Patrick Hagge Cording

Early detection of COPD in general practice

Background and aim Early detection enables the possibility for interventions to reduce the future burden of COPD. The Danish National Board of Health recommends that individuals >35 years with tobacco/occupational exposure, and at least 1 respiratory symptom should be offered a spirometry to facilitate early detection of COPD. The aim, therefore, was to provide evidence for the feasibility and impact of doing spirometry in this target population. Methods Participating general practitioners (GPs) (n = 335; 10% of the Danish GPs) recruited consecutively, subjects with >35 years exposure, no previous diagnosis of obstructive lung disease, and at least 1 of the following symptoms: cough, dyspnea, wheezing, sputum, or recurrent respiratory infection. Data on age, smoking status, pack-years, body mass index (BMI), dyspnea score (Medical Research Council, MRC), and pre-bronchodilator spirometry (FEV1, FEV1% predicted, FEV1/FVC) were obtained. Results A total of 3.095 (51% females) subjects was included: mean age 58 years, BMI 26.3, and 31.5 pack-years. The majority of subjects (88%) reported MRC score 1 or 2. FEV1/FVC-ratio ≤ 0.7 was found in 34.8% of the subjects; the prevalence of airway obstruction increased with age and decreased with increasing BMI, and was higher in men and current smokers. According to the level of FEV1, 79% of the subjects with airway obstruction had mild to moderate COPD. Conclusions More than one-third of the recruited subjects had airway obstruction (FEV1/ FVC < 0.7). Early detection of COPD appears to be feasible through offering spirometry to adults with tobacco/occupational exposure and at least 1 respiratory symptom.

Detection of previously undiagnosed cases of COPD in a high-risk population identified in general practice.

Abstract Background and Aim: Under-diagnosis of COPD is a widespread problem. This study aimed to identify previously undiagnosed cases of COPD in a high-risk population identified through general practice. Methods: Participating GPs (n = 241) recruited subjects with no previous diagnosis of lung disease, >35 yrs, and at least one respiratory symptom. Age, smoking status, pack-years, BMI, dyspnoea score (MRC), and pre-bronchodilator spirometry data was obtained. Subjects with airway obstruction (FEV1/FVC ≤ 0.7) at initial spirometry were tested for reversibility, according to Danish COPD guidelines, with bronchodilator and, if necessary, corticosteroids in order to confirm a diagnosis of COPD. Results: A total of 4.049 (49% females) subjects were included; mean age 58 yrs, BMI 27, and 32 pack-years. The COPD prevalence was 21.7%; 8.3% in subjects younger than 48 years. Most patients were classified in GOLD stages I and II (36% and 50%, respectively). The number needed to screen (NNS) for a new diagnosis of COPD was 4.6. COPD diagnosis was related to gender, age, BMI (p < 0.001), pack-years, and cough (p < 0.001), wheezing (p < 0.001) and sputum production (p = 0.002). A threshold of 10% pre-test risk of COPD would have reduced the number of spirometry tests by 35% although 90% of the patients with COPD would still have been identified (NNS 3.9). Conclusions: Of the at-risk subjects studied, 22% were diagnosed with COPD. A case-finding strategy providing questionnaire assessment and diagnostic spirometry to high-risk subjects in primary care, and therefore, identifies a large proportion of undiagnosed COPD patients, especially in the early stages of the disease.

Access, Rank, and Select in Grammar-compressed Strings

Given a string S of length N on a fixed alphabet of σ symbols, a grammar compressor produces a context-free grammar G of size n that generates S and only S. In this paper we describe data structures to support the following operations on a grammar-compressed string: access(S,i,j) (return substring S[i,j]), rank c (S,i) (return the number of occurrences of symbol c before position i in S), and select c (S,i) (return the position of the ith occurrence of c in S). Our main result for access is a method that requires \(\O(n\log N)\) bits of space and \(\O(\log N+m/\log_\sigma N)\) time to extract m = j − i + 1 consecutive symbols from S. Alternatively, we can achieve \(\O(\log_\tau N+m/\log_\sigma N)\) query time using \(\O(n\tau\log_\tau (N/n)\log N)\) bits of space, matching a lower bound stated by Verbin and Yu for strings where N is polynomially related to n when τ = log e N. For rank and select we describe data structures of size \(\O(n\sigma\log N)\) bits that support the two operations in \(\O(\log N)\) time. We also extend our other structure to support both operations in \(\O(\log_\tau N)\) time using \(\O(n\tau\sigma\log_\tau (N/n)\log N)\) bits of space. When τ = log e N the query time is O(logN/loglogN) and we provide a hardness result showing that significantly improving this would imply a major breakthrough on a hard graph-theoretical problem.

Compressed Subsequence Matching and Packed Tree Coloring

We present a new algorithm for subsequence matching in grammar compressed strings. Given a grammar of size n compressing a string of size N and a pattern string of size m over an alphabet of size

Compact q-Gram Profiling of Compressed Strings

\sigma

Fingerprints in compressed strings

σ, our algorithm uses

Dynamic Relative Compression, Dynamic Partial Sums, and Substring Concatenation

O(n+\frac{n\sigma }{w})