-way interactions between the variables selected by the stepwise procedure were not significant (F tests) (Table 4).
The model finally selected included the FTP score, FL150, cervical perimeter, and age. The root mean square error for this model was 0.454, and the R2 statistic was 0.748. The parameter estimates and F tests are shown in Table 4 along with partial R2 values. Note that although F tests were significant, the partial contribution of FL150, age, and cervical perimeter to the fit (as measured by the partial R2 statistic) was negligible. The final predictive equation for the expected log AHI was −0.320 + 0.814 FTP (score) − 0.409 FL150 (dm3/s) + 0.033 Cervical Perimeter (cm) + 0.006 Age (years).
Obstructive sleep apnea syndrome is very common and affects a considerable proportion of the population. If untreated, it causes considerable increases in cardiac and cerebrovascular morbidity and mortality.13 Many patients with obstructive OSAS remain undiagnosed owing to inadequate resources for case detection and investigation, a situation that has clear repercussions for their quality of life.3,6,7,14-21 Moreover, OSAS represents a considerable socioeconomic burden, owing to comorbidity, increased health care utilization in the primary and secondary health care sectors, increased use of medication, impact on employment, and loss of income. Treatment of OSAS reduces morbidity, mortality, and hospitalization rates, and its cost-effectiveness has been demonstrated.22 So, there is a clear need to establish optimal procedures to identify patients at risk.
Traditionally, OSAS diagnosis has been performed using in-hospital, overnight polysomnography. This procedure is time consuming and expensive, and, since its capacity is limited, waiting lists tend to lengthen.
In recent decades, several attempts have been made to find predictive models based on clinical examination of the upper airway, combined or not with cli