“a strong trend”

Furthermore, there was however a strong trend in CPD across age groups; cases in the uppermost quantile having a cigarette consumption of 3.2 CPD less than those in the lowest age quantile ( P = 3.01×10 −21 ).

These “High DMRs” were found closer to the TSS of genes and had higher CpG density; there was a strong trend for increasing overlaps with CpG islands and shores with increasing ΔMe (χ 2 292.3 and 233.6 respectively, p < 22.e-16) with 4.5% and 27.8% of ≥0.3 DMRs overlapping CpG Islands or Shores respectively (Supplementary Fig.

For example, in a large pooled analysis of 14 cohort studies, there was a strong trend with smoking interval before first birth after adjustment for potential confounders that included age at first birth and number of live births ( P = 0.0000002), whereas after stratification by age at first birth, the trends in each stratum were weaker ( P = 0.12, 0.02, and 0.28) [ 8 ], which is suggestive of confounding.

The mean difference found in the forest plot was 3.28, with a confidence interval of 1.92 to 4.65, indicating a strong trend favoring Control, with very strong statistical significance (p<0.00001).

Recession Reduction In the meta‐analysis of recession reduction, there was weak evidence of a difference between the two groups for the single recessions ( p = 0.74); however, by considering the multiple recessions, there was a strong trend for SCTG to provide better results in terms of recession reduction ( p < 0.00001).

WS+CNO p = 0.3443), there was still a strong trend towards more exploratory rearing observed in stressed females that were treated with CNO (Fig. 6F , main effect of stress F 1,29 = 51.94, p < 0.0001; WS+VEH vs.

We initially compared the two genotypes including all the trials, and we observed a strong trend towards increased latency in juvenile Scn2a +/− female mice (two‐way repeated measure ANOVA on both days, F (4.177, 154.5) = 8.796, p < 0.0001 for trial effect, F (1.37) = 3.895, p = 0.056 for genotype effect and F (5.185) = 0.4196, p = 0.83 for genotype × trial interaction), but no difference in adult mice (two‐way repeated measure ANOVA on both days, F (3.460, 86.51) = 4.052, p = 0.0068 for trial effect, F (1.25) = 0.9008, p = 0.35 for genotype effect and F (5.125) = 0.51, p = 0.7693 for genotype trial interaction).

A strong trend of linearity was found between increased prevalence and increased age (F = 124.9, P = 0.0001, R 2 = 0.9615, sample size = 23,785) (see Figure 3 ).

There was a strong trend (p < .0001) in the relationship between number of prescription medications used and responsiveness to DTC advertisements.

The effect was highly significant in the crude model ( β = −1.445; P < .0001) and, after full adjustment in Model 2, showed a strong trend that approached statistical significance ( β = −0.401; P = .091).

There was a strong trend of increasing mortality with increasing interval between breast cancer and endometrial cancer diagnosis ( P = 0.0001), which, after stratification by morphology, remained statistically significant among those with endometrioid tumors ( P < 0.0003).

There was a strong trend of rising expression with progression (Figure 1 B; r = 0.647; P < 0.0001).

Increasing education displayed a strong trend (Cochran-Armitage Trend Test, p<0.0001) with increasing levels of education associated with increased use of condoms, such that compared to men with less than four years of education, men with post-high school education were 13 times more likely to reported higher levels of condom use.

Analysis of all completers and withdrawals showed a strong trend over time ( p < 0.0001), and a difference in rate of change between groups (delayed-image: −0.50 kg, early-image: −0.27 kg, p = 0.0008).

Details are provided in Table 3 , which indicates a strong trend toward airflow obstruction in the COPD diagnosis group (p < 0.0001; chi squared test).

Drone mortality followed a similar trend as in experiment 1 with a strong trend toward higher mortality among the control treatment ( χ 2 1 = 47.0; p < 0.0001) driven by strong differences in mortality among control sources ( χ 2 2 = 84.3; p < 0.0001) rather than treatment sources ( χ 2 1 = 1.3 × 10 −30 ; p = 1) and a clear confounded factor of near total mortality of a single control source (Fig. 2d ).

There was a strong trend to reduction of initial ICS prescribing over time, falling from 77% in 2005 to 47% at the end of the study ( p < 0.0001).

For the period when beavers are generally active (1 April—30 September), there was a strong trend for warmer average daily temperatures ( F 1,3292 = 13.51, p = 0.0002), minimum daily temperatures ( F 1,3292 = 16.21, p < 0.001), and maximum daily temperatures over time ( F 1,3292 = 9.04, p < 0.003; Figure 3 ).

However, there was a strong trend in the hydrocephalic group when rats were at 90° ( P = 0.0004), indicating that in hydrocephalic animals, the mean ICP decreased as weight increased.

The magnitude of the association is as high as 6-fold with a strong trend across the CVD risk scores ( p = 0.0005).

If the intervention has a strong trend for improving post-operative pulmonary complications (as defined above) with a p -value < 0.0005 is found at 300 patients or <0.014 at 600 patients, termination of the study is considered.

However, when sample datasets with no hypermutated sequences were excluded there was a strong trend for hypermutated sequences to decline with increasing viral loads: p = 0.0006 and 0.06 for gag at the first and second time windows, respectively, and p = 0.005 and 0.02 for env (Supplementary Fig. 4 ).

In FRDA patients, significant correlations were found between HMM state 4 MLT and the mean within‐DMN rsFC (MLT, R = 0.79, p = .00023), a strong trend for correlation between HMM state 4 FO and the mean within‐DMN rsFC (FO, R = 0.75, p = .00079) as well as a trend between HMM state 4 and 5 power levels and the mean within‐DMN rsFC (State 4 power level, R = −0.58, p = .016; State 5 power level, R = 0.56, p = .021).

On univariate analysis of survival, preoperative anemia was associated with a strong trend toward worse OS (HR 1.54; 95% CI 1.39–1.70; p < 0.001) as well as on multivariable analysis (HR 1.36; 95% CI 1.20–1.55; p < 0.001).

In patients with high nuclear ORF1p and ORF2p expression, there was a strong trend for lymph node metastasis ( p = 0.001).