Pointer States in the Born-Markov Approximation.

Quantum states least affected by interactions with environment play a pivotal role in both foundations and applications of quantum mechanics. Known as pointer states, they surprisingly lacked a systematic description. Working within the Born-Markov approximation, we combine methods of group theory and open quantum systems and derive general conditions describing pointer states. Contrary to common expectations, they are in general different from coherent states. Thus the two notions of being "closest to the classical"-one defined by the uncertainty relations and the other by the interaction with the environment-are in general different. As an example, we study spin-spin and spin-boson models with an arbitrary central spin J.

Use of appropriate statistical tools in biomedical research: Current trend & status.

Background & objectives: Due to lack of appropriate statistical knowledge, published research articles contain various errors related to the design, analysis and interpretation of results in the area of biomedical research. If research contains statistical error, however, costly, it may be of no use and the purpose of the investigation gets defeated. Many biomedical research articles published in different peer reviewed journals may retain several statistical errors and flaws in them. This study aimed to examine the trend and status of application of statistics in biomedical research articles. Study design, sample size estimation and statistical measures are crucial components of a study. These points were evaluated in published original research articles to understand the use or misuse of statistical tools. Methods: Three hundred original research articles from the latest issues of selected 37 journals were reviewed. These journals were from the five internationally recognized publication groups (CLINICAL KEY, BMJ Group, WILEY, CAMBRIDGE and OXFORD) accessible through the online library of SGPGI, Lucknow, India. Results: Among articles assessed under present investigation, 85.3 per cent (n=256) were observational, and 14.7 per cent (n=44) were interventional studies. In 93 per cent (n=279) of research articles, sample size estimation was not reproducible. The simple random sampling was encountered rarely in biomedical studies even though none of the articles was adjusted by design effect and, only five articles had used randomized test. The testing of assumption of normality was mentioned in only four studies before applying parametric tests. Interpretation & conclusions: In order to present biomedical research results with reliable and precise estimates based on data, the role of engaging statistical experts need to be appreciated. Journals must have standard rules for reporting study design, sample size and data analysis tools. Careful attention is needed while applying any statistical procedure as, it will not only help readers to trust in the published articles, but also rely on the inferences the published articles draw.

Correlates of Cigarette Smoking Among Adolescents in India.

BACKGROUND: The use of cigarettes/tobacco among adolescents is quite high in India. Worldwide, nearly, all (88%) initiation of smoking occurs before the age of 18 years. Smoking caused about 1 million deaths or 10% of all deaths in India, with about 70% of these deaths occurring at the ages of 30-69 years. AIMS AND OBJECTIVES: Different correlates of cigarette smoking among adolescents were investigated, which may help to improve public health interventions in India. MATERIALS AND METHODS: Global Youth Tobacco Survey data collected in India during 2009 were taken. Bivariate analysis, logistic regression, receiver operating characteristic, and nomogram were used to examine association between exposure and outcome variables. Cigarette smoking within the past 30 days preceding the survey was the outcome variable while independent variables were age, education, gender, parental smoking, people smoking at home/smoking in the presence of adolescents, felt boys/girls who smoke have more friends, accepting cigarette offered by one of the best friends, perception of attractiveness of boys/girls who smoke, perception smoking makes one loss or gain weight, and perception cigarettes smoking harmful. RESULTS: 11768 adolescents participated, of which 9951 (48% males and 52% female) responded on cigarette smoking. Current cigarette smoking was associated with female gender (odds ratio [OR]: 0.68; 95% confidence interval [CI]: 0.52-0.90), parental smoking (OR: 1.00; 95% CI: 0.62-1.60), smoking cigarette at home (OR: 3.66; 95% CI: 2.64-5.09), and smoking cigarette in presence of adolescent (OR: 4.14; 95% CI: 2.92-5.87). Observed associations between the outcome and exposure variables reported in this study should be considered in the design of public health interventions. CONCLUSION: To eliminate smoking habits, efforts should also be made in the exploration of new ideas and their implementation by the public health experts in collaboration with international agencies, various nongovernmental organizations, and academic and research institutions. Let's plan for active action to make smoke-free environment based on evidence.

Assessment of iodine nutrition of schoolchildren in Gonda, India, indicates improvement and effectivity of salt iodisation.

OBJECTIVE: To study the total goitre rate (TGR), urinary iodine concentration (UIC) and salt iodine content among schoolchildren in a previously endemic area for severe iodine deficiency disorder (IDD). DESIGN: Cross-sectional epidemiological study. SETTING: The study was carried out in the Gonda district (sub-Himalayan region) of North India. PARTICIPANTS: Nine hundred and seventy-seven schoolchildren (6-12 years) were studied for parameters such as height, weight, UIC and salt iodine content. Thyroid volume (TV) was measured by ultrasonography to estimate TGR. RESULTS: The overall TGR in the study population was 2·8 % (95 % CI 1·8, 3·8). No significant difference in TGR was observed between boys and girls (3·5 % v. 1·9 %, P = 0·2). There was a non-significant trend of increasing TGR with age (P = 0·05). Median UIC was 157·1 µg/l (interquartile range: 94·5-244·9). At the time of the study, 97 % of salt sample were iodised and nearly 86 % of salt samples had iodine content higher than or equal to 15 part per million. Overall, TGR was significantly lower (2·8 % v. 31·0 %, P < 0·001), and median UIC was significantly higher (157·1 v. 100·0 µg/l, P < 0·05) than that reported in the same area in 2009. CONCLUSIONS: A marked improvement was seen in overall iodine nutrition in the Gonda district after three and a half decades of Universal Salt Iodisation (USI). To sustainably control IDD, USI and other programmes, such as health education, must be continuously implemented along with putting mechanisms to monitor the programme at regular intervals in place.

Forecasting spread of COVID-19 using google trends: A hybrid GWO-deep learning approach.

The recent outbreak of COVID-19 has brought the entire world to a standstill. The rapid pace at which the virus has spread across the world is unprecedented. The sheer number of infected cases and fatalities in such a short period of time has overwhelmed medical facilities across the globe. The rapid pace of the spread of the novel coronavirus makes it imperative that its' spread be forecasted well in advance in order to plan for eventualities. An accurate early forecasting of the number of cases would certainly assist governments and various other organizations to strategize and prepare for the newly infected cases, well in advance. In this work, a novel method of forecasting the future cases of infection, based on the study of data mined from the internet search terms of people in the affected region, is proposed. The study utilizes relevant Google Trends of specific search terms related to COVID-19 pandemic along with European Centre for Disease prevention and Control (ECDC) data on COVID-19 spread, to forecast the future trends of daily new cases, cumulative cases and deaths for India, USA and UK. For this purpose, a hybrid GWO-LSTM model is developed, where the network parameters of Long Short Term Memory (LSTM) network are optimized using Grey Wolf Optimizer (GWO). The results of the proposed model are compared with the baseline models including Auto Regressive Integrated Moving Average (ARIMA), and it is observed that the proposed model achieves much better results in forecasting the future trends of the spread of infection. Using the proposed hybrid GWO-LSTM model incorporating online big data from Google Trends, a reduction in Mean Absolute Percentage Error (MAPE) values for forecasting results to the extent of about 98% have been observed. Further, reduction in MAPE by 74% for models incorporating Google Trends was observed, thus, confirming the efficacy of utilizing public sentiments in terms of search frequencies of relevant terms online, in forecasting pandemic numbers.

Application of student's t-test, analysis of variance, and covariance.

Student's t test (t test), analysis of variance (ANOVA), and analysis of covariance (ANCOVA) are statistical methods used in the testing of hypothesis for comparison of means between the groups. The Student's t test is used to compare the means between two groups, whereas ANOVA is used to compare the means among three or more groups. In ANOVA, first gets a common P value. A significant P value of the ANOVA test indicates for at least one pair, between which the mean difference was statistically significant. To identify that significant pair(s), we use multiple comparisons. In ANOVA, when using one categorical independent variable, it is called one-way ANOVA, whereas for two categorical independent variables, it is called two-way ANOVA. When using at least one covariate to adjust with dependent variable, ANOVA becomes ANCOVA. When the size of the sample is small, mean is very much affected by the outliers, so it is necessary to keep sufficient sample size while using these methods.

Selection of appropriate statistical methods for data analysis.

In biostatistics, for each of the specific situation, statistical methods are available for analysis and interpretation of the data. To select the appropriate statistical method, one need to know the assumption and conditions of the statistical methods, so that proper statistical method can be selected for data analysis. Two main statistical methods are used in data analysis: descriptive statistics, which summarizes data using indexes such as mean and median and another is inferential statistics, which draw conclusions from data using statistical tests such as student's t-test. Selection of appropriate statistical method depends on the following three things: Aim and objective of the study, Type and distribution of the data used, and Nature of the observations (paired/unpaired). All type of statistical methods that are used to compare the means are called parametric while statistical methods used to compare other than means (ex-median/mean ranks/proportions) are called nonparametric methods. In the present article, we have discussed the parametric and non-parametric methods, their assumptions, and how to select appropriate statistical methods for analysis and interpretation of the biomedical data.

Descriptive statistics and normality tests for statistical data.

Descriptive statistics are an important part of biomedical research which is used to describe the basic features of the data in the study. They provide simple summaries about the sample and the measures. Measures of the central tendency and dispersion are used to describe the quantitative data. For the continuous data, test of the normality is an important step for deciding the measures of central tendency and statistical methods for data analysis. When our data follow normal distribution, parametric tests otherwise nonparametric methods are used to compare the groups. There are different methods used to test the normality of data, including numerical and visual methods, and each method has its own advantages and disadvantages. In the present study, we have discussed the summary measures and methods used to test the normality of the data.

Scales of measurement and presentation of statistical data.

Measurement scale is an important part of data collection, analysis, and presentation. In the data collection and data analysis, statistical tools differ from one data type to another. There are four types of variables, namely nominal, ordinal, discrete, and continuous, and their nature and application are different. Graphs are a common method to visually present and illustrate relationships in the data. There are several statistical diagrams available to present data sets. However, their use depends on our objectives and data types. We should use the appropriate diagram for the data set, which is very useful for easily and quickly communicating summaries and findings to the audience. In the present study, statistical data type and its presentation, which are used in the field of biomedical research, have been discussed.

Seroprevalence of selected viral pathogens in pigs reared in organized farms of Meghalaya from 2014 to 16.

AIM: A pilot study was carried out to find out the seroprevalence of Porcine circovirus 2 (PCV2), classical swine fever virus (CSFV), and Porcine respiratory and reproductive syndrome virus (PRRS) in pig population of Meghalaya. MATERIALS AND METHODS: Serum samples were collected from piglets of 40-45 days age group, growers, and sows reared under organized and unorganized management in 11 districts of Meghalaya situated in the Khasi, Jaintia, and Garo hills divisions in the time period of 2014-2016 from apparently healthy and suspected pigs. Seroprevalence of PCV2, CSFV, and PRRS specific antibodies was detected by enzyme-linked immunosorbent assay (ELISA). RESULTS: A total of 1899 serum samples were collected and screened using antibody ELISA kits specific for PCV2, CSFV, and PRRS. The highest antibody prevalence during the selected time periods was detected for PCV2 (80.8% in 2014, 79.1% in 2015, and 96.2% in 2016) followed by CSFV (76.4% in 2014, 66.09% in 2015, and 25.5% in 2016) and PRRS (2.8% in 2014, 2.7% in 2015, and 3.62% in 2016). The result indicates high seroprevalence for PCV2, which can be considered as an inducement factor due to the immunosuppressive nature of the virus, for animals being susceptible to other pathogens in farms where airborne transmission of PCV2 and postweaning multisystemic wasting syndrome among animals reared in close pens can be a major possibility. CONCLUSIONS: The data from this study indicates ubiquitous prevalence of PCV2 antibodies in the farm animals along with the endemic presence of swine fever and emergence of PRRS in an organized farm. There are few reports regarding PCV2 infections/outbreaks in pigs associated with reproductive failure from northern and southern part of India, but till date, there are no reports regarding concomitant infection of CSFV and PCV2 from India. Considerable high seropositivity of PCV2 indicates the need for high impact hygiene practice in farms, routine seromonitoring and implementation the vaccination program. To the author's best knowledge, this is the first documented report on the seroprevalence of PCV2, CSFV, and PRRS from pig population of Meghalaya.

High Prevalence of Osteoporosis and Morphometric Vertebral Fractures in Indian Males Aged 60 Years and Above: Should Age for Screening Be Lowered?

Current guidelines recommend bone mineral density (BMD) measurement in asymptomatic men above age 70 years and vertebral fracture (VF) assessment above 80 years with T-score <-1.0 with risk factors. We studied the prevalence of osteoporosis and morphometric VF in asymptomatic males aged 60 years and above in North India. Free-living community-dwelling men (n = 241, age: mean ± standard deviation 68.0 ± 6.2 years) underwent a detailed history, physical examination, biochemical evaluation, and BMD measurements at 3 sites: lumbar spine, total hip (TH), and femoral neck (FN). Morphometric VF were assessed by instant vertebral assessment using Genant et al's semiquantitative method. We observed osteoporosis, osteopenia, and normal BMD in 19%, 56%, and 25% of subjects, respectively. The decade wise prevalence of osteoporosis in the age groups 60-70 years, 71-80 years, and >80 years was 16.9%, 17%, and 50%, respectively. Mean serum 25OHD levels were 17.2 ± 10.3 ng/mL. Vitamin D deficiency (<20 ng/mL) and secondary hyperparathyroidism (plasma intact parathyroid hormone >65 ng/mL) were present in 68.8% and 45.4%, respectively. VF were present in 29.6% subjects (grade I: 58%, grade II: 32.4%, and grade III: 8.8%). Age and iPTH had significant negative correlation with BMD at FN and TH. Serum 25OHD had no correlation with BMD at any site. The prevalence of VF was positively associated with age (p = 0.018) and negatively associated with BMD at FN (p = 0.002) and TH (p = 0.013). Osteoporosis and VF are common in asymptomatic Indian males aged 60 years and above. Screening for osteoporosis and instant vertebral assessment may be recommended earlier than currently existing guidelines.

Maximum Relative Entropy of Coherence: An Operational Coherence Measure.

The operational characterization of quantum coherence is the cornerstone in the development of the resource theory of coherence. We introduce a new coherence quantifier based on maximum relative entropy. We prove that the maximum relative entropy of coherence is directly related to the maximum overlap with maximally coherent states under a particular class of operations, which provides an operational interpretation of the maximum relative entropy of coherence. Moreover, we show that, for any coherent state, there are examples of subchannel discrimination problems such that this coherent state allows for a higher probability of successfully discriminating subchannels than that of all incoherent states. This advantage of coherent states in subchannel discrimination can be exactly characterized by the maximum relative entropy of coherence. By introducing a suitable smooth maximum relative entropy of coherence, we prove that the smooth maximum relative entropy of coherence provides a lower bound of one-shot coherence cost, and the maximum relative entropy of coherence is equivalent to the relative entropy of coherence in the asymptotic limit. Similar to the maximum relative entropy of coherence, the minimum relative entropy of coherence has also been investigated. We show that the minimum relative entropy of coherence provides an upper bound of one-shot coherence distillation, and in the asymptotic limit the minimum relative entropy of coherence is equivalent to the relative entropy of coherence.

Prevalence of celiac disease in Indian children with type 1 diabetes.

BACKGROUND: Type 1 diabetes (T1D) patients are at an increased risk of having celiac disease (CD). We evaluated the prevalence and clinical profile of CD in children and adolescents with T1D and reviewed the Indian literature to determine prevalence and reasons for variability. METHODS: In this cross-sectional study, subjects with T1D were prospectively evaluated with a demographic and gastrointestinal (GI) questionnaire, human IgA-tissue transglutaminase (IgA-tTGA), and endoscopic duodenal biopsy in serology positive patients. Studies evaluating prevalence of CD in T1D from India were reviewed. RESULTS: Fourteen (13.6 %) of the 103 (52 boys, 13 years [2-20]) T1D patients were IgA-tTGA (182 U [47-300]) positive and 3.8 % (4/103) had villous atrophy on histology. Subjects with T1D and CD (n = 4) were younger at onset of T1D (32.5 ± 12.6 vs. 110.5 ± 53.8 months; p < 0.005) and more often had GI symptoms (pain abdomen [2/4 vs. 6/89; p = 0.01], stool frequency of 2-3/day [3/4 vs. 38/89; p = 0.004]) than screen negative T1D (n = 89). Growth and glycemic control were not different between the groups. In the 7 Indian studies involving 915 children and adults, 13.8 % (8 % to 17.8 %) T1D were serology positive. Prevalence of CD was reported as 6.9 % (2.3 % to 11.1 %), but only 3.1 % (2.3 % to 4.2 %) had villous atrophy on histology. CONCLUSIONS: Potential CD and CD were present in 13.6 % and 3.8 % children with T1D respectively. T1D with CD have onset of diabetes at younger age and were more often symptomatic than screen negative T1D.

Disparity in maternal, newborn and child health services in high focus states in India: a district-level cross-sectional analysis.

OBJECTIVES: To examine the level and trend in the coverage gap of a set of interventions of maternal and child health services using a summary index and to assess the disparity in usage of maternal and child health services in the districts of high focus states of India. DESIGN: Data for the present study are taken from the Annual Health Survey (AHS), 2010-2013 and Census of India, 2011. SETTINGS: This study used secondary data from states having higher mortality and fertility rates, termed as high focus states in India. PARTICIPANTS: District-level information regarding children aged 12-23 months and ever married women aged 15-49 years has been extracted from the AHS (2010-2013), and household amenities, female literacy and main workforce information has been obtained from the Census of India 2011. MEASURES: 2 summary indexes were calculated first for maternal and child health services and another for socioeconomic and development status, using data from AHS and Census. Cronbach's α was used to assess the internal consistency of the items used in the index. RESULTS: The result shows that the coverage gap is highest in Uttar Pradesh (37%) and lowest in Madhya Pradesh (21%). Converge gap and socioeconomic development are negatively correlated (r=-0.49, p=0.01). The average coverage gap was highest in the lowest quintile of socioeconomic development. There was an absolute change of 1.5% per year in coverage gap during 2009-2013. In regression analysis, the coefficient of determination was 0.24, ß=-30.05, p=0.01 for a negative relationship between socioeconomic development and coverage gap. CONCLUSIONS: There is a significant disparity in the usage of maternal and child healthcare services in the districts of India. Resource-rich people (urban residents and richest quintile) are way ahead of marginalised people (rural residents and poorest quintile) in the usage of healthcare services.

Prevalence of colonic polyp and its predictors in patients with acromegaly.

BACKGROUND: There are conflicting data regarding the prevalence of colorectal polyp in patients with acromegaly. SUBJECTS AND METHODS: Consecutive forty-seven acromegalic patients (21 men, 26 women), with a mean age of (40 ± 12 years) attending endocrinology outpatient department underwent full colonoscopy. All the patients underwent clinical and biochemical evaluation (glucose suppressed growth hormone (GH), Insulin-like growth factor-1 [IGF-1], fasting insulin, and glucose). The control group (n = 120) for colonoscopy was adult subjects undergoing evaluation for symptoms of irritable bowel syndrome. Clinical and biochemical parameters in acromegalic patients with colonic polyp were compared to those without a polyp. RESULTS: Patients with acromegaly had significantly higher prevalence of colonic polyp as compared to control subjects (10.6% vs. 0.8%). None of the patients with polyp had skin tags. There was no significant difference between subjects with and without colonic polyp in duration of illness, basal, and glucose-suppressed GH and most recent IGF-1. Fasting blood sugar was significantly higher (P < 0.05) in adenoma group after adjusting for age, body mass index (BMI), and insulin levels. Patients in adenoma group showed a trend toward male gender and younger age as compared to those without adenoma. CONCLUSIONS: Subjects with acromegaly as compared to control have a higher prevalence of colonic polyps. There was no association of polyps seen with age, BMI, skin tags, homeostasis model assessment of insulin resistance index, duration of disease, and basal and glucose-suppressed GH and IGF-1 levels. There were no specific predictive factors detected. Screening full colonoscopy is recommended in all cases with acromegaly.

Quantum Rényi relative entropies affirm universality of thermodynamics.

We formulate a complete theory of quantum thermodynamics in the Rényi entropic formalism exploiting the Rényi relative entropies, starting from the maximum entropy principle. In establishing the first and second laws of quantum thermodynamics, we have correctly identified accessible work and heat exchange in both equilibrium and nonequilibrium cases. The free energy (internal energy minus temperature times entropy) remains unaltered, when all the entities entering this relation are suitably defined. Exploiting Rényi relative entropies we have shown that this "form invariance" holds even beyond equilibrium and has profound operational significance in isothermal process. These results reduce to the Gibbs-von Neumann results when the Rényi entropic parameter α approaches 1. Moreover, it is shown that the universality of the Carnot statement of the second law is the consequence of the form invariance of the free energy, which is in turn the consequence of maximum entropy principle. Further, the Clausius inequality, which is the precursor to the Carnot statement, is also shown to hold based on the data processing inequalities for the traditional and sandwiched Rényi relative entropies. Thus, we find that the thermodynamics of nonequilibrium state and its deviation from equilibrium together determine the thermodynamic laws. This is another important manifestation of the concepts of information theory in thermodynamics when they are extended to the quantum realm. Our work is a substantial step towards formulating a complete theory of quantum thermodynamics and corresponding resource theory.

Measuring Quantum Coherence with Entanglement.

Quantum coherence is an essential ingredient in quantum information processing and plays a central role in emergent fields such as nanoscale thermodynamics and quantum biology. However, our understanding and quantitative characterization of coherence as an operational resource are still very limited. Here we show that any degree of coherence with respect to some reference basis can be converted to entanglement via incoherent operations. This finding allows us to define a novel general class of measures of coherence for a quantum system of arbitrary dimension, in terms of the maximum bipartite entanglement that can be generated via incoherent operations applied to the system and an incoherent ancilla. The resulting measures are proven to be valid coherence monotones satisfying all the requirements dictated by the resource theory of quantum coherence. We demonstrate the usefulness of our approach by proving that the fidelity-based geometric measure of coherence is a full convex coherence monotone, and deriving a closed formula for it on arbitrary single-qubit states. Our work provides a clear quantitative and operational connection between coherence and entanglement, two landmark manifestations of quantum theory and both key enablers for quantum technologies.

Giant Cell Tumor of Bone in Skeletally Immature Patients - A Clinical Perspective.

INTRODUCTION: Giant cell tumors of skeleton are very rare in pediatric and adolescent population. Here we report two cases-one a fifteen year old child with swelling distal humerus and another a case of a thirteen year old child with pain and swelling proximal tibia. CASE REPORT: A fifteen year old child presented to department of orthopedics of our institute with complaint of difficulty in moving upper limb and swelling distal humerus. Another patient who was a 13 years old male had painful ambulation and swelling in upper tibia. MRI followed by core needle biopsy was done in both the patients confirming the mass to be giant cell tumor which is quite rare in this age group. First patient was managed by wide excision and total elbow replacement and second one by curettage, cementation and augmentation with plate-screw construct. CONCLUSION: Giant cell tumour of skeleton is highly uncommon in pediatric age group. It should be considered as one of the differential diagnosis of epiphyseo metaphyseal lesions in pediatric population in spite of its rarity.

A combination of the modified Mallampati score, thyromental distance, anatomical abnormality, and cervical mobility (M-TAC) predicts difficult laryngoscopy better than Mallampati classification.

OBJECTIVE: Unanticipated difficult tracheal intubation is a significant source of morbidity and mortality in anesthetized patients. A number of modules have been developed to predict difficult airways, but they are often complex in nature. We combined the modified Mallampati score (M), thyromental distance (T), anatomical abnormality (A), and cervical mobility (C) into a single scoring system with the acronym M-TAC, and evaluated it against Mallampati scoring. METHODS: We prospectively analyzed 500 adult patients of the American Society of Anesthesiologists (ASA) class I or II, scheduled for elective surgery under general anesthesia. Preoperative airway assessments using M-TAC were performed, all of which were given a score. Anesthesiologists, blinded to the pre-anesthetic airway assessment, performed laryngoscopy and graded the laryngoscopic view as per Cormack and Lehane's classification. For the study purpose, difficult laryngoscopy was defined as Cormack and Lehane Grade 3 or 4 of laryngoscopic view. RESULTS: An M-TAC score ≥ 4 had a significantly higher sensitivity (96% vs. 72%) and specificity (86% vs. 78%) with a high positive predictive value (44% vs. 28%) and a very low false negative value (2% vs. 15%) in comparison with Mallampati scoring (p < 0.05). Analysis of the receiver operating characteristic (ROC) curve for predicting difficult laryngoscopy revealed an area under the curve of 0.83 (95% CI = 0.78-0.88) for Mallampati scoring and 0.94 (95% CI = 0.92-0.96) for M-TAC scoring system. CONCLUSION: The M-TAC scoring system has provided a higher sensitivity and specificity in predicting difficult laryngoscopy in comparison with Mallampati classification.