You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:

- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.
- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.
- Prevention: The content covers measures to prevent the spread of COVID-19.
- Mechanism: The paragraph explains the biological mechanisms of the virus.
- Case Report: The content is a report of a COVID-19 case.
- Transmission: The paragraph discusses how COVID-19 is transmitted.
- Diagnosis: The content is about diagnosing COVID-19 in individuals.

Your classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: ["Topic1", "Topic2", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.

Article:

Objective: To measure the correlation between single breath counting (SBC) and forced vital capacity (liters, FVCL) in amyotrophic lateral sclerosis (ALS) patients and to define the utility of SBC for determining when patients meet the threshold for initiation of noninvasive positive pressure ventilation (FVC < 50% predicted [FVCpred]). Methods: Both patient paced (SBCpp) or externally paced (SBCep) counting along with FVCL+pred and standard clinical data were collected. Linear regression was used to examine SBCpp and SBCep as a predictor of FVCL. Receiver operating characteristic curve analysis evaluated the sensitivity and specificity of SBC categorically predicting FVCpred of </=50%. Results: In 30 ALS patients, SBC explained a moderate proportion of the variance in FVCL (SBCpp: R(2)= 0.431, p < 0.001; SBCep: R(2) = 0.511, p < 0.01); this proportion improved when including covariates (SBCpp: R(2)= 0.635, p < 0.01; SBCep: R(2)= 0.657, p < 0.01). Patients with minimal speech involvement performed similarly in unadjusted (SBCpp: R(2) = 0.511, p < 0.01; SBCep: R(2)= 0.595, p < 0.01) and adjusted (SBCpp: R(2) = 0.634, p < 0.01; SBCep: R(2)= 0.650, p < 0.01) models. SBCpp had 100% sensitivity and 60% specificity (area under curve (AUC) = 0.696) for predicting FVCpred <50%. SBCep had 100% sensitivity and 56% specificity (AUC = 0.696). With minimal speech involvement SBCpp and SBCep both had 100% sensitivity and 76.1% specificity (SPCpp: AUC = 0.845; SBCep: AUC = 0.857). Conclusions: SBC explains a moderate proportion of variance in FVC and is an extremely sensitive marker of poor FVC. When FVC cannot be obtained, such as during the current COVID-19 pandemic, SBC is helpful in directing patient care.
["Prevention"]