Should I proceed to diff-in-diff with variables with so many unbalanced observations after matching

[Chul-Kyoo Jung]

Hi I have been struggling to choose the right covariates for matching and the following (kernel density distribution of propensity score and matching result) is the outcome.
I was wondering if I could still use these variables for regression such as difference and differences with variables that suffer from imbalance after matching.
With these variables, diff-in-diff regression may suffer from biased estimates?
Any tip or suggestion for improving the analysis outcome would be much appreciated.

 pstest der roi ebit hhi_sales lnl lnk ksic2c, both

----------------------------------------------------------------------------------------
                Unmatched |       Mean               %reduct |     t-test    |  V(T)/
Variable          Matched | Treated Control    %bias  |bias| |    t    p>|t| |  V(C)
--------------------------+----------------------------------+---------------+----------
der                    U  | 278.12   198.33      5.9         |   1.73  0.084 |  0.27*
                       M  | 251.17   364.17     -8.3   -41.6 |  -0.98  0.328 |  0.08*
                          |                                  |               |
roi                    U  | .03556   .04006     -4.9         |  -1.69  0.092 |  0.95
                       M  | .03398   .03154      2.7    45.8 |   0.61  0.542 |  1.31*
                          |                                  |               |
ebit                   U  | 2.6e+11   3.6e+10     37.4         |  19.11  0.000 | 12.88*
                       M  | 1.9e+11   1.8e+11      1.3    96.5 |   0.28  0.779 |  1.23*
                          |                                  |               |
hhi_sales              U  |  .2943   .24938     21.8         |   7.57  0.000 |  1.05
                       M  | .28274   .27715      2.7    87.6 |   0.54  0.586 |  0.67*
                          |                                  |               |
lnl                    U  | 7.8331   6.1254    148.0         |  53.98  0.000 |  1.41*
                       M  | 7.3532   7.4134     -5.2    96.5 |  -1.15  0.250 |  0.92
                          |                                  |               |
lnk                    U  | 26.683   24.625    130.4         |  48.53  0.000 |  1.59*
                       M  | 26.148   26.122      1.7    98.7 |   0.34  0.737 |  0.94
                          |                                  |               |
sectors                U  | 38.882   30.204     48.1         |  17.06  0.000 |  1.20*
                       M  | 36.116   37.686     -8.7    81.9 |  -1.71  0.088 |  0.68*
                          |                                  |               |
----------------------------------------------------------------------------------------
* if variance ratio outside [0.90; 1.11] for U and [0.88; 1.14] for M

-----------------------------------------------------------------------------------
 Sample    | Ps R2   LR chi2   p>chi2   MeanBias   MedBias      B      R     %Var
-----------+-----------------------------------------------------------------------
 Unmatched | 0.316   2391.26    0.000     56.7      37.4     160.8*   1.32     71
 Matched   | 0.003      8.68    0.192      4.4       2.7      13.3    0.56     71
-----------------------------------------------------------------------------------
* if B>25%, R outside [0.5; 2]